Obesity is one of the major contributors to the excess mortality seen in people with severe mental illness (SMI) and in low- and middle-income countries people with SMI may be at an even greater risk. In this study, we aimed to determine the prevalence of obesity and overweight in people with SMI and investigate the association of obesity and overweight with sociodemographic variables, other physical comorbidities, and health-risk behaviours. This was a multi-country cross-sectional survey study where data were collected from 3989 adults with SMI from three specialist mental health institutions in Bangladesh, India, and Pakistan. The prevalence of overweight and obesity was estimated using Asian BMI thresholds. Multinomial regression models were then used to explore associations between overweight and obesity with various potential determinants. There was a high prevalence of overweight (17·3 %) and obesity (46·2 %). The relative risk of having obesity (compared to normal weight) was double in women (RRR = 2·04) compared with men. Participants who met the WHO recommendations for fruit and vegetable intake had 2·53 (95 % CI: 1·65–3·88) times greater risk of having obesity compared to those not meeting them. Also, the relative risk of having obesity in people with hypertension is 69 % higher than in people without hypertension (RRR = 1·69). In conclusion, obesity is highly prevalent in SMI and associated with chronic disease. The complex relationship between diet and risk of obesity was also highlighted. People with SMI and obesity could benefit from screening for non-communicable diseases, better nutritional education, and context-appropriate lifestyle interventions.

In addition to student assessment, curriculum assessment is a critical element to any pedagogy. It helps the educator assess the teaching of concepts, determine what may be lacking, and make changes for continual improvement. Meaningful assessment can be complicated when disciplines converge or when new approaches are implemented. To facilitate this, we present a network-based visualization schema to represent a materials informatics curriculum that combines materials science and data science concepts. We analyze the curriculum using network representations and relevant concepts from graph theory. This reveals established connections, linkages between materials science and data science, and the extent to which different concepts are connected. We also describe how some materials science topics are introduced from a data perspective, and present an illustrative case study from the curriculum.

This paper demonstrates the application of Natural Language Processing (NLP) tools to explore large libraries of documents and to correlate heuristic associations between text descriptions in figure captions with interpretations of images and figures. The use of visualization tools based on NLP methods permits one to quickly assess the extent of the research described in the literature related to a specific topic. The authors demonstrate how the use of NLP methods on only the figure captions without having to navigate the entire text of a document can provide an accelerated assessment of the literature in a given domain.

The present work aims to understand the effect of zinc and rare-earth element addition (i.e., 2 wt% Gd, 2 wt% Dy, and 2 wt% of Gd and Nd individually) on the microstructure evolution, mechanical properties, in vitro corrosion behavior, and cytotoxicity of Mg for biomedical application. The microstructure results indicate that the Mg–Zn–Gd alloy consists of the lamellar long period stacking ordered phase. The electrochemical and immersion corrosion behavior were studied in Hanks balanced salt solution. Enhanced corrosion resistance with reduced hydrogen evolution volume and magnesium (Mg2+) ion release were estimated for the Mg–Zn–Gd alloy as compared to the other two alloy systems. At the early stage of corrosion, formation of the oxide film inhibited the corrosion propagation. However, at the later stages, the breaking of the oxide film leads to shallow pitting mode of corrosion. The ultimate tensile strength of Mg–Zn–Gd–Nd is better than the other two alloys due to the uniform distribution of the Mg12Nd precipitate phase. The moderate strength in the Mg–Zn–Gd alloy is due to the low volume fraction of the secondary phase. The MTT (methylthiazoldiphenyl-tetrazolium bromide) assay study was carried out to understand the cell cytotoxicity on the alloy surfaces. Studies revealed that all three alloys had significant cellular adherence and no adverse effect on cells.

With the development of high-speed computers, networks, and huge storage, researchers can utilize a large volume and wide variety of materials data generated by experimental facilities and computations. The emergence of these big data and advanced analytical techniques has opened unprecedented opportunities for materials research. The discovery of many kinds of materials, such as energy-harvesting materials, structural materials, catalysts, optoelectronic materials, and magnetic materials, have been greatly accelerated through high-throughput screening. The utility of data-centric science for materials research is likely to grow significantly in the future. Unraveling the complexities inherent in big data could lead to novel design rules as well as new materials and functionalities.

Information on density and abundance of globally threatened species such as tigers Panthera tigris is essential for effective conservation as well as to evaluate the success of conservation programmes. We monitored tigers in Parsa Widlife Reserve, Nepal, using camera traps, in 2013, 2014 and 2016. Once believed to be a sink for tigers from adjacent Chitwan National Park, Parsa now provides a new hope for tigers. Spatially explicit capture–recapture analysis over 3 survey years revealed an increase in tiger density from 0.78 to 1.38 individuals per 100 km2 from 2013 to 2016. The tiger abundance was estimated to be seven (6–13), 11 (10–16) and 17 (17–20) in 2013, 2014 and 2016, respectively. Resettlement of communities from the core area, reduced anthropogenic pressure, and improved security have made Parsa Wildlife Reserve a suitable habitat for tigers. Tiger abundance increased considerably within a 5 km radius of the evacuated village sites, from two in 2013 to eight in 2014 and 10 in 2016. Population turnover has remained moderate (< 30% per year), with persistence of individuals in multiple years. Dispersing tigers from Chitwan's source population accounted for a large portion (c. 40%) of the tigers detected in Parsa. Conservation efforts along with annual monitoring should be continued in Parsa to sustain the increase and monitor the persistence of tigers. The Chitwan–Parsa complex should be managed as a single ecological unit for conserving the Endangered tiger and other wide-ranging species.

The study of microstructure–property relationships and processing history leading to those relationships is at the core of materials engineering. The historical evolution of the understanding of processing–microstructure–property relationships has largely relied on empirical evidence that, in turn, has helped catalyze theories iteratively linking modeling to experiments, which has then helped the maturation process of materials design. While the power of modeling methods has increased, we have, as of yet, no unified mathematical formalism to seamlessly connect materials chemistry with kinetics and micro- and mesoscale information despite decades of work. In this article, we provide an overview of how “microstructural informatics” permits one to capture the interaction between processing variables and their influence on microstructure–chemistry–property correlations. This includes a particular focus on the use of manifold representations and data compression methods for defining microstructure–chemistry–property relationships that can explain known materials behavior and aid in designing new processing pathways of materials with enhanced properties. The concept of identifying an irreducible representation of microstructure is introduced.