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2,031 results for “transformers”
Various seasonal pattern and mechanisms of soil nitrogen transformation along elevations in the Hengduan Mountains
<p><span>Soil nitrogen (N) transformation, a key microbial process in global N cycling, is thought to alter soil N availability and subsequently regulate ecosystem functioning. In particular, the gross rates of N transformation can provide a deeper understanding of internal N dynamics and mechanisms, but questions of whether gross N transformation processes and their underlying drivers change with seasons and elevations remain large uncertain.</span></p> <p><span>Based on field collection along an elevational gradient and laboratory incubation experiments, we investigated the seasonal processes of soil N mineralization and nitrification with 15N isotope dilution technique, and also explored the potential mechanisms involved in the Hengduan Mountains.</span></p> <p><span>Unimodal soil gross/net mineralization rates were higher in the wet season (61.32 mg kg<sup>-1</sup> d<sup>-1</sup>; 1.01 mg kg<sup>-1</sup> d<sup>-1</sup>; respectively) than in the dry season (10.88 mg kg<sup>-1</sup> d<sup>-1</sup>; 0.55 mg kg<sup>-1</sup> d<sup>-1</sup>; respectively) (P < 0.001), with a peak at medium elevation. Soil gross/net nitrification rates were lower in the wet season (1.43 mg kg<sup>-1</sup> d<sup>-1</sup>; -0.017 mg kg<sup>-1</sup> d<sup>-1</sup>) than in the dry season (2.49 mg kg<sup>-1</sup> d<sup>-1</sup>; 0.004 mg kg<sup>-1</sup> d<sup>-1</sup>; respectively) (P < 0.001), which increased with increasing elevation. The results detected the dominant drivers of the gross transformation rates, specifically microbial attributes occupied crucial roles in controlling the gross mineralization/nitrification</span> <span>in the wet season, and soil physicochemical properties were dominant controllers on the gross mineralization/nitrification</span> <span>during the dry season.</span></p> <p><span>This study revealed the divergent patterns and drivers of N transformation, suggesting that seasonal N cycling should no longer be overlooked if we are to predict N biogeochemical cycles in response to environmental change accurately.</span></p>
The Transformative Storytelling Technique for Developing Guided Digital Narratives in Mental Health Support. Pilot study
<p>In a society where advances and innovations occur on a daily basis, the development of digital mental health tools continues at almost uncontrollable rates. Following trends in the utilization of storytelling across fields and reflecting on the lack of working models and frameworks for the application of storytelling for mental health support, the Transformative Storytelling Technique (TST) is designed and developed as a part of this work. This technique represents a new category for creating hybrid content to guide the experience of audiences, starting with the case of informal caregivers. In this pilot study, a TST caregiver story is assessed pre-post in an interventional study, investigating the potential role of mental health audio stories in supporting informal caregiver wellbeing. The anonymized raw dataset is available.</p>
Raw simulation results for Second-order homogenisation of crystal plasticity and martensitic transformation
<p>This dataset contains the raw simulation results used in the article entitled "Second-order homogenisation of crystal plasticity and martensitic transformation" (under review - 2023/05/15), by Igor A. Rodrigues Lopes, Miguel Vieira de Carvalho, João A. Marques da Silva, Rui P. Cardoso Coelho and Francisco M. Andrade Pires (INEGI and Faculty of Engineering of the University of Porto, Portugal).<br> These numerical results have been generated with the in-house finite element code LINKS.</p> <p>The dataset contains the datafiles, with information about the finite element mesh, plain text files with readable results, and vtu files that allow visualising the results in Paraview.</p>
PIsToN: Evaluating Protein Binding Interfaces with Transformer Networks (dataset)
<p>Computational protein-binding studies are widely used to investigate fundamental biological processes and facilitate the development of modern drugs, vaccines, and therapeutics. Scoring functions aim to assess and rank the binding strength of the predicted protein complex. Accurate scoring of protein binding interfaces remains a challenge. PIsToN (evaluating Protein binding Interfaces with Transformer Networks) represents a novel approach to distinguish native-like protein complexes from incorrect conformations. Protein interfaces are transformed into a collection of 2D images (interface maps), each corresponding to a geometric or biochemical property. Pixel intensities represent the feature values. A neural network was adapted from a popular vision transformer (ViT) with several enhancements: a hybrid component to accept empirical-based energy terms, a multi-attention module to highlight essential features and binding sites, and the use of contrastive learning for better ranking performance. The resulting PIsToN model significantly outperforms state-of-the-art scoring functions on well-known datasets.</p> <p>This repository contains proteins and pre-computed interface maps for the PIsToN work.</p>
