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FIGURE 1. Best scoring 28S in Contribution to the taxonomy of Sistotremastrum (Trechisporales, Basidiomycota) and the description of two new species, S. fibrillosum and S. aculeocrepitans
FIGURE 1. Best scoring 28S rDNA phylogram of the corticioid lineages in the Basidiomycetes most closely related to the Sistotremastrum clade obtained in RAxML. Nodes supported by>0.95 Bayesian PP or>70% ML BP are shown annotated. Root branch length was altered for publishing.
Transcutaneous spinal cord stimulation enhances motor score and gait recovery in incomplete spinal cord injury. A double-blind randomized controlled trial
<p><strong><span>Background: </span></strong><span>Although transcutaneous spinal cord stimulation (tSCS) has been suggested as a safe and feasible intervention for gait rehabilitation, no studies have determined its effectiveness compared to sham stimulation.</span></p> <p><strong><span>Objective: </span></strong><span>To determine the effectiveness of tSCS combined with robotic-assisted gait training (RAGT) on lower limb muscle strength and walking function in incomplete spinal cord injury (iSCI) participants.</span></p> <p><strong><span>Methods: </span></strong><span>A randomized, double-blind, sham-controlled clinical trial was designed. Twenty-seven subacute iSCI participants were randomly allocated to tSCS or sham-tSCS group. The intervention consisted of 20 sessions of standard Lokomat walking training enhanced with tSCS. Primary outcomes were the lower extremity motor score (LEMS) and dynamometry. Secondary outcomes included the 10-Meter Walk Test (10MWT), the Timed Up and Go test (TUG), the 6-Minute Walk test (6MWT), the Spinal Cord Independence Measure III (SCIM III) and the Walking Index for Spinal Cord Injury II (WISCI-II). Assessments were performed before and after the intervention and at 1-month follow-up.</span></p> <p><strong><span>Results: </span></strong><span>Although no significant differences between groups were detected after the intervention, the tSCS group showed greater effects than the sham-tSCS group for LEMS (3.4 points; p=0.033), 10MWT (37.5s; p=0.030), TUG (47.7s; p=0.009), and WISCI-II (3.4 points; p=0.023) at the 1-month follow-up. Furthermore, the percentage of subjects who were able to walk at the follow-up was greater in the tSCS group (85.7%) compared to the sham group (43.1%; p=0.029).</span></p> <p><strong><span>Conclusions:</span></strong><span> The combination of standard RAGT with tSCS for 20 sessions was effective for LEMS and gait recovery in subacute iSCI participants after one month of follow-up.</span></p> <p><strong><span>Key words: </span></strong><span>Spinal cord injury; Transcutaneous spinal cord stimulation; Lokomat; Robotic-assisted gait training; Motor function; </span><span>Gait rehabilitation.</span></p>
The suitability score of BESS locations in Yau Tsim Mong, Hong Kong
<p><a name="_Hlk171934804"></a><span>Climate change and extreme weather events are imposing threats to city power systems with regional power shortages. To enhance urban power system’s resilience amid climate change, photovoltaic (PV) and battery energy storage systems (BESS) are crucial for maintaining self-sufficient power during outages. However, the optimal installation location and capacity sizing and allocation of BESS remain uncertain when considering multi-criteria, including</span> <span><span>safety, energy flexibility, accessibility and energy resilience. This study proposes a new approach, i.e., Geographic Information System (GIS) integrated with Multi-Criteria Decision-Making (MCDM) approach, to identify optimal installation<a name="_Hlk171932259"></a> locations and capacity allocation of BESS. This approach comprehensively considers geographical conditions (such as slope,</span></span><span><span> land use,</span> </span><span><span>open space)</span></span><span><span>, safety, energy flexibility, accessibility and energy resilience</span></span><span><span>, while accounting for the entire distribution network’s <span>granularity</span>, intermittent solar supply, and unstable electricity demand</span></span><span><span>. The methodology can guide the</span> </span><span><span>optimal BESS siting and sizing for energy resilience under future climate change and associated extreme weather events. Results indicate that suitable installation locations based on the proposed GIS-MCDM method are concentrated in central and southern regions in Yau Tsim Mong. Subsequently, BESS with the optimal and specific installation location and capacity allocation is in districts with high electricity demand and favourable safety geographical conditions.