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16 Sep 20:59

Will machine learning create new diagnostic categories, or just refine the ones we already have?

by The Neurocritic

How do we classify and diagnose mental disorders?

In the coming era of Precision Medicine, we'll all want customized treatments that “take into account individual differences in people’s genes, environments, and lifestyles.” To do this, we'll need precise diagnostic tools to identify the specific disease process in each individual. Although focused on cancer in the near-term, the longer-term goal of the White House initiative is to apply Precision Medicine to all areas of health. This presumably includes psychiatry, but the links between Precision Medicine, the BRAIN initiative, and RDoC seem a bit murky at present.1

But there's nothing a good infographic can't fix. Science recently published a Perspective piece by the NIMH Director and the chief architect of the Research Domain Criteria (RDoC) initiative (Insel & Cuthbert, 2015). There's Deconstruction involved, so what's not to like? 2

ILLUSTRATION: V. Altounian and C. Smith / SCIENCE

In this massively ambitious future scenario, the totality of one's genetic risk factors, brain activity, physiology, immune function, behavioral symptom profile, and life experience (social, cultural, environmental) will be deconstructed and stratified and recompiled into a neat little cohort. 3

The new categories will be data driven. The project might start by collecting colossal quantities of expensive data from millions of people, and continue by running classifiers on exceptionally powerful computers (powered by exceptionally bright scientists/engineers/coders) to extract meaningful patterns that can categorize the data with high levels of sensitivity and specificity. Perhaps I am filled with pathologically high levels of negative affect (Loss? Frustrative Nonreward?), but I find it hard to be optimistic about progress in the immediate future. You know, for a Precision Medicine treatment for me (and my pessimism)...

But seriously.

Yes, RDoC is ambitious (and has its share of naysayers). But what you may not know is that it's also trendy! Just the other day, an article in The Atlantic explained Why Depression Needs A New Definition (yes, RDoC) and even cited papers like Depression: The Shroud of Heterogeneity. 4

But let's just focus on the brain for now. For a long time, most neuroscientists have viewed mental disorders as brain disorders. [But that's not to say that environment, culture, experience, etc. play no role! cf. Footnote 3]. So our opening question becomes, How do we classify and diagnose brain disorders neural circuit disorders in a fashion consistent with RDoC principles? Is there really One Brain Network for All Mental Illness, for instance? (I didn't think so.)

Our colleagues in Asia and Australia and Europe and Canada may not have gotten the funding memo, however, and continue to run classifiers based on DSM categories. 5 In my previous post, I promised an unsystematic review of machine learning as applied to the classification of major depression. You can skip directly to the Appendix to see that.

Regardless of whether we use DSM-5 categories or RDoC matrix constructs, what we need are robust and reproducible biomarkers (see Table 1 above). A brief but excellent primer by Woo and Wager (2015) outlined the characteristics of a useful neuroimaging biomarker:
1. Criterion 1: diagnosticity

Good biomarkers should produce high diagnostic performance in classification or prediction. Diagnostic performance can be evaluated by sensitivity and specificity. Sensitivity concerns whether a model can correctly detect signal when signal exists. Effect size is a closely related concept; larger effect sizes are related to higher sensitivity. Specificity concerns whether the model produces negative results when there is no signal. Specificity can be evaluated relative to a range of specific alternative conditions that may be confusable with the condition of interest.

2. Criterion 2: interpretability

Brain-based biomarkers should be meaningful and interpretable in terms of neuroscience, including previous neuroimaging studies and converging evidence from multiple sources (eg, animal models, lesion studies, etc). One potential pitfall in developing neuroimaging biomarkers is that classification or prediction models can capitalize on confounding variables that are not neuroscientifically meaningful or interesting at all (eg, in-scanner head movement). Therefore, neuroimaging biomarkers should be evaluated and interpreted in the light of existing neuroscientific findings.

3. Criterion 3: deployability

Once the classification or outcome-prediction model has been developed as a neuroimaging biomarker, the model and the testing procedure should be precisely defined so that it can be prospectively applied to new data. Any flexibility in the testing procedures could introduce potential overoptimistic biases into test results, rendering them useless and potentially misleading. For example, “amygdala activity” cannot be a good neuroimaging biomarker without a precise definition of which “voxels” in the amygdala should be activated and the relative expected intensity of activity across each voxel. A well-defined model and standardized testing procedure are crucial aspects of turning neuroimaging results into a “research product,” a biomarker that can be shared and tested across laboratories.

4. Criterion 4: generalizability

Clinically useful neuroimaging biomarkers aim to provide predictions about new individuals. Therefore, they should be validated through prospective testing to prove that their performance is generalizable across different laboratories, different scanners or scanning procedures, different populations, and variants of testing conditions (eg, other types of chronic pain). Generalizability tests inherently require multistudy and multisite efforts. With a precisely defined model and standardized testing procedure (criterion 3), we can easily test the generalizability of biomarkers and define the boundary conditions under which they are valid and useful.
[Then the authors evaluated the performance of a structural MRI signature for IBS presented in an accompanying paper.]

Should we try to improve on a neuroimaging biomarker (or “neural signature”) for classic disorders in which “Neuroanatomical diagnosis was correct in 80% and 72% of patients with major depression and schizophrenia, respectively...” (Koutsouleris et al., 2015)? That study used large cohorts and evaluated the trained biomarker against an independent validation database (i.e., it was more thorough than many other investigations). Or is the field better served by classifying when loss and agency and auditory perception go awry? What would individualized treatments for these constructs look like? Presumably, the goal is to develop better treatments, and to predict who will respond to a specific treatment(s).

OR should we adopt the surprisingly cynical view of some prominent investigators, who say:
...identifying a genuine neural signature would necessitate the discovery of a specific pattern of brain responses that possesses nearly perfect sensitivity and specificity for a given condition or other phenotype. At the present time, neuroscientists are not remotely close to pinpointing such a signature for any psychological disorder or trait...

If that's true, then we'll have an awfully hard time with our resting state fMRI classifier for neuro-nihilism.


1 Although NIMH Mad Libs does a bang up job...

2 Derrida's Deconstruction and RDoc are diametrically opposed, as irony would have it.

3 Or maybe an n of 1...  I'm especially curious about how life experience will be incorporated into the mix. Perhaps the patient of the future will upload all the data recorded by their memory implants, as in The Entire History of You (an episode of Black Mirror).

4 The word “shroud” always makes everything sound so dire and deathly important... especially when used as a noun.

5 As do many research groups in the US. This is meant to be snarky, but not condescending to anyone who follows DSM-5 in their research.


Insel, T., & Cuthbert, B. (2015). Brain disorders? Precisely. Science, 348 (6234), 499-500 DOI: 10.1126/science.aab2358

Woo, C., & Wager, T. (2015). Neuroimaging-based biomarker discovery and validation. PAIN, 156 (8), 1379-1381 DOI: 10.1097/j.pain.0000000000000223


Below are 34 references on MRI/fMRI applications of machine learning used to classify individuals with major depression (I excluded EEG/MEG for this particular unsystematic review). The search terms were combinations of "major depression" "machine learning" "support vector" "classifier".

Here's a very rough summary of methods:

Structural MRI: 1, 14, 22, 29, 31, 32

DTI: 6, 12, 18, 19

Resting State fMRI: 3, 5, 8, 9 11, 16, 17, 21, 28, 33

fMRI while viewing different facial expressions: 2, 7, 10, 24, 26, 27, 34

comorbid panic: 13

verbal working memory: 25

guilt: 15 (see The Idiosyncratic Side of Diagnosis by Brain Scan and Machine Learning)

Schizophrenia vs. Bipolar vs. Schizoaffective: 16

Psychotic Major Depression vs. Bipolar Disorder: 20

Schizophrenia vs. Major Depression: 23, 31

Unipolar vs. Bipolar Depression: 24, 32, 34

This last one is especially important, since an accurate diagnosis can avoid the potentially disastrous prescribing of antidepressants in bipolar depression.

Idea that may already be implemented somewhere: Individual labs or research groups could perhaps contribute to a support vector machine clearing house (e.g., at NTRIC or OpenfMRI or GitHub) where everyone can upload the code for data processing streams and various learning/classification algorithms to try out on each others' data.

Brain. 2012 May;135(Pt 5):1508-21. doi: 10.1093/brain/aws084.
Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder.
Mwangi B Ebmeier KP, Matthews K, Steele JD.

Bipolar Disord. 2012 Jun;14(4):451-60. doi: 10.1111/j.1399-5618.2012.01019.x.
Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression.
Mourão-Miranda J Almeida JR, Hassel S, de Oliveira L, Versace A, Marquand AF, Sato JR, Brammer M, Phillips ML.

PLoS One. 2012;7(8):e41282. doi: 10.1371/journal.pone.0041282. Epub 2012 Aug 20.
Changes in community structure of resting state functional connectivity in unipolar depression.
Lord A Horn D, Breakspear M, Walter M.

Neuroreport. 2012 Dec 5;23(17):1006-11. doi: 10.1097/WNR.0b013e32835a650c.
Machine learning classifier using abnormal brain network topological metrics in major depressive disorder.
Guo H Cao X, Liu Z, Li H, Chen J, Zhang K.

