In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?

It is often said that a deep learning model is "invariant" to some specific type of transformation. However, what is meant by this statement strongly depends on the context in which it is made. In this paper we explore the nature of invariance and equivariance of deep learning models with the goal of better understanding the ways in which they actually capture these concepts on a formal level. We introduce a family of invariance and equivariance metrics that allows us to quantify these properties in a way that disentangles them from other metrics such as loss or accuracy. We use our metrics to better understand the two most popular methods used to build invariance into networks: data augmentation and equivariant layers. We draw a range of conclusions about invariance and equivariance in deep learning models, ranging from whether initializing a model with pretrained weights has an effect on a trained model's invariance, to the extent to which invariance learned via training can generalize to out-of-distribution data.Comment: To appear at NeurIPS 202

Assessing the optimized precision of the aircraft mass balance method for measurement of urban greenhouse gas emission rates through averaging

To effectively address climate change, aggressive mitigation policies need to be implemented to reduce greenhouse gas emissions. Anthropogenic carbon emissions are mostly generated from urban environments, where human activities are spatially concentrated. Improvements in uncertainty determinations and precision of measurement techniques are critical to permit accurate and precise tracking of emissions changes relative to the reduction targets. As part of the INFLUX project, we quantified carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4) emission rates for the city of Indianapolis by averaging results from nine aircraft-based mass balance experiments performed in November-December 2014. Our goal was to assess the achievable precision of the aircraft-based mass balance method through averaging, assuming constant CO2, CH4 and CO emissions during a three-week field campaign in late fall. The averaging method leads to an emission rate of 14,600 mol/s for CO2, assumed to be largely fossil-derived for this period of the year, and 108 mol/s for CO. The relative standard error of the mean is 17% and 16%, for CO2 and CO, respectively, at the 95% confidence level (CL), i.e. a more than 2-fold improvement from the previous estimate of ~40% for single-flight measurements for Indianapolis. For CH4, the averaged emission rate is 67 mol/s, while the standard error of the mean at 95% CL is large, i.e. ±60%. Given the results for CO2 and CO for the same flight data, we conclude that this much larger scatter in the observed CH4 emission rate is most likely due to variability of CH4 emissions, suggesting that the assumption of constant daily emissions is not correct for CH4 sources. This work shows that repeated measurements using aircraft-based mass balance methods can yield sufficient precision of the mean to inform emissions reduction efforts by detecting changes over time in urban emissions

A non-synonymous coding change in the CYP19A1 gene Arg264Cys (rs700519) does not affect circulating estradiol, bone structure or fracture

Background The biosynthesis of estrogens from androgens is catalyzed by aromatase P450 enzyme, coded by the CYP19A1 gene on chromosome 15q21.2. Genetic variation within the CYP19A1 gene sequence has been shown to alter the function of the enzyme. The aim of this study is to investigate whether a non-synonymous Arg264Cys (rs700519) single nucleotide polymorphism (SNP) is associated with altered levels of circulating estradiol, areal bone mineral density or fracture. Methods This population- based study of 1,022 elderly Caucasian women (mean age 74.95 ± 2.60 years) was genotyped for the rs700519 SNP were analyzed to detect any association with endocrine and bone phenotypes. Results The genotype frequencies were 997 wildtype (97.6%), 24 heterozygous (2.3%) and 1 homozygous (0.1%). When individuals were grouped by genotype, there was no association between the polymorphism and serum estradiol (wildtype 27.5 ± 16.0; variants 31.2 ± 18.4, P = 0.27). There was also no association seen on hip bone mineral density (wildtype 0.81 ± 0.12; 0.84 ± 0.14 for variants, P = 0.48) or femoral neck bone mineral density (0.69 ± 0.10 for wildtype; 0.70 ± 0.12 for variants, P = 0.54) before or after correction of the data with age, height, weight and calcium therapy. There were also no associations with quantitative ultrasound measures of bone structure (broadband ultrasound attenuation, speed of sound and average stiffness). Conclusions In a cohort of 1,022 elderly Western Australian women, the presence of Arg264Cys (rs700519) polymorphism was not found to be associated with serum estradiol, bone structure or phenotypes

Having a lot of a good thing: multiple important group memberships as a source of self-esteem.

