Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychophysics of Artificial Neural Networks Questions Classical Hue Cancellation Experiments

We show that classical hue cancellation experiments lead to human-like opponent curves even if the task is done by trivial (identity) artificial networks. Specifically, human-like opponent spectral sensitivities always emerge in artificial networks as long as (i) the retina converts the input radiation into any tristimulus-like representation, and (ii) the post-retinal network solves the standard hue cancellation task, e.g. the network looks for the weights of the cancelling lights so that every monochromatic stimulus plus the weighted cancelling lights match a grey reference in the (arbitrary) color representation used by the network. In fact, the specific cancellation lights (and not the network architecture) are key to obtain human-like curves: results show that the classical choice of the lights is the one that leads to the best (more human-like) result, and any other choices lead to progressively different spectral sensitivities. We show this in two ways: through artificial psychophysics using a range of networks with different architectures and a range of cancellation lights, and through a change-of-basis theoretical analogy of the experiments. This suggests that the opponent curves of the classical experiment are just a by-product of the front-end photoreceptors and of a very specific experimental choice but they do not inform about the downstream color representation. In fact, the architecture of the post-retinal network (signal recombination or internal color space) seems irrelevant for the emergence of the curves in the classical experiment. This result in artificial networks questions the conventional interpretation of the classical result in humans by Jameson and Hurvich.
The relaxation of a turbulent boundary layer in an adverse pressure gradient

The relaxation of a reattached turbulent boundary layer downstream of a wall fence has been investigated. The boundary layer has an adverse pressure gradient imposed upon it which is adjusted in an attempt to bring the boundary layer into equilibrium. This is done by adjusting the pressure gradient so as to bring the Clauser parameter (G) down to a value of about 11.4 and then maintain it constant. In the region from the reattachment point to 2 or 3 reattachment lengths downstream, the boundary layer recovers from the initial major effects of reattachment. Farther downstream (where G is constant) the pressure-gradient parameter changes very slowly and profiles of non-dimensionalized eddy viscosity appear self-similar. However, pressure gradient and eddy viscosity are both roughly twice as large as expected on the basis of previous studies of equilibrium turbulent boundary layers. It is not known whether equilibrium has been achieved in this downstream region. This is another illustration of the great sensitivity of boundary-layer structure to perturbations.
Scaling of the wall-normal turbulence component in high-Reynolds-number pipe flow

Streamwise and wall-normal turbulence components are obtained in fully developed turbulent pipe over a Reynolds number range from 1.1 × 105 to 9.8 × 106. The streamwise intensity data are consistent with previous measurements in the same facility. For the wall-normal turbulence intensity, a constant region in v'r.m.s. is found for the region 200 ≤ y+ ≤ 0.1R+ for Reynolds numbers up to 1.0 × 106. An increase in v'r.m.s. is observed below about y+ ∼ 100, although additional measurements will be required to establish its generality. The wall-normal spectra collapse in the energy-containing region with inner scaling, but for the low-wavenumber region a y/R dependence is observed, which also indicates a continuing influence from the outer flow on the near-wall motions.
Cow's milk and hen's egg anaphylaxis: A comprehensive data analysis from the European Anaphylaxis Registry

