Automated Fidelity Assessment for Strategy Training in Inpatient Rehabilitation using Natural Language Processing

Strategy training is a multidisciplinary rehabilitation approach that teaches skills to reduce disability among those with cognitive impairments following a stroke. Strategy training has been shown in randomized, controlled clinical trials to be a more feasible and efficacious intervention for promoting independence than traditional rehabilitation approaches. A standardized fidelity assessment is used to measure adherence to treatment principles by examining guided and directed verbal cues in video recordings of rehabilitation sessions. Although the fidelity assessment for detecting guided and directed verbal cues is valid and feasible for single-site studies, it can become labor intensive, time consuming, and expensive in large, multi-site pragmatic trials. To address this challenge to widespread strategy training implementation, we leveraged natural language processing (NLP) techniques to automate the strategy training fidelity assessment, i.e., to automatically identify guided and directed verbal cues from video recordings of rehabilitation sessions. We developed a rule-based NLP algorithm, a long-short term memory (LSTM) model, and a bidirectional encoder representation from transformers (BERT) model for this task. The best performance was achieved by the BERT model with a 0.8075 F1-score. This BERT model was verified on an external validation dataset collected from a separate major regional health system and achieved an F1 score of 0.8259, which shows that the BERT model generalizes well. The findings from this study hold widespread promise in psychology and rehabilitation intervention research and practice.Comment: Accepted at the AMIA Informatics Summit 202

SN 2021zny: an early flux excess combined with late-time oxygen emission suggests a double white dwarf merger event

We present a photometric and spectroscopic analysis of the ultra-luminous and slowly evolving 03fg-like Type Ia SN 2021zny. Our observational campaign starts from $\sim5.3$ hours after explosion (making SN 2021zny one of the earliest observed members of its class), with dense multi-wavelength coverage from a variety of ground- and space-based telescopes, and is concluded with a nebular spectrum $\sim10$ months after peak brightness. SN 2021zny displayed several characteristics of its class, such as the peak brightness ($M_{B}=-19.95$ mag), the slow decline ($\Delta m_{15}(B) = 0.62$ mag), the blue early-time colours, the low ejecta velocities and the presence of significant unburned material above the photosphere. However, a flux excess for the first $\sim1.5$ days after explosion is observed in four photometric bands, making SN 2021zny the third 03fg-like event with this distinct behavior, while its $+313$ d spectrum shows prominent [O I] lines, a very unusual characteristic of thermonuclear SNe. The early flux excess can be explained as the outcome of the interaction of the ejecta with $\sim0.04\:\mathrm{M_{\odot}}$ of H/He-poor circumstellar material at a distance of $\sim10^{12}$ cm, while the low ionization state of the late-time spectrum reveals low abundances of stable iron-peak elements. All our observations are in accordance with a progenitor system of two carbon/oxygen white dwarfs that undergo a merger event, with the disrupted white dwarf ejecting carbon-rich circumstellar material prior to the primary white dwarf detonation.Comment: 19 pages, 16 figures, accepted for publication in MNRA

Illustrated Abstracts of the 5th EUPLAN International Conference

These illustrated capsules have been prepared by some speakers of State-of-the-Art talks and of original investigations, presented at the 5th European Platelet Network (EUPLAN) International Conference, which was held at the Università degli Studi di Milano (Italy) on September 28-30, 2022. The programme featured various state-of-the-art lectures and a selection of oral presentations covering a broad range of topics in platelet and megakaryocyte biology, from basic science to recent advances in clinical studies. As usual, the meeting brought together senior scientists and trainees in an informal atmosphere to discuss platelet science in person

The sustainable materials roadmap

Over the past 150 years, our ability to produce and transform engineered materials has been responsible for our current high standards of living, especially in developed economies. However, we must carefully think of the effects our addiction to creating and using materials at this fast rate will have on the future generations. The way we currently make and use materials detrimentally affects the planet Earth, creating many severe environmental problems. It affects the next generations by putting in danger the future of the economy, energy, and climate. We are at the point where something must drastically change, and it must change now. We must create more sustainable materials alternatives using natural raw materials and inspiration from nature while making sure not to deplete important resources, i.e. in competition with the food chain supply. We must use less materials, eliminate the use of toxic materials and create a circular materials economy where reuse and recycle are priorities. We must develop sustainable methods for materials recycling and encourage design for disassembly. We must look across the whole materials life cycle from raw resources till end of life and apply thorough life cycle assessments (LCAs) based on reliable and relevant data to quantify sustainability. We need to seriously start thinking of where our future materials will come from and how could we track them, given that we are confronted with resource scarcity and geographical constrains. This is particularly important for the development of new and sustainable energy technologies, key to our transition to net zero. Currently 'critical materials' are central components of sustainable energy systems because they are the best performing. A few examples include the permanent magnets based on rare earth metals (Dy, Nd, Pr) used in wind turbines, Li and Co in Li-ion batteries, Pt and Ir in fuel cells and electrolysers, Si in solar cells just to mention a few. These materials are classified as 'critical' by the European Union and Department of Energy. Except in sustainable energy, materials are also key components in packaging, construction, and textile industry along with many other industrial sectors. This roadmap authored by prominent researchers working across disciplines in the very important field of sustainable materials is intended to highlight the outstanding issues that must be addressed and provide an insight into the pathways towards solving them adopted by the sustainable materials community. In compiling this roadmap, we hope to aid the development of the wider sustainable materials research community, providing a guide for academia, industry, government, and funding agencies in this critically important and rapidly developing research space which is key to future sustainability.journal articl

Data on vegetation across forest edges from the FERN(Forest Edge Research Network)

Published versionMany studies have focused on vegetation across forest edges to study impacts of edges created by human activities on forest structure and composition, or patterns of vegetation at inherent natural edges. Our objective was to create a database of plant-related variables across different types of edges from various studies (mainly from across Canada, but also in Brazil and Belize) to facilitate edge research. We compiled data on vegetation along more than 300 transects perpendicular to forest edges adjacent to clear-cuts, burned areas, bogs, lakes, barrens, insect disturbances, and riparian areas from 24 studies conducted over the past three decades. Data were compiled for more than 400 plant species and forest structure variables (e.g., trees, logs, canopy cover). All data were collected with a similar sampling design of quadrats along transects perpendicular to forest edges, but with varying numbers of transects and quadrats, and distances from the edge. The purpose for most of the studies was either to determine the distance of edge influence (edge width) or to explore the pattern of vegetation along the edge to interior gradient. We provide data tables for the cover of plant species and functional groups, the species and size of live and dead trees, the density of saplings, maximum height of functional groups and shrub species, and the cover of functional groups at different heights (vertical distribution of vegetation). The Forest Edge Research Network (FERN) database provides extensive data on many variables that can be used for further study including meta-analyses and can assist in answering questions important to conservation efforts (e.g., how is distance of edge influence from created edges affected by different factors?). We plan to expand this database with subsequent studies from the authors and we invite others to contribute to make this a more global database. The data are released under a CC0 license. When using these data, we ask that you cite this data paper and any relevant publications listed in our metadata file. We also encourage you to contact the first author if you are planning to use or contribute to this database

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant