Επιστήμη

Αν δεν έχει κατηγορία γι'αυτό βάλτε το εδώ...
pipinos1976
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Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

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Μία εξαιρετική παρουσίαση σχετικά με τον κόσμο της ηλεκτρονικής κατασκοπίας. Ξεκινάει μια σύντομη αναδρομή από το παρελθόν και φτάνει μέχρι το πώς δουλεύουν σήμερα.

Confessions of a cyber spy hunter | Eric Winsborrow | TEDxVancouver
With over 20 years of experience leading high technology companies out of Silicon Valley, Eric has played a part in shaping the industry as an executive at heavyweights like McAfee, Symantec, and Cisco.

Today, he is the CEO of ZanttZ, a company that is developing stealth cyber security technology solutions. Eric and his company are at the forefront of the latest developments in the world of global espionage, and the merging of man and machine. He attests that the Hollywood-created image of the daring secret agent sneaking into a foreign government's laser protected server room to steal top secret information couldn't be further from modern reality. In fact, the "James Bond" of the 21st century doesn't just use a computer, he is the computer.




Ευχαριστώ.


pipinos1976
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Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

Δημοσίευση από pipinos1976 »

Μια νέα μελέτη σχετικά με την ακτινοβολία που δέχονται οι αστροναύτες, όταν εγκαταλείπουν την Γη. Η μελέτη έλαβε χώρα κυρίως στην επιφάνεια της Σελήνης και προέκυψαν συγκριτικά αποτελέσματα για διάφορες περιπτώσεις. Η επιφάνεια της Σελήνης, σε σχέση με τον ΔΔΣ - Διεθνή Διαστημικό Σταθμό δέχεται 200 φορές μεγαλύτερη ακτινοβολία. Αυτό προέρχεται από το γεγονός ότι ο ΔΔΣ βρίσκεται σε ύψος περίπου 400km από την επιφάνεια της Γης, οπότε βρίσκεται εντός της προστασίας του μαγνητικού πεδίου της Γης. Δεχόμαστε ότι το διάστημα ξεκινάει κάπου στα 100km (γραμμή Κάρμαν), ενώ η μαγνητόσφαιρα φτάνει και στα 1000km.

SOS για τους αστροναύτες: H ακτινοβολία στη Σελήνη είναι 200 φορές μεγαλύτερη από τη Γη
SOS για τους αστροναύτες: H ακτινοβολία στη Σελήνη είναι 200 φορές μεγαλύτερη από τη Γη

Τα επίπεδα ακτινοβολίας στην επιφάνεια του φεγγαριού είναι 2,6 φορές μεγαλύτερα σε σχέση με τα αντίστοιχα στο Διεθνή Διαστημικό Σταθμό (ΔΣΣ), σύμφωνα με μια νέα γερμανο-κινεζική επιστημονική μελέτη, την πρώτη που κάνει αυτή τη σύγκριση. Γι' αυτό οι μελλοντικοί αστροναύτες στη Σελήνη θα χρειασθούν -λόγω των κινδύνων για την υγεία τους- κατάλληλα μέτρα προφύλαξης.

Τα επίπεδα ακτινοβολίας στην επιφάνεια του φεγγαριού είναι 2,6 φορές μεγαλύτερα σε σχέση με τα αντίστοιχα στο Διεθνή Διαστημικό Σταθμό (ΔΣΣ), σύμφωνα με μια νέα γερμανο-κινεζική επιστημονική μελέτη, την πρώτη που κάνει αυτή τη σύγκριση. Γι’ αυτό οι μελλοντικοί αστροναύτες στη Σελήνη θα χρειασθούν -λόγω των κινδύνων για την υγεία τους- κατάλληλα μέτρα προφύλαξης.

Η Αμερικανική Διαστημική Υπηρεσία (NASA), η οποία σχεδιάζει να στείλει στη Σελήνη αστροναύτες ξανά έως το τέλος του 2024 -τον πρώτο άνδρα μετά το 1972 και την πρώτη γυναίκα στην ιστορία- στο πλαίσιο του νέου προγράμματος «’Αρτεμις», νοιάζεται να τους προστατεύσει από την ακτινοβολία. Αρχικά το πρώτο ζευγάρι Αμερικανών αστροναυτών αναμένεται να μείνει περίπου μια εβδομάδα στο φεγγάρι, υπερδιπλάσιο χρόνο από ό,τι τα πληρώματα των αποστολών «Απόλλων» πριν μισό αιώνα, τα οποία διέθεταν φορητά δοσίμετρα ακτινοβολίας. Αργότερα και εφόσον δημιουργηθεί κάποια βάση στη Σελήνη, οι αποστολές θα διαρκούν ένα έως δύο μήνες. Το επόμενο βήμα για τη NASA θα είναι η αποστολή αστροναυτών στον ‘Αρη μέσα στη δεκαετία του 2030.

Πώς θα προστατευτούν οι αστροναύτες στη Σελήνη από την ακτινοβολία;

Οι ερευνητές, με επικεφαλής τον δρα Τόμας Μπέργκερ του Γερμανικού Αεροδιαστημικού Κέντρου, οι οποίοι χρησιμοποίησαν το όργανο LND (Lunar Neutron and Dosimetry) που βρίσκεται στο ρομποτικό κινεζικό σκάφος Chang’e-4 (προσεληνώθηκε στη σκοτεινή πλευρά του φεγγαριού τον Ιανουάριο του 2019) και έκαναν τη σχετική δημοσίευση στο περιοδικό «Science Advances», μπόρεσαν για πρώτη φορά να μετρήσουν με ακρίβεια τα επίπεδα ακτινοβολίας στη σεληνιακή επιφάνεια.

Η μέτρηση αποκάλυψε μια μέση δόση ακτινοβολίας της τάξης των 60 μικροσίβερτς την ώρα. Συγκριτικά, οι επιβάτες μιας υπερατλαντικής πτήσης μεταξύ Φρανκφούρτης-Νέας Υόρκης εκτίθενται σε δόσεις πέντε έως δέκα φορές χαμηλότερες, ενώ στη επιφάνεια της Γης η μέση ακτινοβολία είναι περίπου 200 φορές μικρότερη.

Γιατί δεν είμαστε φτιαγμένοι να αντέχουμε τη διαστημική ακτινοβολία;

«Οι άνθρωποι δεν είμαστε φτιαγμένοι να αντέχουμε τη διαστημική ακτινοβολία. Όμως οι αστροναύτες μπορούν και πρέπει να προστατευθούν όσο είναι δυνατό στη διάρκεια της μακράς παραμονής τους στο φεγγάρι, για παράδειγμα καλύπτοντας τα οικήματα τους με ένα παχύ στρώμα σεληνιακού εδάφους πάχους 50 έως 80 εκατοστών», δήλωσε ο φυσικός δρ Ρόμπερτ Βίμερ-Σβαϊνγκρούμπερ του Πανεπιστημίου του Κιέλου.

Τα επίπεδα ακτινοβολίας αναμένεται να είναι περίπου τα ίδια οπουδήποτε πάνω στη Σελήνη, με εξαίρεση κοντά στα τοιχώματα των βαθιών κρατήρων. «Βασικά, όσο λιγότερο βλέπει κανείς τον ουρανό από το φεγγάρι, τόσο το καλύτερο. Αυτός είναι η πρωταρχική πηγή ακτινοβολίας», ανέφερε ο ίδιος.

Τα επίπεδα ακτινοβολίας που βρήκε η νέα μελέτη, συμφωνούν σε μεγάλο βαθμό με αυτά που έχουν προκύψει από άνωθεν μετρήσεις αμερικανικού σκάφους, το οποίο βρίσκεται σε τροχιά γύρω από τη Σελήνη εδώ και χρόνια.

Η διαστημική ακτινοβολία, η οποία αποτελείται από φορτισμένα σωματίδια όπως τα πρωτόνια και οι βαρείς πυρήνες χωρίς ηλεκτρόνια, μπορεί να διαπεράσει το ανθρώπινο δέρμα και να προξενήσει βλάβες στο DNA και καρκίνο. Προέρχεται από δύο βασικές πηγές: τις ισχυρές ηλιακές εκλάμψεις που βομβαρδίζουν περιοδικά τη Σελήνη και τη συνεχή «βροχή» γαλαξιακών κοσμικών ακτίνων από το βαθύ διάστημα.

Αντίθετα με τη Γη, η Σελήνη δεν διαθέτει μαγνητικό πεδίο που να προστατεύει από την ηλιακή και κοσμική ακτινοβολία. Επιπλέον, υπάρχει ο κίνδυνος από τις ακτίνες-γάμα που παράγονται από τις αλληλεπιδράσεις ανάμεσα στη διαστημική ακτινοβολία και στο σεληνιακό έδαφος.

Πηγή: ΑΠΕ-ΜΠΕ
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pipinos1976
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Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

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Μία ενδιαφέρουσα είδηση σχετικά με το περιβάλλον.

Γροιλανδία : Ανακαλύφθηκε η χαμηλότερη θερμοκρασία όλων των εποχών για το βόρειο ημισφαίριο
Γροιλανδία : Ανακαλύφθηκε η χαμηλότερη θερμοκρασία όλων των εποχών για το βόρειο ημισφαίριο

Η θερμοκρασία, που καταγράφηκε 30 χρόνια πριν, είναι χαμηλότερη σχεδόν κατά 2 βαθμούς Κελσίου σε σχέση με αυτό που πίστευαν οι επιστήμονες

Κλιματικοί… ντετέκτιβ του Παγκόσμιου Μετεωρολογικού Οργανισμού ( WMO) ανακάλυψαν την πιο κρύα θερμοκρασία που έχει καταγραφεί ποτέ στο βόρειο ημισφαίριο.

Ψάχνοντας στα αρχεία του WMO για τις καταγραφές θερμοκρασίας στους μετεωρολογικούς σταθμούς που βρίσκονται στην κορυφή του πλανήτη, οι ερευνητές ανακάλυψαν ότι η χαμηλότερη θερμοκρασία που έχει καταγραφεί, από αυτόματο μετεωρολογικό σταθμό στη Γροιλανδία, στο μέσον του χειμώνα πριν από σχεδόν 30 χρόνια, ήταν σχεδόν 2 βαθμούς Κελσίου πιο χαμηλή από ό,τι έδειχναν τα μέχρι τώρα στοιχεία.

Ο σταθμός Κλινκ στη Γροιλανδία, κοντά στην κορυφή του φύλλου πάγου, κατέγραψε -69,8 βαθμούς Κελσίου στις 22 Δεκεμβρίου 1991. Η θερμοκρασία είναι σημαντικά χαμηλότερη από τους -67,8 βαθμούς Κελσίου που είχαν καταγραφεί στο Βέρκχογιάνσκ της Ρωσίας τον Φεβρουάριο του 1892, αλλά και στο Όιμεκον της Ρωσίας τον Ιανουάριο του 1933.

Και οι τρεις θερμοκρασίες είναι ασυνήθιστες για το βόρειο ημισφαίριο, όμως πολύ θερμότερες από την χαμηλότερη θερμοκρασία που έχει καταγραφεί ποτέ στον πλανήτη. Στις 22 Ιουλίου του 1983,κ στο μέσον του χειμώνα για το νότιο ημισφαίριο, ο μετεωρολογικός σταθμός Βόστοκ της Ανταρκτικής κατέγραψε -89,2 βαθμούς Κελσίου.
Οι ακραίες καιρικές συνθήκες στους πόλους έχουν μεγάλο ενδιαφέρον για τους επιστήμονες, καθώς δημιουργούν μοντέλα του παρελθοντικού και και του μελλοντικού κλίματος.

Οι θερμοκρασίες στον αρκτικό κύκλο ήταν πολύ υψηλές φέτος το καλοκαίρι, με έναν καύσωνα στη Σιβηρία και ασυνήθιστη ζέστη σε όλη την περιοχή. Ο μετεωρολογικός σταθμός Βέρκχογιανσκ, που έχασε το ρεκόρ από τη νέα ανακάλυψη, κατέγραψε θερμοκρασία 38 βαθμών Κελσίου φέτος τον Ιούνιο, με τον WMO να θεωρεί ότι ενδέχεται να είναι η υψηλότερη θερμοκρασία που έχει καταγραφεί πάνω από τον αρκτικό κύκλο.

Ο Πετέρι Τααλάς, γενικός γραμματέας του WMO, δήλωσε: «Στην εποχή της κλιματικής αλλαγής, δίνουμε μεγάλη σημασία στα νέα ρεκόρ ζέστης. Το καινούργιο ρεκόρ χαμηλότερης θερμοκρασίας, είναι σημαντική υπενθύμιση των έντονων αντιθέσεων που υπάρχουν στον πλανήτη μας».

Η έρευνα των αρχείων επιτρέπει στους επιστήμονες να ψάξουν για μοτίβα θερμοκρασιών, και προσφέρει πολύτιμα στοιχεία για κλιματικά μοντέλα. Ο μετεωρολογικός σταθμός Κλινκ λειτούργησε για δύο χρόνια στις αρχές της δεκαετίας του 1990, πριν τα αυτοματοποιημένα όργανά του σταλούν για χρήση στην Ανταρκτική.

Το ρεκόρ ήρθε στο φως μόνο αφού μια ομάδα του WMO κατάφερε να έρθει σε επαφή με την αρχική επιστημονική ομάδα. Τα στοιχεία έπρεπε να ελεγχθούν διεξοδικά πριν το νέο ρεκόρ γίνει αποδεκτό.

Η εκτίμησή τους δημοσιεύθηκε στο Quarterly Journal of the Royal Meteorological Society.

Πηγή: www.theguardian.com
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Johnny
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Εγγραφή: 14 Ιούλ 2010, 20:23
Τοποθεσία: Μεταμόρφωση - Αττικής (Κουκου city)

Re: Επιστήμη

Δημοσίευση από Johnny »

Παγώνει το βλέμα σου. :shock: :shock:
Η ανθρωπότητα δεν έχει προχωρήσει ούτε ένα βήμα μπροστά, από την στιγμή που υπάρχει έστω και ένα παιδί που υποφέρει.
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MacPap
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Εγγραφή: 08 Ιούλ 2010, 03:00

Re: Επιστήμη

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Johnny έγραψε: 27 Σεπ 2020, 18:49 Παγώνει το βλέμα σου. :shock: :shock:
Σίγουρα!!!!!

