Style2Paints NN: V4 now released (paper for V3; multiple layers of anime lineart coloring now supported: flat colors, then adding lines, then color gradients/shading, then illumination. Uses Danbooru2017 for training data via data-augmentation/corruption to train recoloring. Discussion: 1/2/Twitter)
“How We All Failed In Performance Contracting”, Page 1972 (social impact bonds before social impact bonds: killed by failure in one of the largest education randomized experiments ever run—6 contractors, 18 school districts, and 25,000 students)
“Words”, Radiolab 2010 (language & abstraction: a deaf adult learning what words are for the first time; brain damage causing enlightenment, see also Martin 2013; <6yo children unable to understand directions like “left of the blue wall”)
Well-Played 3.0, ed Davidson 2011 (good: “And if You Go Chasing Rabbits: The Inner Demons of American McGee’s Alice”; “The Neverhood; A Different Kind of Never Never Land. You Had Me at Claymation”; “Uncharted 2: Among Thieves—Becoming a Hero”; “The World Ends With You”; “The Opposite of Accessible: Street Fighter IV”; “Siren is the Scariest Game Ever Made”)
Newsletter tag: archive of all issues back to 2013 for the gwern.net newsletter (monthly updates, which will include summaries of projects I’ve worked on that month (the same as the changelog), collations of links or discussions from my subreddit, and book/movie reviews.)
This page is a changelog for Gwern.net: a monthly reverse chronological list of recent major writings/changes/additions.
Following my writing can be a little difficult because it is often so incremental. So every month, in addition to my regular /r/Gwern subreddit submissions, I write up reasonably-interesting changes and send it out to the mailing list in addition to a compilation of links & reviews (archives).
A subreddit for posting links of interest and also for announcing updates to gwern.net (which can be used as a RSS feed). Submissions are categorized similar to the monthly newsletter and typically will be collated there.
I review John Bradshaw’s book on cat psychology, Cat Sense, after difficulties dealing with my own cat. Bradshaw reviews the history of domestic cats from their apparent Middle Eastern origins as a small solitary desert predator to their domestication in Ancient Egypt where breeding millions of cats for sacrifice may have played a critical role (as opposed to any unique role as a vermin exterminator) through to the modern day and psychological studies of the learning abilities and personalities of cats, with particular emphasis on cat social skills in “cat colonies” & plasticity in kittenhood. As Bradshaw diagnoses it, these are responsible for what ability they have to modern pet life, even though they are not bred for this like dogs; every tame cat still has the feral cat in them, and are in many ways unsuited for contemporary living, with disturbing hints that human lack of selective breeding plus recent large-scale spay/neuter population control efforts may be producing a subtle dysgenic effect on domestication, and this double neglect & backfire may be responsible for disturbingly high rates of cat maladaptation & chronic stress diseases.
Can deer evolve under the selection pressure of car accidents to learn to avoid roads? Probably, but it'll take a long time.
I’ve noticed while driving many deer corpses over the years. Cars seem like they could be a major source of deer mortality. If they are, deer might be evolving behavior to avoid cars. But deer/car accident rates appear stable or increasing (perhaps due to human population growth & construction). How fast would we expect to see any deer adaptation?
Looking at some of the mortality statistics, I model it as a liability threshold trait being selected on via truncation selection, and calculate some hypotheticals about whether and how fast they could adapt.
Background: Suicide is a major issue for global public health. ‘Suicidality’ describes a broad clinical spectrum of thoughts and behaviours, some of which are common in the general population.
Methods: UK Biobank recruited ~0·5 million middle age individuals from the UK, of whom 157,000 completed an assessment of suicidality. Mutually exclusive groups were assessed in an ordinal genome-wide association study of suicidality: ‘no suicidality’ controls (n = 83,557); ‘thoughts that life was not worth living’ (n = 21,063); ‘ever contemplated self-harm’ (n = 13,038); ‘an act of deliberate self-harm in the past’ (n = 2,498); and ‘a previous suicide attempt’ (n = 2,666). Linkage of UK Biobank to death certification records identified a small sub-group of ‘completed suicide’ (n = 137).
