Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images

Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs provide a viable model of human vision when tested with challenging noisy images of objects, sometimes presented at the very limits of visibility. We show that popular state-of-the-art DNNs perform in a qualitatively different manner than humans—they are unusually susceptible to spatially uncorrelated white noise and less impaired by spatially correlated noise. We implemented a noise training procedure to determine whether noise-trained DNNs exhibit more robust responses that better match human behavioral and neural performance. We found that noise-trained DNNs provide a better qualitative match to human performance; moreover, they reliably predict human recognition thresholds on an image-by-image basis. Functional neuroimaging revealed that noise-trained DNNs provide a better correspondence to the pattern-specific neural representations found in both early visual areas and high-level object areas. A layer-specific analysis of the DNNs indicated that noise training led to broad-ranging modifications throughout the network, with greater benefits of noise robustness accruing in progressively higher layers. Our findings demonstrate that noise-trained DNNs provide a viable model to account for human behavioral and neural responses to objects in challenging noisy viewing conditions. Further, they suggest that robustness to noise may be acquired through a process of visual learning.

Characteristics and outcomes of an international cohort of 400,000 hospitalised patients with Covid-19

Background: Policymakers need robust data to respond to the COVID-19 pandemic. We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, the world's largest international, standardised cohort of hospitalised patients. Methods: The dataset analysed includes COVID-19 patients hospitalised between January 2020 and May 2021. We investigated how symptoms on admission, comorbidities, risk factors, and treatments varied by age, sex, and other characteristics. We used Cox proportional hazards models to investigate associations between demographics, symptoms, comorbidities, and other factors with risk of death, admission to intensive care unit (ICU), and invasive mechanical ventilation (IMV). Findings: 439,922 patients with laboratory-confirmed (91.7%) or clinically-diagnosed (8.3%) SARS-CoV-2 infection from 49 countries were enrolled. Age (adjusted hazard ratio [HR] per 10 years 1.49 [95% CI 1.49-1.50]) and male sex (1.26 [1.24-1.28]) were associated with a higher risk of death. Rates of admission to ICU and use of IMV increased with age up to age 60, then dropped. Symptoms, comorbidities, and treatments varied by age and had varied associations with clinical outcomes. Tuberculosis was associated with an 86% higher risk of death, and HIV with an 87% higher risk of death. Case fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients. Interpretation: The size of our international database and the standardized data collection method makes this study a reliable and comprehensive international description of COVID-19 clinical features. This is a viable model to be applied to future epidemics.

Distributing State Responsibility

Chapter 5 contrasts the intentional participation framework with other accounts, builds on the normative and empirical findings of the previous chapters, and develops a viable model for the distribution of remedial responsibility within the state. It examines five alternative principles that could justify a nonproportional distribution: “national responsibility,” democratic authorization, benefiting from state wrongdoing, having a special capacity to address it, and having special associative obligations to the victims of the wrongdoing. While each of these principles has important limitations, under some circumstances they can play a role in explaining citizens’ obligations with respect to their state’s wrongdoings. The chapter then outlines a context-sensitive process for determining how a state’s responsibility should be distributed between its citizens in specific cases. Typically, this process will conclude that in democratic states, a nonproportional distribution is overall justified, while in many authoritarian states it is not.

The Chx10-Traf3 Knockout Mouse as a Viable Model to Study Neuronal Immune Regulation

Uncontrolled inflammation is associated with neurodegenerative conditions in central nervous system tissues, including the retina and brain. We previously found that the neural retina (NR) plays an important role in retinal immunity. Tumor necrosis factor Receptor-Associated Factor 3 (TRAF3) is a known immune regulator expressed in the retina; however, whether TRAF3 regulates retinal immunity is unknown. We have generated the first conditional NR-Traf3 knockout mouse model (Chx10-Cre/Traf3f/f) to enable studies of neuronal TRAF3 function. Here, we evaluated NR-Traf3 depletion effects on whole retinal TRAF3 protein expression, visual acuity, and retinal structure and function. Additionally, to determine if NR-Traf3 plays a role in retinal immune regulation, we used flow cytometry to assess immune cell infiltration following acute local lipopolysaccharide (LPS) administration. Our results show that TRAF3 protein is highly expressed in the NR and establish that NR-Traf3 depletion does not affect basal retinal structure or function. Importantly, NR-Traf3 promoted LPS-stimulated retinal immune infiltration. Thus, our findings propose NR-Traf3 as a positive regulator of retinal immunity. Further, the NR-Traf3 mouse provides a tool for investigations of neuronal TRAF3 as a novel potential target for therapeutic interventions aimed at suppressing retinal inflammatory disease and may also inform treatment approaches for inflammatory neurodegenerative brain conditions.