Ευγε pipinos1976 για το νήμα! :biritses
Καλός οδηγός σημαίνει απαραίτητα τήρηση του ΚΟΚ.
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pipinos1976
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Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

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Μια εντυπωσιακή είδηση, αν, τελικά, αποδειχθεί ότι ισχύει.

Μεγάλη ανακάλυψη από Ελληνα καθηγητή: Π ... ερία νάρκη
Μεγάλη ανακάλυψη από Ελληνα καθηγητή: Προγονικό είδος των Νεάντερταλ έπεφτε σε χειμερία νάρκη

Η δημοσίευση έγινε για τη χειμερία νάρκη των "Νεάντερταλ" στο υψηλού κύρους γαλλικό επιστημονικό περιοδικό L'anthropologie

Στην μεγάλη ανακάλυψη ότι ένα προγονικό είδος των Νεάντερταλ, πριν από μισό εκατομμύριo χρόνια, έπεφτε σε χειμερία νάρκη για να αντιμετωπίσει τους παγετώνες και την έλλειψη τροφής, προχώρησε ο έλληνας καθηγητής, Αντώνης Μπαρτσιώκας.

Η δημοσίευση έγινε στις 28 Νοεμβρίου 2020 στο υψηλού κύρους γαλλικό επιστημονικό περιοδικό L'anthropologie από τον Ομότιμο Καθηγητή Φυσικής Ανθρωπολογίας & Παλαιοανθρωπολογίας στο Δημοκρίτειο Πανεπιστήμιο Θράκης, Αντώνη Μπαρτσιώκα, και τον Διευθυντή της ανασκαφής στα σπήλαια Atapuerca της Ισπανίας, καθηγητή Juan Luis Arsuaga. Δείτε πιο κάτω την πρώτη συνέντευξη του Έλληνα καθηγητή αποκλειστικά στο Σίγμα και το Sigmalive.

Η θαρραλέα και εντυπωσιακή επιστημονική εργασία, που δημοσιεύθηκε πριν λίγες μέρες, ανοίγει τα μάτια της ανθρωπότητας μετά από πολλά χρόνια "χειμερίας νάρκης". Είναι η πρώτη που προαναγγέλλει το τέλος της κυριαρχίας των Αγγλοαμερικανών στην παλαιοανθρωπολογία και μάλιστα γίνεται με ελληνική συμμετοχή.

Η εργασία προτείνει ότι σε περιόδους παγετώνων και πείνας οι άνθρωποι κατέφευγαν σε χειμερία νάρκη τον χειμώνα μέσα σε σπηλιές όπου κατανάλωναν το λίπος που είχαν αποθηκεύσει στο σώμα τους πριν τον χειμώνα. Τα σκελετικά στοιχεία που υποστηρίζουν αυτή την φυσιολογία ανακαλύφθηκαν στην Ισπανία στα σπήλαια της Atapuerca, νότια των Πυρηναίων. Τα σπήλαια της Atapuerca είναι διάσημα παγκοσμίως καθώς περιέχουν την πιο πλούσια στον κόσμο παλαιοανθρωπολογική ανασκαφή από άποψη αριθμού ανθρώπινων απολιθωμένων οστών και στρωματογραφικής διαρκειας, που υπερβαίνει το ένα εκατομμύριο χρόνια.

Στο σπήλαιο Mayor, στο οποίο έγινε η συγκεκριμένη μελέτη, έχουν βρεθεί μέχρι σήμερα τουλάχιστον 7.500 οστά που ανήκουν σε τουλάχιστον 29 άτομα και κάθε χρόνο βρίσκονται όλο και περισσότερα. Έχουν ηλικία σχεδόν μισό εκατομμύριο χρόνια και ανήκουν σε ένα προγονικό είδος των Νεάντερταλ (πιθανόν Homo heidelbergensis). Ένα καινούργιο είδος έχει, επίσης, βρεθεί στα σπήλαια της περιοχής, ο Homo antecessor.

Μέχρι σήμερα, η χειμερία νάρκη περιορίζεται σε ορισμένα είδη ζώων, όχι στον άνθρωπο

Η χειμερία νάρκη είναι μια προσαρμογή στη φυσιολογία ενός είδους για επερχόμενο λιμό και περιλαμβάνει μείωση του μεταβολισμού και της θερμοκρασίας του σώματος σε μέρος με συνεχές σκοτάδι, όπως τα σπήλαια. Μέχρι σήμερα, η χειμερία νάρκη περιορίζεται σε ορισμένα είδη ζώων, όχι στον άνθρωπο. Η ιδέα ότι οι άνθρωποι μπορούν να πέσουν σε χειμερία νάρκη μπορεί να ακούγεται σαν επιστημονική φαντασία, αλλά το γεγονός ότι η χειμερία νάρκη απαντάται σε πολύ πρωτόγονα θηλαστικά (πλακουντοφόρα, μαρσιποφόρα, και μονοτρήματα), όπως και εξελιγμένα, όπως τα πρωτεύοντα ζώα στα οποία ανήκει και ο άνθρωπος (π.χ., σε λορίσιους και λεμούριους), οδηγεί στο συμπέρασμα ότι η γενετική βάση και η φυσιολογία για έναν τέτοιο υπομεταβολισμό θα μπορούσε να διατηρηθεί σε πολλά είδη θηλαστικών, συμπεριλαμβανομένου και του ανθρώπου.

Πράγματι, πειράματα σε ανθρώπους δείχνουν ότι υπό ορισμένες συνθήκες η χειμερία νάρκη είναι δυνατόν να προκληθεί σε αυτούς με τεχνητό τρόπο. Αλλά υπάρχουν και ιστορικά στοιχεία. Για παράδειγμα, υπάρχουν ιστορικές αναφορές για έναν τύπο υπομεταβολισμού που ονομάζεται Lotska στη Ρωσία, όπου σε μια περιοχή κοντά στην Λετονία ο πληθυσμός μέχρι πριν από 100 χρόνια επεφτε σε ένα είδος χειμερίας νάρκης για έξι μήνες. Στο ίδιο φαινόμενο αναφέρθηκε στην αρχαιότητα και ο πατέρας της Ιστορίας Ηρόδοτος, για ανθρώπους που ζούσαν βόρεια της Σκυθίας (δηλαδή στην σημερινή Ρωσία) "που κοιμούνται για μισό χρόνο".

Εξετάστηκαν τα οστά των ανθρωπίνων του είδους Homo heidelbergensis

Ο Δρ. Μπαρτσιώκας βρήκε ότι τόσο η χειμερία νάρκη των ζώων όσο και η ανθρώπινη νεφρική οστεοδυστροφία χαρακτηρίζονται από υψηλά επίπεδα παραθυρεοειδούς ορμόνης στο αίμα. Για να διαπιστωθεί κατά πόσον υπήρχε χειμερία νάρκη σε ένα ανθρώπινο είδος που έχει εξαφανιστεί (δηλ. σε έναν ανθρωπίνη όπως ονομάζεται), εξετάστηκαν τα οστά των ανθρωπίνων του είδους Homo heidelbergensis που βρέθηκαν στη σπηλιά Mayor στην Atapuerca της Ισπανίας, για ενδείξεις υπερπαραθυρεοειδισμού.

Ο Δρ. Αντώνης Μπαρτσιώκας μελέτησε την μορφολογία και την δομή των ανθρώπινων απολιθωμένων οστών, χρησιμοποιώντας μακροφωτογραφία, μικροσκοπία, ιστολογία και αξονική τομογραφία. Βρήκε δοκίδες σπογγώδους οστού με μικροσκοπικά τούνελ μέσα τους που είχαν τη μορφή σωλήνα, ενώ οι φυσιολογικές δοκίδες είναι σαν συμπαγείς ράβδοι. Αυτό γίνεται γιατί οι οστέινες δοκίδες διαβρώνονται από μέσα λόγω της παραθυρεοειδούς ορμόνης που τρώει το οστούν για να αναπληρώσει την έλλειψη ασβεστίου στο αίμα. Βρήκε, επίσης, και οστεοπλάκες που σχηματίστηκαν από ραχίτιδα (δηλ. υποβιταμίνωση D) και κενά μεταξύ των στρώσεών τους, κυρίως στον εφηβικό πληθυσμό αυτών των "ανθρωπίνων".

Δεδομένου ότι οι παραπάνω παθολογικές αλλοιώσεις είναι διαγνωστικές, κατέληξε στο συμπέρασμα ότι αυτό το εξαφανισμένο είδος ανθρώπου υπέφερε ετησίως από νεφρική ραχίτιδα, κρανιόφθιση, υπερπαραθυρεοειδισμό και νεφρική οστεοδυστροφία, που σχετίζεται με τη Χρόνια Νεφρική Νόσο (CKD), λόγω της χειμερίας νάρκης στην οποία έπεφταν μέσα στην σπηλιά. Αυτό αποδεικνύεται ιδιαίτερα από τις οστεοπλάκες της ραχίτιδας και τις κενές στρώσεις μεταξύ τους που εμφανίζονται κυρίως στα εφηβικά άτομα μαζί με ενδείξεις της επούλωσης, κυρίως στα ενήλικα.

Διαπιστώθηκε, επίσης, και η παρουσία εφηβείας που αποδεικνύεται για πρώτη φορά σε ένα εξαφανισμένο ανθρώπινο είδος. Η ανακάλυψη της χειμερίας νάρκης σε αυτόν τον αρχέγονο πληθυσμό είναι σύμφωνη με τα γενετικά στοιχεία από το αρχαίο DNA και το γεγονός ότι οι ανθρωπίνες αυτοί έζησαν κατά την διάρκεια της αρχής ενός παγετώνα και σε μεγάλο υψόμετρο. Η έρευνα αυτή διαφωτίζει την φυσιολογία του αρχέγονου ανθρώπινου μεταβολισμού και μας βοηθάει να καταλάβουμε πώς ζούσαν οι πρωτόγονοι άνθρωποι.

Ζούσαν σε τεράστιες σπηλιές μερικές από τις οποίες χρησιμοποιούσαν και οι αρκούδες Ursus deningeri

Αξίζει να σημειωθεί ότι οι "ανθρωπίνες" αυτοί ζούσαν σε αυτές τις τεράστιες σπηλιές μερικές από τις οποίες χρησιμοποιούσαν και οι αρκούδες του είδους Ursus deningeri που και αυτές έπεφταν σε χειμερία νάρκη για να επιβιώσουν σε αυτό το ψυχρό περιβάλλον. Οι συνθήκες των σπηλαίων, όπως το συνεχές σκοτάδι, το κρύο και η πείνα μπορούν να προκαλέσουν μια σειρά μεταβολικών διεργασιών κατά την διάρκεια της χειμερίας νάρκης, όπως έκκριση κορτιζόλης, λιπόλυση, χαμηλές τιμές ασβεστίου, ανεπάρκεια βιταμίνης D, μείωση της αυξητικής ορμόνης, υπερέκκριση παραθυρεοειδούς ορμόνης, διάβρωση των οστών και νεφρική οστεοδυστροφία (δηλ. Χρόνια Νεφρική Νόσο, CKD), όπως αποδεικνύεται από τον ετήσιο σχηματισμό κενών στρώσεων στα οστά, που εν ζωή πληρούνταν από την πρωτεΐνη του κολλαγόνου. Αυτές οι αλλοιώσεις και οι ασθένειες στα οστά τους ταυτίζονται με εκείνες των ζώων που πέφτουν σε χειμερία νάρκη.

Για παράδειγμα, οι κενές στρώσεις μεταξύ των οστεοπλακών οφείλονται τόσο στο συνεχές σκοτάδι όσο και στο κρύο και προκαλούνται από υπερέκκριση κορτιζόλης και διακοπή στην ανάπτυξη, αποτελούν δε διαγνωστικά στοιχεία της χειμερίας νάρκης καθώς εμφανίζονται μόνο σε ζώα που πέφτουν σε χειμερία νάρκη, όπως οι νυχτερίδες κ.ά.

Η μεγάλη θνησιμότητα των εφήβων σε αυτόν τον πληθυσμό είναι αποτέλεσμα του λιμού λόγω ανεπάρκειας στην ποσότητα του σωματικού λίπους κατά την διάρκεια της χειμερίας νάρκης και λόγω των μεγάλων ενεργειακών αναγκών τους εξαιτίας της ταχείας του ανάπτυξης ως εφήβων. Έτσι, η χειμερία νάρκη εξολόθρευε τους εφήβους, με αποτέλεσμα λίγα άτομα να επιβιώνουν ως ενήλικα. Αυτό είναι και ένα άλλο χαρακτηριστικό της χειμερίας νάρκης.

Μόνο λίγες από τις αλλοιώσεις της χειμερίας νάρκης στα οστά των εφήβων εμφανίζονται στα ενήλικα άτομα, επειδή είχαν επαρκή αποθέματα λίπους για να αντέξουν κατά την διάρκεια της χειμερίας νάρκης. Αυτό συμβαίνει επειδή δεν χρειάστηκαν να αντιμετωπίσουν τις επιπλέον ενεργειακές απαιτήσεις που θέτει η εφηβεία. Η επούλωση που ελάμβανε χώρα μετά την εφηβεία στους ενήλικες έκανε αυτές τις βλάβες να εξαφανίζονται σε μεγάλο βαθμό στα ενήλικα άτομα. Ως αποτέλεσμα, τα ενήλικα άτομα δεν υπέφεραν τόσο πολύ από τις επιπτώσεις της χειμερίας νάρκης, λόγω επαρκών αποθεμάτων λίπους.

Τα ευρήματα της μελέτης αυτής είναι τα μόνα στον κόσμο που δείχνουν παρουσία ραχίτιδας, χρόνιας νεφρικής ανεπάρκειας (CKD) και χειμερίας νάρκης σε ανθρώπινα οστά από σπήλαιο. Είναι επίσης η μόνη μελέτη που φωτίζει την φυσιολογία ενός ανθρώπινου είδους που έχει εκλείψει. Έτσι, υπό ορισμένες συνθήκες, ορισμένοι "ανθρωπίνες" μπορεί να βρεθούν σε μεταβολικές καταστάσεις που τους βοηθούν να επιβιώσουν για μεγάλες χρονικές περιόδους σε ψυχρές συνθήκες και έλλειψης τροφής αλλά με αρκετή αποθήκευση σωματικού λίπους, καθόσον το λίπος εκτός από ενέργεια και νερό παρέχει και βιταμίνες.