Time Series Measurement Data of Office Building in Jakarta Indonesia - Incoming Transformer of 20 kV | 0.4 kV
<p>Time Series Measurement Data of Office Buildings in Jakarta Indonesia - Incoming Three Transformers of 2 MVA rating (20 kV | 0.4 kV)<br> The data was taken by Standardized Power Quality Analyzer within minutes span data during eight days in 2016. <br> The data consist of Voltage, Current, Active/Reactive/Apparent Power, Power Factor, Total Harmonic Distortion (THD) within three-phase measurement. Related data was also included from with it i.e., calculated data for active power losses, Unbalanced Voltage per phase, efficiency etc</p>
Time Series Measurement Data of Medium Voltage | Low Voltage [MV|LV] Feeders in Jabodetabek Regions Indonesia – District Incoming Transformers of 630 kVA & 400 kVA (20 kV | 0.4 kV)
<p>Time Series Measurement Data of Medium Voltage | Low Voltage (MV|LV] Feeders in Jabodetabek Regions Indonesia – District Incoming Transformers of 630 kVA & 400 kVA (20 kV | 0.4 kV)<br> Standardized Power Quality Analyzer took the data within 1- and 5 minutes span data during seven days in 2016. <br> The data consist of Voltage, Current, Active/Reactive/Apparent Power, Power Factor, and Total Harmonic Distortion (THD) within three-phase measurement. Related data was also included with it i.e., calculated data for active power losses, Unbalanced Voltage per phase, efficiency etc</p>
Data from Widespread exposure to altered fire regimes under 2°C warming is projected to transform conifer forests of the Western United States
<p>This archive includes a minimal dataset needed to reproduce the analysis as well as a table (CSV) and spatial polygons (ESRI shapefile) of the resulting output from the publication:</p> <p>Hoecker, T.J., S. A. Parks, M. Krosby & S. Z. Dobrowski. 2023. Widespread exposure to altered fire regimes under 2°C warming is projected to transform conifer forests of the Western United States. <em>Communications Earth and Environment</em>.</p> <p>Publication abstract:</p> <p>Changes in wildfire frequency and severity are altering conifer forests and pose threats to biodiversity and natural climate solutions. Where and when feedbacks between vegetation and fire could mediate forest transformation are unresolved. Here, for the western U.S., we used climate analogs to measure exposure to fire-regime change; quantified the direction and spatial distribution of changes in burn severity; and intersected exposure with fire-resistance trait data. We measured exposure as multivariate dissimilarities between contemporary distributions of fire frequency, burn severity, and vegetation productivity and distributions supported by a 2 °C-warmer climate. We project exposure to fire-regime change across 65% of western US conifer forests and mean burn severity to ultimately decline across 63% because of feedbacks with forest productivity and fire frequency. We find that forests occupying disparate portions of climate space are vulnerable to projected fire-regime changes. Forests may adapt to future disturbance regimes, but trajectories remain uncertain.</p>
Fig. 60. Character transformations within clade 4 in An Appraisal of the Higher Classification of Cicadas (Hemiptera: Cicadoidea) with Special Reference to the Australian Fauna
Fig. 60. Character transformations within clade 4 of the same tree shown in Fig. 59. Numbered nodes relate to discussion in the text. Note that resolution within this clade differs little from the strict consensus tree shown in Fig. 56. Tribal groupings are those proposed under this study. Black bars = non-homoplasious forward change; grey bars = homoplasious forward change; white bars = reversal (whether homoplasious or not).
Fig. 62. Character transformations within clade 13 in An Appraisal of the Higher Classification of Cicadas (Hemiptera: Cicadoidea) with Special Reference to the Australian Fauna
Fig. 62. Character transformations within clade 13 of the same tree shown in Fig. 59. Note that resolution within this clade differs little from the strict consensus tree shown in Fig. 56. Numbered nodes relate to discussion in the text. The tribal grouping is that proposed under this study. Black bars = nonhomoplasious forward change; grey bars = homoplasious forward change; white bars = reversal (whether homoplasious or not).
Fig. 61. Character transformations within clade 7 in An Appraisal of the Higher Classification of Cicadas (Hemiptera: Cicadoidea) with Special Reference to the Australian Fauna
Fig. 61. Character transformations within clade 7 of the same tree shown in Fig. 59. Numbered nodes relate to discussion in the text. Note that resolution within this clade differs little from the strict consensus tree shown in Fig. 56. Tribal groupings are those proposed under this study. Black bars = non-homoplasious forward change; grey bars = homoplasious forward change; white bars = reversal (whether homoplasious or not).