Outcomes: We identified three novel genome-wide significant loci for suicidality (on Chromosomes 9, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81). Higher polygenic risk scores for suicidality were associated with increased risk of completed suicide relative to controls in an independent sub-group (n = 137 vs n = 5,330, OR 1·23, 95%CI 1·06 to 1·41, p = 0.03). Rs598046-G (chromosome 11) demonstrated a similar effect size and direction (p = 0·05) within a Danish suicidality study.
Interpretation: These findings have significant implications for our understanding of genetic vulnerability to suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level.
Funding: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217).
Background: Psychiatric disorders show phenotypic as well as genetic overlaps. Factor analyses of child and adult psychopathology have found that phenotypic overlaps largely can be explained by a latent general “p” factor that reflects general liability to psychopathology. We investigated whether shared genetic liability across disorders would be reflected in associations between multiple different psychiatric polygenic risk scores (PRS) and a ‘general psychopathology’ factor in childhood.
Methods: The sample was a UK, prospective, population-based cohort (ALSPAC), including data on psychopathology at age 7 (N = 8161) years. PRS were generated from large published genome-wide association studies.
The general psychopathology factor was associated with both schizophrenia PRS and attention-deficit/hyperactivity disorder (ADHD) PRS, whereas there was no strong evidence of association with major depressive disorder and autism spectrum disorder PRS. Schizophrenia PRS was also associated with a specific “emotional” problems factor.
Our findings suggest that genetic liability to schizophrenia and ADHD may contribute to shared genetic risks across childhood psychiatric diagnoses at least partly via the ‘general psychopathology’ factor. However, the pattern of observations could not be explained by a general “p” factor on its own.
This work was supported by the Wellcome Trust (204895/Z/16/Z).Introduction
Complex traits and common disease are highly polygenic: thousands of common variants are causal, and their effect sizes are almost always small. Polygenicity could be explained by negative selection, which constrains common-variant effect sizes and may reshape their distribution across the genome. We refer to this phenomenon as flattening, as genetic signal is flattened relative to the underlying biology. We introduce a mathematical definition of polygenicity, the effective number of associated SNPs, and a robust statistical method to estimate it. This definition of polygenicity differs from the number of causal SNPs, a standard definition; it depends strongly on SNPs with large effects. In analyses of 33 complex traits (average N = 361k), we determined that common variants are ~4x more polygenic than low-frequency variants, consistent with pervasive flattening. Moreover, functionally important regions of the genome have increased polygenicity in proportion to their increased heritability, implying that heritability enrichment reflects differences in the number of associations rather than their magnitude (which is constrained by selection). We conclude that negative selection constrains the genetic signal of biologically important regions and genes, reshaping genetic architecture.
The so-called domestic cat occupies a unique position within the truly domestic animals since it freely interbreeds with feral populations, and there is considerable gene flow in both directions. This is possible because the likelihood of an individual cat forming a relationship with people is strongly affected by its experiences during the socialisation period (3–8 weeks of age), although this does not preclude differences between owned and feral populations in the relative frequencies of alleles which affect social behaviour towards humans. We suggest a hitherto unconsidered reason why a separate domesticated population of cats (apart from pedigree breeds) has not yet emerged: the unusual and stringent nutrient requirements of the cat may historically have militated against successful breeding on a completely human-provided diet, and led to the retention of the ability to achieve a nutritionally complete diet by scavenging and/or hunting. More recently, the widespread availability of nutritionally complete manufactured foods and veterinary care in western countries appears to be leading towards a rapid change in the population dynamics and population genetics of both owned and feral cats. [Keywords: Domestication, Feral populations, Population dynamics, Cat]
The domesticated silver fox is a form of the silver fox which has been to some extent domesticated under laboratory conditions. The silver fox is a melanistic form of the wild red fox. Domesticated silver foxes are the result of an experiment which was designed to demonstrate the power of selective breeding to transform species, as described by Charles Darwin in On the Origin of Species. The experiment explored whether selection for behaviour rather than morphology may have been the process that had produced dogs from wolves, by recording the changes in foxes when in each generation only the most tame foxes were allowed to breed. Many of the descendant foxes became both tamer and more dog-like in morphology, including displaying mottled or spotted coloured fur.
Statistical methodology has played a key role in scientific animal breeding. Approximately one hundred years of statistical developments in animal breeding are reviewed. Some of the scientific foundations of the field are discussed, and many milestones are examined from historical and critical perspectives. The review concludes with a discussion of some future challenges and opportunities arising from the massive amount of data generated by livestock, plant, and human genome projects.