Ο απλοποιημένος μηχανισμός της φυσιολογίας της χειμερίας νάρκης έχει ως εξής: Η έλλειψη βιταμίνης D λόγω του σπηλαίου σκότους προκαλεί έλλειψη ασβεστίου στο αίμα, που με την σειρά της προκαλεί υπερπαραθυρεοειδισμό, ο οποίος καταλήγει σε νεφρική οστεοδυστροφία και χρόνια νεφρική ανεπάρκεια, καταστάσεις που καταγράφονται στα οστά.

Πηγή: SigmaLive
pipinos1976
Δημοσιεύσεις: 1194
Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

Δημοσίευση από pipinos1976 »

Ένα παλιό άρθρο για έναν μεγάλο, αλλά εξαιρετικά "περίεργο" μαθηματικό.

Paul Erdös: «Το μυαλό μου είναι ανοικτό…»
Paul Erdös: «Το μυαλό μου είναι ανοικτό…»

«Ο Πολ Έρντος, ένας από τους σημαντικότερους μαθηματικούς του 20ού αιώνα, και αναμφιβόλως ο πιο εκκεντρικός, μέχρι τα δεκαεπτά του είχε ήδη αναγνωριστεί διεθνώς ως παιδί-θαύμα. Το νόημα της ζωής του ήταν η διατύπωση μαθηματικών εικασιών και η επίλυση μαθηματικών προβλημάτων. Χάρη στο εκπληκτικό έργο του στη Συνδυαστική, τη Θεωρία Γραφημάτων, τη Θεωρία Αριθμών, τη Θεωρία Πιθανοτήτων και τη Θεωρία Συνόλων, απέκτησε τον τίτλο του πιο παραγωγικού μαθηματικού που έζησε ποτέ.

Ο Μπρους Σέχτερ σηκώνει το πέπλο της πιο σουρεαλιστικής κλειστής λέσχης και αποκαλύπτει την παράξενη ζωή του πιο γόνιμου μαθηματικού του κόσμου. Σελίδα τη σελίδα, δενόμαστε τόσο πολύ με αυτόν τον χαρισματικό κύριο, ώστε, στο τέλος του βιβλίου, νιώθουμε άτυχοι που δεν τον συναντήσαμε».

Ως και το 1996 διάφοροι επιφανείς μαθηματικοί ανά τον κόσμο ήξεραν ότι το κουδούνι του σπιτιού τους μπορούσε να χτυπήσει ξαφνικά μέσα στη νύχτα. Δεν ανησυχούσαν. Ήταν σχεδόν βέβαιοι ότι ανοίγοντας την πόρτα θα έβλεπαν μπροστά τους έναν κοντόσωμο άνδρα με χοντρά γυαλιά και παλιό, φθαρμένο κοστούμι που κρατούσε στο ένα χέρι μια βαλίτσα και στο άλλο μια πλαστική σακούλα γεμάτη χαρτιά. «Το μυαλό μου είναι ανοιχτό» θα τους έλεγε χαμογελώντας και θα άρχιζε να εκθέτει μια απίθανη μαθηματική ιδέα. Ήταν ο Πολ Έρντος, ο «περιπατητικός μαθηματικός», ένας από τους μεγαλύτερους του 20ού αιώνα. Στη βαλίτσα είχε όλα τα υπάρχοντά του. Στη σακούλα τις σημειώσεις από τις πρόσφατες μελέτες του.


Η ιδιοκτησία είναι μεγάλος μπελάς

Αεικίνητος, ο Έρντος δεν στεκόταν ποτέ σε ένα μέρος. Θεωρούσε ότι ο άνθρωπος δεν έχει ανάγκη από αποκτήματα και χρήματα. «Δεν θέλησα ποτέ υλικά αγαθά»δήλωνε. «Ένα παλιό ελληνικό ρητό λέει ότι ο σοφός άνθρωπος δεν έχει τίποτε που να μην μπορεί να κουβαλήσει στα χέρια του». Όλα του τα αγαθά τα είχε λοιπόν στα δυο του χέρια. Και μέσα στο μυαλό του.

Πίστευε πως «η ιδιοκτησία είναι μεγάλος μπελάς», δεν είχε μόνιμη κατοικία, ούτε αυτοκίνητο. Δεν χρειαζόταν να «κόβει» επιταγές, ούτε να πληρώνει φόρους εισοδήματος. Ο εκκεντρικός Πολ Έρντος ήταν ένας νομάδας στη χώρα των μαθηματικών. Του οφείλουμε την επίλυση πολυάριθμων μαθηματικών προβλημάτων, κυρίως στη θεωρία των αριθμών και στη συνδυαστική.

Γεννήθηκε στη Βουδαπέστη από εβραίους μαθηματικούς γονείς, οι οποίοι όμως δεν ασκούσαν την εβραϊκή θρησκεία. Ήταν «παιδί-θαύμα» και στα 17 του παρουσίασε μια μαθηματική απόδειξη που τον έκανε γνωστό έξω από την πατρίδα του. Στα 21 του πήρε το διδακτορικό του από το Πανεπιστήμιο της Βουδαπέστης- κατ΄ εξαίρεση, εφόσον οι εβραίοι δεν γίνονταν δεκτοί εκείνη την εποχή στα ουγγρικά πανεπιστήμια- και αμέσως μετά, λόγω της καταγωγής του, αναγκάστηκε να εγκαταλείψει τη χώρα. Αρχικά πήγε στη Βρετανία, στο Πανεπιστήμιο του Μάντσεστερ, και στη συνέχεια στις Ηνωμένες Πολιτείες, ως καθηγητής στο Πανεπιστήμιο του Πρίνστον, το οποίο τον βρήκε υπερβολικά«αντισυμβατικό» για να τον κρατήσει σε μόνιμη βάση.


Τι πιστεύετε για τον Καρλ Μαρξ;

Τα επόμενα χρόνια δίδαξε σε διάφορα αμερικανικά πανεπιστήμια δίνοντας παράλληλα διαλέξεις στο εξωτερικό. Οι συχνές επαφές του με την Ουγγαρία- εκεί ζούσαν η μητέρα του και οι συγγενείς του- και η αλληλογραφία του με μαθηματικούς από κομμουνιστικά κράτη προκάλεσαν τις υποψίες των αμερικανικών αρχών. Το 1956, όταν δίδασκε στο Πανεπιστήμιο Νοτρ Νταμ, στο Σαόυθ Μπέντ της Ιντιάνα, «ανακρίθηκε» από έναν υπάλληλο της Υπηρεσίας Μεταναστών ο οποίος τον ρώτησε, μεταξύ άλλων, «Τι πιστεύετε για τον Καρλ Μαρξ;» Ο Έρντος παραδέχτηκε ότι είχε διαβάσει μόνο το Κομμουνιστικό Μανιφέστο, επομένως δεν ήταν «ικανός να εκφράσει μια κρίση. Αλλά αναμφιβόλως ήταν σπουδαίος άνθρωπος». Η απάντηση αυτή είχε ως αποτέλεσμα, οι αρχές να του στερήσουν την βίζα επανεισόδου στη χώρα και βρέθηκε σε δίλημμα: ή θα έμενε στο Νοτρ Νταμ και δεν θα ταξίδευε πια ή θα έφευγε από τις Ηνωμένες Πολιτείες.

Διάλεξε το δεύτερο και έκτοτε δεν έμεινε ποτέ «στάσιμος» διδάσκοντας σε διάφορα πανεπιστήμια ανά τον κόσμο (η είσοδος στην Αμερική τού επετράπη ξανά το 1963), δίνοντας διαλέξεις, μετέχοντας σε συνέδρια και εργαστήρια, συζητώντας με άλλους μαθηματικούς. Τα χρήματα που συγκέντρωνε από τις αμοιβές του τα χάριζε σε συναδέλφους και φοιτητές που τα είχαν ανάγκη ή τα χρησιμοποιούσε για να χρηματοδοτήσει έρευνες γύρω από μαθηματικά προβλήματα. To 1984 κέρδισε το περίφημο βραβείο Βολφ, το οποίο συνοδευόταν από χρηματικό έπαθλο 50.000 δολαρίων – δίχως άλλο, το μεγαλύτερο ποσό που είχε εισπράξει ποτέ. Διέθεσε 30.000 δολάρια για να χρηματοδοτήσει μια μεταδιδακτορική υποτροφία, με το όνομα των γονέων του στο ΙνστιτούτοΤέκνιον του Ισραήλ, και χρησιμοποίησε τα υπόλοιπα για να βοηθήσει συγγενείς, μεταπτυχιακούς φοιτητές και συναδέλφους του. «Κράτησα μόνο 720 δολάρια», θυμόταν αργότερα.

Εφόσον είχε υπάρξει και ο ίδιος παιδί-θαύμα, ενδιαφερόταν ιδιαιτέρως να συναντά νέους μαθηματικούς και να βοηθά στην ανάπτυξη του ταλέντου τους. Πολλοί κορυφαίοι μαθηματικοί ανά τον κόσμο, οφείλουν τη σταδιοδρομία τους σε μαι πρώιμη γνωριμία με τον Έρντος.

Ο Έρντος αποτελεί τον ορισμό του εκκεντρικού μαθηματικού, χάρη όμως στον χαρούμενο και καλοσυνάτο χαρακτήρα του- και φυσικά στην ιδιοφυΐα του- όσοι τον γνώριζαν του συγχωρούσαν τις ιδιορρυθμίες του. Ηταν πολύ αγαπητός και, παρά το γεγονός ότι απέφευγε τις δεσμεύσεις για να μπορεί να αφοσιωθεί στα μαθηματικά, την κύρια εμμονή του, ήταν πάντα πρόθυμος να βοηθήσει τους συναδέλφους του με κάθε τρόπο. Δεν του άρεσε όμως να τον αγκαλιάζουν και να τον αγγίζουν και έπλενε διαρκώς τα χέρια του- κατάλοιπα ίσως από το γεγονός ότι οι γονείς του τον μεγάλωσαν υπερπροστατευμένο μέσα στο σπίτι ύστερα από τον θάνατο των δύο αδελφών του από οστρακιά.

Εθισμένος στον καφέ και τις αμφεταμίνες, υπερδραστήριος, με σκέψη κρυστάλλινης διαύγειας, ιδιοφυής και χιουμορίστας, αδημονούσε να μοιραστεί απλόχερα τις πρωτοποριακές ιδέες του με όποιον ήταν πρόθυμος να του προσφέρει λίγο χώρο και είχε όρεξη να ιντριγκάρει τον νου του. Ένα διανοητικό ταξίδι στο μαθηματικό σύμπαν του Έρντος, εκτός από δραστηριότητα πλήρους απόλαυσης, αποτελούσε, για όλους, πρώτης γραμμής ενημέρωση σε ό,τι αφορούσε νέα θεωρήματα και αποδείξεις.

Δεν είχε καμία επαφή με τα πρακτικά ζητήματα, όπως το να πληρώσει λογαριασμούς ή να ετοιμάσει έστω και ένα απλό φαγητό.«Μπορώ να φτιάξω εξαιρετικά κρύα δημητριακά» έλεγε«και ίσως θα μπορούσα να βράσω ένα αβγό,δεν έχω όμως προσπαθήσει ποτέ». Χρησιμοποιούσε ένα εντελώς δικό του λεξιλόγιο: τα παιδιά ήταν«έψιλον», από το «ε» που συμβολίζει τις μικρές ποσότητες στα μαθηματικά, οι γυναίκες «αφεντικά»,οι άντρες«δούλοι», η μουσική«θόρυβος»και τα αλκοολούχα ποτά«δηλητήριο».


Στα χρόνια πριν από το διαδίκτυο, υπήρχε ο Έρντος

Το παροιμιώδες μνημονικό του και οι γνώσεις του σε πλήθος μαθηματικών πεδίων, έκαναν τον Πολ ανεξάντλητη πηγή εξειδικευμένης πληροφορίας. «Στα χρόνια πριν από το διαδίκτυο, υπήρχε ο Έρντος», έλεγαν όσοι φίλοι του φρόντιζαν, γενναιόδωρα, για τη συντήρηση αυτής της αλησμόνητης, αξιαγάπητης μαθηματικής φυσιογνωμίας που ανακάλυπτε – σαν κρυμμένους θησαυρούς– καθολικές ιδέες και ταύτιζε τις λαμπρές αποδείξεις με την ποίηση. Το μυαλό του ήταν γεμάτο με τα πιο πρόσφατα κουτσομπολιά, ενώ αποτελούσε ταυτοχρόνως μια εκπληκτική βάση δεδομένων του κόσμου των μαθηματικών. Γνώριζε τους πάντες, ήξερε τι τους ενδιέφερε, ποια εικασία είχαν διατυπώσει, τι είχαν αποδείξει, ή τι επιχειρούσαν να αποδείξουν, τους αριθμούς τηλεφώνων τους, τα ονόματα και τις ηλικίες των συζύγων, των παιδιών και των κατοικιδίων τους ∙ και πολύ περισσότερα. Μπορούσε από μνήμης να πει σε ποια σελίδα κάποιου δυσεύρετου ρωσικού περιοδικού του 1922 αποδεικνυόταν ένα θεώρημα παρόμοιο με αυτό στο οποίο εργαζόταν κάποιος. Αν, λόγου χάρη, συναντούσε έναν μαθηματικό στη Βαρσοβία, συνέχιζε αμέσως τη συζήτηση που είχαν αφήσει στη μέση πριν από δυο χρόνια.


Υπέρτατος φασίστας

Δεν πίστευε στον Θεό αλλά στο «Βιβλίο»με τις μαθηματικές αλήθειες. Ο Θεός, αν υπήρχε, ήταν ο «Υ.Φ.» – ο Υπέρτατος Φασίστας – που του έκρυβε τις κάλτσες και το διαβατήριό του και κρατούσε πεισματικά για τον εαυτό του τις περισσότερες αποδείξεις. Αυτό δεν σημαίνει ότι ο Έρντος δεν βρήκε αποδείξεις, κάθε άλλο: ως τον θάνατό του, το 1996, σε ηλικία 83 ετών, έγραψε περίπου 1.475 εργασίες, «κατόρθωμα» το οποίο τον τοποθετεί στη θέση του δεύτερου παραγωγικότερου μαθηματικού μετά τον Όϊλερ.

Οι μαθηματικοί, αν και θετικοί άνθρωποι, έχουν και αυτοί τις «δοξασίες» τους. Μία από αυτές είναι ο περίφημος Αριθμός Έρντος, ο οποίος «βαθμολογεί» τους συναδέλφους τους ανάλογα με τη σχέση τους με τον μεγάλο ούγγρο μαθηματικό. Ξεκίνησε ως αστείο, όλοι όμως ομολογούν ότι ασυναίσθητα τον κοιτάζουν όταν πρόκειται να αξιολογήσουν έναν συνεργάτη και ότι εντυπωσιάζονται όταν είναι πολύ μικρός.