</span></span><span><span> Compared to BESS without GIS-MCDM, the optimal BESS deployment with GIS-MCDM decreases the <a name="_Hlk171932540"></a>power shortage from 13,184 MWh to 12,931 MWh. Additionally, it increases the maximum power shortage reduction density from 176.04 kWh/m<sup>2</sup> to 364.2 kWh/m<sup>2</sup>, and the area with a power shortage reduction above 100 kWh/m<sup>2</sup> expands from 1.24×10<sup>5</sup> m<sup>2 </sup>to 2.17×10<sup>5</sup> m<sup>2</sup>. </span></span><span><span>This study contributes a new approach to determine optimal BESS installation locations and capacity allocation in urban-scale information modelling, planning and deployment<a name="_Hlk171932579"></a>, with</span></span><span><span><span> frontier guidelines <a name="_Hlk171934602"></a>for system designers and urban planners to collaboratively develop resilience <a name="_Hlk171932653"></a>and survivability </span></span></span><span><span>of urban power systems under extreme events.</span></span></p>
Health Professionals' Attitudes and Demographics in Central Ethiopia: A Study of Attitude Scores and Specialties
<p>his dataset contains information collected from health professionals in Central Ethiopia. The data primarily includes:</p> <ul> <li><strong>Profession and Specialization:</strong> The type of health professional (e.g., specialty doctors).</li> <li><strong>Attitude Scores:</strong> Numerical scores representing the health professionals' attitudes towards prescribing physical activity, potentially for managing non-communicable diseases or musculoskeletal injuries.</li> <li><strong>Demographics:</strong> Gender of the health professionals.</li> </ul> <p>This dataset is part of a study aimed at understanding the attitudes of health professionals in the region, which could inform future interventions or policies related to physical activity prescriptions in healthcare.</p>
Genetic risk score and age at onset
Open the record for dataset details and reuse information.
GAPS (Guitar-Aligned Performance Scores) Dataset
<p>Release of the aligned MIDI transcriptions, scores and downbeats that constitute the GAPS dataset. Links to YouTube URLs for audio and video are provided in the accompanying metadata file. See below for the abstract of the publication.</p> <p>Abstract:</p> <p>We introduce GAPS (Guitar-Aligned Performance Scores), a new dataset of classical guitar performances, and a benchmark guitar transcription model that achieves state-of-the-art performance on GuitarSet in both supervised and zero-shot settings. GAPS is the largest dataset of real guitar audio, containing 14 hours of freely available audio-score aligned pairs, recorded in diverse conditions by over 200 performers, together with high-resolution note-level MIDI alignments and performance videos. These enable us to train a state-of-the-art model for automatic transcription of solo guitar recordings which can generalise well to real world audio that is unseen during training.</p>
Do the predicted suitability scores from species distribution models correlate with species performance on-ground?
<p>Species distribution models are a very popular statistical tool for inferring potential distribution range of species across space and time and are thought to be a good predictor for habitat suitability. Some studies have suggested that if these models are reliable, predicted habitat suitability (PHS) should relate to species traits visualization, growth potential, body size, abundance. We validated this hypothesis by estimating association between the PHS and species abundance for 17 avian species endemic to the Western Ghats - Sri Lanka biodiversity hotspot. Additionally, we compared the PHS of sites where species were detected in both seasons (wet and dry) against sites where they were detected in the dry season alone. As a proxy for abundance, we estimated single-season occupancy estimates (ψ) using detection/non-detection data from multiple visits to the survey sites. We report significant and positive PHS-ψ correlation, though the strength of this association varied across species and models. Half of the species showed higher suitability scores for the sites where they were detected year round. The results presented here suggest that the predictive models can be used as a proxy for habitat quality, in addition to inferring the potential distribution.</p>
FIGURE 1. The best scoring RAxML tree from 42 in Camarosporium sensu stricto in Pleosporinae, Pleosporales with two new species
FIGURE 1. The best scoring RAxML tree from 42 strains based on combined dataset of LSU, SSU and ITS sequences. Bootstrap support values for maximum-likelihood (ML) and maximum-parsimony (MP) values greater than 50% are given above the nodes. Posterior Probability values (PP) greater than 0.7 are given below the nodes. The culture collection numbers are given after the species names. The tree is rooted to Montagnula anthostomoides (CBS 615.86) All type and ex-type strains are in bold and newly generated sequences are in red.
