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4,578 results for “Assistance”
Effect of hip abduction assistance on metabolic cost and balance during human walking
<p>The use of wearable robots to provide walking assistance has rapidly grown over the last decade, with significant advances made in robot design and control methods toward reducing physical effort while performing an activity. The reduction in the walking effort has mainly been achieved by assisting forward progression in the sagittal plane. Human gait, however, is a complex movement that combines motions in three planes, not only the sagittal but also the transverse and frontal planes. In the frontal plane, the hip joint plays a key role in gait, including balance. However, wearable robots targeting this motion have rarely been investigated. In this study, we developed a hip abduction assistance wearable robot by formulating the hypothesis that assistance that mimics the biological hip abduction moment or power could reduce the metabolic cost of walking and affect the dynamic balance. We found that hip abduction assistance with a biological moment second peak mimic profile reduced the metabolic cost of walking by 11.6% compared to the normal walking condition (p=0.009). The assistance also influenced balance-related parameters, including the margin of stability. Hip abduction assistance influenced the center-of-mass movement in the mediolateral direction. When the robot assistance was applied as the center of mass moved toward the opposite leg, the assistance replaced some of the efforts that would have otherwise been provided by a human. This indicates that hip abduction assistance can reduce physical effort during human walking while influencing balance.</p>
Data from: Deep learning-assisted near-Earth asteroid tracking in astronomical images
<p>This repository is the data release of our paper <em>Deep learning-assisted near-Earth asteroid tracking in astronomical images</em>. There are two categories in this repository:</p> <ul> <li>Simulated training dataset for training the star segmentation network. </li> </ul> <p>The dataset consists of two folders: image (grayscale images) and mask (binary images). The size of each image is 256*256.</p> <ul> <li>Example data for testing asteroid tracking algorithm.<br><br></li> </ul> <p>If you find this work useful, please cite our paper:</p> <div> <div>@article{du2024ASR,</div> <div>title = {Deep learning-assisted near-Earth asteroid tracking in astronomical images},</div> <div>journal = {Advances in Space Research},</div> <div>volume = {73},</div> <div>number = {10},</div> <div>pages = {5349-5362},</div> <div>year = {2024},</div> <div>issn = {0273-1177},</div> <div>doi = {https://doi.org/10.1016/j.asr.2024.02.048},</div> <div>url = {https://www.sciencedirect.com/science/article/pii/S0273117724001911},</div> <div>author = {Zhenhong Du and Hai Jiang and Xu Yang and Hao-Wen Cheng and Jing Liu},</div> <div>keywords = {Near-Earth asteroid, Deep learning, Convolutional neural network, Faint object extraction, Moving object linking},</div> <div>}</div> </div>
SMART: Spatial transcriptomics deconvolution using marker-gene-assisted topic model
<p>Source code and simulated datasets used in manuscript "SMART: Spatial transcriptomics deconvolution using marker-gene-assisted topic model"</p>
USPTO-LLM: A Large Language Model-Assisted Information-enriched Chemical Reaction Dataset
<p>USPTO-LLM is an <strong>information-enriched chemical reaction dataset</strong> that provides more side information (reaction conditions and reaction steps division) for developing new reaction prediction and retrosynthesis methods and inspires new problems, such as reaction condition prediction. It comprises over <strong>247K chemical reactions</strong> extracted from the patent documents of USPTO (United States Patent and Trademark Office), encompassing abundant information on reaction conditions. </p> <p>We employ large language models to expedite the data collection procedures automatically with a reliable quality control process. The extracted chemical reactions are organized as <strong>heterogeneous directed graphs</strong>, allowing us to formulate a series of prediction tasks, such as reaction prediction, retrosynthesis, and reaction condition prediction, in a unified graph-filling framework.</p>
Machine Assisted Translation of Wikipedia Articles into Low Resource Languages
<p><strong>Wikipedia is the largest encyclopedia ever assembled with the vision of enabling every human being to freely share in the sum of all knowledge. Wikipedia currently has a total of more than six million articles and over 17 billion words in its English edition. Unfortunately, millions of people cannot access this resource because it’s not available in their language. For instance, at the moment there are only 218 Tigrinya Wikipedia and 15,018 Amharic Wikipedia articles.</strong></p> <p><strong>In this project, we investigate the problem of translating Wikipedia articles from a high resource language into low resource languages using human-in-the-loop MT systems. In particular, we investigate different approaches to translate a sample of English Wikipedia articles into Tigrinya and Amharic. Currently, this repository contains 100k English Wikipeida abstracts translated using Lesan (https://lesan.ai) into Amharic and Tigrinya.</strong><br> <br> </p> <p><strong>Structure of data directory:</strong></p> <p><strong>data<br> ├── human<br> └── mt<br> ├── google<br> ├── lesan<br> │ ├── am.txt<br> │ ├── en.txt<br> │ └── ti.txt<br> └── microsoft</strong><br> </p>
