Balancing the Picture: Debiasing Vision-Language Datasets with Synthetic Contrast Sets

Vision-language models are growing in popularity and public visibility to generate, edit, and caption images at scale; but their outputs can perpetuate and amplify societal biases learned during pre-training on uncurated image-text pairs from the internet. Although debiasing methods have been proposed, we argue that these measurements of model bias lack validity due to dataset bias. We demonstrate there are spurious correlations in COCO Captions, the most commonly used dataset for evaluating bias, between background context and the gender of people in-situ. This is problematic because commonly-used bias metrics (such as Bias@K) rely on per-gender base rates. To address this issue, we propose a novel dataset debiasing pipeline to augment the COCO dataset with synthetic, gender-balanced contrast sets, where only the gender of the subject is edited and the background is fixed. However, existing image editing methods have limitations and sometimes produce low-quality images; so, we introduce a method to automatically filter the generated images based on their similarity to real images. Using our balanced synthetic contrast sets, we benchmark bias in multiple CLIP-based models, demonstrating how metrics are skewed by imbalance in the original COCO images. Our results indicate that the proposed approach improves the validity of the evaluation, ultimately contributing to more realistic understanding of bias in vision-language models.Comment: Github: https://github.com/oxai/debias-gensynt

A convolutional neural network to characterize mouse hindlimb foot strikes during voluntary wheel running

Voluntary wheel running (VWR) is widely used to study how exercise impacts a variety of physiologies and pathologies in rodents. The primary activity readout of VWR is aggregated wheel turns over a given time interval (most often, days). Given the typical running frequency of mice (∼4 Hz) and the intermittency of voluntary running, aggregate wheel turn counts, therefore, provide minimal insight into the heterogeneity of voluntary activity. To overcome this limitation, we developed a six-layer convolutional neural network (CNN) to determine the hindlimb foot strike frequency of mice exposed to VWR. Aged female C57BL/6 mice (22 months, n = 6) were first exposed to wireless angled running wheels for 2 h/d, 5 days/wk for 3 weeks with all VWR activities recorded at 30 frames/s. To validate the CNN, we manually classified foot strikes within 4800 1-s videos (800 randomly chosen for each mouse) and converted those values to frequency. Upon iterative optimization of model architecture and training on a subset of classified videos (4400), the CNN model achieved an overall training set accuracy of 94%. Once trained, the CNN was validated on the remaining 400 videos (accuracy: 81%). We then applied transfer learning to the CNN to predict the foot strike frequency of young adult female C57BL6 mice (4 months, n = 6) whose activity and gait differed from old mice during VWR (accuracy: 68%). In summary, we have developed a novel quantitative tool that non-invasively characterizes VWR activity at a much greater resolution than was previously accessible. This enhanced resolution holds potential to overcome a primary barrier to relating intermittent and heterogeneous VWR activity to induced physiological responses

The effects of cold working on sensitization and intergranular corrosion behavior of AISI 304 stainless steel

The effects of prior cold rolling of up to an 80 pct reduction in thickness on the sensitization-desensitization behavior of Type AISI 304 stainless steel and its susceptibility to intergranular corrosion have been studied by electrochemical potentiokinetic reactivation (EPR) and Strauss-test methods. The results indicate that the prior deformation accelerated the sensitization as compared to the undeformed stainless steel. The deformed Type 304 stainless steel experienced desensitization at higher temperatures and times, and it was found to be enhanced by increased cold deformation. This could be attributed to the increased long-range chromium diffusion, possibly brought on by increasing pipe diffusion and vacancies. The role of the deformation-induced martensite (DIM) and texture, introduced by uniaxial cold rolling, on the sensitization-desensitization kinetics has also been discussed. This study could not reveal any systematic relationship between texture and the degree of sensitization (DOS) obtained. The effect of DIM on DOS seems to be pronounced at 500 °C when the steel retained significant amounts of DIM; however, the retained DIM is insignificant at higher sensitization times and temperatures

Rescuing Loading Induced Bone Formation at Senescence

The increasing incidence of osteoporosis worldwide requires anabolic treatments that are safe, effective, and, critically, inexpensive given the prevailing overburdened health care systems. While vigorous skeletal loading is anabolic and holds promise, deficits in mechanotransduction accrued with age markedly diminish the efficacy of readily complied, exercise-based strategies to combat osteoporosis in the elderly. Our approach to explore and counteract these age-related deficits was guided by cellular signaling patterns across hierarchical scales and by the insight that cell responses initiated during transient, rare events hold potential to exert high-fidelity control over temporally and spatially distant tissue adaptation. Here, we present an agent-based model of real-time Ca2+/NFAT signaling amongst bone cells that fully described periosteal bone formation induced by a wide variety of loading stimuli in young and aged animals. The model predicted age-related pathway alterations underlying the diminished bone formation at senescence, and hence identified critical deficits that were promising targets for therapy. Based upon model predictions, we implemented an in vivo intervention and show for the first time that supplementing mechanical stimuli with low-dose Cyclosporin A can completely rescue loading induced bone formation in the senescent skeleton. These pre-clinical data provide the rationale to consider this approved pharmaceutical alongside mild physical exercise as an inexpensive, yet potent therapy to augment bone mass in the elderly. Our analyses suggested that real-time cellular signaling strongly influences downstream bone adaptation to mechanical stimuli, and quantification of these otherwise inaccessible, transient events in silico yielded a novel intervention with clinical potential