To solve complex real-world problems with reinforcement learning, we cannot rely on manually specified reward functions. Instead, we can have humans communicate an objective to the agent directly. In this work, we combine two approaches to learning from human feedback: expert demonstrations and trajectory preferences. We train a deep neural network to model the reward function and use its predicted reward to train an DQN-based deep reinforcement learning agent on 9 Atari games. Our approach beats the imitation learning baseline in 7 games and achieves strictly superhuman performance on 2 games without using game rewards. Additionally, we investigate the goodness of fit of the reward model, present some reward hacking problems, and study the effects of noise in the human labels.
Traditionally, medical discoveries are made by observing associations, making hypotheses from them and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can often be difficult because of the wide variety of features, patterns, colours, values and shapes that are present in real data. Here, we show that deep learning can extract new knowledge from retinal fundus images. Using deep-learning models trained on data from 284,335 patients and validated on two independent datasets of 12,026 and 999 patients, we predicted cardiovascular risk factors not previously thought to be present or quantifiable in retinal images, such as age (mean absolute error within 3.26 years), gender (area under the receiver operating characteristic curve (AUC) = 0.97), smoking status (AUC = 0.71), systolic blood pressure (mean absolute error within 11.23 mmHg) and major adverse cardiac events (AUC = 0.70). We also show that the trained deep-learning models used anatomical features, such as the optic disc or blood vessels, to generate each prediction.
Github repo with screenshot samples of style2paints, a neural network for colorizing anime-style illustrations (trained on Danbooru2018), with or without user color hints, which was available as an online service in 2018. style2paints produces high-quality colorizations often on par with human colorizations. Many examples can be seen on Twitter or the Github repo:
Sketch or line art colorization is a research field with significant market demand. Different from photo colorization which strongly relies on texture information, sketch colorization is more challenging as sketches may not have texture. Even worse, color, texture, and gradient have to be generated from the abstract sketch lines. In this paper, we propose a semi-automatic learning-based framework to colorize sketches with proper color, texture as well as gradient. Our framework consists of two stages. In the first drafting stage, our model guesses color regions and splashes a rich variety of colors over the sketch to obtain a color draft. In the second refinement stage, it detects the unnatural colors and artifacts, and try to fix and refine the result.Comparing to existing approaches, this two-stage design effectively divides the complex colorization task into two simpler and goal-clearer subtasks. This eases the learning and raises the quality of colorization. Our model resolves the artifacts such as water-color blurring, color distortion, and dull textures.
We build an interactive software based on our model for evaluation. Users can iteratively edit and refine the colorization. We evaluate our learning model and the interactive system through an extensive user study. Statistics shows that our method outperforms the state-of-art techniques and industrial applications in several aspects including, the visual quality, the ability of user control, user experience, and other metric
Sketch or line art colorization is a research field with significant market demand. Different from photo colorization which strongly relies on texture information, sketch colorization is more challenging as sketches may not have texture. Even worse, color, texture, and gradient have to be generated from the abstract sketch lines. In this paper, we propose a semi-automatic learning-based framework to colorize sketches with proper color, texture as well as gradient. Our framework consists of two stages. In the first drafting stage, our model guesses color regions and splashes a rich variety of colors over the sketch to obtain a color draft. In the second refinement stage, it detects the unnatural colors and artifacts, and try to fix and refine the result. Comparing to existing approaches, this two-stage design effectively divides the complex colorization task into two simpler and goal-clearer subtasks. This eases the learning and raises the quality of colorization. Our model resolves the artifacts such as water-color blurring, color distortion, and dull textures. We build an interactive software based on our model for evaluation. Users can iteratively edit and refine the colorization. We evaluate our learning model and the interactive system through an extensive user study. Statistics shows that our method outperforms the state-of-art techniques and industrial applications in several aspects including, the visual quality, the ability of user control, user experience, and other metrics.