Το σύστημα έχει ως εξής. Ο Πολ Έρντος- και μόνον αυτός- έχει τον αριθμό 0. Όλοι οι υπόλοιποι βαθμολογούνται με βάση τη «στενότητα» της σχέσης τους μαζί του. Όποιος έχει συνυπογράψει μια εργασία με τον Έρντος βαθμολογείται με 1, όποιος έχει συνυπογράψει μια εργασία με κάποιον συνυπογράψαν τα του Έρντος βαθμολογείται με 2 και ούτω καθ΄ εξής. Ο Αϊνστάιν έχει τον αριθμό 2: δεν είχε συνεργαστεί ποτέ με τον Έρντος, συνέγραψε όμως εργασίες με ορισμένους από τους συνεργάτες του.

Το νόημα της ζωής, έλεγε συχνά ο Έρντος, είναι να αποδεικνύεις και να διατυπώνεις εικασίες. Η απόδειξη και η εικασία είναι τα εργαλεία με τα οποία οι μαθηματικοί εξερευνούν το πλατωνικό σύμπαν της καθαρής μορφής, ένα σύμπαν που για πολλούς απ’ αυτούς είναι εξίσου πραγματικό με το Σύμπαν στο οποίο πρέπει απρόθυμα να κατοικήσουν και να ζήσουν, και πολύ πιο όμορφο. «Αν δεν είναι όμορφοι οι αριθμοί, τότε δεν ξέρω τι είναι όμορφο», επαναλάμβανε συχνά ο Έρντος….
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pipinos1976
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Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

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Μία δημοσίευση του 2015 η οποία περιγράφει πώς οι επιστήμονες - και οι άνθρωποι γενικότερα - κάνουν πολλές φορές λάθη, ακόμα και σε επιστημονικές μελέτες, αλλά δεν το καταλαβαίνουν επειδή θεωρούν τα αποτελέσματα που προκύπτουν ως λογικά.

How scientists fool themselves – and how they can stop
How scientists fool themselves – and how they can stop
Humans are remarkably good at self-deception. But growing concern about reproducibility is driving many researchers to seek ways to fight their own worst instincts.

Regina Nuzzo

In 2013, five years after he co-authored a paper showing that Democratic candidates in the United States could get more votes by moving slightly to the right on economic policy(1), Andrew Gelman, a statistician at Columbia University in New York City, was chagrined to learn of an error in the data analysis. In trying to replicate the work, an undergraduate student named Yang Yang Hu had discovered that Gelman had got the sign wrong on one of the variables.

Gelman immediately published a three-sentence correction, declaring that everything in the paper's crucial section should be considered wrong until proved otherwise.

Reflecting today on how it happened, Gelman traces his error back to the natural fallibility of the human brain: “The results seemed perfectly reasonable,” he says. “Lots of times with these kinds of coding errors you get results that are just ridiculous. So you know something's got to be wrong and you go back and search until you find the problem. If nothing seems wrong, it's easier to miss it.”

This is the big problem in science that no one is talking about: even an honest person is a master of self-deception. Our brains evolved long ago on the African savannah, where jumping to plausible conclusions about the location of ripe fruit or the presence of a predator was a matter of survival. But a smart strategy for evading lions does not necessarily translate well to a modern laboratory, where tenure may be riding on the analysis of terabytes of multidimensional data. In today's environment, our talent for jumping to conclusions makes it all too easy to find false patterns in randomness, to ignore alternative explanations for a result or to accept 'reasonable' outcomes without question — that is, to ceaselessly lead ourselves astray without realizing it.

Failure to understand our own biases has helped to create a crisis of confidence about the reproducibility of published results, says statistician John Ioannidis, co-director of the Meta-Research Innovation Center at Stanford University in Palo Alto, California. The issue goes well beyond cases of fraud. Earlier this year, a large project that attempted to replicate 100 psychology studies managed to reproduce only slightly more than one-third(2). In 2012, researchers at biotechnology firm Amgen in Thousand Oaks, California, reported that they could replicate only 6 out of 53 landmark studies in oncology and haematology(3). And in 2009, Ioannidis and his colleagues described how they had been able to fully reproduce only 2 out of 18 microarray-based gene-expression studies(4).

Although it is impossible to document how often researchers fool themselves in data analysis, says Ioannidis, findings of irreproducibility beg for an explanation. The study of 100 psychology papers is a case in point: if one assumes that the vast majority of the original researchers were honest and diligent, then a large proportion of the problems can be explained only by unconscious biases. “This is a great time for research on research,” he says. “The massive growth of science allows for a massive number of results, and a massive number of errors and biases to study. So there's good reason to hope we can find better ways to deal with these problems.”

When crises like this issue of reproducibility come along, it's a good opportunity to advance our scientific tools,” says Robert MacCoun, a social scientist at Stanford. That has happened before, when scientists in the mid-twentieth century realized that experimenters and subjects often unconsciously changed their behaviour to match expectations. From that insight, the double-blind standard was born.

“People forget that when we talk about the scientific method, we don't mean a finished product,” says Saul Perlmutter, an astrophysicist at the University of California, Berkeley. “Science is an ongoing race between our inventing ways to fool ourselves, and our inventing ways to avoid fooling ourselves.” So researchers are trying a variety of creative ways to debias data analysis — strategies that involve collaborating with academic rivals, getting papers accepted before the study has even been started and working with strategically faked data.


The problem

Although the human brain and its cognitive biases have been the same for as long as we have been doing science, some important things have changed, says psychologist Brian Nosek, executive director of the non-profit Center for Open Science in Charlottesville, Virginia, which works to increase the transparency and reproducibility of scientific research. Today's academic environment is more competitive than ever. There is an emphasis on piling up publications with statistically significant results — that is, with data relationships in which a commonly used measure of statistical certainty, the p-value, is 0.05 or less. “As a researcher, I'm not trying to produce misleading results,” says Nosek. “But I do have a stake in the outcome.” And that gives the mind excellent motivation to find what it is primed to find.

Another reason for concern about cognitive bias is the advent of staggeringly large multivariate data sets, often harbouring only a faint signal in a sea of random noise. Statistical methods have barely caught up with such data, and our brain's methods are even worse, says Keith Baggerly, a statistician at the University of Texas MD Anderson Cancer Center in Houston. As he told a conference on challenges in bioinformatics last September in Research Triangle Park, North Carolina, “Our intuition when we start looking at 50, or hundreds of, variables sucks.”

Andrew King, a management specialist at Dartmouth College in Hanover, New Hampshire, says that the widespread use of point-and-click data-analysis software has made it easy for researchers to sift through massive data sets without fully understanding the methods, and to find small p-values that may not actually mean anything. “I believe we are in the steroids era of social science,” he says. “I've been guilty of using some of these performance-enhancing practices myself. My sense is that most researchers have fallen at least once.”

Just as in competitive sport, says Hal Pashler, a psychologist at the University of California, San Diego, this can set up a vicious circle of chasing increasingly better results. When a few studies in behavioural neuroscience started reporting improbably strong correlations of 0.85, Pashler says, researchers who had more moderate (and plausible) results started to worry: “Gee, I just got a 0.4, so maybe I'm not really doing this very well.”


Hypothesis myopia

One trap that awaits during the early stages of research is what might be called hypothesis myopia: investigators fixate on collecting evidence to support just one hypothesis; neglect to look for evidence against it; and fail to consider other explanations. “People tend to ask questions that give 'yes' answers if their favoured hypothesis is true,” says Jonathan Baron, a psychologist at the University of Pennsylvania in Philadelphia.

For example, says Baron, studies have tried to show how disgust influences moral condemnation, “by putting the subject in a messy room, or a room with 'fart spray' in the air”. The participants are then asked to judge how to respond to moral transgressions; if those who have been exposed to clutter or smells favour harsher punishments, researchers declare their 'disgust hypothesis' to be supported(5). But they have not considered competing explanations, he says, and so they ignore the possibility that participants are lashing out owing to anger at their foul treatment, not simply disgust. By focusing on one hypothesis, researchers might be missing the real story entirely.

Courtrooms face a similar problem. In 1999, a woman in Britain called Sally Clark was found guilty of murdering two of her sons, who had died suddenly as babies. A factor in her conviction was the presentation of statistical evidence that the chances of two children in the same family dying of sudden infant death syndrome (SIDS) were only 1 in 73 million — a figure widely interpreted as fairly damning. Yet considering just one hypothesis leaves out an important part of the story. “The jury needs to weigh up two competing explanations for the babies' deaths: SIDS or murder,” wrote statistician Peter Green on behalf of the Royal Statistical Society in 2002 (see go.nature.com/ochsja). “The fact that two deaths by SIDS is quite unlikely is, taken alone, of little value. Two deaths by murder may well be even more unlikely. What matters is the relative likelihood of the deaths under each explanation, not just how unlikely they are under one explanation.” Mathematician Ray Hill of the University of Salford, UK, later estimated(6) that a double SIDS death would occur in roughly 1 out of 297,000 families, whereas two children would be murdered by a parent in roughly 1 out of 2.7 million families — a likelihood ratio of 9 to 1 against murder. In 2003, Clark's conviction was overturned on the basis of new evidence. The Attorney General for England and Wales went on to release two other women who had been convicted of murdering their children on similar statistical grounds.


The Texas sharpshooter

A cognitive trap that awaits during data analysis is illustrated by the fable of the Texas sharpshooter: an inept marksman who fires a random pattern of bullets at the side of a barn, draws a target around the biggest clump of bullet holes, and points proudly at his success.

His bullseye is obviously laughable — but the fallacy is not so obvious to gamblers who believe in a 'hot hand' when they have a streak of wins, or to people who see supernatural significance when a lottery draw comes up as all odd numbers.

Nor is it always obvious to researchers. “You just get some encouragement from the data and then think, well, this is the path to go down,” says Pashler. “You don't realize you had 27 different options and you picked the one that gave you the most agreeable or interesting results, and now you're engaged in something that's not at all an unbiased representation of the data.”

Psychologist Uri Simonsohn at the University of Pennsylvania, gives an explicit nod to this naivety in his definition of 'p-hacking': “Exploiting — perhaps unconsciously — researcher degrees of freedom until p < 0.05.” In 2012, a study of more than 2,000 US psychologists(7) suggested how common p-hacking is. Half had selectively reported only studies that 'worked', 58% had peeked at the results and then decided whether to collect more data, 43% had decided to throw out data only after checking its impact on the p-value and 35% had reported unexpected findings as having been predicted from the start, a practice that psychologist Norbert Kerr of Michigan State University in East Lansing has called HARKing, or hypothesizing after results are known. Not only did the researchers admit to these p-hacking practices, but they defended them.

This May, a journalist described how he had teamed up with a German documentary filmmaker and demonstrated that creative p-hacking, carried out over one “beer-fueled” weekend, could be used to 'prove' that eating chocolate leads to weight loss, reduced cholesterol levels and improved well-being (see go.nature.com/blkpke). They gathered 18 different measurements — including weight, blood protein levels and sleep quality — on 15 people, a handful of whom had eaten some extra chocolate for a few weeks. With that many comparisons, the odds were better than 50–50 that at least one of them would look statistically significant just by chance. As it turns out, three of them did — and the team cherry-picked only those to report.


Asymmetric attention

The data-checking phase holds another trap: asymmetric attention to detail. Sometimes known as disconfirmation bias, this happens when we give expected results a relatively free pass, but we rigorously check non-intuitive results. “When the data don't seem to match previous estimates, you think, 'Oh, boy! Did I make a mistake?'” MacCoun says. “We don't realize that probably we would have needed corrections in the other situation as well.”

The evidence suggests that scientists are more prone to this than one would think. A 2004 study(8) observed the discussions of researchers from 3 leading molecular-biology laboratories as they worked through 165 different lab experiments. In 88% of cases in which results did not align with expectations, the scientists blamed the inconsistencies on how the experiments were conducted, rather than on their own theories. Consistent results, by contrast, were given little to no scrutiny.

In 2011, an analysis of over 250 psychology papers found(9) that more than 1 in 10 of the p-values was incorrect — and that when the errors were big enough to change the statistical significance of the result, more than 90% of the mistakes were in favour of the researchers' expectations, making a non-significant finding significant.


Just-so storytelling

As data-analysis results are being compiled and interpreted, researchers often fall prey to just-so storytelling — a fallacy named after the Rudyard Kipling tales that give whimsical explanations for things such as how the leopard got its spots. The problem is that post-hoc stories can be concocted to justify anything and everything — and so end up truly explaining nothing. Baggerly says that he has seen such stories in genetics studies, when an analysis implicates a huge number of genes in a particular trait or outcome. “It's akin to a Rorschach test,” he said at the bioinformatics conference. Researchers will find a story, he says, “whether it's there or not. The problem is that occasionally it ain't real.”

Another temptation is to rationalize why results should have come up a certain way but did not — what might be called JARKing, or justifying after results are known. Matthew Hankins, a statistician at King's College London, has collected more than 500 creative phrases that researchers use to convince readers that their non-significant results are worthy of attention (see go.nature.com/pwctoq). These include “flirting with conventional levels of significance (p > 0.1)”, “on the very fringes of significance (p = 0.099)” and “not absolutely significant but very probably so (p > 0.05)”.


The solutions

In every one of these traps, cognitive biases are hitting the accelerator of science: the process of spotting potentially important scientific relationships. Countering those biases comes down to strengthening the 'brake': the ability to slow down, be sceptical of findings and eliminate false positives and dead ends.

One solution that is piquing interest revives an old tradition: explicitly considering competing hypotheses, and if possible working to develop experiments that can distinguish between them. This approach, called strong inference(10), attacks hypothesis myopia head on. Furthermore, when scientists make themselves explicitly list alternative explanations for their observations, they can reduce their tendency to tell just-so stories.

In 2013, researchers reported(11) using strong-inference techniques in a study of what attracts female túngara frogs (Engystomops pustulosus) during mating calls. The existing data could be explained equally well by two competing theories — one in which females have a preset neural template for mating calls, and another in which they flexibly combine auditory cues and visual signals such as the appearance of the males' vocal sacs. So the researchers developed an experiment for which the two theories had opposing predictions. The results showed that females can use multisensory cues to judge attractiveness.