Figure 9. Principal component scores for 186 in Morphometric and molecular variation in mountain catfishes (Amphiliidae: Amphilius) in Guinea, West Africa
Figure 9. Principal component scores for 186 Amphilius platychir specimens in lateral analysis. Specimens examined: Senegal (X) n = 22, Rio Corubal (Δ) n = 20, Konkouré (+) n = 111, Niger (o) n = 4, A. kakrimensis (Þ) n = 1, Badi () n = 2, Fatala (q) n = 24, and Tinguilinta (Ɨ) n = 1. Bold plots represent basins where tissue samples were collected. With deformation grids (exaggerated by two).
Precision, Recall and F1 score
<p>Precision, Recall and F1 score calculated to compare the automatic annotation with that from domain experts.</p>
Genome-wide association study of polygenic risk score-defined phenotype suffers from inflated test-statistics
<p>Simulation results from running the following script 100 times: https://github.com/euffelmann/paper-ad_prs_extremes/blob/main/scripts/ad_prs_extremes_simulation.R.</p> <p>These files can be used to reproduce tables and figures in: https://github.com/euffelmann/paper-ad_prs_extremes</p>
A dataset of Korean weather with anomaly score from 2010 to 2020
<p>This dataset describes the weather data of 64 cities in Korea for each day and the weather anomaly scores for each day from 2010 to 2020. The dataset includes city name, dates, temperature, humidity, vapor pressure, dew point temperature, sea level pressure, ground pressure, ground temperature, LOF anomaly score, IF anomaly score, COPOD anomaly score, ABOD anomaly score, HBOS anomaly score, SOD anomaly score and ROD anomaly score. In the dataset, the weather data and the weather anomaly score of each day for 64 Korean cities from 2010 to 2020 are stroed into 64 csv files. Each csv file in the dataset represents each city. The 64 cities include Seoul, the capital of Korea, and the 6 metropolitan cities of Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. In addition, the weather data and weather anomaly scores for 19 coastal cities and 4 islands in Korea are included in the dataset.</p>
University of Chicago Breast Cancer Recurrence Score Dataset
<p>Extracted tiles from slide images used for validation of our deep learning recurrence score model.</p> <p>Please refer to the <a href="https://github.com/fmhoward/DLRS">github project page</a> for instructions on use.</p> <p>The UCH_BRCA_RS zip file contains the image tiles used for model validation. The 'tfrecords' element in the 'UCH_BRCA_RS' entry in the dataset.json file should be updated to reflect the location where this folder is extracted.</p> <p>The ROI zip file contains the tumor region annotations used for tumor likelihood model training. The TCGA BRCA project 'roi' entries in the dataset.json file should be updated to point to these subfolders.</p> <p>The PROJECTS zip file contains trained models used for the published analysis of this work. This should be extracted into the PROJECTS directed included as part of the github repository. </p>
Leveraging the Crowd to Assess the Risk of Automated Dependency Updates: A Study on the Compatibility Score - Replication Package
<p>Replication package for FSE 2023 submission: Leveraging the Crowd to Assess the Risk of Automated Dependency Updates: A Study on the Compatibility Score</p> <p>Includes datasets used for the study and additional appendix material.</p>
Polygenic risk score in Africa populations: progress and challenges
<p>Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects SNPs that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has application which investigate the genetic basis of several traits which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we reviewed the conventional PRS methods and their application to Sub-Saharan African communities. We concluded that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to Sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating, and analyzing Africa population data for clinical evaluation of PRSs of interest and predicting rare diseases.</p>
A dataset of Korean weather with anomaly score from 2010 to 2020