PLoS One. 2012;7(9):e45972. doi: 10.1371/journal.pone.0045972. Epub 2012 Sep 26.
Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
Fang P Zeng LL, Shen H, Wang L, Li B, Liu L, Hu D.

PLoS One. 2013;8(4):e60121. doi: 10.1371/journal.pone.0060121. Epub 2013 Apr 1.
What does brain response to neutral faces tell us about major depression? evidence from machine learning and fMRI.
Oliveira L Ladouceur CD, Phillips ML, Brammer M, Mourao-Miranda J.

Hum Brain Mapp. 2014 Apr;35(4):1630-41. doi: 10.1002/hbm.22278. Epub 2013 Apr 24.
Unsupervised classification of major depression using functional connectivity MRI.
Zeng LL Shen H, Liu L, Hu D.

Psychiatry Clin Neurosci. 2014 Feb;68(2):110-9. doi: 10.1111/pcn.12106. Epub 2013 Oct 31.
Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

Neuroimage. 2015 Jan 15;105:493-506. doi: 10.1016/j.neuroimage.2014.11.021. Epub 2014 Nov 15.
Sparse network-based models for patient classification using fMRI.
Rosa MJ Portugal L Hahn T Fallgatter AJ Garrido MI Shawe-Taylor J Mourao-Miranda J.

Proc IEEE Int Symp Biomed Imaging. 2014 Apr;2014:246-249.
Sacchet MD Prasad G Foland-Ross LC Thompson PM Gotlib IH.

Front Psychiatry. 2015 Feb 18;6:21. doi: 10.3389/fpsyt.2015.00021. eCollection 2015.
Support vector machine classification of major depressive disorder using diffusion-weighted neuroimaging and graph theory.
Sacchet MD Prasad G Foland-Ross LC Thompson PM Gotlib IH.

J Affect Disord. 2015 Sep 15;184:182-92. doi: 10.1016/j.jad.2015.05.052. Epub 2015 Jun 6.
Separating depressive comorbidity from panic disorder: A combined functional magnetic resonance imaging and machine learning approach.
Lueken U Straube B Yang Y Hahn T Beesdo-Baum K Wittchen HU Konrad C Ströhle A Wittmann A Gerlach AL Pfleiderer B, Arolt V, Kircher T.

PLoS One. 2015 Jul 17;10(7):e0132958. doi: 10.1371/journal.pone.0132958. eCollection 2015.
Structural MRI-Based Predictions in Patients with Treatment-Refractory Depression (TRD).
Johnston BA Steele JD Tolomeo S Christmas D Matthews K.

Psychiatry Res. 2015 Jul 5. pii: S0925-4927(15)30025-1. doi: 10.1016/j.pscychresns.2015.07.001. [Epub ahead of print]
Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.
Sato JR Moll J Green S Deakin JF Thomaz CE Zahn R.

Neuroimage. 2015 Jul 24. pii: S1053-8119(15)00674-6. doi: 10.1016/j.neuroimage.2015.07.054. [Epub ahead of print]
A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: Application to schizophrenia, bipolar, and schizoaffective disorders.
Du Y Pearlson GD Liu J Sui J Yu Q He H Castro E Calhoun VD.

Neuroreport. 2015 Aug 19;26(12):675-80. doi: 10.1097/WNR.0000000000000407.
Predicting clinical responses in major depression using intrinsic functional connectivity.
Qin J, Shen H, Zeng LL, Jiang W, Liu L, Hu D.

J Affect Disord. 2015 Jul 15;180:129-37. doi: 10.1016/j.jad.2015.03.059. Epub 2015 Apr 4.
Altered anatomical patterns of depression in relation to antidepressant treatment: Evidence from a pattern recognition analysis on the topological organization of brain networks.
Qin J, Wei M, Liu H Chen J Yan R Yao Z Lu Q.

Magn Reson Imaging. 2014 Dec;32(10):1314-20. doi: 10.1016/j.mri.2014.08.037. Epub 2014 Aug 29.
Abnormal hubs of white matter networks in the frontal-parieto circuit contribute to depression discrimination via pattern classification.
Qin J, Wei M, Liu H Chen J Yan R Hua L Zhao K Yao Z Lu Q.

Biomed Res Int. 2014;2014:706157. doi: 10.1155/2014/706157. Epub 2014 Jan 19.
Neuroanatomical classification in a population-based sample of psychotic major depression and bipolar I disorder with 1 year of diagnostic stability.
Serpa MH, Ou Y Schaufelberger MS Doshi J Ferreira LK Machado-Vieira R Menezes PR Scazufca M Davatzikos C Busatto GF Zanetti MV.

Psychiatry Res. 2013 Dec 30;214(3):306-12. doi: 10.1016/j.pscychresns.2013.09.008. Epub 2013 Oct 7.
Identifying major depressive disorder using Hurst exponent of resting-state brain networks.
Wei M Qin J, Yan R, Li H, Yao Z, Lu Q.

J Psychiatry Neurosci. 2014 Mar;39(2):78-86.
Characterization of major depressive disorder using a multiparametric classification approach based on high resolution structural images.
Qiu L Huang X Zhang J Wang Y Kuang W Li J Wang X Wang L Yang X Lui S Mechelli A Gong Q2.

PLoS One. 2013 Jul 2;8(7):e68250. doi: 10.1371/journal.pone.0068250. Print 2013.
Convergent and divergent functional connectivity patterns in schizophrenia and depression.
Yu Y Shen H, Zeng LL, Ma Q, Hu D.

Eur Arch Psychiatry Clin Neurosci. 2013 Mar;263(2):119-31. doi: 10.1007/s00406-012-0329-4. Epub 2012 May 26.
Discriminating unipolar and bipolar depression by means of fMRI and pattern classification: a pilot study.
Grotegerd D Suslow T, Bauer J, Ohrmann P, Arolt V, Stuhrmann A, Heindel W, Kugel H, Dannlowski U.

Neuroreport. 2008 Oct 8;19(15):1507-11. doi: 10.1097/WNR.0b013e328310425e.
Neuroanatomy of verbal working memory as a diagnostic biomarker for depression.
Marquand AF Mourão-Miranda J, Brammer MJ, Cleare AJ, Fu CH.

Biol Psychiatry. 2008 Apr 1;63(7):656-62. Epub 2007 Oct 22.
Pattern classification of sad facial processing: toward the development of neurobiological markers in depression.
Fu CH Mourao-Miranda J, Costafreda SG, Khanna A, Marquand AF, Williams SC, Brammer MJ.

Neuroreport. 2009 May 6;20(7):637-41. doi: 10.1097/WNR.0b013e3283294159.
Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression.
Costafreda SG Khanna A, Mourao-Miranda J, Fu CH.

Magn Reson Med. 2009 Dec;62(6):1619-28. doi: 10.1002/mrm.22159.
Disease state prediction from resting state functional connectivity.
Craddock RC Holtzheimer PE 3rd, Hu XP, Mayberg HS.

Neuroimage. 2011 Apr 15;55(4):1497-503. doi: 10.1016/j.neuroimage.2010.11.079. Epub 2010 Dec 3.
Prognostic prediction of therapeutic response in depression using high-field MR imaging.
Gong Q Wu Q, Scarpazza C, Lui S, Jia Z, Marquand A, Huang X, McGuire P, Mechelli A.

Neuroimage. 2012 Jun;61(2):457-63. doi: 10.1016/j.neuroimage.2011.11.002. Epub 2011 Nov 7.
Diagnostic neuroimaging across diseases.
Klöppel S Abdulkadir A, Jack CR Jr, Koutsouleris N, Mourão-Miranda J, Vemuri P.

Brain. 2015 Jul;138(Pt 7):2059-73. doi: 10.1093/brain/awv111. Epub 2015 May 1.
Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers.
Koutsouleris N Meisenzahl EM Borgwardt S Riecher-Rössler A Frodl T Kambeitz J Köhler Y Falkai P Möller HJ Reiser M Davatzikos C.

JAMA Psychiatry. 2014 Nov;71(11):1222-30. doi: 10.1001/jamapsychiatry.2014.1100.
Brain morphometric biomarkers distinguishing unipolar and bipolar depression. A voxel-based morphometry-pattern classification approach.
Redlich R Almeida JJ Grotegerd D Opel N Kugel H Heindel W Arolt V Phillips ML Dannlowski U.

Brain Behav. 2013 Nov;3(6):637-48. doi: 10.1002/brb3.173. Epub 2013 Sep 22.
A reversal coarse-grained analysis with application to an altered functional circuit in depression.
Guo S Yu Y Zhang J Feng J.

Hum Brain Mapp. 2014 Jul;35(7):2995-3007. doi: 10.1002/hbm.22380. Epub 2013 Sep 13.
Amygdala excitability to subliminally presented emotional faces distinguishes unipolar and bipolar depression: an fMRI and pattern classification study.
Grotegerd D Stuhrmann A, Kugel H, Schmidt S, Redlich R, Zwanzger P, Rauch AV, Heindel W, Zwitserlood P, Arolt V, Suslow T, Dannlowski U.

20 Aug 14:17

Por que Carlos Ruas está mais ofensivo em suas tirinhas?

by Carlos Ruas



Em tempos de paz, ideias fofinhas; em tempos de guerra, ideias críticas. É assim que funciona a área artística: Ela se molda ao universo que se apresenta ao seu redor. E eu não posso “calar” o meu lápis quando uma minoria religiosa fanática resolve ameaçar a laicidade do meu País.
É nesse momento que surgem interpretações erradas de meu trabalho. Nunca irei generalizar algo exercido por uma minoria radical; existem igrejas que fazem ótimos trabalhos sociais junto à sociedade, mas ao mesmo tempo ela pode ser usada para outros fins. O meu alvo sempre foi e sempre será as pessoas que buscam poder, dinheiro e visibilidade se utilizando do nome de Deus para alcançar esse objetivo. Existe uma grande máfia legalizada que vem crescendo a cada dia em nosso país e agora ela chegou na política, impondo leis a favor do Deus deles e indo contra o progresso natural de uma nação, com a justificativa de que um livro de leis de 2 mil anos atrás não permite isso.

13 Aug 19:24

Workplace WIN: Campbells to Begin Selling Andy Warhol Soup Cans

Andy Warhol campbells soup cans Target tomato soup

It's about time! Each can will be sold at Target at regular price. If there were no soup can collectors that existed before this moment, I'm sure there are now.

Submitted by: Unknown

12 Aug 16:56

Parents in Silicon Valley

12 Aug 16:55

Dogs in space

12 Aug 16:55

Are you completely sure?

12 Aug 16:55

How serious illness occurs

11 Aug 17:35

Alphabet and Google

by Tyler Cowen

Peter Klein has an interesting Rand Journal piece (pdf) on conglomerates:

This paper challenges the conventional wisdom that the 1960s conglomerates were inefficient. I offer valuation results consistent with recent event-study evidence that markets typically rewarded diversifying acquisitions. Using new data, I compute industry-adjusted valuation, profitability, leverage, and investment ratios for thirty-six large, acquisitive conglomerates from 1966 to 1974. During the early 1970s, the conglomerates were less valuable and less profitable than standalone firms, favoring an agency explanation for unrelated diversification. In the 1960s, however, conglomerates were not valued at a discount. Evidence from acquisition histories suggests that conglomerate diversification may have added value by creating internal capital markets.

In other words, today’s Google announcement isn’t as crazy as it may sound.  Here is further positive evidence on conglomerates, and Glenn Hubbard also thinks the 1960s conglomerates were largely efficient.  Here is some evidence, however, that conglomerates tend to be less innovative.  Scharfstein and Stein are less positive more generally.  Here is some evidence that the non-Google divisions will receive favoritism in the allocation of capital within the conglomerate.  That all said, conglomerates are understudied in microeconomics, in part because they are hard to study.

What do you all think of the news?

11 Aug 11:52

Muitirinhas #189

by Fábio Coala
10 Aug 16:14

Effective Computation in Physics

by John

Earlier this week I had a chance to talk with Anthony Scopatz and Katy Huff about their new book, Effective Computation in Physics.

JC: Thanks for giving me a copy of the book when we were at SciPy 2015. It’s a nice book. It’s about a lot more than computational physics.

KH: Right. If you think of it as physical science in general, that’s the group we’re trying to target.

JC: Targeting physical science more than life science?

KH: Yes. You can see that more in the data structures we cover which are very float-based rather than things like strings and locations.

AS: To second that, I’d say that all the examples are coming from the physical sciences. The deep examples, like in the parallelism chapter, are most relevant to physicists.

JC: Even in life sciences, there’s a lot more than sequences of base pairs.

KH: Right. A lot of people have asked what chapters they should skip. It’s probable that ecologists or social scientists are not going to be interested in the chapter about HDF5. But the rest of the book, more or less, could be useful to them.

JC: I was impressed that there’s a lot of scattered stuff that you need to know that you’ve brought into one place. This would be a great book to hand a beginning grad student.

KH: That was a big motivation for writing the book. Anthony’s a professor now and I’m applying to be a professor and I can’t spend all my time ramping students up to be useful researchers. I’d rather say “Here’s a book. It’s yours. Come to me if it’s not in the index.”

JC: And they’d rather have a book that they could access any time than have to come to you.  Are you thinking of doing a second edition as things change over time?

AS: It’s on the table to do a second edition eventually. Katy and I will have the opportunity if the book is profitable and the material becomes out of date. O’Reilly could ask someone else to write a second edition, but they would ask us first.

JC: Presumably putting out a second edition would not be as much work as creating the first one.

KH: I sure hope not!

AS: There’s a lot of stuff that’s not in this book. Greg Wilson jokingly asked us when Volume 2 would come out. There may be a need for a more intermediate book that extends the topics.

KH: And maybe targets languages other than Python where you’re going to have to deal with configuring and building, installing and linking libraries, that kind of stuff. I’d like to cover more of that, but Python doesn’t have that problem!

JC: You may sell a lot of books when the school year starts.

KH: Anthony and I both have plans for courses based around this book. Hopefully students will find it helpful.

JC: Maybe someone else is planning the same thing. It would be nice if they told you.

AS: A couple people have approached us about doing exactly that. Something I’d like to see is for people teaching courses around it to pull their curriculum together.

JC: Is there a web site for the book, other than an errata page at the publisher?

KH: Sure, there’s Anthony put that up.

AS: There’s also a GitHub repo, physics-codes. That’s where you can find code for all the examples, and that should be kept up to date. We also have a YouTube channel.

JC: When did y’all start writing the book?

AS: It was April or May last year when we finally started writing. There was a proposal cycle six or seven months before that. Katy and I were simultaneously talking to O’Reilly, so that worked out well.

KH: In a sense, the book process started for me in graduate school with The Hacker Within and Software Carpentry. A lot of the flows in the book come from the outlines of Hacker Within tutorials and Software Carpentry tutorials years ago.

AS: On that note, what happened for me, I took those tutorials and turned them into a masters course for AIMS, African Institute for Mathematical Sciences. At the end I thought it would be nice if this were a book. It didn’t occur to me that there was a book’s worth of material until the end of the course at AIMS. I owe a great debt to AIMS in that way.

JC: Is there something else you’d like to say about the book that we haven’t talked about?

KH: I think it would be a fun exercise for someone to try to determine which half of the chapters I wrote and which Anthony wrote. Maybe using some sort of clustering algorithm or pun detection. If anyone wants to do that sort of analysis, I’d love to see if you guess right. Open competition. Free beer from Katy if you can figure out which half. We split the work in half, but it’s really mixed around.  People who know us well will probably know that Anthony’s chapters have a high density of puns.

AS: I think the main point that I would like to see come across is that the book is useful to a broader audience outside the physical sciences. Even for people who are not scientists themselves, it’s useful to describe the mindset of physical scientists to software developers or managers. That communication protocol kinda goes both ways, though I didn’t expect that when we started out.

JC: I appreciate that it’s one book. Obviously it won’t cover everything you need to know. But it’s not like here’s a book on Linux, here’s a book on git, here are several books on Python. And some of the material in here isn’t in any book.

KH: Like licensing. Anthony had the idea to add the chapter on licensing. We get asked all the time “Which license do you use? And why?” It’s confusing, and you can get it really wrong.

* * *

Check out Effective Computation in Physics. It’s about more than physics. It’s a lot of what you need to know to get started with scientific computing in Python, all in one place.


10 Aug 12:07

AEP : 5 Reasons Iain M. Banks' Culture Should Be the Next Big Sci-Fi Adaptation

excession_by_iain_m_banksIt’s a wonderful time to be a science fiction fan. The television adaptation of James S.A. Corey’s Expanse space opera series is poised to drag SyFy back from the brink. Ann Leckie’s excellent Ancillary Justice has been optioned, as has basically everything with John Scalzi’s name on the cover, from Lock In, to Redshirts , to The Ghost Brigades.

But there’s one series I don’t see on those in-development lists, and it boggles my mind. For years now, we’ve been teased by rumors of plans to adapt Iain M. Banks’ Culture novels, but they’ve remained just that—rumors. This must change. The Culture is space opera on a grand-scale, set in a hedonistic utopian society watched over by benevolent artificial intelligences. Collectively, it is one of the most brilliant works of sci-fi ever created, but apart from a few whispers about a movie deal, not one of its 10 books has even come close to hitting the screen (big or small). That’s an absolute shame, and here’s why.

5. It’s packed with action…
I’ll go with the easiest first: the Culture is a series full of big, brilliant, beautiful action scenes. The very first book, Consider Phlebas, starts in the middle of an interstellar war. There’s a firefight with a scout ship that thinks in four dimensions. Two or three chapters later, a group of space pirates attempt a forced landing on a massive, ring-shaped space station. This is a series of titanic battles over something as simple as board games. In one book, the Culture invades Hell itself (or at least a virtual-reality simulacrum) and stands poised to take on bigger threats still. In these days of CGI miracles, these stunning set pieces would redefine the genre on the small screen. Provided there’s network that could afford to create them…

4. There’s also plenty of intrigue
So maybe big, bright action isn’t your thing. Maybe you’re more appreciative of the backstabbing and political dealing of Game of Thrones. The books have you covered there, too. The Culture is an egalitarian utopia that prefers not to use force whenever possible, choosing instead to act through elaborate schemes and subterfuge. The artificial minds behind “Special Circumstances” (the covert ops arm of the Culture) create multi-tiered plots so intricate, a person in complete defiance of their edicts can be fooled into doing doing exactly what the Culture wants without ever realizing it. The antagonists are no slouches, either: Inversions is about a dense conspiracy that the Culture doesn’t have a direct hand in, and while Special Circumstances does intervene in the action in Matter, the protagonists are already embroiled in several ongoing intrigues.