Copyright: © 2015 Jetten et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedMembership in important social groups can promote a positive identity. We propose and test an identity resource model in which personal self-esteem is boosted by membership in additional important social groups. Belonging to multiple important group memberships predicts personal self-esteem in children (Study 1a), older adults (Study 1b), and former residents of a homeless shelter (Study 1c). Study 2 shows that the effects of multiple important group memberships on personal self-esteem are not reducible to number of interpersonal ties. Studies 3a and 3b provide longitudinal evidence that multiple important group memberships predict personal self-esteem over time. Studies 4 and 5 show that collective self-esteem mediates this effect, suggesting that membership in multiple important groups boosts personal self-esteem because people take pride in, and derive meaning from, important group memberships. Discussion focuses on when and why important group memberships act as a social resource that fuels personal self-esteem.This study was supported by 1. Australian Research Council Future Fellowship (FT110100238) awarded to Jolanda Jetten (see http://www.arc.gov.au) 2. Australian Research Council Linkage Grant (LP110200437) to Jolanda Jetten and Genevieve Dingle (see http://www.arc.gov.au) 3. support from the Canadian Institute for Advanced Research Social Interactions, Identity and Well-Being Program to Nyla Branscombe, S. Alexander Haslam, and Catherine Haslam (see http://www.cifar.ca)

Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe- LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research

Biallelic Variants in PYROXD2 Cause a Severe Infantile Metabolic Disorder Affecting Mitochondrial Function

Pyridine Nucleotide-Disulfide Oxidoreductase Domain 2 (PYROXD2; previously called YueF) is a mitochondrial inner membrane/matrix-residing protein and is reported to regulate mitochondrial function. The clinical importance of PYROXD2 has been unclear, and little is known of the protein’s precise biological function. In the present paper, we report biallelic variants in PYROXD2 identified by genome sequencing in a patient with suspected mitochondrial disease. The child presented with acute neurological deterioration, unresponsive episodes, and extreme metabolic acidosis, and received rapid genomic testing. He died shortly after. Magnetic resonance imaging (MRI) brain imaging showed changes resembling Leigh syndrome, one of the more common childhood mitochondrial neurological diseases. Functional studies in patient fibroblasts showed a heightened sensitivity to mitochondrial metabolic stress and increased mitochondrial superoxide levels. Quantitative proteomic analysis demonstrated decreased levels of subunits of the mitochondrial respiratory chain complex I, and both the small and large subunits of the mitochondrial ribosome, suggesting a mitoribosomal defect. Our findings support the critical role of PYROXD2 in human cells, and suggest that the biallelic PYROXD2 variants are associated with mitochondrial dysfunction, and can plausibly explain the child’s clinical presentation

Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe-LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research

The source model of group threat: responding to internal and external threats

We introduce a model of group threat that articulates the opposing effects of intergroup (between-groups) and intragroup (within-group) threat on identity processes and group relations. The source model of group threat argues that the perceived source of a threat is critical in predicting its consequences, such that perceptions of intergroup threat will strengthen (in)group identity processes and relations, whereas perceptions of intragroup threat has the potential to undermine the same. In addition to reviewing the large literature on intergroup threat and a smaller body of unsynthesized work on intragroup threat, we discuss how these processes are captured in representations of monsters (aliens, vampires, and zombies) in popular media and how these ideas can inform interpretation of current political debates, such as those around homegrown terrorism. This model provides a novel summary of the core effects of intergroup and intragroup threat, generating testable hypotheses about the psychological effects of different types of threat. Applying this model will help to make sense of seemingly contradictory findings in the literature, illustrating how appraisal of a threat as originating from an intergroup or intragroup source has the capacity to change the group-based effects of that threat