Modeling of music audio semantics has been previously tackled through learning of mappings from audio data to high-level tags or latent unsupervised spaces. The resulting semantic spaces are theoretically limited, either because the chosen high-level tags do not cover all of music semantics or because audio data itself is not enough to determine music semantics. In this paper, we propose a generic framework for semantics modeling that focuses on the perception of the listener, through EEG data, in addition to audio data. We implement this framework using a novel end-to-end 2-view Neural Network (NN) architecture and a Deep Canonical Correlation Analysis (DCCA) loss function that forces the semantic embedding spaces of both views to be maximally correlated. We also detail how the EEG dataset was collected and use it to train our proposed model. We evaluate the learned semantic space in a transfer learning context, by using it as an audio feature extractor in an independent dataset and proxy task: music audio-lyrics cross-modal retrieval. We show that our embedding model outperforms Spotify features and performs comparably to a state-of-the-art embedding model that was trained on 700 times more data. We further discuss improvements to the model that are likely to improve its performance.
Particular deep artificial neural networks (ANNs) are today’s most accurate models of the primate brain’s ventral visual stream. Here we report that, using a targeted ANN-driven image synthesis method, new luminous power patterns (i.e. images) can be applied to the primate retinae to predictably push the spiking activity of targeted V4 neural sites beyond naturally occurring levels. More importantly, this method, while not yet perfect, already achieves unprecedented independent control of the activity state of entire populations of V4 neural sites, even those with overlapping receptive fields. These results show how the knowledge embedded in today’s ANN models might be used to non-invasively set desired internal brain states at neuron-level resolution, and suggest that more accurate ANN models would produce even more accurate control.
In mathematics, the theory of optimal stopping or early stopping is concerned with the problem of choosing a time to take a particular action, in order to maximise an expected reward or minimise an expected cost. Optimal stopping problems can be found in areas of statistics, economics, and mathematical finance. A key example of an optimal stopping problem is the secretary problem. Optimal stopping problems can often be written in the form of a Bellman equation, and are therefore often solved using dynamic programming.
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. It is often used when the search space is discrete. For problems where finding an approximate global optimum is more important than finding a precise local optimum in a fixed amount of time, simulated annealing may be preferable to exact algorithms such as gradient descent, Branch and Bound.
“Many Labs 2: Investigating Variation in Replicability Across Sample and Setting”, Richard Klein, Michelangelo, Vianello, Fred, Hasselman, Byron, Adams, Reginald B. Adams, Jr., Sinan Alper, Mark Aveyard, Jordan Axt, Mayowa Babalola, Štěpán Bahník, Mihaly Berkics, Michael Bernstein, Daniel Berry, Olga Bialobrzeska, Konrad Bocian, Mark Brandt, Robert Busching, Huajian Cai, Fanny Cambier, Katarzyna Cantarero, Cheryl Carmichael, Zeynep Cemalcilar, Jesse Chandler, Jen-Ho Chang, Armand Chatard, Eva CHEN, Winnee Cheong, David Cicero, Sharon Coen, Jennifer Coleman, Brian Collisson, Morgan Conway, Katherine Corker, Paul Curran, Fiery Cushman, Ilker Dalgar, William Davis, Maaike de Bruijn, Marieke de Vries, Thierry Devos, Canay Doğulu, Nerisa Dozo, Kristin Dukes, Yarrow Dunham, Kevin Durrheim, Matthew Easterbrook, Charles Ebersole, John Edlund, Alexander English, Anja Eller, Carolyn Finck, Miguel-Ángel Freyre, Mike Friedman, Natalia Frankowska, Elisa Galliani, Tanuka Ghoshal, Steffen Giessner, Tripat Gill, Timo Gnambs, Angel Gomez, Roberto Gonzalez, Jesse Graham, Jon Grahe, Ivan Grahek, Eva Green, Kakul Hai, Matthew Haigh, Elizabeth Haines, Michael Hall, Marie Heffernan, Joshua Hicks, Petr Houdek, Marije van, der Hulst, Jeffrey Huntsinger, Ho Huynh, Hans IJzerman, Yoel Inbar, Åse Innes-Ker, William Jimenez-Leal, Melissa-Sue John, Jennifer Joy-Gaba, Roza Kamiloglu, Andreas Kappes, Heather Kappes, Serdar Karabati, Haruna Karick, Victor Keller, Anna Kende, Nicolas Kervyn, Goran Knezevic, Carrie Kovacs, Lacy Krueger, German Kurapov, Jaime Kurtz, Daniel Lakens, Ljiljana Lazarevic, Carmel Levitan, Neil Lewis, Samuel Lins, Esther Maassen, Angela Maitner, Winfrida Malingumu, Robyn Mallett, Satia Marotta, Jason McIntyre, Janko Međedović, Taciano Milfont, Wendy Morris, Andriy Myachykov, Sean Murphy, Koen