Alabama Ground Operations during the Deep Convective Clouds and Chemistry Experiment

The Deep Convective Clouds and Chemistry (DC3) field campaign investigates the impact of deep, midlatitude convective clouds, including their dynamical, physical and lighting processes, on upper tropospheric composition and chemistry. DC3 science operations took place from 14 May to 30 June 2012. The DC3 field campaign utilized instrumented aircraft and ground ]based observations. The NCAR Gulfstream ]V (GV) observed a variety of gas ]phase species, radiation and cloud particle characteristics in the high ]altitude outflow of storms while the NASA DC ]8 characterized the convective inflow. Groundbased radar networks were used to document the kinematic and microphysical characteristics of storms. In order to study the impact of lightning on convective outflow composition, VHF ]based lightning mapping arrays (LMAs) provided detailed three ]dimensional measurements of flashes. Mobile soundings were utilized to characterize the meteorological environment of the convection. Radar, sounding and lightning observations were also used in real ]time to provide forecasting and mission guidance to the aircraft operations. Combined aircraft and ground ]based observations were conducted at three locations, 1) northeastern Colorado, 2) Oklahoma/Texas and 3) northern Alabama, to study different modes of deep convection in a variety of meteorological and chemical environments. The objective of this paper is to summarize the Alabama ground operations and provide a preliminary assessment of the ground ]based observations collected over northern Alabama during DC3. The multi ] Doppler, dual ]polarization radar network consisted of the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR), the UAHuntsville Mobile Alabama X ]band (MAX) radar and the Hytop (KHTX) Weather Surveillance Radar 88 Doppler (WSR ]88D). Lightning frequency and structure were observed in near real ]time by the NASA MSFC Northern Alabama LMA (NALMA). Pre ]storm and inflow proximity soundings were obtained with the UAHuntsville mobile sounding unit and the Redstone Arsenal (QAG) morning sounding

Gut Flora Metabolism of Phosphatidylcholine Promotes Cardiovascular Disease

Metabolomics studies hold promise for the discovery of pathways linked to disease processes. Cardiovascular disease (CVD) represents the leading cause of death and morbidity worldwide. Here we used a metabolomics approach to generate unbiased small-molecule metabolic profiles in plasma that predict risk for CVD. Three metabolites of the dietary lipid phosphatidylcholine—choline, trimethylamine N-oxide (TMAO) and betaine—were identified and then shown to predict risk for CVD in an independent large clinical cohort. Dietary supplementation of mice with choline, TMAO or betaine promoted upregulation of multiple macrophage scavenger receptors linked to atherosclerosis, and supplementation with choline or TMAO promoted atherosclerosis. Studies using germ-free mice confirmed a critical role for dietary choline and gut flora in TMAO production, augmented macrophage cholesterol accumulation and foam cell formation. Suppression of intestinal microflora in atherosclerosis-prone mice inhibited dietary-choline-enhanced atherosclerosis. Genetic variations controlling expression of flavin monooxygenases, an enzymatic source of TMAO, segregated with atherosclerosis in hyperlipidaemic mice. Discovery of a relationship between gut-flora-dependent metabolism of dietary phosphatidylcholine and CVD pathogenesis provides opportunities for the development of new diagnostic tests and therapeutic approaches for atherosclerotic heart disease

CERT1 mutations perturb human development by disrupting sphingolipid homeostasis

Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome.This work was supported by the National Institute of Neurological Disorders and Stroke (NINDS), NIH (R01NS109858, to VAG); the Paul A. Marks Scholar Program at the Columbia University Vagelos College of Physicians and Surgeons (to VAG); a TIGER grant from the TAUB Institute at the Columbia Vagelos College of Physicians and Scientists (to VAG); the Swiss National Science Foundation (SNF 31003A-179371, to TH); the European Joint Program on Rare Diseases (EJP RD+SNF 32ER30-187505, to TH); the Swiss Cancer League (KFS-4999-02-2020, to GD); the EPFL institutional fund (to GD); the Kristian Gerhard Jebsen Foundation (to GD); the Swiss National Science Foundation (SNSF) (310030_184926, to GD); the Swiss Foundation for Research on Muscle Disease (FSRMM, to MAL); the Natural Science and Engineering Research Council of Canada (Discovery Grant 2020-04241, to JEB); the Italian Ministry of Health Young Investigator Grant (GR-2011-02347754, to EL); the Fondazione Istituto di Ricerca Pediatrica – Città della Speranza (18-04, to EL); the Wroclaw Medical University (SUB.E160.21.004, to RS); the National Science Centre, Poland (2017/27/B/NZ5/0222, to RS); Telethon Undiagnosed Diseases Program (TUDP) (GSP15001); the Temple Street Foundation/Children’s Health Foundation Ireland (RPAC 19-02, to IK); the Deutsche Forschungsgemeinschaft (DFG) (PO2366/2–1, to BP); the Instituto de Salud Carlos III, Spain (to ELM, EBS, and BMD); the National Natural Science Foundation of China (81871079 and 81730036, to HG and KX); and the National Institutes of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH (R01 DK115574, to SSC).The DEFIDIAG study is funded by grants from the French Ministry of Health in the framewok of the national French initiative for genomic medicine. The funders were not involved in the study design, data acquisition, analysis, or writing of the manuscript. Funding for the DECIPHER project was provided by Wellcome. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between Wellcome and the Department of Health, and the Wellcome Sanger Institute (grant number WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of Wellcome or the Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12, granted by the Republic of Ireland REC). The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network.S