<p>This dataset describes the weather data of 64 cities in Korea for each day and the weather anomaly scores for each day from 2010 to 2020. The dataset includes city name, dates, temperature, humidity, vapor pressure, dew point temperature, sea level pressure, ground pressure, ground temperature, LOF anomaly score, IF anomaly score, COPOD anomaly score, ABOD anomaly score, HBOS anomaly score, SOD anomaly score and ROD anomaly score. In the dataset, the weather data and the weather anomaly score of each day for 64 Korean cities from 2010 to 2020 are stored into 64 csv files. Each csv file in the dataset represents each city. The 64 cities include Seoul, the capital of Korea, and the 6 metropolitan cities of Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. In addition, the weather data and weather anomaly scores for 19 coastal cities and 4 islands in Korea are included in the dataset.</p>
A social niche breadth score reveals niche range strategies of generalists and specialists
<p><strong>Abstract</strong></p> <p>Generalists can survive in many environments whereas specialists are restricted to a single environment. Although a classical concept in ecology, niche breadth has remained challenging to quantify for microbes because it depends on an objective definition of the environmental conditions. Here, by defining the environment of a microbe as the community it resides in, we integrated information from over 22 thousand environmental sequencing samples to derive a quantitative measure of the niche, which we call ‘social niche breadth’. At the level of genera, we explored niche range strategies throughout the prokaryotic tree of life. We found that social generalists include opportunists that stochastically dominate local communities, while social specialists are stable but low in abundance. Social generalists have a more diverse and open pan genome than social specialists, but we found no global correlation between social niche breadth and genome size. Instead, we observed two distinct evolutionary strategies, where specialists have relatively small genomes in habitats with low local diversity, but relatively large genomes in habitats with high local diversity. Together, our analysis shines data-driven light on microbial niche range strategies.</p> <p><strong>Inside this repository</strong></p> <p>This is the directory structure and code used to generate all data and figures in the paper "A social niche breadth score reveals niche range strategies of generalists and specialists" by F. A. Bastiaan von Meijenfeldt, Paulien Hogeweg, and Bas E. Dutilh. The code was made by F. A. Bastiaan von Meijenfeldt.</p> <ul> <li>The code inside the ./MGnify directory was used to download the MGnify data.</li> <li>The code inside the ./niche_breadth directory was used to generate all other data and uses the MGnify data.</li> <li>The code inside the ./figures directory was used to generate all figures.<br> </li> <li>Each directory in ./MGnify and ./niche_breadth contains a commands.sh that if run, and if source files are present, will generate all content in that directory. No files are written outside the directory. For example running ./MGnify/commands.sh will generate all files within ./MGnify. The generated files are source files for some of the scripts in ./MGnify/2019-08-20_extra and ./MGnify/2019-08-20_extra/commands.sh can now be run to generate all files within. Source files for the ./niche_breadth subdirectories can be from the ./MGnify directory or from other subdirectories within ./niche_breadth.</li> <li>The ./figures directory and its subdirectories contain *.ipynb Jupyter Notebook files that if run, and source files are present, will generate the vector files that were used as raw input for the final figures.<br> </li> <li>The file ./figures/mappings.Figure_to_Notebook.txt contains the mapping of the figure to the notebook that was used to generate the figure. In some cases only part of the notebook output was used in the final figures.</li> </ul>
Table S3. Univariate analyses of early BCR in high-risk and very high-risk patients after propensity score matching.
<p>Table S3. Univariate analyses of early BCR in high-risk and very high-risk patients after propensity score matching.</p>
Table S2. Univariate analyses of PSM in high-risk and very high-risk patients after propensity score matching.
<p>Table S2. Univariate analyses of PSM in high-risk and very high-risk patients after propensity score matching.</p>
Table S1. Univariate analyses of early continence in high-risk and very high-risk patients after propensity score matching.
<p>Table S1. Univariate analyses of early continence in high-risk and very high-risk patients after propensity score matching.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.