3. The cast is diverse
Diversity and reputation in SFF is one of the most widely discussed issues in the genre today. Iain Banks may have been an OWG (Old White Guy), but he never steered away from including a diverse array of races and genders among his protagonists. The Culture features men, women, aliens (who are actually alien, and not humanoids with fancy foreheads), transgendered people, transspecies people, a wide spectrum of sexualities, and characters of every possible creed, color, and (pardon the pun) culture. Technology has even advanced sufficiently to allow characters to change genders over the course of a novel, both fathering and giving birth to children along the way. Given how many fans are clamoring for more diverse casts, the Culture would be a perfect solution—if faithfully adapted, that is.

2. It has a great sense of humor
While it’s never a very happy series, Banks’ Culture novels display a uniformly excellent sense of humor. Whether it’s the intelligent ships who have given themselves names like We Haven’t Met But You’re A Great Fan Of Mine, Conflict Of Interest, and So Much for SubtletyCheradine Zakalwe’s unusual chair phobia [Editor’s note: You thought that was funny? You are a dark, dark man.], or a running gag sparked when someone told the artificial Minds to name their ships with “a little more gravitas” (which they took way too seriously), there’s a dark, quirky sense of humor at work throughout the series, hitting the right balance between unnerving, absurd, and hilarious.

1. The setting is huge. As in, properly huge.
The series’ most impressive characteristic is its sheer scale. There are ships that can self-manufacture battle fleets large enough to kill a planet. Orbital ring colonies that encircle a star. Truly alien races. And all of it feels completely unique. Banks hardly repeats himself across 10 length novels, and even when he revisits a theme or locale, he manages to make it feel historic and organic. To wit: the Culture’s meddling during the Idiran-Culture War of Consider Phlebas provides the seed for the plot of Look To Windward, which takes place centuries later. Banks’ world-building is so dense, a TV series based on it could range far and wide from the plots of the novels and still never run out of material.

The Culture is the sci-fi TV series we need. It’s the sci-fi TV series we deserve. An adaptation has been teased since 1988. It needs to be the next big thing to make the leap to the screen.

10 Aug 09:18

Spaniard fatally gored while trying to film bull run on smartphone

by Sam Machkovech
Albener Pessoa

Darwin award!!

While the Spanish town of Pamplona hosts the world's most well-known running of the bulls, other cities in Spain, Portugal, and nearby nations host their own annual runs where bulls run through city streets while locals and tourists run alongside—or away from—the giant beasts.

For one participant of a Sunday bull run in Villasecra de la Sagra, Spain, trying to share his experience by way of a smartphone recording ended traumatically. According to details ascertained from a local Spanish-language report, an English-language AFP report, and bystander video of the incident, a 32-year-old man was gored from behind while attempting to film that city's annual bull run.

The bystander video, posted Sunday on Instagram (not linked here due to its graphic nature), showed the currently unidentified victim standing near a barricade so that he was behind other viewers and away from the general fray of the bull run. However, a stray bull appeared to become separated from the general herd, at which point it ran at full speed behind the crowd and struck the 32-year-old while he was holding a smartphone to film in the opposite direction. According to reports, after receiving brief treatment at a nearby bullring's medical center, the victim was transferred to a hospital in nearby Toledo, where he was soon pronounced dead from neck and thigh wounds.

Read 2 remaining paragraphs | Comments

10 Aug 01:47

The new Fable of the Bees

by Tyler Cowen

This Leah Sottile WaPo piece is excellent in many ways.  Here are a few bits:

Bees are still dying at unacceptable rates…Ohio State University’s Honey Bee Update noted that losses among the state’s beekeepers over the past winter were as high as 80 percent.

…Researchers say innovative beekeepers will be critical to helping bees bounce back.

“People ask me, ‘The bees are going to be extinct soon?’ ” said Ramesh Sagili, principal investigator at the Oregon State University Honey Bee Lab. “I’m not worried about bees being extinct here. I’m worried about beekeepers being extinct.”

Commercial beekeepers are leaving the sector and innovative bee hobbyists are taking on a much larger role:

“I feel a social responsibility to provide good bees,” Prescott said. “It makes me happy to look at the part that I’m playing.”

…Obsessing over bee health was unheard of 50 years ago, said Marla Spivak, a University of Minnesota professor of entomology. “In the past, it was very easy to keep bees. Throw them in a box, and they make honey and survive. Now, it takes lots of management.”

The story has some excellent examples:

Henry Storch, 32, does it because he felt a calling to beekeeping. A farrier by trade, Storch said he could make more money shoeing horses. But five years ago, he became obsessed with the notion that he could build a better bee…He barely flinched as a bee stung him on the upper lip.

…Storch’s mountain-bred “survivor” bees are like open-range cows: tough, hardened and less in need of close management than the bees he trucks to the California almond fields. Storch compares the effort to growing organic, non-GMO food.

The good news is this:

Amid the die-off, beekeepers have been going to extraordinary lengths to save both their bees and their livelihoods.

That effort may finally be paying off. New data from the Agriculture Department show the number of managed honeybee colonies is on the rise, climbing to 2.7 million nationally in 2014, the highest in 20 years.

Recommended.  To trace the longer story, here are previous MR posts on bees.

09 Aug 19:56

AEP : Esse garoto sobe na cadeira e conta uma piada. Ninguém ri porque todos estão perplexos demais.

O aluno comediante é um vídeo produzido para chamar atenção de um assunto pouco discutido, mesmo nos dias de hoje. Doenças psicológicas não são brincadeiras bobas.

No vídeo vemos um aluno entrando na sala de aula atrasado e não é bem recebido pelo professor. Então ele sobe na cadeira e faz uma pergunta para a sala:

“Quantos professores são necessários para trocar uma lâmpada?”

O que acontece em seguida é inesperado. O garoto se abre, deixa que todos fiquem desconfortáveis com sua transparência. No fim todos estão sem palavras e de acordo com o desabafo.

Clique no play para assistir

Clique e veja no YouTube

O vídeo original foi produzido pela organização Time to Change que promove debates importantes sobre doenças mentais.

Eles apontam que esses problemas são comuns, mas silenciosos. E o que é pior: 9 em 10 pessoas que sofrem disso alegam enfrentar discriminação.

O assunto é sério. Ajude espalhar a mensagem.

Se quiser, você pode compartilhar o vídeo com seus amigos.

09 Aug 18:47

AEP : 35 Innocent Photos That Are Somehow Completely Filthy

This Summer adventure.

This adorable napping baby.

This hot Bible story.

This summertime Barbie doll.


This bedtime story.

This bottle of "body" lotion.

This musical instruction.


This teacher holding some balloons.


This plump sausage.


These frogs having a wet and wild adventure.


This Spiderman balloon that is happy to see you.


This fresh dip.


This sign teaching you how to ride it.


This Disney package.


This bowling ad that makes it seem more fun than it is.


This toy that wants you to feel some kid's wood.


This racer that needed to celebrate.


This demanding insect repellent.


This candy that has four fingers for you.


This ad that has to be intentional.


These shockingly great glove.


This mom who obviously didn't run this plate idea past anyone first.


These finger-licking good cookies.


This informercial.

This woman that should probably carry her neck pillow differently next time.


This book that might not realize what prayer looks like.


These balls that are yummy in my mouth.


These dinosaurs having a good time.


This girl with impeccable hand placement.


This slide that I think just had twins.


This toy with a pleased pony.


This apple statue that wants your seed.


This poster that explains why you scream for ice cream.


This air freshener that I don't want to know what scent it is.


This sauce is the perfect way to finish up.


07 Aug 19:50

Ele está entre nós

by O Criador

Depois nasce um Jesus e ninguém sabe explicar! ¬¬

The post Ele está entre nós appeared first on

07 Aug 19:48

Cat Lesson

by Doug
07 Aug 19:48

An Apple

by Doug

An Apple

Marketing is everything.

07 Aug 18:09

AEP : NeuroLogica Blog » Registering Studies Reduces Positive Outcomes

Aug 06 2015

The science of science itself is critically important. Improvements in our understanding of the world and our technological ability to affect it is arguably the strongest factor determining many aspects of our quality of life. We invest billions of dollars in scientific research, to improve medical practice, feed the world, reduce our impact on the environment, make better use of resources, to do more with less.

It seems obvious that it is in our best interest for that scientific research to be as efficient and effective as possible. Bad scientific research wastes resources, wastes time, and may produce spurious results that are then used to waste further resources.

This is why I have paid a lot of attention to studies which look at the process of science itself, from the lab to the pages of scientific journals. To summarize the identified problems: most studies that are published are small and preliminary (meaning they are not highly rigorous), and this leads to many false positives in the literature. This is exacerbated by the current pressure to publish in academia.

There is researcher bias – researchers want positive outcomes. It is easy to exploit so-called
“researcher degrees of freedom” in order to manufacture positive results even out of dead-negative data.  Researcher can also engage in citation bias to distort the apparent consensus of the published literature.