Transparency

Another solution that has been gaining traction is open science. Under this philosophy, researchers share their methods, data, computer code and results in central repositories, such as the Center for Open Science's Open Science Framework, where they can choose to make various parts of the project subject to outside scrutiny. Normally, explains Nosek, “I have enormous flexibility in how I analyse my data and what I choose to report. This creates a conflict of interest. The only way to avoid this is for me to tie my hands in advance. Precommitment to my analysis and reporting plan mitigates the influence of these cognitive biases.”

An even more radical extension of this idea is the introduction of registered reports: publications in which scientists present their research plans for peer review before they even do the experiment. If the plan is approved, the researchers get an 'in-principle' guarantee of publication, no matter how strong or weak the results turn out to be. This should reduce the unconscious temptation to warp the data analysis, says Pashler. At the same time, he adds, it should keep peer reviewers from discounting a study's results or complaining after results are known. “People are evaluating methods without knowing whether they're going to find the results congenial or not,” he says. “It should create a much higher level of honesty among referees.” More than 20 journals are offering or plan to offer some format of registered reports.


Team of rivals

When it comes to replications and controversial topics, a good debiasing approach is to bypass the typical academic back-and-forth and instead invite your academic rivals to work with you. An adversarial collaboration has many advantages over a conventional one, says Daniel Kahneman, a psychologist at Princeton University in New Jersey. “You need to assume you're not going to change anyone's mind completely,” he says. “But you can turn that into an interesting argument and intelligent conversation that people can listen to and evaluate.” With competing hypotheses and theories in play, he says, the rivals will quickly spot flaws such as hypothesis myopia, asymmetric attention or just-so storytelling, and cancel them out with similar slants favouring the other side.

Psychologist Eric-Jan Wagenmakers of the University of Amsterdam has engaged in this sort of proponent–sceptic collaboration, when he teamed up with another group in an attempt(12) to replicate its research suggesting that horizontal eye movements help people to retrieve events from their memory. It is often difficult to get researchers whose original work is under scrutiny to agree to this kind of adversarial collaboration, he says. The invitation is “about as attractive as putting one's head on a guillotine — there is everything to lose and not much to gain”. But the group that he worked with was eager to get to the truth, he says. In the end, the results were not replicated. The sceptics remained sceptical, and the proponents were not convinced by a single failure to replicate. Yet this was no stalemate. “Although our adversarial collaboration has not resolved the debate,” the researchers wrote, “it has generated new testable ideas and has brought the two parties slightly closer.” Wagenmakers suggests several ways in which this type of collaboration could be encouraged, including a prize for best adversarial collaboration, or special sections for such collaborations in top journals.


Blind data analysis

One debiasing procedure has a solid history in physics but is little known in other fields: blind data analysis (see page 187). The idea is that researchers who do not know how close they are to desired results will be less likely to find what they are unconsciously looking for(13).

One way to do this is to write a program that creates alternative data sets by, for example, adding random noise or a hidden offset, moving participants to different experimental groups or hiding demographic categories. Researchers handle the fake data set as usual — cleaning the data, handling outliers, running analyses — while the computer faithfully applies all of their actions to the real data. They might even write up the results. But at no point do the researchers know whether their results are scientific treasures or detritus. Only at the end do they lift the blind and see their true results — after which, any further fiddling with the analysis would be obvious cheating.

Perlmutter used this method for his team's work on the Supernova Cosmology Project in the mid-2000s. He knew that the potential for the researchers to fool themselves was huge. They were using new techniques to replicate estimates of two crucial quantities in cosmology — the relative abundances of matter and of dark energy — which together reveal whether the Universe will expand forever or eventually collapse into a Big Crunch. So their data were shifted by an amount known only to the computer, leaving them with no idea what their findings implied until everyone agreed on the analyses and the blind could be safely lifted. After the big reveal, not only were the researchers pleased to confirm earlier findings of an expanding Universe(14), Perlmutter says, but they could be more confident in their conclusions. “It's a lot more work in some sense, but I think it leaves you feeling much safer as you do your analysis,” he says. He calls blind data analysis “intellectual hygiene, like washing your hands”.

Data blinding particularly appeals to young researchers, Perlmutter says — not least because of the sense of suspense it gives. He tells the story of a recent graduate student who had spent two years under a data blind as she analysed pairs of supernova explosions. After a long group meeting, Perlmutter says, the student presented all her analyses and said that she was ready to unblind if everyone agreed.

“It was 6 o'clock in the evening and time for dinner,” says Perlmutter. And everyone in the audience said, “If the result comes out wrong, it's going to be a very disappointing evening, and she's going to have to think really hard about what she's going to do with her PhD thesis. Maybe we should wait until morning.”

“And we all looked at each other, and we said, 'Nah! Let's unblind now!' So we unblinded, and the results looked great, and we all cheered and applauded.”

Nature 526, 182–185 (08 October 2015) doi:10.1038/526182a

References
  1. Gelman, A. & Cai, C. J. Ann. Appl. Stat. 2, 536–549 (2008).
  2. Open Science Collaboration. Science http://dx.doi.org/10.1126/science.aac4716 (2015).
  3. Begley, C. G. & Ellis, L. M. Nature 483, 531–533 (2012).
  4. Ioannidis, J. P. A. et al. Nature Genet. 41, 149–155 (2009).
  5. Landy, J. F. & Goodwin, G. P. Perspect. Psychol. Sci. 10, 518–536 (2015).
  6. Hill, R. Paediatr. Perinatal Epidemiol. 18, 320–326 (2004).
  7. John, L. K., Loewenstein, G. & Prelec, D. Psychol. Sci. 23, 524–532 (2012).
  8. Fugelsang, J. A., Stein, C. B., Green, A. E. & Dunbar, K. N. Can. J. Exp. Psychol. 58, 86–95 (2004).
  9. Bakker, M. & Wicherts, J. M. Behav. Res. Meth. 43, 666–68 (2011).
  10. Platt, J. R. Science 146, 347–353 (1964).
  11. Taylor, R. C. & Ryan, M. J. Science 341, 273–274 (2013).
  12. Matzke, D. et al. J. Exp. Psychol. Gen. 144, e1–e15 (2015).
  13. MacCoun, R. & Perlmutter, S. in Psychological Science Under Scrutiny: Recent Challenges and Proposed Solutions (eds Lilienfeld, S. O. & Waldman, I.) (Wiley, in the press); Preprint available at http://ssrn.com/abstract=2563337
  14. Conley, A. et al. Astrophys. J. 644, 1–20 (2006).
Ευχαριστώ.
pipinos1976
Δημοσιεύσεις: 1194
Εγγραφή: 08 Απρ 2011, 23:52

Re: Επιστήμη

Δημοσίευση από pipinos1976 »

Ένα εξαιρετικό άρθρο για μια υπόθεση σχετική με την σήμανση και το DNA. Με λίγα λόγια: μετά από μια δολοφονία ανακάλυψαν ίχνη DNA και κατηγόρησαν ως θύτη έναν άνθρωπο που δεν είχε καμία σχέση με το έγκλημα. Το πρόβλημα ήταν ότι το DNA του μεταφέρθηκε στο σπίτι του θύματος μέσω κοινών επαφών (νοσοκομείο) και η αστυνομία, λόγω προϊστορίας, θεώρησε ότι ήταν ένας πιθανός θύτης.

How DNA Transfer Nearly Convicted an Innocent Man of Murder
How DNA Transfer Nearly Convicted an Innocent Man of Murder

Katie Worth

This investigation was published in partnership with The Marshall Project and FRONTLINE (PBS).

When the DNA results came back, even Lukis Anderson thought he might have committed the murder.

"I drink a lot," he remembers telling public defender Kelley Kulick as they sat in a plain interview room at the Santa Clara County, California, jail. Sometimes he blacked out, so it was possible he did something he didn't remember. "Maybe I did do it."

Kulick shushed him. If she was going to keep her new client off death row, he couldn't go around saying things like that. But she agreed. It looked bad.

Before he was charged with murder, Anderson was a 26-year-old homeless alcoholic with a long rap sheet who spent his days hustling for change in downtown San Jose. The murder victim, Raveesh Kumra, was a 66-year-old investor who lived in Monte Sereno, a Silicon Valley enclave 10 miles and many socioeconomic rungs away.

Around midnight on November 29, 2012, a group of men had broken into Kumra's 7,000-square-foot mansion. They found him watching CNN in the living room, tied him, blindfolded him, and gagged him with mustache-print duct tape. They found his companion, Harinder, asleep in an upstairs bedroom, hit her on the mouth, and tied her up next to Raveesh. Then they plundered the house for cash and jewelry.

After the men left, Harinder, still blindfolded, felt her way to a kitchen phone and called 911. Police arrived, then an ambulance. One of the paramedics declared Raveesh dead. The coroner would later conclude that he had been suffocated by the mustache tape.

Three and a half weeks later, the police arrested Anderson. His DNA had been found on Raveesh's fingernails. They believed the men struggled as Anderson tied up his victim. They charged him with murder. Kulick was appointed to his case.

Public defender Kelley Kulick was appointed to Lukis Anderson's case after he was charged with first-degree murder.
Carlos Chavarría/The Marshall Project

As they looked at the DNA results, Anderson tried to make sense of a crime he had no memory of committing.

"Nah, nah, nah. I don't do things like that," he recalls telling her. "But maybe I did."

"Lukis, shut up," Kulick says she told him. "Let's just hit the pause button till we work through the evidence to really see what happened."

What happened, although months would pass before anyone figured it out, was that Lukis Anderson's DNA had found its way onto the fingernails of a dead man he had never even met.

Back in the 1980s, when DNA forensic analysis was still in its infancy, crime labs needed a speck of bodily fluid—usually blood, semen, or spit—to generate a genetic profile.

That changed in 1997, when Australian forensic scientist Roland van Oorschot stunned the criminal justice world with a nine-paragraph paper titled "DNA Fingerprints from Fingerprints." It revealed that DNA could be detected not just from bodily fluids but from traces left by a touch. Investigators across the globe began scouring crime scenes for anything—a doorknob, a countertop, a knife handle—that a perpetrator may have tainted with incriminating "touch" DNA.

Everyone, including Anderson, leaves a trail of DNA everywhere they go.
Carlos Chavarría/The Marshall Project

Sometimes that DNA can end up at a crime scene.
Carlos Chavarría/The Marshall Project

But van Oorschot's paper also contained a vital observation: Some people's DNA appeared on things that they had never touched.

In the years since, van Oorschot's lab has been one of the few to investigate this phenomenon, dubbed "secondary transfer." What they have learned is that, once it's out in the world, DNA doesn't always stay put.

In one of his lab's experiments, for instance, volunteers sat at a table and shared a jug of juice. After 20 minutes of chatting and sipping, swabs were deployed on their hands, the chairs, the table, the jug, and the juice glasses, then tested for genetic material. Although the volunteers never touched each other, 50 percent wound up with another's DNA on their hand. A third of the glasses bore the DNA of volunteers who did not touch or drink from them.

Then there was the foreign DNA—profiles that didn't match any of the juice drinkers. It turned up on about half of the chairs and glasses, and all over the participants' hands and the table. The only explanation: The participants unwittingly brought with them alien genes, perhaps from the lover they kissed that morning, the stranger with whom they had shared a bus grip, or the barista who handed them an afternoon latte.

In a sense, this isn't surprising: We leave a trail of ourselves everywhere we go. An average person may shed upward of 50 million skin cells a day. Attorney Erin Murphy, author of Inside the Cell, a book about forensic DNA, has calculated that in two minutes the average person sheds enough skin cells to cover a football field. We also spew saliva, which is packed with DNA. If we stand still and talk for 30 seconds, our DNA may be found more than a yard away. With a forceful sneeze, it might land on a nearby wall.

To find out the prevalence of DNA in the world, a group of Dutch researchers tested 105 public items—escalator rails, public toilet door handles, shopping basket handles, coins. Ninety-one percent bore human DNA, sometimes from half a dozen people. Even items intimate to us—the armpits of our shirts, say—can bear other people's DNA, they found.

The itinerant nature of DNA has serious implications for forensic investigations. After all, if traces of our DNA can make their way to a crime scene we never visited, aren't we all possible suspects?

Forensic DNA has other flaws: Complex mixtures of many DNA profiles can be wrongly interpreted, certainty statistics are often wildly miscalculated, and DNA analysis robots have sometimes been stretched past the limits of their sensitivity.

But as advances in technology are solving some of these problems, they have actually made the problem of DNA transfer worse. Each new generation of forensic tools is more sensitive; labs today can identify people with DNA from just a handful of cells. A handful of cells can easily migrate.

A survey of the published science, interviews with leading scientists, and a review of thousands of pages of court and police documents associated with the Kumra case has elucidated how secondary DNA transfer can undermine the credibility of the criminal justice system's most-trusted tool. And yet, very few crime labs worldwide regularly and robustly study secondary DNA transfer.

This is partly because most forensic scientists believe DNA to be the least of their field's problems. They're not wrong: DNA is the most accurate forensic science we have. It has exonerated scores of people convicted based on more flawed disciplines like hair or bite-mark analysis. And there have been few publicized cases of DNA mistakenly implicating someone in a crime.

But, like most human enterprises, DNA analysis is not perfect. And without study, the scope and impact of that imperfection is difficult to assess, says Peter Gill, a British forensic researcher. He has little doubt that his field, so often credited with solving crimes, is also responsible for wrongful convictions.

"The problem is we're not looking for these things," Gill says. "For every miscarriage of justice that is detected, there must be a dozen that are never discovered."

The phone rang five times.

"Are you awake?" the dispatcher asked.

"Yeah," lied Corporal Erin Lunsford.

"Are you back on full duty or you still light duty?" she asked, according to a tape of the call.

Lunsford had been off crutches for two weeks already, but it was 2:15 am and pouring rain. Probably some downed tree needed to be policed. "Light duty," Lunsford said.

"Oh," she said. "Never mind."

"Why, what are you calling about?" he asked.

"We had a home invasion that turned into a 187," she said. Cop slang for murder.

"Shit, seriously?" Lunsford said, waking up.

Sergeant Erin Lunsford of the Los Gatos-Monte Sereno Police Department was the lead investigator in Kumra’s murder.
Carlos Chavarría/The Marshall Project

Lunsford had served all 15 of his professional years as a police officer at the Los Gatos–Monte Sereno Police Department, a 38-officer agency that policed two drowsy towns. He rose through the ranks and was working a stint in the department's detective bureau. He had mostly been investigating property crimes. Los Gatos, a wealthy bedroom community of Silicon Valley, averaged a homicide once every three or four years. Monte Sereno, a bedroom community of the bedroom community, hadn't had a homicide in roughly 20.