Implementation of Inclusive Education in Pakistan: A Case of School Culture

There is growing awareness and desire to implement inclusive education in Pakistan. This quantitative study tried to assess the level of implementation of inclusive practices in public and private sector schools through the voices of headteachers and teachers. The status of implementation is explored by using a five-point Likert type scale developed on the framework of Index of Inclusion (Booth and Ainscow, 2002) and Framework of Indicators developed by Kyriazopoulou and Weber (2009). The sample of the study comprised 51 inclusive schools representing four inclusive models. Headteachers and teachers engaged in implementation were asked to unfold their experiences and voices as the evidence for successful inclusivity in schools reflected through school culture. In its quantitative part, the study found that majority of the respondents had a positive opinion regarding the implementation of inclusive enabling indicators pertaining to school culture. Overall the study found that all these 51 inclusive schools are moving forward to achieve inclusivity in schools. This study recommended that a standard definition of inclusive education and a viable model for the implementation of inclusivity in schools.

A natural composite Higgs via universal boundary conditions

We present a novel realization of a composite Higgs, which can naturally produce top partners above the current LHC bounds without increasing the tuning above 10%. The essential ingredients are softened breaking of the Higgs shift symmetry as well as maximal symmetry, which turn out to perfectly complement each other. The 5D realization of this model is particularly simple: universal UV and IR boundary conditions for the bulk fermions containing the SM fields will cure the problems of existing holographic composite Higgs models and provide a complete viable model for a naturally light Higgs without much tuning.

The Promise of the Zebrafish Model for Parkinson’s Disease: Today’s Science and Tomorrow’s Treatment

The second most prevalent neurodegenerative disorder in the elderly is Parkinson’s disease (PD). Its etiology is unclear and there are no available disease-modifying medicines. Therefore, more evidence is required concerning its pathogenesis. The use of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is the basis of most animal models of PD. MPTP is metabolized by monoamine oxidase B (MAO B) to MPP + and induces the loss of dopaminergic neurons in the substantia nigra in mammals. Zebrafish have been commonly used in developmental biology as a model organism, but owing to its perfect mix of properties, it is now emerging as a model for human diseases. Zebrafish (Danio rerio) are cheap and easy to sustain, evolve rapidly, breed transparent embryos in large amounts, and are readily manipulated by different methods, particularly genetic ones. Furthermore, zebrafish are vertebrate species and mammalian findings obtained from zebrafish may be more applicable than those derived from genetic models of invertebrates such as Drosophila melanogaster and Caenorhabditis elegans. The resemblance cannot be taken for granted, however. The goal of the present review article is to highlight the promise of zebrafish as a PD animal model. As its aminergic structures, MPTP mode of action, and PINK1 roles mimic those of mammalians, zebrafish seems to be a viable model for studying PD. The roles of zebrafish MAO, however, vary from those of the two types of MAO present in mammals. The benefits unique to zebrafish, such as the ability to perform large-scale genetic or drug screens, should be exploited in future experiments utilizing zebrafish PD models.

Cosmological inflation driven by a scalar torsion function

A viable model for inflation driven by a torsion function in a Friedmann background is presented. The scalar spectral index in the interval $$0.92\lesssim n_{s}\lesssim 0.97$$ 0.92 ≲ n s ≲ 0.97 is obtained in order to satisfy the initial conditions for inflation. The post inflationary phase is also studied, and the analytical solutions obtained for scale factor and energy density generalizes that ones for a matter dominated universe, indicating just a small deviation from the standard model evolution. The same kind of torsion function used also describes satisfactorily the recent acceleration of the universe, which could indicate a possible unification of different phases, apart form specific constants