Schriftliche Stellungnahmen der öffentlichen Konsultation zur Transformation des Vergaberechts ("Vergabetransformationspaket") durch das Bundesministerium für Wirtschaft und Klimaschutz
<p>Bis Juni 2023 haben sich über 450 Stakeholder im Zuge der öffentlichen Konsultation zur Transformation des Vergaberechts ("Vergabetransformationspaket") eingebracht. Die Stellungnahmen kommen aus allen mit dem Vergaberecht befassten Bereichen und decken somit die gesamte Breite an Praxiswissen und Interessenslagen in Deutschland ab. Beteiligt hat sich ein breiter Kreis von Auftraggebern von der Bundes- bis zur kommunalen Ebene sowie aus einer Vielzahl von Sektoren. Stellungnahmen wurden auch vielfältig von Auftragnehmern eingereicht, vom Solo-Selbständigen, Mittelstandsunternehmen bis hin zu großen Branchenverbänden. Darüber hinaus sind auch viele Stellungnahmen von Initiativen und Verbänden etwa zu Umwelt-, Sozial- oder Digitalisierungsthemen eingegangen.</p> <p>Die Stellungnahmen und weitere Informationen und Daten zur öffentlichen Konsultation wurden hier veröffentlicht, soweit kein Widerspruch gegen ihre Veröffentlichung eingelegt wurde:<br> <a href="http://www.bmwk.de/Redaktion/DE/Artikel/Service/Gesetzesvorhaben/oeffentliche-konsultation-zur-transformation-des-vergaberechts.html">www.bmwk.de/Redaktion/DE/Artikel/Service/Gesetzesvorhaben/oeffentliche-konsultation-zur-transformation-des-vergaberechts.html</a></p> <p>Diese zusätzliche Datenveröffentlichung auf Zenodo dient der Bereitstellung der Stellungnahmen in einem maschinenlesbaren Format (csv) und in persistenter Form. Hierfür wurden die Stellungnahmen aus einzelnen PDF-Dateien in eine CSV-Datei zusammengeführt. Bei der Transformation und Strukturierung der Daten, die zum Teil manuell erfolgte, kann es unter Umständen zu fehlerhaften Zuordnungen und Formatierungsfehlern gekommen sein. Das BMWK übernimmt für die Richtigkeit der Daten im Vergleich zu den ursprünglichen Stellungnahmen keine Gewähr. Die ursprünglichen Stellungnahmen im PDF-Format können hier heruntergeladen werden: <a href="http://www.bmwk.de/Redaktion/DE/Downloads/Stellungnahmen/vergabetransformationspaket.html">www.bmwk.de/Redaktion/DE/Downloads/Stellungnahmen/vergabetransformationspaket.html</a></p> <p> </p>
Supplementary Data to: "Quantifying sub-seasonal growth rate changes in fossil giant clams using wavelet transformation of daily Mg/Ca cycles" in Geochemistry, Geophysics, Geosystems
<p>El/Ca data and high resolution images of 3 laser-ablation tracks on a fossil giant calm. The following Isotopes were monitored <sup>11</sup>B, <sup>23</sup>Na, <sup>24</sup>Mg, <sup>27</sup>Al, <sup>43</sup>Ca, <sup>88</sup>Sr, <sup>89</sup>Y and <sup>138</sup>Ba. The data was measured with laser-ablation inductively coupled plasma mass spectrometry (LA-ICPMS) using a 3 x 33 µm laser slit. El/Ca ratios were calibrated using NIST SRM 612 as bracketing external standard (Jochum et al., 2011) with updated Mg values from Evans & Müller (2018) and <sup>43</sup>Ca as the internal standard; data quantification follows Longerich et al. (1996) and was performed using the software iolite 4 (Paton et al., 2011). For details see main text.</p> <p>References:</p> <p>Evans, D., & Müller, W. (2018). Automated Extraction of a Five-Year LA-ICP-MS Trace Element Data Set of Ten Common Glass and Carbonate Reference Materials: Long-Term Data Quality, Optimisation and Laser Cell Homogeneity. <em>Geostandards and Geoanalytical Research</em>, <em>42</em>(2), 159–188. https://doi.org/10.1111/ggr.12204</p> <p>Jochum, K. P., Weis, U., Stoll, B., Kuzmin, D., Yang, Q., Raczek, I., Jacob, D. E., Stracke, A., Birbaum, K., Frick, D. A., Günther, D., & Enzweiler, J. (2011). Determination of Reference Values for NIST SRM 610–617 Glasses Following ISO Guidelines. <em>Geostandards and Geoanalytical Research</em>, <em>35</em>(4), 397–429. https://doi.org/10.1111/j.1751-908X.2011.00120.x</p> <p>Longerich, H. P., Jackson, S. E., & Günther, D. (1996). Inter-laboratory note. Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation. <em>Journal of Analytical Atomic Spectrometry</em>, <em>11</em>(9), 899–904. https://doi.org/10.1039/JA9961100899</p> <p>Paton, C., Hellstrom, J., Paul, B., Woodhead, J., & Hergt, J. (2011). Iolite: Freeware for the visualisation and processing of mass spectrometric data. <em>Journal of Analytical Atomic Spectrometry</em>, <em>26</em>(12), 2508–2518. https://doi.org/10.1039/C1JA10172B</p>