Lunsford got dressed. He drove through the November torrent. He spotted cop cars clustered around a brick and iron gate. An ambulance flashed quietly in the driveway. Beyond it, the lit Kumra mansion.

Lunsford's boss told him to take the lead on the investigation. The on-scene supervisor walked him through the house. Dressers emptied, files dumped. A cellphone in a toilet, pissed on. A refrigerator beeping every 10 seconds, announcing its doors were ajar. Raveesh’s body, heavyset and disheveled, on the floor near the kitchen. His eyes still blindfolded.

An investigator from the county coroner's office arrived and moved Kumra's body into a van. Lunsford followed her to the morgue for the autopsy. A doctor undressed the victim and scraped and cut his fingernails for evidence.

Lunsford recognized Raveesh, a wealthy businessman who had once owned a share of a local concert venue. Lunsford had come to the Kumra mansion a couple times on "family calls" that never amounted to anything: "Just people arguing," he recalled. He had also run into him at Goguen's Last Call, a dive frequented by Raveesh as a regular and Lunsford as a cop responding to calls. Raveesh was an affable extrovert, always buying rounds; the unofficial mayor of that part of town, Lunsford called him.

In the coming days, as Lunsford interviewed people who knew the Kumras, he was told that Raveesh also had relationships with sex workers. Raveesh and Harinder had divorced around 2010 after more than 30 years of marriage, but still lived together.

While Lunsford attended the autopsy, a team of gloved investigators combed the mansion. They tucked paper evidence into manila envelopes; bulkier items into brown paper bags. They amassed more than 100.

Teams specializing in crime scene investigations were first assembled over a century ago, after the French scientist Edmond Locard devised the principle that birthed the field of forensics: A perpetrator will bring something to a crime scene and leave with something from it. Van Oorschot's touch DNA discovery had unveiled the most literal expression imaginable of Locard's principle.

Like those early teams, the investigators in the Kumra mansion were looking for fingerprints, footprints, and hair. But unlike their predecessors, they devoted considerable time to thinking through everything the perpetrators may have touched.

Some perpetrators are giving thought to this as well. A 2013 Canadian study of 350 sexual homicides found that about a third of perpetrators appeared to have taken care not to leave DNA, killing their victims in tidier ways than beating or strangling, which are likely to leave behind genetic clues, for instance. And it worked: In those "forensically aware" cases, police solved the case 50 percent of the time, compared to 83 percent of their sloppier counterparts.

The men who killed Kumra seemed somewhat forensically aware, albeit clumsily. They had worn latex gloves through their rampage; a pile of them were left in the kitchen sink, wet and soapy, as though someone had tried to wash off the DNA.

In the weeks after the murder, Tahnee Nelson Mehmet, a criminalist at the county crime lab, ran dozens of tests on the evidence collected from the Kumra mansion. Most only revealed DNA profiles consistent with Raveesh or Harinder.

But in her first few batches of evidence, Mehmet hit forensic pay dirt: a handful of unknown profiles—including on the washed gloves. She ran them through the state database of people arrested for or convicted of felonies and got three hits, all from the Bay Area: 22-year-old DeAngelo Austin on the duct tape; 21-year-old Javier Garcia on the gloves; and, on the fingernail clippings, 26-year-old Lukis Anderson.

Within weeks of the DNA hits, Lunsford had plenty of evidence implicating Austin and Garcia: Both were from Oakland, but a warrant for their cellphone records showed they'd pinged towers near Monte Sereno the night of the homicide. Police records showed that Austin belonged to a gang linked to a series of home burglaries. And most damning of all, Austin's older sister, a 32-year-old sex worker named Katrina Fritz, had been involved with Raveesh for 12 years. Police had even found her phone backed up on Raveesh's computer. Eventually she would admit that she had given her brother a map of the house.

Connecting Anderson to the crime proved trickier. There were no phone records showing he had traveled to Monte Sereno that night. He wasn't associated with a gang. But one thing on his rap sheet drew Lunsford's attention: A felony residential burglary.

Eventually Lunsford found a link. A year earlier, Anderson had been locked up in the same jail as a friend of Austin's named Shawn Hampton. Hampton wore an ankle monitor as a condition of his parole. It showed that two days before the crime he had driven to San Jose. He made a couple of stops downtown, right near Anderson's territory.

It started to crystallize for Lunsford: When Austin was planning the break-in, he wanted a local guy experienced in burglary. So Hampton hooked him up with his jail buddy Anderson.

Anderson had recently landed back in jail after violating his probation on the burglary charge. Lunsford and his boss, Sergeant Mike D'Antonio, visited him there. They taped the interview.

"Does this guy look familiar to you? What about this lady?" Lunsford said, laying out pictures of the victims on the interview room table.

"I don't know, man," Anderson said.

Lunsford pulled out a picture of Anderson's mother.

"All right, what about this lady here? You don't know who she is?" Lunsford said.

Anderson met Lunsford's sarcasm with silence.

Lunsford set down a letter from the state of California showing the database match between Anderson's DNA and the profile found on the victim's fingernails.

"This starting to ring some bells?" Lunsford said.

"My guess is you didn't think anybody was gonna be home," D'Antonio said. "My guess is it went way farther than you ever thought it would go."

"I don't know what you're talking about, sir," Anderson said.

"You do," Lunsford said. "You won't look at their pictures. The only picture you looked at good was your mom."

Finally, D'Antonio took a compromising tone.

"Lukis, Lukis, Lukis," he said. "I don't have a crystal ball to know what the truth is. Only you do. And in all the years I've been doing this I've never seen a DNA hit being wrong."

Anderson had been in jail on the murder charge for over a month when a defense investigator dropped a stack of records on Kulick's desk. Look at them, the investigator said. Now.

They were Anderson's medical records. Because his murder charge could carry the death penalty, Kulick had the investigator pull everything pertinent to Anderson's medical history, including his mental health, in case they had to ask for leniency during sentencing.

Documents from Lukis Anderson's case on public defender Kelley Kulick's desk.
Carlos Chavarría/The Marshall Project

She suspected Anderson could be a good candidate for such leniency. He spent much of his childhood homeless. In early adulthood, he was diagnosed with a mental health disorder and diabetes. And he had developed a mighty alcohol addiction. One day, while drunk, he stepped off a curb and into the path of a moving truck. He survived, but his memory was never quite right again. He lost track of days, sometimes several in a row.

That's not to say his life was bleak. He made friends easily. He had a coy sense of humor and dimples that shone like headlights. His buddies, many on the streets themselves, looked after him, as did some downtown shopkeepers. Kulick and her investigator had spoken to several of them. They shook their heads. Anderson might be a drunk, they said, but he wasn't a killer.

His rap sheet seemed to agree. It was filled with petty crimes: drunk in public, riding a bike under the influence, probation violations. The one serious conviction—the residential burglary that had caught Lunsford's attention—seemed more benign upon careful reading. According to the police report, Anderson had drunkenly broken the front window of a home and tried to crawl through. The horrified resident had pushed him back out with blankets. Police found him a few minutes later standing on the sidewalk, dazed and bleeding. Though nothing had been stolen, he had been charged with a felony and pleaded no contest. His DNA was added to the state criminal database.

The medical records showed that Anderson was also a regular in county hospitals. Most recently, he had arrived in an ambulance to Valley Medical Center, where he was declared inebriated nearly to the point of unconsciousness. Blood alcohol tests indicated he had consumed the equivalent of 21 beers. He spent the night detoxing. The next morning he was discharged, somewhat more sober.

The date on that record was November 29. If the record was right, Anderson had been in the hospital precisely as Raveesh Kumra was suffocating on duct tape miles away.

Kulick remembers turning to the investigator, who was staring back at her. She was used to alibis being partial and difficult to prove. This one was signed by hospital staff. More than anything, she felt terrified. "To know that you have a factually innocent client sitting in jail facing the death penalty is really scary," she said later. "You don't want to screw up."

She knew Lunsford and the prosecutors would try to find holes: Perhaps the date on the record was wrong, or someone had stolen his ID, or there was more than one Lukis Anderson.

So she and the investigator systematically retraced his day. Anderson had only patchy recollections of the night in question. But they found a record that a 7-Eleven clerk called authorities at 7:54 pm complaining that Anderson was panhandling. He moved on before the police arrived.

His meanderings took him four blocks east, to S&S Market. The clerk there told Kulick that Anderson sat down in front of the store at about 8:15 pm, already drunk, and got drunker. A couple of hours later, he wandered into the store and collapsed in an aisle. The clerk called the authorities.

The police arrived first, followed by a truck from the San Jose Fire Department. A paramedic with the fire department told Kulick he had picked up Anderson drunk so often that he knew his birth date by heart. Two other paramedics arrived with an ambulance. They wrestled Anderson onto a stretcher and took him to the hospital. According to his medical records, he was admitted at 10:45 pm. The doctor who treated him said Anderson remained in bed through the night.

Harinder Kumra had said the men who killed Raveesh rampaged through her house sometime between 11:30 pm and 1:30 am.

Kulick called the district attorney's office. She wanted to meet with them and Lunsford.

In 2008, German detectives were on the trail of the "Phantom of Heilbronn." A serial killer and thief, the Phantom murdered immigrants and a cop, robbed a gemstone trader, and munched on a cookie while burglarizing a caravan. Police mobilized across borders, offered a large reward, and racked up more than 16,000 hours on the hunt. But they struggled to discern a pattern to the crimes, other than the DNA profile the Phantom left at 40 crime scenes in Germany, France, and Austria.

At long last, they found the Phantom: An elderly Polish worker in a factory that produced the swabs police used to collect DNA. She had somehow contaminated the swabs as she worked. Crime scene investigators had, in turn, contaminated dozens of crime scenes with her DNA.

Contamination, the unintentional introduction of DNA into evidence by the very people investigating the crime, is the best understood form of transfer. And after Lunsford heard Kulick's presentation—then retraced Anderson's day himself, concluded he had jailed an innocent man, and felt sick to his stomach for a while—he counted contamination among his leading theories.

As the Phantom of Heilbronn case demonstrated, contamination can happen long before evidence arrives in a lab. A 2016 study by Gill, the British forensic researcher, found DNA on three-quarters of crime scene tools he tested, including cameras, measuring tapes, and gloves. Those items can pick up DNA at one scene and move it to the next.

Once it arrives in the lab, the risk continues: One set of researchers found stray DNA in even the cleanest parts of their lab. Worried that the very case files they worked on could be a source of contamination, they tested 20. Seventy-five percent held the DNA of people who hadn't handled the file.

In Santa Clara County, the district attorney's office reviewed the Kumra case and found no obvious evidence of errors or improper use of tools in the crime lab. They checked if Anderson's DNA had shown up in any other cases the lab had recently handled, and inadvertently wandered into the Kumra case. It had not.

So they began investigating a second theory: That Raveesh and Anderson somehow met in the hours or days before the homicide, at which point Anderson's DNA became caught under Raveesh's fingernails.

"We are convinced that at some point—we just don't know when in the 24 hours, 48 hours, or 72 hours beforehand—that their paths crossed," deputy district attorney Kevin Smith told a San Francisco Chronicle reporter.

There now exists a small pile of studies exploring how DNA moves: If a man shakes someone's hand and then uses the restroom, could their DNA wind up on his penis? ( Yes.) If someone drags another person by the ankles, how often does their profile clearly show up? (40 percent of the time.) And, of utmost relevance to Lukis Anderson, how many of us walk around with traces of other people's DNA on our fingernails? (1 in 5.)

Whether someone's DNA moves from one place to another—and then is found there—depends on a handful of factors: quantity (two transferred cells are less likely to be detected than 2,000), vigor of contact (a limp handshake relays less DNA than a bone-crushing one), the nature of the surfaces involved (a tabletop's chemical content affects how much DNA it picks up), and elapsed time (we're more likely carrying DNA of someone we just hugged than someone we hugged hours ago, since foreign DNA tends to rub off over time).

Then there's a person's shedding status: "Good" shedders lavish their DNA on their environment; "poor" shedders move through the world virtually undetectable, genetically speaking. In general, flaky, sweaty, or diseased skin is thought to shed more DNA than healthy, arid skin. Nail chewers, nose pickers, and habitual face touchers spread their DNA around, as do hands that haven't seen a bar of soap lately—discarded DNA can accumulate over time, and soap helps wash it away.

And some people simply seem to be naturally superior shedders. Mariya Goray, a forensic science researcher in van Oorschot's lab who coauthored the juice study with him, has found one of her colleagues to be an outrageously prodigious shedder. "He's amazing," she said, her voice tinged with admiration. "Maybe I'll do a study on him. And the study will just be called, 'James.'"

She hopes to develop a test to determine a person's shedder status, which could be deployed to assess a suspect's claims that their DNA arrived somewhere innocently.

Such a test could have been useful in the case of David Butler, an English cabdriver. In 2011, DNA found on the fingernails of a woman who had been murdered six years earlier was run through a database and matched Butler's. He swore he'd never met the woman. His defense attorney noted that he had a skin condition so severe that fellow cabbies had dubbed him "Flaky." Perhaps he had given a ride to the actual murderer that day, who inadvertently picked up Butler's DNA in the cab and later deposited it on the victim, they theorized.

Investigators didn't buy the explanation, but jurors did. Butler was acquitted after eight months in jail. Upon release, he excoriated police for their blind faith in the evidence.

"DNA has become the magic bullet for the police," Butler told the BBC. "They thought it was my DNA, ergo it must be me."

Traditional police work would have never steered police to Anderson. But the DNA hit led them to seek other evidence confirming his guilt. "It wasn't malicious. It was confirmation bias," Kulick says. "They got the DNA, and then they made up a story to fit it."

Had the case gone to trial, jurors may well have done the same. A 2008 series of studies by researchers at the University of Nevada, Yale, and Claremont McKenna College found that jurors rated DNA evidence as 95 percent accurate and 94 percent persuasive of a suspect's guilt.

Eleven leading DNA transfer scientists contacted for this story were in consensus that the criminal justice system must be willing to question DNA evidence. They were also in agreement about whose job it should be to navigate those queries: forensic scientists.

As it stands, forensic scientists generally stick to the question of source (whose DNA is this?) and leave activity (how did it get here?) for judges and juries to wrestle with. But the researchers contend that forensic scientists are best armed with the information necessary to answer that question.