Abstract Background Cow's milk (CM) and hen's egg (HE) are leading triggers of anaphylaxis in early childhood. The aim of this study was to identify clinical phenotypes and therapeutic measures for CM anaphylaxis (CMA) compared to HE anaphylaxis (HEA) in children up to 12 years of age, based on a large pan‐European dataset from the European Anaphylaxis Registry. Methods Data from 2007 to 2020 on clinical phenotypes and treatment from 10 European countries, as well as Brazil, were analysed. The two‐step cluster analysis was used to identify the most frequent phenotypes. For each trigger, three clusters were extracted based on sex, age, and existence of symptoms in four vitally important systems. Results Altogether 284 children with CMA and 200 children with HEA were identified. They were characterised as male (69% vs. 64%), infants (65% vs. 61%), with a most frequent grade III of Ring&Messmer classification (62% vs. 64%), in CMA versus HEA, respectively. Respiratory symptoms occurred more often in CMA (91% vs. 83%, p = 0.010), especially in infants (89% vs. 79%, p = 0.008). Cardiovascular symptoms were less frequent in CMA (30% vs. 44%, p = 0.002), in both infants (33% vs. 46%, p = 0.027), and older children (25% vs. 42%, p = 0.021). The clusters extracted in the CMA group were characterised as: (1) mild dermal infants with severe GI (40%), 2. severe dermal (35%), 3. respiratory (25%). While in HEA group: 1. infants with severe GI and/or reduction of alertness (40%), (2) conjunctival (16%), (3) mild GI without conjunctivitis (44%). The severity of the reaction was independent from the amount of ingested allergen protein, regardless of trigger. The first‐line adrenaline application differed between the countries (0%–92%, as well as the reasons for not administering adrenaline, p < 0.001). Conclusions Despite the similarity of their age, sex, and severity grade, the clinical profiles differed between the CMA and HEA children. Adrenaline was underused, and its administration was country dependent. Further studies are needed to assess to what extent the differences in the clinical profiles are related to matrix and/or absorption effects, and/or the allergen itself.
Fake it Till You Make it: Learning Transferable Representations from Synthetic ImageNet Clones

Recent image generation models such as Stable Diffusion have exhibited an impressive ability to generate fairly realistic images starting from a simple text prompt. Could such models render real images obsolete for training image prediction models? In this paper, we answer part of this provocative question by investigating the need for real images when training models for ImageNet classification. Provided only with the class names that have been used to build the dataset, we explore the ability of Stable Diffusion to generate synthetic clones of ImageNet and measure how useful these are for training classification models from scratch. We show that with minimal and class-agnostic prompt engineering, ImageNet clones are able to close a large part of the gap between models produced by synthetic images and models trained with real images, for the several standard classification benchmarks that we consider in this study. More importantly, we show that models trained on synthetic images exhibit strong generalization properties and perform on par with models trained on real data for transfer. Project page: https://europe.naverlabs. com/imagenet-sd
Enhancement Encoding: A Novel Imbalanced Classification Approach via Encoding the Training Labels

Class imbalance, which is also called long-tailed distribution, is a common problem in classification tasks based on machine learning. If it happens, the minority data will be overwhelmed by the majority, which presents quite a challenge for data science. To address the class imbalance problem, researchers have proposed lots of methods: some people make the data set balanced (SMOTE), some others refine the loss function (Focal Loss), and even someone has noticed the value of labels influences class-imbalanced learning (Yang and Xu. Rethinking the value of labels for improving class-imbalanced learning. In NeurIPS 2020), but no one changes the way to encode the labels of data yet. Nowadays, the most prevailing technique to encode labels is the one-hot encoding due to its nice performance in the general situation. However, it is not a good choice for imbalanced data, because the classifier will treat majority and minority samples equally. In this paper, we innovatively propose the enhancement encoding technique, which is specially designed for the imbalanced classification. The enhancement encoding combines re-weighting and cost-sensitiveness, which can reflect the difference between hard and easy (or minority and majority) classes. To reduce the number of validation samples and the computation cost, we also replace the confusion matrix with a novel soft-confusion matrix which works better with a small validation set. In the experiments, we evaluate the enhancement encoding with three different types of loss. And the results show that enhancement encoding is very effective to improve the performance of the network trained with imbalanced data. Particularly, the performance on minority classes is much better.
Prior choice and data requirements of Bayesian multivariate hierarchical models fit to tag‐recovery data: The need for power analyses