Vibration assisted drilling (VAD) application to the manufactured maraging steel X3NiCoMoTi18-9-5 (1.2709) and aluminium AlSi10Mg (EN AC-43000) parts
<p>Repository containing data from vibration assisted drilling (VAD) experiments on steel and Aluminum 3D powderbed manufactured parts.</p> <p>Please refer to README.MD (or .PDF), which contains a brief description of the chosen materials, parts and tools An explanation of the data aquisition and processing methods, together with the used nomenclature is given as well.</p>
Performance investigation of an ejector-assisted transcritical CO2 heat pump with brazed plate tri-partite gas cooler for space heating and hot water production
<p>The carbon dioxide (CO<sub>2</sub>) heat pump water heater is recognized as a potential technology for the production of domestic hot water (DHW) and space heating (SH). In this paper, the performance of a transcritical CO<sub>2</sub> heat pump water heater with a tri-partite gas cooler is discussed using a numerical model. The heat pump operates in three modes: (1) DHW mode, (2) SH mode, and (3) DHW+SH mode, which provides space heating at 35 °C and hot water up to 70 °C. The simulation model is validated with the experimental data. The effects of different parameters on system performance are investigated, and the coefficient of performance (COP) of the system under different operating conditions is evaluated. The results show that higher heat sink outlet temperatures lower the COP and increase SH/DHW-Ratio for the investigated cases. The maximum COP is investigated for various heat loads by continuous high-pressure (HP) modulation, reaching highest values at 50 % to 60 % of maximum heat load. The SH/DHW-Ratio is investigated for the presented simulation cases in DHW+SH mode, reaching 0.68 to 1.06 for different heat loads.</p>
Machine Learning Assisted SSH Keys Extraction From The Heap Dump
<p>This dataset contains heap dump of OpenSSH that contains session keys.</p> <p>On the performance test data, we also include the PCAP file that contains the encrypted SSH network traffic. With the correct session keys, it can be decrypted.</p>
Running the validation assistant tool on pesticide dossiers in IUCLID
<p>Before submitting a dossier, <strong>applicants</strong> are recommended to use the Validation Assistant tool to check the dossier is technically complete. It is important to resolve all validation assistant quality warnings as this will support the Admissibility Check of the RMS/EMS. The <strong>RMS/EMS</strong> should also run the validation assistant report before declaring the admissibility of a dossier to make sure the dossier is complete.</p> <p>If the report shows a business rule failure (anything starting with BR, e.g. BR_PPP_033) this will prevent the applicant from successfully submitting the dossier and therefore must be resolved.</p> <p>This demonstration is supporting RMS/EMS and applicants on how to run the validation assistant tool and extract the report. </p>
The effects of robotic assistance on upper limb spatial muscle synergies in healthy people during planar upper-limb training
<p>This is the minimal dataset underlying the paper:</p> <p>"The effects of robotic assistance on upper limb spatial muscle synergies in healthy people during planar upper-limb training"</p>
Magnetic Soft Robotic Bladder for Assisted Urination
<p>The poor contractility of the detrusor muscle in underactive bladders (UABs) fails to increase the pressure inside the UAB, leading to strenuous and incomplete urination. However, existing therapeutic strategies by modulating/repairing detrusor muscles, e.g., neurostimulation and regenerative medicine, still have low efficacy and/or adverse effects. Here, we present an implantable magnetic soft robotic bladder (MRB) that can directly apply mechanical compression to the UAB to assist urination. Composed of a biocompatible elastomer composite with optimized magnetic domains, the MRB enables on-demand contraction of the UAB when actuated by magnetic fields. A representative MRB for an UAB in a porcine model is demonstrated and MRB-assisted urination is validated by in situ computed tomography imaging after 14-day implantation. The urodynamic tests show a series of successful urination with a high pressure increase and fast urine flow. Our work paves the way for developing MRB to assist urination for humans with UABs.</p>
Figure 3 in Comparative effectiveness of EDTA and citric acid assisted phytoremediation of Ni contaminated soil by using canola (Brassica napus)
Figure 3. The role of EDTA and citric acid on (a) leaf turgor potential and (b) water use efficiency, (c) potassium and (d) sodium at vegetative stage for phytoremediation of Ni by using canola plant.