Traditional journals want to maximize their impact factor, which means they are motivated to publish new and exciting results, which are the one most likely to be false. Insufficient space is given to replications, which are critically important in science to know what is really real. We are also now faced with a large number of open-access journals with frightfully low standards, some with predatory practices, flooding the literature with low-grade science.

All of this biases published science in the same direction, that of false positive studies. In most cases the science eventually works itself out, but this arguably takes a lot longer than it has to, and scientists pursue many false leads that could have been avoided with better research up front.

Attention is being paid to this problem, although not enough, in my opinion. One specific intervention aimed at reducing false positive studies is pre-registration of clinical trials (at, for example). The idea here is that scientists have to register a scientific study on people before they start gathering data. This means they cannot simply hide the study in a file drawer if they don’t like the results. Further, they have to declare their methods ahead of time, including what outcomes they are going to measure.

Pre-registering scientific studies, therefore, has the effect of reducing researcher degrees of freedom. They cannot simply decide after they collect the data which outcomes to follow or which comparisons to make, in order to tease out a positive result. Does this practice actually work? The answer seems to be yes, according to a new study published in PLOS One: Likelihood of Null Effects of Large NHLBI Clinical Trials Has Increased over Time.

The researchers looked at 30 large National Heart Lung, and Blood Institute (NHLBI) funded trials between 1970 and 2000. Of those studies, 17 or 57% showed a significant positive result. They then compared that to 25 similar studies published between 2000 and 2012. Of those, only 2 or 8% were positive. That is a significant drop – from 57% to 8% positive studies.

They also found that there was no difference in the design of the studies, whether they were placebo-controlled, for example. There was also no effect from industry funding.

What was different was that starting in 2000 these trials had to be pre-registered in Pre-registration strongly correlated with a negative outcome. In addition to pre-registration there was also the adoption of transparent reporting standards.

These results are simultaneously very encouraging and a bit frightening. This itself is one study, although it is fairly straightforward and the results clear, but it still needs to be replicated with other databases. Taken at face value, however, it means that at least half of all published clinical trials are false positives, while only about 10% are true positive, and 40% are negative (both true and false negative). Also keep in mind – these were large studies, not small preliminary trials.

This study seems to confirm what all the other studies I reviewed above appear to be saying, that loose scientific methods are leading to a massive false positive bias in the medical literature. The encouraging part, however, is that this one simple fix seems to work remarkably well.


This study should be a wake-up call, but it is not getting as much play in the media as I would hope or like. I do not go as far as to say that science is broken. In the end it does work, it just takes a lot longer to get there than it should because we waste incredible resources and time chasing false positive outcomes.

The infrastructure of doing and reporting science has significant and effective built-in quality control, but it is currently not sufficient. The research is showing glaring holes and biases in the system. In some cases we know how to fix them.

At this point there is sufficient evidence to warrant full requirement for all human research to be registered prior to collecting data, declaring methods and outcomes to be measured. We need high standards of scientific rigor with full transparency in reporting. These measures are already working.

We further need an overhaul of the system by which we publish scientific studies. There is too much of a bias in traditional journals toward exciting results that are unlikely to be replicated, and too little toward boring replications that are actually the workhorses of scientific progress. We also need to reign in the new open-access journals, weed out the predators, and institute better quality control.

With online publishing it is actually easier to accomplish these goals than before. Journals can no longer argue they don’t have “space” or that it is too expensive.

The scientific community, in my opinion, needs to pay more attention to these issues.

07 Aug 18:07

AEP : Psychopaths Versus Sociopaths

Psychopath and sociopath are popular psychology terms to describe violent monsters born of our worst nightmares. Think Hannibal Lecter in Silence of the Lambs (1991), Norman Bates in Psycho (1960) and Annie Wilkes in Misery (1990). In making these characters famous, popular culture has also burned the words used to describe them into our collective consciousness.

Most of us, fortunately, will never meet a Hannibal Lecter, but psychopaths and sociopaths certainly do exist. And they hide among us. Sometimes as the most successful people in society because they’re often ruthless, callous and superficially charming, while having little or no regard for the feelings or needs of others.

These are known as “successful” psychopaths, as they have a tendency to perform premeditated crimes with calculated risk. Or they may manipulate someone else into breaking the law, while keeping themselves safely at a distance. They’re master manipulators of other peoples’ feelings, but are unable to experience emotions themselves.

Sound like someone you know? Well, heads up. You do know one; at least one. Prevalence rates come in somewhere between 0.2% and 3.3% of the population.

If you’re worried about yourself, you can take a quiz to find out, but before you click on that link let me save you some time: you’re not a psychopath or sociopath. If you were, you probably wouldn’t be interested in taking that personality test.

You just wouldn’t be that self-aware or concerned about your character flaws. That’s why both psychopathy and sociopathy are known as anti-social personality disorders, which are long-term mental health conditions.

Although most of us will never meet someone like Hannibal Lecter from Silence of the Lambs, we all know at least one sociopath. from

What’s The Difference?

Psychopaths and sociopaths share a number of characteristics, including a lack of remorse or empathy for others, a lack of guilt or ability to take responsibility for their actions, a disregard for laws or social conventions, and an inclination to violence. A core feature of both is a deceitful and manipulative nature. But how can we tell them apart?

Sociopaths are normally less emotionally stable and highly impulsive – their behaviour tends to be more erratic than psychopaths. When committing crimes – either violent or non-violent – sociopaths will act more on compulsion. And they will lack patience, giving in much more easily to impulsiveness and lacking detailed planning.

Psychopaths, on the other hand, will plan their crimes down to the smallest detail, taking calculated risks to avoid detection. The smart ones will leave few clues that may lead to being caught. Psychopaths don’t get carried away in the moment and make fewer mistakes as a result.

Both act on a continuum of behaviours, and many psychologists still debate whether the two should be differentiated at all. But for those who do differentiate between the two, one thing is largely agreed upon: psychiatrists use the term psychopathy to illustrate that the cause of the anti-social personality disorder is hereditary. Sociopathy describes behaviours that are the result of a brain injury, or abuse and/or neglect in childhood.

Psychopaths are born and sociopaths are made. In essence, their difference reflects the nature versus nurture debate.

There’s a particularly interesting link between serial killers and psychopaths or sociopaths – although, of course, not all psychopaths and sociopaths become serial killers. And not all serial killers are psychopaths or sociopaths.

Thomas Hemming murdered two people in 2014 just to know what it felt like to kill. Tracey Nearmy/AAP Image

But America’s Federal Bureau of Investigation (FBI) has noted certain traits shared between known serial killers and these anti-social personality disorders. These include predatory behaviour (for instance, Ivan Milat, who hunted and murdered his seven victims); sensation-seeking (think hedonistic killers who murder for excitement or arousal, such as 21-year-old Thomas Hemming who, in 2014, murdered two people just to know what it felt like to kill); lack of remorse; impulsivity; and the need for control or power over others (such as Dennis Rader, an American serial killer who murdered ten people between 1974 and 1991, and became known as the “BTK (bind, torture, kill) killer”).

A Case Study

The Sydney murder of Morgan Huxley by 22-year-old Jack Kelsall, who arguably shows all the hallmarks of a psychopath, highlights the differences between psychopaths and sociopaths.

In 2013, Kelsall followed Huxley home where he indecently assaulted the 31-year-old before stabbing him 28 times. Kelsall showed no remorse for his crime, which was extremely violent and pre-meditated.

There’s no doubt in my mind he’s psychopathic rather than sociopathic because although the murder was frenzied, Kelsall showed patience and planning. He had followed potential victims before and had shared fantasies he had about murdering a stranger with a knife with his psychiatrist a year before he killed Huxley, allegedly for “the thrill of it”.

Whatever Kelsall’s motive, regardless of whether his dysfunction was born or made, the case stands as an example of the worst possible outcome of an anti-social personality disorder: senseless violence perpetrated against a random victim for self-gratification. Throughout his trial and sentencing, Kelsall showed no sign of remorse, no guilt, and gave no apology.

A textbook psychopath, he would, I believe, have gone on to kill again. In my opinion – and that of the police who arrested him – Kelsall was a serial killer in the making.

In the end, does the distinction between a psychopath and sociopath matter? They can both be dangerous and even deadly, the worst wreaking havoc with people’s lives. Or they can spend their life among people who are none the wiser for it.

The Conversation

Xanthe Mallett is Senior Lecturer in Forensic Criminology at University of New England.

This article was originally published on The Conversation. Read the original article.

07 Aug 17:49

AEP : Tech’s Enduring Great-Man Myth

Albener Pessoa

Via Murilo Queiroz

Since Steve Jobs’s death, in 2011, Elon Musk has emerged as the leading celebrity of Silicon Valley. Musk is the CEO of Tesla Motors, which produces electric cars; the CEO of SpaceX, which makes rockets; and the chairman of SolarCity, which provides solar power systems. A self-made billionaire, programmer, and engineer—as well as an inspiration for Robert Downey Jr.’s Tony Stark in the Iron Man movies—he has been on the cover of Fortune and Time. In 2013, he was first on the Atlantic’s list of “today’s greatest inventors,” nominated by leaders at Yahoo, Oracle, and Google. To believers, Musk is steering the history of technology. As one profile described his mystique, his “brilliance, his vision, and the breadth of his ambition make him the one-man embodiment of the future.”