Abstract Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag‐recovery data. In these applications, increasingly negative correlation between survival and recovery has been interpreted as evidence for increasingly additive harvest mortality. The power of these hierarchal models to detect nonzero correlations has rarely been evaluated, and these few studies have not focused on tag‐recovery data, which is a common data type. We assessed the power of multivariate hierarchical models to detect negative correlation between annual survival and recovery. Using three priors for multivariate normal distributions, we fit hierarchical effects models to a mallard (Anas platyrhychos) tag‐recovery data set and to simulated data with sample sizes corresponding to different levels of monitoring intensity. We also demonstrate more robust summary statistics for tag‐recovery data sets than total individuals tagged. Different priors led to substantially different estimates of correlation from the mallard data. Our power analysis of simulated data indicated most prior distribution and sample size combinations could not estimate strongly negative correlation with useful precision or accuracy. Many correlation estimates spanned the available parameter space (−1,1) and underestimated the magnitude of negative correlation. Only one prior combined with our most intensive monitoring scenario provided reliable results. Underestimating the magnitude of correlation coincided with overestimating the variability of annual survival, but not annual recovery. The inadequacy of prior distributions and sample size combinations previously assumed adequate for obtaining robust inference from tag‐recovery data represents a concern in the application of Bayesian hierarchical models to tag‐recovery data. Our analysis approach provides a means for examining prior influence and sample size on hierarchical models fit to capture–recapture data while emphasizing transferability of results between empirical and simulation studies.
3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views

Developing gaze estimation models that generalize well to unseen domains and in-the-wild conditions remains a challenge with no known best solution. This is mostly due to the difficulty of acquiring ground truth data that cover the distribution of faces, head poses, and environments that exist in the real world. Most recent methods attempt to close the gap between specific source and target domains using domain adaptation. In this work, we propose to train general gaze estimation models which can be directly employed in novel environments without adaptation. To do so, we leverage the observation that head, body, and hand pose estimation benefit from revising them as dense 3D coordinate prediction, and similarly express gaze estimation as regression of dense 3D eye meshes. To close the gap between image domains, we create a large-scale dataset of diverse faces with gaze pseudo-annotations, which we extract based on the 3D geometry of the scene, and design a multi-view supervision framework to balance their effect during training. We test our method in the task of gaze generalization, in which we demonstrate improvement of up to 30% compared to state-of-the-art when no ground truth data are available, and up to 10% when they are. The project material are available for research purposes at https://github.com/Vagver/3DGazeNet.
Uniqueness theorems for meromorphic inner functions and canonical systems

We prove uniqueness problems for meromorphic inner functions on the upper half-plane. In these problems we consider spectral data depending partially or fully on the spectrum, derivative values at the spectrum, Clark measure or the spectrum of the negative of a meromorphic inner function. Moreover we consider applications of these uniqueness results to inverse spectral theory of canonical Hamiltonian systems and obtain generalizations of Borg-Levinson two-spectra theorem for canonical Hamiltonian systems and unique determination of a Hamiltonian from its spectral measure under some conditions.
Eine obere Schranke der Anzahl der durch vier teilbaren Invarianten der absoluten Klassengruppe im quadratischen Zahlenkörper.

Ich werde hier aus meinem Satze l ) über die Anzahl e^ der durch vier teilbaren Invarianten der absoluten Klassengruppe eines beliebigen quadratischen Zahlkörpers k eine obere Schranke für e± bestimmen. Ich nenne eine Fundamentaldiskriminante eine solche ganze rationale Zahl, die auch die Diskriminante eines quadratischen Zahlkörpers ist, und die nur einen einzigen rationalen Primteiler hat; diese sind also — 4, 8, — 8 und die (positiven oder negativen) Primzahlen der Gestalt im + 1. Offenbar läßt sich die Diskriminante D von k in der Form D = d±d2 · · · dt darstellen, wobei die Faktoren dt paarweise relativ prime Fündamentaldiskriminanten sind, die, von der Reihenfolge abgesehen, eindeutig durch k bestimmt sind. Davon sei bzw. 2r2 — v die Anzahl der positiven bzw. negativen, wobei / , r2 nicht negative ganze Zahlen sind, und v = 0 oder 1. Es ist t die Anzahl der verschiedenen rationalen Primfaktoren von D und es besteht (1) i = r1 + 2r2— . Ich setze (2) r = ri + rz — l. Satz. Es ist (3) *4^r1 + r2-l(=r). Damit ist für e± eine echte obere Schranke gegeben, in dem Sinne, daß es für jedes System ? 2) (i + 2r2 — v ̂ 1) unendlich viele solche k gibt, für welche in (3) ,, = " besteht ).
Chronic cannabis use and error awareness: The effect on learning from errors