Figure 4 in Comparative effectiveness of EDTA and citric acid assisted phytoremediation of Ni contaminated soil by using canola (Brassica napus)
Figure 4. The role of EDTA and citric acid on (a) SOD and (b) CAT, (c) POD, (d) total free amino acid, (e) total soluble proteins, (f) total soluble sugars at vegetative stage for phytoremediation of Ni by using canola plant and the role of EDTA and citric acid on Ni contents (mg/ pot) in above ground biomass (g) at vegetative stage for phytoremediation of Ni by using canola.
Figure 1 in Comparative effectiveness of EDTA and citric acid assisted phytoremediation of Ni contaminated soil by using canola (Brassica napus)
Figure 1. The role of EDTA and CA on (a) plant height and (b) shoot fresh weight at the vegetative stage of two canola cultivars (Con-II and Oscar, respectively) in control and Ni treatment and the role of EDTA and citric acid on (c) dry weight and (d) photosynthetic rate at vegetative stage for phytoremediation of Ni by using canola plant.
BRAIN Journal-New Computer Assisted Diagnostic to Detect Alzheimer Disease-Figure 19. Accuracy of classification using the three methods: KNN, SVM and our method for MCI subjects
<p>Whatever the patient condition, Normal, MCI or AD, our method has provided us with better results. Advocate Example precision for Normal Patients was found 96% as opposed to 88% for the SVM method and 84% for KNN. For MCI patients was found 88% as opposed to 80% for the SVM method and 72% for KNN. Also for AD patients were found 92% as opposed to 88% for the SVM method and 80% for KNN. Our classification method gave us the best results, finding overall accuracy of 92% as opposed to 84% for the SVM method and 78.66% for KNN. </p>
BRAIN Journal-New Computer Assisted Diagnostic to Detect Alzheimer Disease-Figure 20. The accuracy of classification using the three methods, KNN, SVM and our method, for AD subjects
<p>Whatever the patient condition, Normal, MCI or AD, our method has provided us with better results. Advocate Example precision for Normal Patients was found 96% as opposed to 88% for the SVM method and 84% for KNN. For MCI patients was found 88% as opposed to 80% for the SVM method and 72% for KNN. Also for AD patients were found 92% as opposed to 88% for the SVM method and 80% for KNN. Our classification method gave us the best results, finding overall accuracy of 92% as opposed to 84% for the SVM method and 78.66% for KNN. </p>
BRAIN Journal-New Computer Assisted Diagnostic to Detect Alzheimer Disease-Figure 18. Accuracy of classification using the three methods, KNN, SVM and our method, for normal subjects
<p>We present three figures representing the accuracy of the classification using the three methods, KNN, SVM and our method for normal, MCI and Alzheimer subjects. </p>
BRAIN Journal-New Computer Assisted Diagnostic to Detect Alzheimer Disease-Figure 17. The results of calculating the Hausdorff distances
<p>The results of calculating the Hausdorff distances, Dice, PSNR, MSSD for the four methods<br> (Caselles Chan & Vese, Lanktom, our method) and the ground truth about a Normal subject following the<br> Corpus Calosum segmentation. </p> <p> </p>
BRAIN Journal-New Computer Assisted Diagnostic to Detect Alzheimer Disease-Figure 16. Results of calculating the Hausdorff distances
<p>Results of calculating the Hausdorff distances, Dice, PSNR, MSSD between the four methods (Caselles Chan & Vese, Lanktom, our method) and the ground truth about a subject Normal following segmentation of the Corpus Calosum.</p>
BRAIN Journal-New Computer Assisted Diagnostic to Detect Alzheimer Disease-Figure 15. The results of calculating the Hausdorff distances
<p>The results of calculating the Hausdorff distances, Dice, PSNR, MSSD for the four methods (Caselles Chan & Vese, Lanktom, our method) and the ground truth about a Normal subject following the Corpus Calosum segmentation.</p>
ScienceDex guides
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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.