Inferring shape transformations in a drawing task
<p>Data repository relative to the following publication:</p> <p>Schmidt, F., Tiedemann, H., Fleming, R. W., & Morgenstern, Y. (in press). Inferring shape transformations in a drawing task. <em>Memory & Cognition</em>. <a href="https://doi.org/10.3758/s13421-023-01452-0">https://doi.org/10.3758/s13421-023-01452-0</a></p> <p>The repository includes several MATLAB demos that show how to load the drawings, test, and sample shapes (Figure4_showdrawpercond.m), and scripts that plot Figure 5 and 6 from the manuscript and compute the statistics (Figure5or6_overall_results.m). The latter demo (Figure5or6_overall_results.m) has the option of running the analysis pipeline on the drawing (through analysisScript1.m) or using precomputed analysis. Note that running the analysis pipeline will require that you have ShapeComp, which you can download here: <a href="https://sites.google.com/view/yanivmorgenstern/home/tools/shapecomp">https://sites.google.com/view/yanivmorgenstern/home/tools/shapecomp</a></p> <p>If you use this data or code, please cite our paper.</p> <p>For questions or suggestions, please contact Filipp Schmidt (filipp.schmidt@psychol.uni-giessen.de) and/or Yaniv Morgenstern (Yaniv.Morgenstern@gmail.com).</p>
Dataset for "Demystifying food systems transformation: a review of the state of the field"
<p>Datasets offer the raw and analysed data used for the review article: "Demystifying food systems transformation: a review of the state of the field". This file contains the three main databases used and variations on the literature data filtering. Dataset 3 includes a breakdown of the analysis criteria adopted and reported on.</p>
Freshwater connectivity transforms spatially integrated signals of biodiversity
<p>Aquatic ecosystems offer a continuum of water flow from headwater streams to inland lakes and coastal marine systems. This spatial connectivity influences the structure, function and dynamics of aquatic communities, which are among the most threatened and degraded on earth. Here, we determine the spatial resolution of eDNA in dendritic freshwater networks, which we use as a model for connected metacommunities. Our intensive sampling campaign comprised over 430 eDNA samples across 21 connected lakes, allowing us to analyse detections at a variety of scales, from different habitats within a lake to entire lake networks. We found strong signals of within-lake variation in eDNA distribution reflective of typical habitat use by both fish and zooplankton. Most importantly, we also found that connecting channels between lakes resulted in an accumulation of downstream eDNA detections in lakes with a higher number of inflows, and as networks increased in length. Environmental DNA achieves biodiversity surveys in these habitats in a high-throughput, spatially integrated way. These findings have profound implications for the interpretation of eDNA detections in aquatic ecosystems in global-scale biodiversity monitoring observations.</p>
Data from: Automatic patient-level recognition of four Plasmodium species on thin blood smear by a Real Time Detector Transformer (RT-DETR) object detection algorithm: a proof-of-concept and evaluation
<p>Automatic patient-level recognition of four <em>Plasmodium</em> species on thin blood smear by a Real Time Dectector Transformer (RT-DETR) object detection algorithm: a proof-of-concept and evaluation</p> <p>Emilie Guemas, Baptiste Routier, Théo Ghelfenstein-Ferreira, Camille Cordier, Sophie Hartuis, Bénédicte Marion, Sébastien Bertout, Emmanuelle Varlet-Marie, Damien Costa, Grégoire Pasquier</p> <p><strong>Abstract:</strong></p> <p>Malaria remains a global health problem with 247 million cases and 619,000 deaths in 2021. Diagnostic of <em>Plasmodium</em> species is important for administering the appropriate treatment. The gold-standard diagnosis from accurate species identification remains the thin blood smear. Nevertheless, this method is time-consuming and requires highly skilled and trained microscopists. To overcome these