Musk’s companies have the potential to change their sectors in fundamental ways. Still, the stories around these advances—and around Musk’s role, in particular—can feel strangely outmoded.

The idea of “great men” as engines of change grew popular in the 19th century. In 1840, the Scottish philosopher Thomas Carlyle wrote that “the history of what man has accomplished in this world is at bottom the history of the Great Men who have worked here.” It wasn’t long, however, before critics questioned this one–dimensional view, arguing that historical change is driven by a complex mix of trends and not by any one person’s achievements. “All of those changes of which he is the proximate initiator have their chief causes in the generations he descended from,” Herbert Spencer wrote in 1873. And today, most historians of science and technology do not believe that major innovation is driven by “a lone inventor who relies only on his own imagination, drive, and intellect,” says Daniel Kevles, a historian at Yale. Scholars are “eager to identify and give due credit to significant people but also recognize that they are operating in a context which enables the work.” In other words, great leaders rely on the resources and opportunities available to them, which means they do not shape history as much as they are molded by the moments in which they live.

Musk insists on a success story that fails to acknowledge the importance of support from the government.

Musk’s success would not have been possible without, among other things, government funding for basic research and subsidies for electric cars and solar panels. Above all, he has benefited from a long series of innovations in batteries, solar cells, and space travel. He no more produced the technological landscape in which he operates than the Russians created the harsh winter that allowed them to vanquish Napoleon. Yet in the press and among venture capitalists, the great-man model of Musk persists, with headlines citing, for instance, “His Plan to Change the Way the World Uses Energy” and his own claim of “changing history.”

The problem with such portrayals is not merely that they are inaccurate and unfair to the many contributors to new technologies. By warping the popular understanding of how technologies develop, great-man myths threaten to undermine the structure that is actually necessary for future innovations.

Space cowboy

Elon Musk, the best-selling biography by business writer Ashlee Vance, describes Musk’s personal and professional trajectory—and seeks to explain how, exactly, the man’s repeated “willingness to tackle impossible things” has “turned him into a deity in Silicon Valley.”

Born in South Africa in 1971, Musk moved to Canada at age 17; he took a job cleaning the boiler room of a lumber mill and then talked his way into an internship at a bank by cold-calling a top executive. After studying physics and economics in Canada and at the Wharton School of the University of Pennsylvania, he enrolled in a PhD program at Stanford but opted out after a couple of days. Instead, in 1995, he cofounded a company called Zip2, which provided an online map of businesses—“a primitive Google maps meets Yelp,” as Vance puts it. Although he was not the most polished coder, Musk worked around the clock and slept “on a beanbag next to his desk.” This drive is “what the VCs saw—that he was willing to stake his existence on building out this platform,” an early employee told Vance. After Compaq bought Zip2, in 1999, Musk helped found an online financial services company that eventually became PayPal. This was when he “began to hone his trademark style of entering an ultracomplex business and not letting the fact that he knew very little about the industry’s nuances bother him,” Vance writes.

When eBay bought PayPal for $1.5 billion, in 2002, Musk emerged with the wherewithal to pursue two passions he believed could change the world. He founded SpaceX with the goal of building cheaper rockets that would facilitate research and space travel. Investing over $100 million of his personal fortune, he hired engineers with aeronautics experience, built a factory in Los Angeles, and began to oversee test launches from a remote island between Hawaii and Guam. At the same time, Musk cofounded Tesla Motors to develop battery technology and electric cars. Over the years, he cultivated a media persona that was “part playboy, part space cowboy,” Vance writes.

Musk sells himself as a singular mover of mountains and does not like to share credit for his success. At SpaceX, in particular, the engineers “flew into a collective rage every time they caught Musk in the press claiming to have designed the Falcon rocket more or less by himself,” Vance writes, referring to one of the company’s early models. In fact, Musk depends heavily on people with more technical expertise in rockets and cars, more experience with aeronautics and energy, and perhaps more social grace in managing an organization. Those who survive under Musk tend to be workhorses willing to forgo public acclaim. At SpaceX, there is Gwynne Shotwell, the company president, who manages operations and oversees complex negotiations. At Tesla, there is JB Straubel, the chief technology officer, responsible for major technical advances. Shotwell and Straubel are among “the steady hands that will forever be expected to stay in the shadows,” writes Vance. (Martin Eberhard, one of the founders of Tesla and its first CEO, arguably contributed far more to its engineering achievements. He had a bitter feud with Musk and left the company years ago.)

Musk’s companies also rely on public-sector support and good timing, a reality that Musk tries to obscure. When he bristles at NASA’s rules or fails to acknowledge SpaceX’s interdependence with the agency, he can seem delusional: “SpaceX is surfing on years and years of government-funded technology and public-sector support,” as Mariana Mazzucato, an economist at the University of Sussex and author of The Entrepreneurial State, points out.

In 2008, after three failed tries, SpaceX launched its first rocket—enough to earn it a $1.6 billion contract from NASA for flights to the International Space Station. Years later, most of the company’s work and plans involve flights to the ISS, which itself exists only as the result of public investment. The core technology of space travel depends heavily on NASA-funded work. This is not to negate the company’s innovations—in particular, lowering the cost of rocket launches and perhaps fanning visions of space exploration cheap enough for non-billionaires. But SpaceX is not driving the future of space exploration. It is capitalizing on a deep pool of technology and highly trained people that already existed, and it is doing so at a moment when national support for NASA has diminished and the government is privatizing key aspects of space travel.

We should determine technological priorities without giving excessive weight to the visions of a few tech celebrities.

Likewise, Musk’s success at Tesla is undergirded by public-sector investment and political support for clean tech. For starters, Tesla relies on lithium-ion batteries pioneered in the late 1980s with major funding from the Department of Energy and the National Science Foundation. Tesla has benefited significantly from guaranteed loans and state and federal subsidies. In 2010, the company reached a loan agreement with the Department of Energy worth $465 million. (Under this arrangement, Tesla agreed to produce battery packs that other companies could benefit from and promised to manufacture electric cars in the United States.) In addition, Tesla has received $1.29 billion in tax incentives from Nevada, where it is building a “gigafactory” to produce batteries for cars and consumers. It has won an array of other loans and tax credits, plus rebates for its consumers, totaling another $1 billion, according to a recent series by the Los Angeles Times.

It is striking, then, that Musk insists on a success story that fails to acknowledge the importance of public-sector support. (He called the L.A. Times series “misleading and deceptive,” for instance, and told CNBC that “none of the government subsidies are necessary,” though he did admit they are “helpful.”)

If Musk’s unwillingness to look beyond himself sounds familiar, Steve Jobs provides a recent antecedent. Like Musk, who obsessed over Tesla cars’ door handles and touch screens and the layout of the SpaceX factory, Jobs brought a fierce intensity to product design, even if he did not envision the key features of the Mac, the iPod, or the iPhone. An accurate version of Apple’s story would give more acknowledgment not only to the work of other individuals, from designer Jonathan Ive on down, but also to the specific historical context in which Apple’s innovation occurred. “There is not a single key technology behind the iPhone that has not been state funded,” says economist Mazzucato. This includes the wireless networks, “the Internet, GPS, a touch-screen display, and … the voice-activated personal assistant Siri.” Apple has recombined these technologies impressively. But its achievements rest on many years of public-sector investment. To put it another way, do we really think that if Jobs and Musk had never come along, there would have been no smartphone revolution, no surge of interest in electric vehicles?

This matters because the great-man narrative carries costs. First, it has helped to corrode the culture of Silicon Valley. Great-man lore helps excuse (or enable) some truly terrible behavior. Musk is known, after all, for humiliating engineers and firing employees on a whim. In 2014, when his assistant, who had devoted her life to Tesla and SpaceX for 12 years, asked for a raise, he summarily let her go. Nor can Musk’s rough edges be justified as good for business. Rather, they have the potential to jeopardize crucial relationships with government agencies, according to a former official interviewed by Vance: Musk’s “biggest enemy will be himself and the way he treats people.” Similarly, Jobs was known for entitled behavior and brutishness to employees. Yet as Walter Isaacson has written in his biography, Steve Jobs: “Nasty was not necessary. It hindered him more than it helped him.” If Silicon Valley, with its well-documented problems with diversity, is to attract a broader pool of talented people, encouraging more supportive managerial practices and telling more inclusive stories about who matters would surely help.

Hero myths like the ones surrounding Musk and Jobs are damaging in other ways, too. If tech leaders are seen primarily as singular, lone achievers, it is easier for them to extract disproportionate wealth. It is also harder to get their companies to accept that they should return some of their profits to agencies like NASA and the National Science Foundation through higher taxes or simply less tax dodging.

And finally, technology hero worship tends to distort our visions of the future. Why should governments do the hard work of fixing and expanding California’s mass transit system when Musk says we could zip people across the state at 760 miles per hour in a “hyperloop”? Is trying to colonize Mars, at a cost in the billions of dollars, actually the right direction for future space exploration and scientific research? We should be able to determine long-term technology priorities without giving excessive weight to the particular visions of a few tech celebrities.

Rather than placing tech leaders on a pedestal, we should put their successes in context, acknowledging the role of government not only as a supporter of basic science but as a partner for new ventures. Otherwise, it is all too easy to denigrate public-sector investment, eroding support for government agencies and training programs and ultimately putting future innovation at risk. As Mazzucato puts it, “It’s precisely because we admire Musk and think his contributions are important that we need to get real about where his success actually comes from.”