Neijenhuijs, Anthony Nelson, Felix Neto, Austin Nichols, Susan O'Donnell, Masanori Oikawa, Gabor Orosz, Malgorzata Osowiecka, Grant Packard, Rolando Pérez, Boban Petrovic, Ronaldo Pilati, Brad Pinter, Lysandra Podesta, Monique Pollmann, Anna Dalla Rosa, Abraham Rutchick, Patricio Saavedra, Airi Sacco, Alexander Saeri, Erika Salomon, Kathleen Schmidt, Felix Schönbrodt, Maciek Sekerdej, David Sirlopu, Jeanine Skorinko, Michael Smith, Vanessa Smith-Castro, Agata Sobkow, Walter Sowden, Philipp Spachtholz, Troy Steiner, Jeroen Stouten, Chris Street, Oskar Sundfelt, Ewa Szumowska, Andrew Tang, Norbert Tanzer, Morgan Tear, Jordan Theriault, Manuela Thomae, David Torres-Fernández, Jakub Traczyk, Joshua Tybur, Adrienn Ujhelyi, Marcel van Assen, Anna van 't Veer, Alejandro, Vásquez-Echeverría Leigh, Ann Vaughn, Alexandra Vázquez, Diego Vega, Catherine Verniers, Mark Verschoor, Ingrid Voermans, Marek Vranka, Cheryl Welch, Aaron Wichman, Lisa Williams, Julie Woodzicka, Marta Wronska, Liane Young, John Zelenski, Brian Nosek (2019-11-19):
We conducted preregistered replications of 28 classic and contemporary published findings with protocols that were peer reviewed in advance to examine variation in effect magnitudes across sample and setting. Each protocol was administered to approximately half of 125 samples and 15,305 total participants from 36 countries and territories. Using conventional statistical significance (p < 0.05), fifteen (54%) of the replications provided evidence in the same direction and statistically significant as the original finding. With a strict significance criterion (p < 0.0001), fourteen (50%) provide such evidence reflecting the extremely high powered design. Seven (25%) of the replications had effect sizes larger than the original finding and 21 (75%) had effect sizes smaller than the original finding. The median comparable Cohen’s d effect sizes for original findings was 0.60 and for replications was 0.15. Sixteen replications (57%) had small effect sizes (< 0.20) and 9 (32%) were in the opposite direction from the original finding. Across settings, 11 (39%) showed significant heterogeneity using the Q statistic and most of those were among the findings eliciting the largest overall effect sizes; only one effect that was near zero in the aggregate showed significant heterogeneity. Only one effect showed a Tau > 0.20 indicating moderate heterogeneity. Nine others had a Tau near or slightly above 0.10 indicating slight heterogeneity. In moderation tests, very little heterogeneity was attributable to task order, administration in lab versus online, and exploratory WEIRD versus less WEIRD culture comparisons. Cumulatively, variability in observed effect sizes was more attributable to the effect being studied than the sample or setting in which it was studied.
Scholarly peer review is the process of subjecting an author's scholarly work, research, or ideas to the scrutiny of others who are experts in the same field, before a paper describing this work is published in a journal, conference proceedings or as a book. The peer review helps the publisher decide whether the work should be accepted, considered acceptable with revisions, or rejected.
In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered to every unit in a randomized experiment. Intuitively, IVs are used when an explanatory variable of interest is correlated with the error term, in which case ordinary least squares and ANOVA give biased results. A valid instrument induces changes in the explanatory variable but has no independent effect on the dependent variable, allowing a researcher to uncover the causal effect of the explanatory variable on the dependent variable.
Difference in differences is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. It calculates the effect of a treatment on an outcome by comparing the average change over time in the outcome variable for the treatment group, compared to the average change over time for the control group. Although it is intended to mitigate the effects of extraneous factors and selection bias, depending on how the treatment group is chosen, this method may still be subject to certain biases.
In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design (RDD) is a quasi-experimental pretest-posttest design that elicits the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. By comparing observations lying closely on either side of the threshold, it is possible to estimate the average treatment effect in environments in which randomisation is unfeasible. First applied by Donald Thistlethwaite and Donald Campbell to the evaluation of scholarship programs, the RDD has become increasingly popular in recent years. Recent study comparisons of randomised controlled trials (RCTs) and RDDs have empirically demonstrated the internal validity of the design.