issues, new diagnostic tools based on deep learning are emerging. This study aimed to evaluate the performances of a RT-DETR (Real-Time Detection Transformer)object detection algorithm to discriminate <em>Plasmodium</em> species on thin blood smears images. The algorithm was trained and validated on a dataset consisting in 24,720 images from 475 thin blood smears corresponding to 2,002,597 labels. Performances were calculated with a test dataset of 4,508 images from 170 smears corresponding to 358,825labels coming from six French university hospital. At the patient level, the RT-DETR algorithm exhibited an overall accuracy of 79.4% (135/170) with a recall of 74% (40/54) and 81.9% (95/116) for negative and positive smears, respectively. Among <em>Plasmodium </em>positive smears, the global sensitivity was 82.7% (91/110) with a sensitivity of 90% (38/42), 81.8% (18/22) and 76.1% (35/46) for <em>P. falciparum</em>, <em>P. malariae </em>and <em>P. ovale/vivax,</em> respectively. The YOLOv5 model achieved a World Health Organization (WHO) competence level 2 for species identification. Besides, the RT-DETR algorithm may be run in real-time on low-cost devices such as a smartphone and could be suitable for deployment in low-resource setting areas where microscopy experts are lacking.</p> <p><strong>Data collection:</strong></p> <p>The training and validation dataset included 24,720 pictures taken from 475 manually May Grunwald-Giemsa (MGG)-stained thin blood smears from the Montpellier University Hospital collection and for a smaller part from the Toulouse University Hospital collection. In Montpellier, the pictures were taken with a Flexcam C1 microscope camera (Leica) attached to a Leica DM 2000 microscope and Leica DF450C microscope camera adapted with a Leica DM2500 microscope at X1000 magnification. Labelling of pictures was performed manually, and then automatically with manual correction with a Computer Visual Annotation Tools (CVAT) free software. Nine categories of labels were used: white blood cells (n=3,338), red blood cells (n=1,887,781), platelets (n=48,520), <em>Trypanosoma brucei </em>(n=2,773), and red blood cells infected by <em>P. falciparum </em>(n=43,545), <em>P. ovale </em>(n=4,651), <em>P. vivax </em>(n=4,115), <em>P. malariae </em>(n=2,849) and <em>Babesia divergens</em> (n=5,142).</p> <p>The test dataset included 4,508 pictures taken from 170 thin blood smears from the same number of patients from the Parasitology laboratories of University Hospitals of Montpellier, Toulouse, Rouen, Lille, Nantes and Saint-Louis in Paris (Table 1). Among these 170 patients, 54 were not infected, including two patients with Howell-Jolly bodies, and 116 were infected with hematozoa. For each patient, between 20 and 30 photos were taken from one thin blood smear with at least one hematozoan parasite per picture for infected patients.</p> <p>Accurate species diagnostic was made by a senior parasitologist, and for recent smears, it was confirmed by specific PCR, either performed locally (Toulouse) or at the Malaria French National Reference Center (Montpellier, Saint Louis, Rouen, Lille, Nantes).</p>
Question Answering auf dem Lehrbuch "Health Information Systems" mit Hilfe von unüberwachtem Training eines Pretrained Transformers
Masterthesis, verwendete Datensätze, Skripte und Ergebnisse des praktischen Teils
Benchmarking Micro2Micro Transformation: An Approach with GNN and VAE
<p>This research ventures into the emerging domain of microservice-to-microservice transformation, a novel concept focused on optimizing existing cloud-native systems. We experiment with a machine learning methodology initially designed for monolith-to-microservices migration, adapting it to the complex microservices landscape, with a specific focus on the train-ticket application.</p>
High Tech and High Touch (HT2): Transforming Patient Engagement Through Portal Technology at the Bedside
ClinicalTrials.gov study NCT02943109. IPD Sharing: YES. Countries: 1. Publications: 3.
Advancing Renal TRANSplant eFficacy and Safety Outcomes With an eveRolimus-based regiMen (TRANSFORM)
ClinicalTrials.gov study NCT01950819. IPD Sharing: UNDECIDED. Countries: 42. Publications: 5.
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.