07 Aug 16:38

America fact of the day

by Tyler Cowen

Today, the most studied language in U.S. higher education, behind Spanish and French, is a homegrown one: American Sign Language.

The study of Spanish, by the way, is slightly in decline.

That is all from Charles King, “The Decline of International Studies: Why Flying Blind is Dangerous.

07 Aug 00:27



TWITTER ► @canalixi
INSTAGRAM ► @canalixioficial

Gabriel Rocha :

John: Cezar Maracujá
Ted: Alan Ribeiro
Rato Borrachudo: Rato Borrachudo

Roteiro: Alan Ribeiro
Produção: Cezar Fieschi
Edição: Alan Ribeiro
Vinheta: Mateus Silva
Direção e Fotografia: Renato Chaves

06 Aug 23:39

AEP : 23 Difficulties An Introvert Faces (By INFJoe)

Albener Pessoa

Figure 2, 16 and 23 are the best

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06 Aug 22:21

AEP : 10 pseudocientistas e suas teorias bizarras

Publicado em 1.02.2015

Ao longo da história, tem havido inúmeras explicações científicas bem aceitas que mais tarde foram consideradas erradas. Mas alguns cientistas passam tão fora da marca que é preciso criar um novo termo para suas teorias bizarras totalmente equivocadas.

10. Wilhelm Reich com “Orgone”

pseudocientistas teorias erradas 10
Nascido em 1897, Wilhelm Reich foi um psiquiatra que trabalhou brevemente com Sigmund Freud e mais tarde começou a sua própria prática, em 1922. Em 1940, ele se mudou para os Estados Unidos e desenvolveu suas teorias. Segundo Reich, ele havia provado cientificamente a existência de um composto, uma forma de energia, que era a manifestação física da libido. Ela se acumulava no corpo e era descarregada com sucesso através de um orgasmo. Reich construiu uma máquina que lhe permitia estudar essa energia, chamada por ele de “orgone”. Com essa energia, formulou teorias sobre tudo, desde a gravidade até o clima.

Reich e seus apoiadores fizeram muita pesquisa sobre as propriedades do orgone. Em 1947, ele escreveu um livro chamado “The Cancer Biopathy” com base em suas experiências com células cancerosas de ratos. O cientista alegava ser capaz de prolongar a vida dos seus animais doentes por semanas, ainda mais quando usava a energia coletada de sua máquina de orgone. Até hoje existem organizações (como o American College of Orgonomy) que estudam formalmente o trabalho de Reich e oferecem tratamento para várias condições, incluindo transtorno de estresse pós-traumático, esquizofrenia, anorexia e transtorno obsessivo-compulsivo.

9. Frederic Petit com “A outra lua”

pseudocientistas teorias erradas 9
De acordo com o astrônomo Frederic Petit, a Terra tem uma segunda lua. Trabalhando em 1846 em um observatório em Toulouse, na França, Petit afirmou que a presença de uma segunda lua explicava todas as irregularidades astronômicas que a comunidade científica estava tendo dificuldades em resolver. Essa segunda lua tinha um tempo orbital de apenas 2 horas, 44 minutos e 59 segundos. No seu ponto mais distante da Terra, estava a cerca de 3.570 km de nós. Ninguém levou suas descobertas a sério, embora ele tenha publicado artigos por 15 anos após a sua “descoberta” inicial.

A teoria de Petit, apesar de bizarra, não é única. Outros também creem que a Terra tem mais de uma lua. Em 1989, Georg Waltemath afirmou ter descoberto que a Terra era orbitada por toda uma rede de “mini-luas”. Algumas iluminavam o céu com a mesma força que o sol, disse. O louco ainda lançou uma série de datas e horários em que as pessoas podiam ver estas pequenas luas, mas ninguém nunca viu nada fora do comum.

8. Marcel Vogel com “Plantas sentimentais e cristais mágicos”

pseudocientistas teorias erradas 8
Marcel Vogel descobriu que as plantas têm sentimentos. Mais ou menos. Técnico da IBM, ele pesquisou as respostas das plantas a estímulos de corte e danos, que provocavam uma reação que poderia ser lida e entendida em termos de energia liberada. De acordo com Vogel, as plantas estavam respondendo em conjunto com suas próprias emoções e energia. Ele determinou que elas estavam armazenando suas energias mentais e liberando-as no momento em que interagiam com ele.

Isso foi na década de 1960. Em 1984, Vogel fundou a Psychic Research Inc. com algumas metas muito ambiciosas. Ele queria purificar a água, reorganizar sua energia e acelerar o processo de envelhecimento de vinhos – tudo usando apenas cristais de quartzo.

Vogel alegou que passou a acreditar no poder dos cristais depois de meditar sobre o rosto da Virgem Maria enquanto se concentrava em um desses objetos. Depois de uma hora de foco, o cristal tomou claramente a forma de sua imagem mental. Alguns dos cristais cortados por Vogel ainda estão disponíveis para a venda – e são caros -, mas não criam energia, apenas amplificam a emitida pelo corpo de uma pessoa. Vogel informou que a força mais poderosa é o amor, e seus cristais são capazes de capturar, armazenar e ampliar o amor.

7. Ignatz Von Peczely com “Iridologia”

pseudocientistas teorias erradas 7
Enquanto nossos olhos podem de fato refletir nosso bem-estar, o médico húngaro Ignatz von Peczely levou essa ideia a um novo nível. Tudo começou quando ele notou uma marca preta no olho de uma coruja cuja perna ele tinha quebrado. Embora o incidente tivesse acontecido quando ele era jovem, Ignatz nunca o esqueceu. Quando se formou em 1867, já havia estudado os olhos de inúmeros pacientes e criado um gráfico de qual parte da íris era relacionada com qual parte do corpo.

De acordo com von Peczely e um contemporâneo chamado Nils Liljequist, qualquer distúrbio no corpo poderia ser diagnosticado através de alterações na cor da íris, sem necessidade de exames. Hoje, ainda existem iridólogos treinados para detectar doenças e defeitos genéticos através dos olhos. As pessoas são classificadas em três “tipos constitucionais” definidos por cor: as de olhos azuis pertencem ao tipo linfático e são predispostas a problemas de pele como acne, caspa, artrite, bronquite e irritações oculares. Pessoas de olhos castanhos são do tipo hematogênico e propensas a desenvolver anemia, doenças do aparelho digestivo, doenças crônicas e degenerativas, diabetes e gases. O terceiro tipo é uma mistura dos dois, chamado de biliar. Se a sua cor dos olhos é verde ou qualquer outra mistura de marrom e azul, significa que você é suscetível a doenças associadas com ambos os tipos, especificamente gases e doenças do sangue.

6. Juiz Edward Jones com “Personologia”

pseudocientistas teorias erradas 6
De acordo com um livro escrito pelo fundador do Centro Internacional para Personologia, a ciência começou na década de 1930 com um juiz do sistema tribunal de Los Angeles, nos EUA. Depois de ver os rostos de réu após réu, o juiz Edward Jones começou a correlacionar as aparências faciais das pessoas com os crimes que haviam cometido.

Mais tarde, mais “pesquisa” foi feita por um editor de jornal chamado Robert Whiteside. De acordo com as suas conclusões, o rosto de uma pessoa pode ser um indicador claro de que tipo de personalidade ela tem. Ele acreditava que ambas as coisas eram geneticamente determinadas e portanto deviam estar conectadas.

5. Alfred William Lawson com “Lawsonomia”

pseudocientistas teorias erradas 5
Alfred William Lawson foi lançador de beisebol profissional por 20 anos. Quando se cansou dessa profissão, se virou para a aviação. Ele é creditado com tendo uma ideia para criar um certo avião, mas suas próprias tentativas de formar uma empresa e construir uma frota falharam miseravelmente. Ele então fundou a Universidade de Lawsonomia, que ensinava apenas uma coisa: a própria Lawsonomia.
E o que seriam esses ensinamentos? Coisas como “não existe energia, apenas uma constante batalha de puxa-e-empurra entre as coisas com alta densidade e baixa densidade”; “a Terra está nadando em éter”; “tudo o que existe na Terra é sugado para o planeta através de um grande buraco perto do Polo Norte e distribuído por todo o mundo através de suas artérias internas” etc.

Alimentação e nutrição são conceitos complicados em Lawsonomia. As plantas são parasitas da Terra, e é provável que estão se comunicando entre si de uma maneira que não entendemos. Também, cozinhar suga toda a vida e os nutrientes de alimentos. Lawson chegou a essa conclusão por causa do que acontece com uma pessoa quando ela é jogada no fogo. É lógico que a mesma coisa acontece com tudo o que vive.

A Universidade de Lawsonomia chegou ao fim depois de uma investigação que questionou o que a instituição sem fins lucrativos estava fazendo com os seus fundos (mas deveria mesmo é ter questionado literalmente tudo sobre “Lawsonomia”).

