Publications by authors named "K Jain Jose"

We present a directed electrostatics strategy integrated as a graph neural network (DESIGNN) approach for predicting stable nanocluster structures on their potential energy surfaces (PESs). The DESIGNN approach is a graph neural network (GNN)-based model for building structures of large atomic clusters with specific sizes and point-group symmetry. This model assists in the structure building of atomic metal clusters by predicting molecular electrostatic potential (MESP) topography minima on their structural evolution paths.

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Background: People living in 'walkable' areas are more active, but common approaches to assessing walkability using audit tools and geospatial data have limitations in rural areas. This project explored the feasibility, acceptability and benefits of using a citizen science approach to audit walkability in rural communities.

Methods: Using a citizen science approach, community members in rural towns completed audit tools and photographs to capture walkability.

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Article Synopsis
  • Participants from 22 research groups utilized various methods, including periodic DFT-D methods, machine learning models, and empirical force fields to assess crystal structures generated from standardized sets.
  • The findings indicate that DFT-D methods generally aligned well with experimental results, while one machine learning approach showed significant promise; however, the need for more efficient research methods was emphasized due to resource consumption.
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During 2022-2023, the School Lunch Project (SLP) provided free nutritious cooked lunches 1-4 days per week to Kinder to Grade 10 students attending 30 schools in areas of high disadvantage in Tasmania, Australia. This analysis examined if the SLP was associated with student attendance. : Staff (teachers, support staff, and principals) from 12 schools completed an online survey and/or participated in focus groups/interviews.

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A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern.

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