Revolutions are most likely to occur when a prolonged period of objective economic and social development is followed by a short period of sharp reversal. People then subjectively fear that ground gained with great effort will be quite lost; their mood becomes revolutionary. The evidence from Dorr's Rebellion, the Russian Revolution, and the Egyptian Revolution supports this notion; tentatively, so do data on other civil disturbances. Various statistics—as on rural uprisings, industrial strikes, unemployment, and cost of living—may serve as crude indexes of popular mood. More useful, though less easy to obtain, are direct questions in cross-sectional interviews. The goal of predicting revolution is conceived but not yet born or mature
Synanon was initially a drug rehabilitation program founded by Charles E. "Chuck" Dederich Sr., (1913–1997) in 1958 in Santa Monica, California. By the early 1960s, Synanon became an alternative community centered on group truth-telling sessions that came to be known as the "Synanon Game". Synanon ultimately became the Church of Synanon in the 1970s. Synanon disbanded in 1991 due to members being convicted of criminal activities and retroactive loss of its tax-free status with the Internal Revenue Service due to financial misdeeds, destruction of evidence, and terrorism. It has been called one of the "most dangerous and violent cults America had ever seen".
[Contemporary SF short story; inspired by NN text generation, social media dynamics, clickbait, and debates like ‘the dress’; imagines AI natural language processing systems run amok after being trained to maximize user reactions to create clickbait, leading to learning ‘scissor statements’, claims which are maximally controversial and divide the population 50-50 between those who find the statement obviously correct and moral, and those who find it equally obviously false and immoral, leading to intractable polarizing debates, contempt, and warfare.]
Lady Mary Wortley Montagu was an English aristocrat, writer, and poet. Born in 1689, Lady Mary spent her early life in England. In 1712, Lady Mary married Edward Wortley Montagu, who later served as the British ambassador to the Sublime Porte. Lady Mary joined her husband in the Ottoman excursion, where she was to spend the next two years of her life. During her time there, Lady Mary wrote extensively on her experience as a woman in Ottoman Istanbul. After her return to England, Lady Mary devoted her attention to the upbringing of her family before dying of cancer in 1762.
Parkinson’s disease (PD) is a progressive, neurodegenerative disease that presents with significant motor symptoms, for which there is no diagnostic test (1–3). We have serendipitously identified a hyperosmic individual, a ‘Super Smeller’ that can detect PD by odor alone, and our early pilot studies have indicated that the odor was present in the sebum from the skin of PD subjects(4). Here, we have employed an unbiased approach to investigate the volatile metabolites of sebum samples obtained non-invasively from the upper back of 64 participants in total (21 controls and 43 PD subjects). Our results, validated by an independent cohort, identified a distinct volatiles-associated signature of PD, including altered levels of perillic aldehyde and eicosane, the smell of which was then described as being highly similar to the scent of PD by our ‘Super Smeller’.
1 sentence summary
Metabolomics identifies volatile odorous compounds from patient sebum that associate with the smell of Parkinson’s.
Margit Wennmachers is a venture capitalist at the Silicon Valley venture capital firm Andreessen Horowitz and a co-founder of OutCast Communications, one of the tech world's top public relations firms according to The New York Times. She is one of a handful of women at high-profile venture capital firms and among the few venture capital marketing executives at the partner level.
Ravelry is a free social networking service and website that beta-launched in May 2007. It functions as an organizational tool for a variety of fiber arts, including knitting, crocheting, spinning, and weaving. Members share projects, ideas, and their collection of yarn, fiber, and tools via various components of the site.
Persistent forms of nondual awareness, enlightenment, mystical experience, and so forth (Persistent Non-Symbolic Experience) have been reported since antiquity. Though sporadic research has been performed on them, the research reported here represents the initial report from the first larger scale cognitive psychology study of this population.
Method: Assessment of the subjective experience of fifty adult participants reporting persistent non-symbolic experience was undertaken using 6–12 hour semi-structured interviews and evaluated using thematic analysis. Additional assessment was performed using psychometric measures, physiological measurement, and experimentation.
