Crystal Structure Prediction for Benzene Using Basin-Hopping Global Optimization

[Image: see text] Organic molecules can be stable in distinct crystalline forms, known as polymorphs, which have significant consequences for industrial applications. Here, we predict the polymorphs of crystalline benzene computationally for an accurate anisotropic model parametrized to reproduce electronic structure calculations. We adapt the basin-hopping global optimization procedure to the case of crystalline unit cells, simultaneously optimizing the molecular coordinates and unit cell parameters to locate multiple low-energy structures from a variety of crystal space groups. We rapidly locate all the well-established experimental polymorphs of benzene, each of which corresponds to a single local energy minimum of the model. Our results show that basin-hopping can be both an efficient and effective tool for polymorphic crystal structure prediction, requiring no a priori experimental knowledge of cell parameters or symmetry

Wheat: Its water use, production and disease detection and prediction

The author has identified the following significant results. Discussed in this report are: (1) the effects of wheat disease on water use and yield; and (2) the use of ERTS-1 imagery in the evaluation of wheat growth and in the detection of disease severity. Leaf area index was linearly correlated with ratios MSS4:MSS5 and MSS5:MSS6. In an area of severe wheat streak mosaic virus infected fields, correlations of ERTS-1 digital counts with wheat yields and disease severity levels were significant at the 5% level for MSS bands 4 and 5 and band ratios 4/6 and 4/7. Data collection platforms were used to gather meteorological data for the early prediction of rust severity and economic loss

Review of next generation hydrogen production from offshore wind using water electrolysis

\ua9 2023 The Author(s)Hydrogen produced using renewable energy from offshore wind provides a versatile method of energy storage and power-to-gas concepts. However, few dedicated floating offshore electrolyser facilities currently exist and therefore conditions of the offshore environment on hydrogen production cost and efficiency remain uncertain. Therefore, this review focuses on the conversion of electrical energy to hydrogen, using water electrolysis located in offshore areas. The challenges associated with the remote locations, fluctuating power and harsh conditions are highlighted and recommendations for future electrolysis system designs are suggested. The latest research in polymer electrolyte membrane, alkaline and membraneless electrolysis are evaluated in order to understand their capital costs, efficiency and current research status for achieving scaled manufacturing to the GW scale required in the next three decades. Operating fundamentals that govern the performance of each device are investigated and future recommendations of research specifically for the integration of water electrolysers with offshore wind turbines is presented

A grid-based infrastructure for distributed retrieval

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicity emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to ‘lift’ the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science

Persistent inequalities in consultation incidence and prevalence of low back pain and osteoarthritis in England between 2004-2019

Objective To determine whether socioeconomic inequalities in primary care consultation rates for two major, disabling musculoskeletal conditions in England narrowed or widened between 2004-2019. Methods We analysed data from Clinical Practice Research Datalink Aurum, a national general practice electronic health records database, linked to national deprivation ranking of each patients’ registered residential postcode. For each year we estimated the age-sex standardised consultation incidence and prevalence for low back pain and osteoarthritis for the most deprived 10% of neighbourhoods through to the least deprived 10%. We then calculated the Slope Index of Inequality and Relative Index of Inequality overall, and by sex, age-group, and geographical region. Results Inequalities in LBP incidence and prevalence over socioeconomic status widened between 2004-2013 and stabilised between 2014-2019. Inequalities in OA incidence remained stable over socioeconomic status within study period, whereas inequalities in OA prevalence markedly widened over socioeconomic status between 2004-2019. Widest gap in LBP incidence and prevalence over socioeconomic status was observed in population resident in Northern English regions and London, and in those of working age, peaking at 45-54 years. Conclusions We found persistent, and generally increasing, socioeconomic inequalities in the rate of adults presenting to primary care in England with low back pain and osteoarthritis between 2004-2019. Lay summary What does this mean for patients? Our study describes the extent of social inequalities in how many adults present to primary care with a painful musculoskeletal condition. We focussed on two of the most common, disabling conditions: back pain and osteoarthritis. We analysed information from primary care electronic medical records across England. People living in the most deprived (“poorest”) neighbourhoods were more likely to seek the help of primary care than people of the same age and sex who lived in the least deprived (“richest”) neighbourhoods. Compared to general practices serving the richest neighbourhoods, a general practice serving the poorest neighbourhoods in England could see 15-40% more patients presenting with a new episode of back pain or osteoarthritis each year. These differences in rates between rich and poor were particularly noticeable among women, among working-age adults, and in the north of England and in London. Inequalities did not appear to have reduced between 2004 and 2019. Our study did not investigate underlying causes. However, it does highlight issues around workload and resourcing of general practices and the need for earlier and sustained preventive actions focussed towards poorer communities across England