Background Cannabis is the third most commonly used drug worldwide, with studies suggesting a deleterious effect on some aspects of performance monitoring. It is unknown, however, whether diminished error awareness influences adaptive behaviour in cannabis users. Therefore, this study examined the effect of error awareness on learning from errors in cannabis users. Methods Thirty-six chronic cannabis users (Mage = 23.81 years; female, 36%) and 34 controls (Mage = 21.53 years; female, 76%) completed a Go/No-Go task that allowed participants to learn from errors and adapt their behaviour. Multilevel models were specified to determine whether the effect of error awareness on learning from errors differs between cannabis users and controls, and whether cannabis-use measures predict error correction while accounting for error awareness. Results While error awareness and correction rates did not differ between the groups, there was a significant effect of age of use onset on error correction in cannabis users. Further, the effect of error awareness was dependent on age of onset, and cannabis use-related frequency and harm. That is, cannabis users reporting an earlier age of regular use or scoring higher on the cannabis use index were less likely to perform correctly following an aware error. Conclusion It appears overall cannabis use might not be tightly coupled to behavioural indices of performance monitoring. There is evidence, however, that aspects of cannabis use predict impairments in learning from errors that may be associated with treatment outcomes.
The Natural Stilbenoid (–)-Hopeaphenol Inhibits HIV Transcription by Targeting Both PKC and NF-κB Signaling and Cyclin-Dependent Kinase 9

Despite effective combination antiretroviral therapy (cART), people living with HIV (PLWH) continue to harbor replication-competent and transcriptionally active virus in infected cells, which in turn can lead to ongoing viral antigen production, chronic inflammation, and increased risk of age-related comorbidities. To identify new agents that may inhibit postintegration HIV beyond cART, we screened a library of 512 pure compounds derived from natural products and identified (–)-hopeaphenol as an inhibitor of HIV postintegration transcription at low to submicromolar concentrations without cytotoxicity. Using a combination of global RNA sequencing, plasmid-based reporter assays, and enzyme activity studies, we document that hopeaphenol inhibits protein kinase C (PKC)- and downstream NF-κB-dependent HIV transcription as well as a subset of PKC-dependent T-cell activation markers, including interleukin-2 (IL-2) cytokine and CD25 and HLA-DRB1 RNA production. ABSTRACT Despite effective combination antiretroviral therapy (cART), people living with HIV (PLWH) continue to harbor replication-competent and transcriptionally active virus in infected cells, which in turn can lead to ongoing viral antigen production, chronic inflammation, and increased risk of age-related comorbidities. To identify new agents that may inhibit postintegration HIV beyond cART, we screened a library of 512 pure compounds derived from natural products and identified (–)-hopeaphenol as an inhibitor of HIV postintegration transcription at low to submicromolar concentrations without cytotoxicity. Using a combination of global RNA sequencing, plasmid-based reporter assays, and enzyme activity studies, we document that hopeaphenol inhibits protein kinase C (PKC)- and downstream NF-κB-dependent HIV transcription as well as a subset of PKC-dependent T-cell activation markers, including interleukin-2 (IL-2) cytokine and CD25 and HLA-DRB1 RNA production. In contrast, it does not substantially inhibit the early PKC-mediated T-cell activation marker CD69 production of IL-6 or NF-κB signaling induced by tumor necrosis factor alpha (TNF-α). We further show that hopeaphenol can inhibit cyclin-dependent kinase 9 (CDK9) enzymatic activity required for HIV transcription. Finally, it inhibits HIV replication in peripheral blood mononuclear cells (PBMCs) infected in vitro and dampens viral reactivation in CD4+ cells from PLWH. Our study identifies hopeaphenol as a novel inhibitor that targets a subset of PKC-mediated T-cell activation pathways in addition to CDK9 to block HIV expression. Hopeaphenol-based therapies could complement current antiretroviral therapy otherwise not targeting cell-associated HIV RNA and residual antigen production in PLWH.
Therapist factors associated with intent to use exposure therapy: a systematic review and meta-analysis