Consider a case in which a man is accused of sexually assaulting his stepdaughter. He looks mighty guilty when his DNA and a fragment of sperm is found on her underwear. But jurors might give the defense more credence if a forensic scientist familiarized them with a 2016 Canadian study showing that fathers' DNA is frequently found on their daughters' clean underwear; occasionally, a fragment of sperm is there too. It migrates there in the wash.

This shift—from reporting on who to reporting on how—has been encouraged by the European Network of Forensic Science Institutes. But the shift has been slow on that continent and virtually nonexistent in the United States, where defense attorneys have argued that forensic scientists—in many communities employed by the prosecutor's office or police department—should be careful to stick to the facts rather than make conjectures.

"The problem is that when forensic scientists get involved in those determinations, they're wrought with confirmation bias," says Jennifer Friedman, a Los Angeles County public defender.

Meanwhile, forensic scientists in the US have resisted the shift, arguing they lack the data to confidently testify about how DNA moves.

Van Oorschot and Gill concede this point. Only a handful of labs in Europe and Australia regularly research transfer. The forensic scientists interviewed for this story say they are not aware of any lab or university in the US that routinely does so.

Funding gets some of the blame: The Australian labs and some European labs get government dollars to study DNA transfer. But British forensic researcher and professor Georgina Meakin of University College London says she must find alternative ways to pay for her own transfer research; the Centre for Forensic Sciences, where Meakin works, has launched a crowdfunding page for a new lab to study trace evidence transfer. In the US, all the grants from the National Science Foundation, the National Institute of Standards and Technology, and the National Institute of Justice for forensics research put together likely sum just $13.5 million a year, according to a 2016 report on forensic science by the President's Council of Advisors on Science and Technology (PCAST); of that, very little has been spent looking into DNA transfer.

"The folks with the greatest interest in making sure forensic science isn't misused are defendants," says Eric Lander, principal leader of the Human Genome Project, who cochaired PCAST under President Obama. "Defendants don't have an awful lot of power."

In 2009, after issuing a report harshly criticizing the paucity of science behind most forensics, the National Academy of Sciences urged Congress to create a new, independent federal agency to oversee the field. There was little political appetite to do that. Instead, in 2013, Obama created a 40-member National Commission on Forensic Science, filled it with people who saw forensics from radically different perspectives—prosecutors, defense attorneys, academics, lab analysts, and scientists—and made a rule that all actions must be approved by a supermajority. Naturally, the commission got off to a slow start. But ultimately it produced more than 40 recommendations and opinions. These lacked the teeth of a regulatory ruling, but the Justice Department was obligated to respond to them.

At the beginning, most of the commission's efforts were focused on improving other disciplines, "because DNA testing as a whole is so much better than much forensic science that we had focused a lot of our attention elsewhere," says US district judge Jed Rakoff, a member of the commission.

According to Rakoff and other members interviewed, the commission was just digging into issues touching on DNA transfer when attorney general Jeff Sessions took office last year. In April 2017, his department announced it would not renew the commission's charter. It never met again.

Then, in August, President Trump signed the Rapid DNA Act of 2017, allowing law enforcement to use new technology that produces DNA results in just 90 minutes. The bill had bipartisan support and received little press. But privacy advocates worry it may usher in an era of widespread "stop and spit" policing, in which law enforcement asks anyone they stop for a DNA sample. This is already occurring in towns in Florida, Connecticut, North Carolina, and Pennsylvania, according to reporting by ProPublica. If law enforcement deems there is probable cause, they can compel someone to provide DNA; otherwise, it is voluntary.

If stop-and-spit becomes more widely used and police databases swell, it could have a disproportionate impact on African Americans and Latinos, who are more often searched, ticketed, and arrested by police. In most states, a felony arrest is enough to add someone in perpetuity to the state database. Just this month, the California Supreme Court declined to overturn a provision requiring all people arrested or charged for a felony to give up their DNA; in Oklahoma, the DNA of any undocumented immigrant arrested on suspicion of any crime is added to a database. Those whose DNA appears in a database face a greater risk of being implicated in a crime they didn't commit.

It was Lunsford who figured it out in the end.

He was reading through Anderson's medical records and paused on the names of the ambulance paramedics who picked up Anderson from his repose on the sidewalk outside S&S Market. He had seen them before.

He pulled up the Kumra case files. Sure enough, there were the names again: Three hours after picking up Anderson, the two paramedics had responded to the Kumra mansion, where they checked Raveesh's vitals.

The prosecutors, defense attorney, and police agree that somehow, the paramedics must have moved Anderson's DNA from San Jose to Monte Sereno. Santa Clara County District Attorney Jeff Rosen has postulated that a pulse oximeter slipped over both patients' fingers may have been the culprit; Kulick thinks it could have been their uniforms or another piece of equipment. It may never be known for sure.

A spokesman for Rural/Metro Corporation, where the paramedics worked, told San Francisco TV station KPIX5 that the company had high sanitation standards, requiring paramedics to change gloves and sanitize the vehicles.

Deputy District Attorney Smith framed the incident as a freak accident. "It's a small world," he told a San Francisco Chronicle reporter.

The trial against the other men implicated in the case moved forward. Austin's older sister, Fritz, testified in trials against him and Garcia. She also testified against a third man, Marcellous Drummer, whose DNA had been found on evidence from the Kumra crime scene months after the initial hits.

During the trials, Harinder Kumra told jurors she was still haunted by the image of the man who split her lip open. "Every day I see that face. Every night when I sleep, when there's a noise, I think it's him," she said. She has sold the mansion. Members of the Kumra family declined to comment for this story.

The DNA in the case did not go uncontested. Garcia's attorney argued that, like Anderson's, Garcia's DNA had arrived at the scene inadvertently. According to the attorney, Austin had come by the trap house where Garcia hung out to pick up Garcia's cousin; the cousin was in on the crime and had borrowed a box of gloves that Garcia frequently used, which is why Garcia's DNA was found on the gloves at the crime scene; the reason Garcia's cellphone pinged towers near Monte Sereno was because his cousin had borrowed it that night. However, the cousin died within weeks of the crime, and therefore wasn't questioned or investigated.

The entrance of Raveesh Kumra's residence, in Monte Sereno, California, a Silicon Valley enclave.
Carlos Chavarría/The Marshall Project

Jurors were not persuaded and convicted Garcia, along with Drummer and Austin, of murder, robbery of an inhabited place, and false imprisonment.

"I get it," says Garcia's attorney Christopher Givens. "People hear DNA and say, oh, sure you loaned your phone to someone."

A jury could have had the same reaction to Anderson, had his alibi not been discovered, Givens says. "The sad thing is, I wouldn't be surprised if he actually pleaded to something. They probably would have offered him a deal, and he would have been scared enough to take it."

Garcia received a sentence of 37 years to life; Drummer and Austin's sentences were enhanced for gang affiliation to life without parole. Garcia and Austin have appeals pending. Fritz received a reduced sentence for her testimony. In 2017 she was released from jail after spending four years in custody.

Lunsford received accolades for his detective work in the Kumra case and has since been promoted to sergeant; his boss, D'Antonio, is now a captain. But Lunsford says his perspective on DNA has forever changed. "We shook hands, and I transferred on you, you transferred on me. It happens. It's just biological," he says.

Based on interviews with prosecutors, defense lawyers and DNA experts, Anderson's case is the clearest known case of DNA transference implicating an innocent man. It's impossible to say how often this kind of thing happens, but law enforcement officials argue that it is well outside the norm. "There is no piece of evidence or science which is absolutely perfect, but DNA is the closest we have," says District Attorney Rosen. "Mr. Anderson was a very unusual situation. We haven't come across it again."

Van Oorschot, the forensic science researcher whose 1997 paper revolutionized the field, cautions against disbelieving too much in the power of touch DNA to solve crimes. "I think it's made a huge impact in a positive way," he says. "But no one should ever rely solely on DNA evidence to judge what's going on."

Anderson's case has altered the criminal justice system in a small but important way, says Kulick.

"As defense attorneys, we used to get laughed out of the courtroom if in closing arguments we argued transfer," she says. "That was hocus-pocus. That was made up fiction. But Lukis showed us that it's real."

The cost of that demonstration was almost half a year of Anderson's life.

Being accused of murder was "gut-wrenching," he says. It pains him that he questioned his own innocence, even though, he says, "deep down I knew I didn't do it."

After he was released, Anderson returned to the streets. As is typical in cases where people are wrongly implicated in a crime, he received no compensation for his time in jail. He has continued to struggle with alcohol but has stayed out of major legal trouble since. He's applying for Social Security, which could help him finally secure housing.

Anderson feels certain he's not the only innocent person to be locked up because of transfer. He considers himself blessed by God to be free. And he has advice about DNA evidence: "There's more that's gotta be looked at than just the DNA," he says. "You've got to dig deeper a little more. Re-analyze. Do everything all over again … before you say 'this is what it is.' Because it may not necessarily be so."
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pipinos1976
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Άλλο ένα εξαιρετικά ενδιαφέρον άρθρο σχετικά με το πώς μαθαίνει ο άνθρωπος και πώς τα μηχανήματα. Αξίζει να το διαβάσετε.

How babies learn – and why robots can’t compete
How babies learn – and why robots can’t compete

Alex Beard

Deb Roy and Rupal Patel pulled into their driveway on a fine July day in 2005 with the beaming smiles and sleep-deprived glow common to all first-time parents. Pausing in the hallway of their Boston home for Grandpa to snap a photo, they chattered happily over the precious newborn son swaddled between them.

This normal-looking suburban couple weren’t exactly like other parents. Roy was an AI and robotics expert at MIT, Patel an eminent speech and language specialist at nearby Northeastern University. For years, they had been planning to amass the most extensive home-video collection ever.

From the ceiling in the hallway blinked two discreet black dots, each the size of a coin. Further dots were located over the open-plan living area and the dining room. There were 25 in total throughout the house – 14 microphones and 11 fish-eye cameras, part of a system primed to launch on their return from hospital, intended to record the newborn’s every move.

It had begun a decade earlier in Canada – but in fact Roy had built his first robots when he was just was six years old, back in Winnipeg in the 1970s, and he’d never really stopped. As his interest turned into a career, he wondered about android brains. What would it take for the machines he made to think and talk? “I thought I could just read the literature on how kids do it, and that would give me a blueprint for building my language and learning robots,” Roy told me.

Over dinner one night, he boasted to Patel, who was then completing her PhD in human speech pathology, that he had already created a robot that was learning the same way kids learn. He was convinced that if it got the sort of input children get, the robot could learn from it.

Toco was little more than a camera and microphone mounted on a Meccano frame, and given character with ping-pong-ball eyes, a red feather quiff and crooked yellow bill. But it was smart. Using voice recognition and pattern-analysing algorithms, Roy had painstakingly taught Toco to distinguish words and concepts within the maelstrom of everyday speech. Where previously computers learned language digitally, understanding words in relation to other words, Roy’s breakthrough was to create a machine that understood their relationship to objects. Asked to pick out the red ball among a range of physical items, Toco could do it.

Patel ran an infant lab in Toronto and Roy flew up there to see what he could learn. Observing the mothers and babies at play, he realised he’d been teaching Toco badly. “I hadn’t structured my learning algorithm correctly,” he explained to Wired magazine in 2007. “Every parent knows that when you’re talking to an 11-month-old, you stay on a very tight subject. If you’re talking about a cup, you stick to a cup and you interact with the cup until the baby gets bored and then the cup goes away.”

His robot had been searching through every phoneme it had ever heard when it was learning a new object, but Roy tweaked its algorithm to give extra weight to its most recent experiences, and began to feed it audio from Patel’s baby lab recordings. Suddenly Toco began to build a basic vocabulary at a rate never seen before in AI research. His dream of “a robot that can learn by listening and seeing objects” felt closer than ever. But it needed to feed on recordings, and these were hard to find.

No one had ever truly studied “in the wild” what happens to a child in those first crucial years. The norm for researchers were weekly hour-long observation sessions – that was how Patel studied mothers and infants in her lab. If you were going to study the way a baby learned to talk, you’d need someone eccentric enough to rig up a house with hidden recording devices.

I first heard about Patel and Roy’s experiment while working as a teacher at a London comprehensive. Most of the children I taught arrived at school aged 11 far behind where they we were expected to be with their language, and as a novice I struggled to help them catch up. Whereas everything I tried seemed outdated, Roy’s approach was scientific. I hoped his findings would unlock a secret that could help kids to realise their full potential. If we could create machines that learned like humans, could we also develop ones that could help us perfect human learning?

Before pressing record, Roy and Patel agreed some ground rules. The recordings would be available only to their most trusted inner circle of researchers. If at any time they felt uncomfortable with the filming, they would junk the footage. When privacy was required, the system could be temporarily shut down. It was a leap of faith, but they agreed it was worth it. Their experiment had the power to unlock new insight into the workings of the infant mind.

Toco was Pinocchio to Roy’s Geppetto. But whereas he was wondering what real kids could teach robots, I wanted to know if those home videos might hint at how to enhance learning for the youngest humans.

In 1995, two researchers, Betty Hart and Todd Risley, published the results of a study in which they trailed 42 Kansas City families to compare the experiences of preschoolers from poor families with their richer peers. Starting when the infants were nine months old, they observed them regularly over a two-and-a-half-year period, recording and transcribing all parent-and-child speech during their hour-long visits. The findings were stark. The number of words a child heard by their third birthday strongly predicted academic success aged nine. The difference was barely fathomable. They estimated that, at the age of four, the richest kids had heard 30m more words than the poorest.

“The problem of skill differences among children at the time of school entry is bigger, more intractable and more important than we thought,” Hart and Risley said. Their research showed it was worth intervening as early as possible. “The longer the effort is put off, the less possible change becomes.”

If the problem was stark, the solution seemed simple. There was a gap, and it had to be filled with words. Hart and Risley’s findings fuelled a word-rush that endures today. Across the English-speaking world, parents flocked to buy flashcards and brain trainers for their tots.

But my experience in the classroom suggested that the interpretation was a little simplistic, equating the development of the human mind with the inputs and outputs of computers. I suspected that there was more to infant learning than the quantity of words you heard.

A professor of early-childhood development at Temple University in Pennsylvania, Kathy Hirsh-Pasek, seemed to agree. She had written that “just as the fast food industry fills us with empty calories, what we call the ‘learning industry’ has convinced many among us that the memorisation of content is all that is needed for learning success and joyful lives”. She had also written an influential book that laid out her reservations about the word-rush: Einstein Never Used Flashcards: How Children Really Learn and Why They Need to Play More and Memorize Less. I thought she might have some answers.