Leveraging machine learning in porous media

\ua9 2024 The Royal Society of Chemistry.The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML), has had a significant impact on engineering and the fundamental sciences, resulting in advances in various fields. The use of ML has significantly enhanced data processing and analysis, eliciting the development of new and improved technologies. Specifically, ML is projected to play an increasingly significant role in helping researchers better understand and predict the behavior of porous media. Furthermore, ML models will be able to make use of sizable datasets, such as subsurface data and experiments, to produce accurate predictions and simulations of porous media systems. This capability could help optimize the design of porous materials for specific applications and improve the effectiveness of industrial processes. To this end, this review paper attempts to provide an overview of the present status quo in this context, i.e., the interface of ML and porous media in six different applications, namely, heat exchanger and storage, energy storage and combustion, electrochemical devices, hydrocarbon reservoirs, carbon capture and sequestration, and groundwater, stressing the advances made in the application of ML to porous media and offering insights into the challenges and opportunities for future research. Each section also entails a supplementary database of the literature as a spreadsheet, which includes the details of ML models, datasets, key findings, etc., and mentions relevant available online datasets that can be used to train ML models. Future research trends include employing hybrid models by combining ML models with physics-based models of porous media to improve predictions concerning accuracy and interpretability

Social marketing and healthy eating : Findings from young people in Greece

This document is the Accepted Manuscript version. The final publication is available at Springer via http://dx.doi.org/10.1007/s12208-013-0112-xGreece has high rates of obesity and non-communicable diseases owing to poor dietary choices. This research provides lessons for social marketing to tackle the severe nutrition-related problems in this country by obtaining insight into the eating behaviour of young adults aged 18–23. Also, the main behavioural theories used to inform the research are critically discussed. The research was conducted in Athens. Nine focus groups with young adults from eight educational institutions were conducted and fifty-nine participants’ views towards eating habits, healthy eating and the factors that affect their food choices were explored. The study found that the participants adopted unhealthier nutritional habits after enrolment. Motivations for healthy eating were good health, appearance and psychological consequences, while barriers included lack of time, fast-food availability and taste, peer pressure, lack of knowledge and lack of family support. Participants reported lack of supportive environments when deciding on food choices. Based on the findings, recommendations about the development of the basic 4Ps of the marketing mix, as well as of a fifth P, for Policy are proposedPeer reviewe

Genetic variation and recombination of RdRp and HSP 70h genes of Citrus tristeza virus isolates from orange trees showing symptoms of citrus sudden death disease

<p>Abstract</p> <p>Background</p> <p>Citrus sudden death (CSD), a disease that rapidly kills orange trees, is an emerging threat to the Brazilian citrus industry. Although the causal agent of CSD has not been definitively determined, based on the disease's distribution and symptomatology it is suspected that the agent may be a new strain of <it>Citrus tristeza virus </it>(CTV). CTV genetic variation was therefore assessed in two Brazilian orange trees displaying CSD symptoms and a third with more conventional CTV symptoms.</p> <p>Results</p> <p>A total of 286 RNA-dependent-RNA polymerase (RdRp) and 284 heat shock protein 70 homolog (HSP70h) gene fragments were determined for CTV variants infecting the three trees. It was discovered that, despite differences in symptomatology, the trees were all apparently coinfected with similar populations of divergent CTV variants. While mixed CTV infections are common, the genetic distance between the most divergent population members observed (24.1% for RdRp and 11.0% for HSP70h) was far greater than that in previously described mixed infections. Recombinants of five distinct RdRp lineages and three distinct HSP70h lineages were easily detectable but respectively accounted for only 5.9 and 11.9% of the RdRp and HSP70h gene fragments analysed and there was no evidence of an association between particular recombinant mosaics and CSD. Also, comparisons of CTV population structures indicated that the two most similar CTV populations were those of one of the trees with CSD and the tree without CSD.</p> <p>Conclusion</p> <p>We suggest that if CTV is the causal agent of CSD, it is most likely a subtle feature of population structures within mixed infections and not merely the presence (or absence) of a single CTV variant within these populations that triggers the disease.</p