ABSTRACT Exposure therapy is effective but widely underused. Numerous studies indicate therapist factors that might explain this pattern of underuse. This systematic review and meta-analysis synthesised those previous research findings, to identify which therapist factors are clearly associated with their intent to use exposure therapy. A systematic review and six random-effects meta-analyses synthesised studies identified in three databases (Scopus, PsychINFO, Web of Science) and through reference lists and citation searches. Most studies relied on a survey design, resulting in weak quality of research. Twenty-six eligible studies were included in the narrative synthesis, (including 5557 participants), while 21 studies yielded sufficient data to enter the meta-analysis. Medium to large pooled effect sizes indicated that therapists with more positive beliefs, a CBT orientation, and training in exposure therapy were significantly more likely to use exposure. Small pooled effect sizes indicated that older and more anxious therapists were less likely to use exposure. Therapist years of experience was not significantly associated with exposure use. There was no evidence of publication bias. Therapist characteristics clearly play a role in the use of exposure therapy, and future clinical and research work is required to address this limitation in the delivery of this effective therapy.
Integrating the pattern of negative emotion processing and acute stress response with childhood stress among healthy young adults

Abstract Childhood adversity might impair corticolimbic brain regions, which play a crucial role in emotion processing and the acute stress response. The dimensional model of childhood adversity proposed that deprivation and threat dimensions might associated with individuals’ development through different mechanisms. However, few studies have explored the relationship between different dimensions of childhood stress, emotion processing, and acute stress reactivity despite the overlapping brain regions of the last two. With the aid of the event-related potentials technique, we explore whether negative emotion processing, which might be particularly relevant for adaptive stress responding among individuals with adverse childhood experience, mediates the relationship between dimensional childhood stress and acute stress response. Fifty-one young adults completed a free-viewing task to evaluate neural response to negative stimuli measured by late positive potential (LPP) of ERPs (Event-related potentials). On a separate day, heart rate and salivary cortisol were collected during a social-evaluative stress challenge (i.e. TSST, Trier Social Stress Test). After the TSST, the childhood trauma questionnaire was measured to indicate the level of abuse (as a proxy of threat) and neglect (as a proxy of deprivation) dimensions. Multiple linear regression and mediation analysis were used to explore the relationship among childhood stress, emotion processing, and acute stress response. Higher level of childhood abuse (but not neglect) was distinctly related to smaller LPP amplitudes to negative stimuli, as well as smaller heart rate reactivity to acute stress. For these participants, smaller LPP amplitudes were linked with smaller heart rate reactivity to acute stress. Furthermore, decreased LPP amplitudes to negative stimuli mediated the relationship between higher level of childhood abuse and blunted heart rate reactivity to stress. Consistent with the dimensional model of childhood stress, our study showed that childhood abuse is distinctly associated with neural as well as physiological response to threat. Furthermore, the blunted neural response to negative stimuli might be the underlying mechanism in which childhood abuse leads to the blunted acute stress response. Considering that all the participants are healthy in the present study, the blunted processing of negative stimuli might rather reflect adaptation instead of vulnerability, in order to prevent stress overshooting in the face of early-life threatening experiences.
Stacks and the homotopy theory of simplicial sheaves

Stacks are described as sheaves of groupoids G satisfying an eective descent condition, or equivalently such that the clas- sifying object BG satisÞes descent. The set of simplicial sheaf homotopy classes (E;BG) is identiÞed with equivalence classes of acyclic homotopy colimits Þbred over BG, generalizing the classical relation between torsors and non-abelian cohomology. Group actions give rise to quotient stacks, which appear as pa- rameter spaces for the separable transfer construction in special cases.