Hirsh-Pasek is legendary in the field of early child development. The author of 12 books and hundreds of academic articles, she is a distinguished faculty fellow who runs Temple’s Infant and Child Laboratory, whose slogan is “Where Children Teach Adults”.

At the lab, scientists were putting tiny humans through their paces. Researchers had developed ingenious experiments that measured changes in heart rate to show some of the things that eight-month-olds already knew. “They know the mobile won’t fall on them,” said Hirsh-Pasek. “They know that if I drop this plate on the table, the plate won’t go through the table. That’s amazing. They know that if I’m sitting across from you, and you can’t see the bottom part of my body, I still have one.”

Until recently, scientists had tended to think of infants as irrational, illogical and egocentric. In his Principles of Psychology in 1890, William James had described babies’ experience of sensory overload: “The baby, assailed by eyes, ears, nose, skin, and entrails at once, feels it all as one great blooming, buzzing confusion.” This understanding had contributed to a mechanistic view of learning, and the idea that the sheer repetition of words was what mattered most. But it wasn’t true.

Even in utero, babies are learning. At that stage, they pick up sounds. One-hour-olds can distinguish their mother’s voice from another person’s. They arrive in the world with a brain primed to learn through sensory stimulation. We are natural-born explorers, ready made for scientific inquiry. We have to understand this if we were to realise our learning potential.

“We enter the world ready to ‘read the perfect cues out of the environment’,” said Hirsh-Pasek. I thought back to Toco. He read the environment, too – or at least what his eye cameras saw and ear microphones heard. But robots can only reach out in ways they have been programmed to, can only learn from stimuli they were instructed to pay attention to. It limits them to a small range of experiences that would shape their behaviours. There is no meaning in their methods. Babies, on the other hand, are social learners.

“We arrive ready to interact with other humans and our culture,” said Hirsh-Pasek. The real genius of human babies is not simply that they learn from the environment – other animals can do that. Human babies can understand the people around them and, specifically, interpret their intentions.

As we evolved, social and cultural transmission became possible. Language was our starting point – the possibility of two beings ascribing a shared meaning to an otherwise abstract concept or symbol. Couldn’t we see the beginnings of this in babies’ behaviour? Infants under a year engaged in proto-conversations with carers. They babbled away, held eye contact, exchanged things, mimicked their expressions or actions. They also experimented with tools, sticking them in their mouths, bashing them on things.

At the Max Planck Institute for Evolutionary Anthropology in Leipzig, Prof Michael Tomasello wrote that our young learn “in an environment of ever-new artefacts and social practices, which, at any one time, represent something resembling the entire collective wisdom of the entire social group throughout its entire cultural history”.

If all of us are to achieve our potential as learners, the question we have to answer is how we ought to shape this environment. Human brains have specially adapted to learn. Our long period of immaturity is a risky evolutionary strategy, making us vulnerable early on to predators or sickness, and delaying for many years our capacity to reproduce, but the payoff is immense. We can actively incorporate enormous amounts of the latest information from our environment and social group into our cognitive development.

Scientists have long recognised the nature-v-nurture debate as fallacy. A huge amount of our brain development takes place in the first three years. In those years, the brain grows in relation to the environment, forming itself in interaction with sensory experience. As Hart and Risley showed in their study of the word gap, that experience can have a huge effect on who that person becomes.

We have evolved to be a species of teachers and learners. Our ability to understand other people arrives around the ninth month, at a moment in their development at which babies begin to check the attention of others by holding or pointing at objects. At a year, they can follow another’s attention, gazing at, touching or listening to the same thing. At 15 months they can direct it. Listen to that! Look over there! Shared attention is the starting point of conscious human learning. It is why infants don’t learn to talk from video, audio or overhearing parental conversations. We haven’t evolved to. That’s why it matters that we talk to our children. It’s also why we can’t learn from robots – yet.

The implication for understanding how we learn sounds like common sense: each generation ought to ensure the next is steeped in their earliest years in the tools, symbols and social practices of the current culture.

In search of the kind of learning environment that might best cultivate our natural abilities, I visited Pen Green Early Childhood Centre, a specialist centre in early child development in the Northamptonshire town of Corby. The outdoor space was cold and overcast, but that wasn’t deterring the children. By a bamboo bush, two small boys splashed at an ever-running tap. “Don’t get me wet!” they squeaked with delight. A teacher bent down to comfort a toddler in a “Be Fast or Come Last” T-shirt. Four small girls were deep in a serious conversation while absent-mindedly digging sand into colourful buckets.

Pen Green had a global reputation for excellence in early child development and family support, a prototype that had inspired successive early-years interventions by government, including Sure Start and Early Excellence. I spoke to the director, Angela Prodger. She had just taken over from the legendary Margy Whalley, who set up the centre in 1983. In the 1980s, Corby was among the UK’s poorest towns, its population of Scottish migrant workers unmoored by the closure of the steelworks for which they had moved south – 11,000 people had been made redundant. The centre was intended as a lifeline for the next generation. Today it serves 1,400 of the UK’s least well-off households.

I asked her about language learning. We knew words mattered, but I’d not heard much talk at playtime. “If we’re not addressing personal, social, emotional development first, you’re not ready to learn,” said Prodger. She explained that before children could acquire the tools of speech and language, you had to ensure they felt a sense of “being and belonging”. Too frequently, she thought, our approaches to early learning skipped these steps. It sounded to me like a nice-to-have, not an essential, but research showed otherwise.

In the 1950s, British psychoanalyst John Bowlby proposed a theory of “attachment”. He hypothesised that infants, unable to regulate their own feelings, were prone to get upset when they were hungry, sad or lonely. A carer was needed to help them “co-regulate” their feelings, which over time would teach the child to self-regulate, provided their early experiences helped them do so. If negative experiences weren’t alleviated with love from a parental figure, they could become established.

The implications for children growing up in poverty-stricken or traumatic environments were significant. This was why Pen Green took care to put the being and belonging of its children first. It also explained some of the behaviour at the school where I had taught. Where I’d missed the signs of kids responding to the stress of the environment in which they were growing up, at Pen Green they worked closely with carers to ensure children built strong, nurturing relationships that would help them thrive in the nursery and ultimately at school. I’d always believed children wanted to wreak havoc. It had never occurred to me that they might simply have been conditioned by their environment to act in a certain way. “Behaviour is always just a sign of children trying to tell you something,” said Prodger.

As we toured the building, Prodger told me that the skill of the practitioners at Pen Green was in learning to attend to what was going on in the minds of the kids, and interpreting it as evidence of what the youngsters were signalling, even before they were able to verbalise it themselves. Children were constantly communicating with us, she told me. We just had to learn to understand.

“It’s about looking,” Prodger said. “What are the children trying to explore? What are they trying to find out?”

Creative play is the foundation on which creativity, language, maths and science are built. If you start too early with flashcards, you lose this developmental stage. “It’s about being free,” Prodger said. “It’s about risk-taking.”

They take the kids out to the forest a few days a week, light fires, let them experiment with scissors and ride BMX bikes. If they want to be outside, they go outside. If they fancy returning to the snug, where the youngest infants roll around, that’s where they would go. The environment dictates the learning. The adults aim only to connect and share attention with the children. Reading and writing could wait. Nurseries ought to be as social as possible, and follow kids’ lead in their play. Before kids can get on with learning, we have to ensure they belong.

The children seemed happy here, learning to belong and laying down foundations for their future success through play. And yet I wondered if we couldn’t do still more to accelerate early learning. The implication of Deb Roy’s robot experiment was that every moment counted. Could we afford to leave so much to chance?

“The accident of birth is the greatest source of inequality in the US,” wrote economist James Heckman. It’s equally true in the UK today, where the strongest predictor of academic achievement is how much your parents earn. Though two-thirds of our kids attain a C or above in English and maths GCSEs each year, that number falls to just over a third of kids on free school meals. Heckman has also shown that the best way to tackle this inequality is to invest in children’s development as early as possible in their lives. It isn’t enough to transform schools – we have to start much earlier than that.

At Temple University, Hirsh-Pasek told me that we can’t simply drop kids in front of iPads and expect them to catch up – but that doesn’t mean we should give up entirely on intelligent machines. Some of her lab’s experiments are aimed at closing developmental gaps between rich and poor kids. Others cover topics such as language development and spatial awareness, and all use technology in different ways. “What the machine can’t do is be a partner,” Hirsh-Pasek told me. “It isn’t social. It’s interactive without being adaptive.”

Hirsh-Pasek’s mission was to change the way we thought about learning, especially for the poorest kids. “We had this vision that it was so important to get the basics into poor kids,” she told me. “We thought we should drop recess – even though we know being physical helps kids learn, helps build better brains. And we thought we should just do reading and maths, and cut out the arts and all this superfluous stuff like social studies.”

It weighed heavily on her. Policymakers and laymen had twisted the science to fit their own ends. No scientist thought flashcards worked. No scientist believed you should start learning to read and write at an ever younger age. It was a fantasy of governments. More recent research has added depth to the language lessons of Hart and Risley’s Kansas Study. In 2003, the psychologist Patricia Kuhl experimented with teaching American infants Mandarin. Split into three groups (video, audio and flesh-and-blood teacher) only those with a human tutor learned anything at all. In 2010 a study of the wildly popular Baby Einstein vocabulary-building DVDs (Time called them “Crack for Babies”) revealed that infants who watched them “showed no greater understanding of words from the program than kids who never saw it”. Nor did babies learn words by eavesdropping on parental conversations or listening to In Our Time on Radio 4, however soothing the mellifluous tones of Melvyn Bragg. More than words, it took a human being for a baby to learn language. They could not learn from screens.

Schools are still guilty of ignoring these insights into infant learning. Erika Christakis, early-childhood expert and author of The Importance of Being Little, charts the slow descent in preschool learning from a multidimensional, ideas-based approach to a two-dimensional naming-and-labelling curriculum. Daphna Bassok at the University of Virginia asks if kindergarten is really the new first grade. The expectation that kindergarteners – aged five or six – can read is now commonplace. Yet this is counter to all the evidence. A Cambridge study comparing groups of children who started formal literacy lessons at five and seven found that starting two years earlier made no difference at all to a child’s reading ability aged 11, “but the children who started at five developed less-positive attitudes to reading, and showed poorer text comprehension than those who started later”.

These findings are clear: if you start on the decoding before you have an underlying understanding of story, experience, sensation and emotion, then you become a worse reader. And you like it less. Treat kids like robots during early learning and you put them off for life.

Instead, Hirsh-Pasek wanted kids to embrace the joy in learning and growing up. Apart from kids, her other great love was music. She often used to break into song, especially on the phone to her granddaughter.

In her book, she suggested six Cs for modern learning: collaboration, communication, content, critical thinking, creative innovation and confidence. Truisms, I had thought, but unlike much education policy, drawn from scientific evidence. If I was to take away one thing, she said, it should be that “from the earliest ages, we learn from people”.

It was the same insight that had prompted a pair of suburban scientists to hit the “record” button.

Deb Roy was dressed in black and still looked youthful when we met at MIT. A few flecks of grey in his hair were the only evidence of 11 years of parenthood. Looking back, the Human Speechome Project – as his and Patel’s home-recoding experiment had been named – seemed a quirk of turn-of-the-millennium enthusiasm about artificial intelligence. In all, they had captured 90,000 hours of video and 140,000 hours of audio. The 200 terabytes of data covered 85% of the first three years of their son’s life (and 18 months of his little sister’s). But now the footage had been gathering dust. “I still have the whole collection,” he said. “I’m waiting for his wedding day, just to bore the hell out of everyone.”

In a way, it was also a great lost home video. With his team at MIT, Roy had developed new approaches to visualising and studying the data they had captured: “Social Hotspots” showed two tightly knotted lines, visual traces of tender moments in which parent and child came together to chat, learn or explore; “Wordscapes” were snow-capped mountains ranged throughout the living room and kitchen, the highest peaks rising where particular words were most often heard. The tools had turned out to be fantastically lucrative as a means for analysing talk on Twitter. Roy and a graduate student had spent the decade building a new media company.

Roy was now back at MIT. His new group was called the Laboratory for Social Machines. He had given up building robots that would compete with humans and instead turned his attention to the augmentation of human learning. What had changed his mind was the process of actually raising a child.

The first time his son uttered something that wasn’t just babble, Roy was sitting with him looking at pictures. “He said ‘fah’,” Roy explained, “but he was actually clearly referring to a fish on the wall that we were both looking at. The way I knew it was not just coincidence was that right after he looked at it and said it, he turned to me. And he had this kind of look, like a cartoon lightbulb going off – an ‘Ah, now I get it’ kind of look. He’s not even a year old, but there’s a conscious being, in the sense of being self-reflective.”

“I guess, putting on my AI hat, it was a humbling lesson,” he continued. “A lesson of like, holy shit, there’s a lot more here.”

Roy was no longer sure you could bring a robot up like a real human – or that we should even try. It didn’t seem there was much to gain by developing robots that took exactly one human childhood to become exactly like one young adult human. That’s what people did. And that was before you got into imagination or emotions, identity or love – things that were impossible for Toco. Watching his son, Roy had been blown away by “the incredible sophistication of what a language learner in the flesh actually looks like and does”. Infant humans didn’t only regurgitate; they created, made new meaning, shared feelings.

The learning process wasn’t decoding, as he had originally thought, but something infinitely more continuous, complex and social. He was reading Helen Keller’s autobiography to his kids, and had been struck by her epiphany at understanding language for the first time. Deaf and blind after an illness in infancy, Keller was seven years old when she got it. “Suddenly I felt a misty consciousness as of something forgotten,” she wrote, “a thrill of returning thought; and somehow the mystery of language was revealed to me. I knew then that ‘w-a-t-e-r’ meant the wonderful cool something that was flowing over my hand. That living word awakened my soul, gave it light, hope, joy, set it free! Everything had a name, and each name gave birth to a new thought. As we returned to the house every object which I touched seemed to quiver with life.”

Roy had recently started working with Hirsh-Pasek, following her insight that machines might augment learning between humans, but would never replace it.

He had discovered that human learning was communal and interactive. For a robot, the acquisition of language was abstract and formulaic. For us, it was embodied, emotive, subjective, quivering with life. The future of intelligence wouldn’t be found in our machines, but in the development of our own minds.
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