4. Hanns Hõrbiger com a “Teoria Cósmica do Gelo”

pseudocientistas teorias erradas 4
Na década de 1920, o austríaco Hanns Hõrbiger inventou a seguinte teoria: tudo era feito de gelo no universo, desde as estrelas no céu até a Terra e o desenvolvimento da vida nela. Sua explicação para o desenvolvimento da ideia era bastante ambiciosa: Hõrbiger teve uma visão em 1894. Foi-lhe revelado que o gelo era a base de tudo. Os fatos que ele estava construindo suas teorias em torno eram baseados em “intuição criativa” e “experimentos artificiais”.

Ao invés de começar com a comunidade científica, Hõrbiger introduziu suas teorias para o público, na esperança de que o apoio popular fosse uma influência positiva. Surpreendentemente, funcionou. Livros e programas de rádio adotaram a Teoria Cósmica do Gelo na Alemanha, mas, depois da guerra, a credibilidade da ideia morreu.

3. John Keely com a “Máquina de Movimento Perpétuo”

pseudocientistas teorias erradas 3
Nascido em 1837, o vigarista John Keely conseguiu convencer muita gente de que tinha criado uma máquina de movimento perpétuo. Ele clamou que havia descoberto uma forma completamente nova de energia física que poderia produzir uma quantidade incrível de poder. Usando moléculas de água, Keely era capaz de sincronizar as vibrações moleculares com sua máquina e criar energia interminável.

Logo, ele conseguiu arrecadar US$ 5 milhões em capital com investidores para iniciar a Keely Motor Company. Ele foi capaz de demonstrar o seu motor de grande escala em 1874. Suas descrições incluíam palavras como “éter-etérico” e “impulsos metálicos”, e a máquina era ligada muitas vezes com a ajuda de vibrações de um instrumento musical. Ele manteve os investidores interessados por muito tempo, ao mesmo tempo se recusando a pedir qualquer patente, com medo de que alguém roubasse sua ideia.

Em 1890, organizações como a Scientific American começaram a questionar a tal máquina. Keely ainda conseguiu manter a empresa por mais oito anos, até morrer em 1898. Em resumo, a Keely Motor Company ficou ativa por 25 anos sem um produto e sem pagar um único dividendo a qualquer investidor. Quando eles foram checar a máquina após a morte do golpista, encontraram um piso falso e um recipiente de ar comprimido que eram a explicação para o “poder” do aparelho.

2. Rene Blondlot com os “Raios-N”

pseudocientistas teorias erradas 2
Em 1903, a comunidade científica estava animada com a descoberta da radiação e dos raios-X. O cientista francês René Blondlot estava experimentando com raios-X quando alegou ter tropeçado em algo ainda mais incrível: raios-N, nomeados assim em homenagem a sua cidade natal, Nancy.

Problema: ninguém conseguiu repetir facilmente os resultados de Blondlot. O cientista detectou pela primeira vez os raios-N quando viu uma pequena faísca do canto do olho. Suas instruções sobre como detectar raios-N eram bastante questionáveis (por exemplo, incluíam trancar-se em um quarto escuro por um tempo antes de realizar os experimentos para garantir que os olhos se ajustassem, e a nota de que algumas pessoas não seriam capazes de vê-los da primeira vez, nem da segunda ou da terceira).

Ainda assim, Blondlot e seus colegas franceses fizeram uma lista das propriedades dos raios-N – eles podiam supostamente passar por qualquer coisa que bloqueasse luz e só seriam parados por materiais transparentes; eram emitidos pelo sol, mas apenas em dias nublados etc. No entanto, pesquisadores na Inglaterra e na Alemanha não estavam convencidos da descoberta, que foi finalmente desmascarada quando um físico da Universidade Johns Hopkins (EUA) foi à França ver o experimento e provou que não havia nenhum raio-N. A carreira de Blondlot foi arruinada.

1. Albert Abrams com “Radiônica”

pseudocientistas teorias erradas 1
No início de 1900, um médico chamado Albert Abrams afirmou ter descoberto o segredo para diagnosticar e curar quase qualquer doença do corpo humano. A resposta estava nas vibrações de cada célula. Estas vibrações, chamadas de reações elétricas de Abrams, podiam ser lidas por muitos dispositivos. A prática, nomeada radiônica, detectava doenças através de amostras de sangue, saliva, unha ou até mesmo por análise de um objeto pessoal do aflito.

Sem surpresa, muitas pessoas chamaram a ciência de fraudulenta. A Scientific American e a Administração de Drogas e Alimentos dos EUA questionaram a ideia de Abrams, e enviaram amostras de sangue a fim de investigar se os resultados seriam precisos. A primeira amostra foi diagnosticada com colite, embora a pessoa de quem foi tirada estivesse morta. Um amputado foi diagnosticado como tendo artrite na perna que tinha perdido, e uma galinha foi diagnosticada com sinusite.

Por incrível que pareça, ainda existem organizações que praticam radiônica, descrita como uma ciência intuitiva utilizada para diagnosticar problemas usando os campos de energia de uma pessoa. [Listverse]

06 Aug 17:04

The best comebacks on Tinder to pick-up lines and rejections.

Albener Pessoa

Must click to read. Some are hilarious

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06 Aug 16:32


05 Aug 17:03

AEP : Blitab: World's first tactile tablet is 'iPad for the blind'

Albener Pessoa

It would be fantastic but with an ETA of September/2016 (more than a year from now) it's just vaporware

blitab braille tablet blind
The Blitlab tablet converts files and web pages into braille and relief images for blind and visually impaired people(IBTimes UK)

The first-ever braille tablet has been developed, using a new liquid-based technology to create tactile relief outputting braille, graphics and maps for the blind and partially sighted.

Austria-based startup Blitab Technology claims the "revolutionary" technology could be used to open up the digital era to the visually impaired, with plans to develop a braille smartphone.

"We are creating the first tactile tablet for blind and visually impaired people," Slavi Slavev, chief technology officer and co-founder of Blitab Technology, told IBTimes UK at the Hello Tomorrow Conference in Paris. "What we are doing is creating a completely new technology which outputs braille in a completely new and innovative way without any mechanical elements.

braille tablet blind blitab slavev
Tactile relief is created instantly through small liquid bubbles on the screen(Blitab)

"This is revolutionary and we want to solve a great issue, and that's the literacy of blind people. The technology is quite scalable so we can output images and put any tactile relief representation like maps and graphics, such as geometric figures, in order to serve as an educational tool for blind people."

Other devices currently on the market are mechanical and only allow for one line of braille to be generated at any one time. They also cost about three-times the price of the €2,500 (£1,778, $2,802) Blitab. More recent refreshable braille concepts, such as the Anagraph e-reader, have run out of funds before being able to bring the product to market.

The Blitab tablet uses liquid bubbles to instantly generate braille text or relief images, while the corresponding technology allows text files to be instantly converted into braille from USB sticks, web browsers or NFC tags.

braille smartphone tablet ipad ereader
Refreshable braille devices currently on the market only offer one line and are typically expensive(Hims)

"Currently there are some solutions which are extremely expensive and they represent only one line [of braille]," Slavev said. "These devices were developed 40 years ago and because no one has offered any new innovations since then, that's still all that's on the market."

In the UK, interest in the Blitab has been shown by the Royal National Institute for the Blind (RNIB) and Barclays bank, due to its potential for helping blind and partially-sighted customers instore.

Blitab is currently in the prototyping stage but if the ongoing investment round is successful the startup is hoping to bring the first product to market by September 2016.

Slavev added: "We think blind people should be included in the digital era in which we live, with all of the smartphones and tablets, but also ensure that they have a proper way to do everything that sighted people do, like web browsing, reading books and downloading books.

"Only 1% of all books worldwide are available in printed braille, as it's very expensive to produce printed braille. Some people are even saying that braille is decreasing among blind people but we want to get to the point where we can actually change this."

05 Aug 14:38

AEP : 13 Awkward Things You Have To Deal With When You Don't Want Kids

1. People who assume you're a kid-hating psychopath.

Liking and wanting are two different things. Geesh.

2. People ask if you have kids YET, as though it's inevitable.

Just say no and move on. It's not worth explaining.

3. Friends with kids come over and all you can offer them are pet toys.

What about a copy of Wired Magazine?

4. People get all smug when they tell you you'll change your mind.

Thanks for assuming I don't know what I want in life. You're so kind.

5. Your parents whine, "But you'd be such a good mom!" and you're not sure what to say.

Because it makes you want to say "No I wouldn't!" but then that's a little weird.

6. People ask if you want to hold their new kid, like it's gonna turn you or something.

"Look into my're feeling the urge to procreate...."

7. Someone brags on their toddler, and you blurt out "My cat does that too!"

But, you know, it's totally different.

8. New parents give you a look when you call their baby "it" rather than "he" or "she."

Like you just shot a puppy.

9. Children ask "Where are your kids?" loud enough for the entire room to hear.


10. Parents wail "Gee I wish I had time for that" when you talk about going to the movies/your weekend getaway/the last video game you played.


11. People with kids feel the need to text, Facebook-message, and email you multiple pictures of their offspring.

I mean, how many times do I have to agree that they're cute?

12. New parents act like they're in on some universal secret you don't know about yet.

We'll see who's smirking in 18 years.

13. Your parents make a squealing gasp every time you say, "I have to tell you something."

No, not that, Mom. Geeze.

05 Aug 14:18

yumathepuma: My absolute favorite moment from What We Do in the...

Albener Pessoa

It is a good movie
(Via Firehouse)


My absolute favorite moment from What We Do in the Shadows.