Domestic cats (Felis catus) prefer freely available food over food that requires effort.

Contrafreeloading is the willingness of animals to work for food when equivalent food is freely available. This behavior is observed in laboratory, domesticated, and captive animals. However, previous research found that six laboratory cats failed to contrafreeload. We hypothesized that cats would contrafreeload in the home environment when given a choice between a food puzzle and a tray of similar size and shape. We also hypothesized that more active cats would be more likely to contrafreeload. We assessed the behavior of 17 neutered, indoor domestic cats (Felis catus) when presented with both a food puzzle and a tray across ten 30-min trials. Each cat wore an activity tracker, and all sessions were video recorded. Cats ate more food from the free feed tray than the puzzle (t (16) = 6.77, p < 0.001). Cats made more first choices to approach and eat from the tray. There was no relationship between activity and contrafreeloading, and there was no effect of sex, age, or previous food puzzle experience on contrafreeloading. Our results suggest that cats do not show strong tendencies to contrafreeload in the home environment, although some cats (N = 4) ate most food offered in the puzzle or showed weak contrafreeloading tendencies (N = 5). Eight cats did not contrafreeload. Cats who consumed more food from the puzzle, consumed more food in general, suggesting a relationship between hunger and effort. Further research is required to understand why domestic cats, unlike other tested species, do not show a strong preference to work for food

Chemistry I No- and Low-Cost Adoption

This adoption of Chemistry: Atoms First 2e from OpenStax, Introduction to Chemistry: General, Organic, and Biological v 1.0 by Ball et. all., Chemistry for Allied Health by Soult, and the low-cost CHEM101 homework platform is as a result of a Round 17 Textbook Transformation Grant.https://oer.galileo.usg.edu/chemistry-collections/1019/thumbnail.jp

Extension of the AIOMFAC model by iodine and carbonate species: applications for aerosol acidity and cloud droplet activation

Iodine and carbonate species are important components in marine and dust aerosols, respectively. The non-ideal interactions between these species and other inorganic and organic compounds within aqueous particle phases affect hygroscopicity, acidity, and gas-particle partitioning of semivolatile components. In this work, we present an extended version of the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model by incorporating the ions I-, IO3-, HCO3-, CO32-, OH-, and CO2(aq) as new species. First, AIOMFAC ion interaction parameters for aqueous solutions were determined based on available thermodynamic data, such as water activity, mean molal activity coefficients, solubility, and vapor-liquid equilibrium measurements. Second, the interaction parameters for the new ions and various organic functional groups were optimized based on experimental data or, where data are scarce, alternative estimation methods such as multiple linear regression or a simple substitution by analogy approach. Additional bulk water activity and electrodynamic balance measurements were carried out to augment the database for the AIOMFAC parameter fit. While not optimal, we show that the use of alternative parameter estimation methods enables physically sound predictions and offers the benefit of a more broadly applicable model. Our implementation of the aqueous carbonate-bicarbonate-CO2(aq) system accounts for the associated temperature-dependent dissociation equilibria explicitly and enables closed- or open-system computations with respect to carbon dioxide equilibration with the gas phase. We discuss different numerical approaches for solving the coupled equilibrium conditions and highlight critical considerations when extremely acidic or basic mixtures are encountered. The fitted AIOMFAC model performance for inorganic aqueous systems is considered excellent over the whole range of mixture compositions where reference data are available. Moreover, the model provides physically meaningful predictions of water activity under highly concentrated conditions. For organic-inorganic mixtures involving new species, the model-measurement agreement is found to be good in most cases, especially at equilibrium relative humidities above g1/4g70g%; reasons for deviations are discussed. Several applications of the extended model are shown and discussed, including the effects of ignoring the auto-dissociation of water in carbonate systems, the effects of mixing bisulfate and bicarbonate compounds in closed- or open-system scenarios on pH and solution speciation, and the prediction of critical cloud condensation nucleus activation of NaI or Na2CO3 particles mixed with suberic acid.ISSN:1680-7375ISSN:1680-736