Adverse impact of neighbourhood socioeconomic deprivation on psychological treatment outcomes : the role of area-level income and crime

Aim: Socioeconomic deprivation is known to be associated with depression and anxiety symptoms. This study aimed to investigate the influence of several domains of neighbourhood deprivation on psychological treatment outcomes. Method: Healthcare records from 44805 patients who accessed psychological treatment were analyzed. Patient-level depression (PHQ-9) and anxiety (GAD-7) outcome measures were linked to their neighbourhood statistics, including area-level indices of income, unemployment, education, health and disability, crime, housing quality, and quality of the local environment. Linear regressions were applied to examine associations between these domains and post-treatment symptom severity after controlling for patient-level and service-level variables. Results: Neighbourhood income and crime rates were associated with depression and anxiety symptoms after controlling for covariates, explaining 4% to 5% of variability in treatment outcomes. Patients living in low-income areas required a higher number of treatment sessions to benefit from therapy. Conclusions: Patients living in economically deprived neighbourhoods tend to have poorer depression and anxiety treatment outcomes and require lengthier interventions

Shade for Cattle on Pasture: A Guide for Ontario Producers

In tropical climates, adequate shade may be essential to ensure the survival and productivity of grazing animals, but in the temperate Ontario climate, the necessity or benefits of providing shade for grazing cattle are less clear, and have proved controversial. Meteorological data indicate that beef cattle in Ontario may be at risk of suffering from heat stress on more than 25% of days during July and August, and may decrease feed intake and benefit from the provision of shade for more than 50% of days during the two hottest summer months. A booklet, entitled ‘Beat the Heat. A Guide to Hot Weather and Shade for Ontario Cattle Producers’, has been written for the Ontario Cattleman’s Association, as a means of providing basic information on heat biology in cattle, and as a focus for discussion on the value of shade to Ontario beef producers

GVdoc: Graph-based Visual Document Classification

The robustness of a model for real-world deployment is decided by how well it performs on unseen data and distinguishes between in-domain and out-of-domain samples. Visual document classifiers have shown impressive performance on in-distribution test sets. However, they tend to have a hard time correctly classifying and differentiating out-of-distribution examples. Image-based classifiers lack the text component, whereas multi-modality transformer-based models face the token serialization problem in visual documents due to their diverse layouts. They also require a lot of computing power during inference, making them impractical for many real-world applications. We propose, GVdoc, a graph-based document classification model that addresses both of these challenges. Our approach generates a document graph based on its layout, and then trains a graph neural network to learn node and graph embeddings. Through experiments, we show that our model, even with fewer parameters, outperforms state-of-the-art models on out-of-distribution data while retaining comparable performance on the in-distribution test set

The use of contrast enhancement techniques in X-ray imaging of lithium-ion battery electrodes

Understanding the microstructural morphology of Li-ion battery electrodes is crucial to improving the electrochemical performance of current Li-ion battery systems and in developing next-generation power systems. The use of 3D X-ray imaging techniques, which are continuously evolving, provides a non-invasive platform to study the relationship between electrode microstructure and performance at various time and length scales. In addition to characterizing a weakly (X-ray) absorbing graphite electrode at multiple length scales, we implement an approach for obtaining improved nano-scale image contrast on a laboratory X-ray microscope by combining information obtained from both absorption-contrast and Zernike phase-contrast X-ray images

Guidelines for Safe, High Performing Li-Ion Battery Designs for Manned Vehicles

New design features and test methods are in development at NASA to take advantage of the newest high power and energy dense commercial Li-ion cell designs and to achieve passively thermal runaway (TR) propagation resistant (PPR) designs for manned missions requiring high power/voltage. The goal is to minimize the parasitic mass and volume of the battery components; thus reaching a balance between high battery specific power (W/kg) and energy (Wh/kg) as well as power (W/L) and energy density (Wh/L). Current 18650 cell designs achieve greater than 275 Wh/kg, greater than 725 Wh/L, but present high risks of side wall breaching during TR which can defeat many other safety features resulting in nearly immediate TR propagation. This work seeks to better understand the phenomena of cell side wall breaches and to determine the effectiveness of promising battery design features for achieving safe, high performing battery designs for high voltage/power applications

Combining Fractional Calorimetry with Statistical Methods to Characterize Thermal Runaway

Fractional thermal runaway calorimetry (FTRC) techniques were introduced to examine thermal runaway (TR) behavior of lithium-ion (Li-ion) cells. Specifically, FTRC considers the total energy released vs. the fraction of the total energy that is released through the cell casing vs. through the ejecta material. This device has been expanded to universally support FTRC testing of additional cell types including 21700-format, D-Cell format, and large prismatic format Li-ion cells. The TR behavior as influenced by cell format, manufacturer, chemistry, capacity, and in situ safety features are described in this presentation

Design of a miniature flow cell for in situ x-ray imaging of redox flow batteries

Flow batteries represent a possible grid-scale energy storage solution, having many advantages such as scalability, separation of power and energy capabilities, and simple operation. However, they can suffer from degradation during operation and the characteristics of the felt electrodes are little understood in terms of wetting, compression and pressure drops. Presented here is the design of a miniature flow cell that allows the use of x-ray computed tomography (CT) to study carbon felt materials in situ and operando, in both lab-based and synchrotron CT. Through application of the bespoke cell it is possible to observe felt fibres, electrolyte and pore phases and therefore enables non-destructive characterisation of an array of microstructural parameters during the operation of flow batteries. Furthermore, we expect this design can be readily adapted to the study of other electrochemical systems

Multi-scale 3D investigations of a commercial 18650 Li-ion battery with correlative electron- and X-ray microscopy

In the present study, a commercial 18650 Li-ion cylindrical cell is investigated with non-destructive 3D X-ray microscopy across a range of length scales, beginning with a survey of the entire cell and non-destructively enlarging a smaller section. Active materials are extracted from a disassembled cell and imaging performed using a combination of sub-micron X-ray microscopy and 2D scanning-electron microscopy, which point toward the need for multi-scale analysis in order to accurately characterize the cell. Furthermore, a small section is physically isolated for 3D nano-scale X-ray microscopy, which provides a measurement of porosity and enables the effective diffusivity and 3-dimensional tortuosities to be calculated via computer simulation. Finally, the 3D X-ray microscopy data is loaded into a correlative microscopy environment, where a representative sub-surface region is identified and, subsequently, analyzed using electron microscopy and energy-dispersive X-ray spectroscopy. The results of this study elucidate the microstructural characteristics and potential degradation mechanisms of a commercial NCA battery and, further, establish a technique for extracting the Bruggeman exponent for a real-world microstructure using correlative microscopy