Results: Five core, consistent categories of change were uncovered: sense-of-self, cognition, emotion, perception, and memory. Participants’ reports formed clusters in which the types of change in each of these categories were consistent. Multiple clusters were uncovered that formed a range of possible experiences. The variety of these experiences and their underlying categories may inform the debate between constructivist, common core, and participatory theorists.
…Over the course of a week, his father died followed very rapidly by his sister. He was also going through a significant issue with one of his children. Over dinner I asked him about his internal state, which he reported as deeply peaceful and positive despite everything that was happening. Having known that the participant was bringing his longtime girlfriend, I’d taken an associate researcher with me to the meeting to independently collect the observations from her. My fellow researcher isolated the participant’s girlfriend at the bar and interviewed her about any signs of stress that the participant might be exhibiting. I casually asked the same questions to the participant as we continued our dinner conversation. Their answers couldn’t have been more different. While the participant reported no stress, his partner had been observing many telltale signs: he wasn’t sleeping well, his appetite was off, his mood was noticeably different, his muscles were much tenser than normal, his sex drive was reduced, his health was suffering, and so forth…It was not uncommon for participants to state that they had gained increased bodily awareness upon their transition into PNSE. I arranged and observed private yoga sessions with a series of participants as part of a larger inquiry into their bodily awareness. During these sessions it became clear that participants believed they were far more aware of their body than they actually were…Many participants discussed the thought, just after their transition to PNSE, that they would have to go to work and explain the difference in themselves to co-workers. They went on to describe a puzzled drive home after a full day of work when no one seemed to notice anything different about them. Quite a few chose to never discuss the change that had occurred in them with their families and friends and stated that no one seemed to notice much of a difference.
There was also a progressively decreasing sense of agency. In the final stage, Location 4, he reports: “These participants reported having no sense of agency or any ability to make a decision. It felt as if life was simply unfolding and they were watching the process happen. Severe memory deficits were common in these participants, including the inability to recall scheduled events that were not regular and ongoing.” And yet, almost all of the subjects reported it as a positive experience. The subjects, at whatever point they were in the scale, were often completely certain about the nature of the experience: “PNSE was often accompanied by a tremendous sense of certainty that participants were experiencing a ‘deeper’ or ‘more true’ reality. As time passed, this often increased in strength.” They also tended to be dogmatic about their PNSE being the real thing (whichever location they were at) and descriptions of other people’s different PNSEs as not the real thing. Another way to say “completely certain” is “unable to doubt”.
The Clock is an art installation by video artist Christian Marclay. It is a looped 24-hour video supercut that feature clocks or timepieces. The artwork itself functions as a clock: its presentation is synchronized with the local time, resulting in the time shown in a scene being the actual time.
A supercut is a genre of video editing consisting of a montage of short clips with the same theme. The theme may be an action, a scene, a word or phrase, an object, a gesture, or a cliché or trope. The technique has its roots in film and television and is related to vidding. The montage obsessively isolates a single element from its source or sources. It is sometimes used to create a satirical or comic effect or to collapse a long and complex narrative into a brief summary.
Gunbuster, known in Japan as Aim for the Top!, is a Japanese OVA anime series produced by Gainax released from 1988 to 1989. It was the directorial debut of Hideaki Anno, best known as the creator and director of Neon Genesis Evangelion. The title is a combination of the titles of classic tennis anime Aim for the Ace! and hit action drama film Top Gun, whose plot inspired Gunbuster's. To celebrate Gainax's 20th anniversary in 2004, an official sequel to Gunbuster, Diebuster, was released as an OVA. The sequel features new characters and mecha, but retains the format and many of the concepts of the original series.
Kedi is a 2016 Turkish documentary film directed by Ceyda Torun about the many stray cats that live in Istanbul. It premiered at the !f Istanbul Independent Film Festival on 21 February 2016 before being given a North American theatrical release on 10 February 2017. It debuted on the YouTube Red streaming service on 10 May 2017. It was released on DVD in the U.S. on 14 November 2017. The film received critical acclaim, and grossed over $5 million. Time magazine listed it as one of its top ten films of 2017.
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The dress is a photograph that became a viral internet sensation on 26 February 2015, when viewers disagreed over whether the dress pictured was coloured black and royal blue, or white and gold. The phenomenon revealed differences in human colour perception, which have been the subject of ongoing scientific investigations into neuroscience and vision science, with a number of papers published in peer-reviewed science journals.