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83 results for “pattern recognition”
Human Leishmaniasis: Antigen Recognition Pattern and Study of New Potential Biomarkers
ClinicalTrials.gov study NCT06307171. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Mycobacterium tuberculosis tRNA induces IL-12p70 via synergistic activation of pattern recognition receptors within a cell network.
GEO Series GSE110325. Homo sapiens. 36 samples. Type: Expression profiling by high throughput sequencing.
Human monocyte subsets are transcriptionally and functionally altered in aging in response to pattern recognition receptor agonists [InVitro]
GEO Series GSE94496. Homo sapiens. 208 samples. Type: Expression profiling by array.
Bacterial pattern recognition in C. elegans by the nuclear hormone receptor NHR-86/HNF4
GEO Series GSE202258. Caenorhabditis elegans. 30 samples. Type: Expression profiling by high throughput sequencing.
Global RNA recognition patterns of post‐transcriptional regulators Hfq and CsrA revealed by UV crosslinking in vivo
GEO Series GSE74425. Salmonella enterica subsp. enterica serovar Typhimurium str. SL1344. 12 samples. Type: Expression profiling by high throughput sequencing.
Human monocyte subsets are transcriptionally and functionally altered in aging in response to pattern recognition receptor agonists
GEO Series GSE94499. Homo sapiens. 262 samples. Type: Expression profiling by array.
EMG database - EMG Pattern Recognition For Prosthesis Control
<p>This database is one of the results of the MSc dissertation of Adriano de Oliveira Andrade (<a href="http://orcid.org/0000-0002-5689-6606">http://orcid.org/0000-0002-5689-6606</a>)</p> <p>The experimental protocol is fully described in the MSc dissertation (Chapter 5 - pp. 56-60).</p> <p>The avaliable program in R (<a href="https://zenodo.org/api/files/e3190c64-2f7d-4fc6-a070-b0cb2b412156/Import_EMG_Files.R">Import_EMG_Files.R</a>) can be used to import and visualize the EMG data available (<a href="https://zenodo.org/api/files/e3190c64-2f7d-4fc6-a070-b0cb2b412156/EMG-DATA-MSc-AOA.zip?versionId=5216f27e-497a-4e31-8690-a5d5e3b46015">EMG-DATA-MSc-AOA.zip</a>). The EMG data are in in the folders "Isometricos" and "Isotonicos".</p> <p> </p> <p><strong>MSc dissertation avaiable @</strong></p> <p>[1] Andrade A de O. Metodologia para classificação de sinais EMG no controle de membros artificiais. [manuscrito]. 2000. Uberlândia: Universidade Federal de Uberlândia. doi: <a href="http://doi.org/10.13140/RG.2.2.17314.02242.">https://doi.org/10.13140/RG.2.2.17314.02242.</a></p> <p>[2] http://search.ebscohost.com/login.aspx?direct=true&db=cat08055a&AN=sapere.000058379&lang=pt-br&site=eds-live</p> <p><strong>Abstract - EMG Pattern Recognition For Prosthesis Control</strong></p> <p>One of the major challenges for prosthesis development is to produce devices which mimic their natural counterparts. In general, articial limbs don't have proper feedback by which the user can assess the status of the prosthesis and the control is very unnatural. Preferably, a subconscious control is desired. Myoelectric control has been widely used as an alternative strategy designed for easier control. However, there is still a lot do be done in order to achieve articial limbs as dextrous as human limbs. In an attempt to contribute to the researches towards better artical limbs, it has been developed an EMG processing system, capable of generate input control to a four degrees of freedom prosthesis. Two major muscle groups (biceps and triceps) were used as source of electromyograc signals, which were discriminated into four different classes: elbow exion, elbow extension, wrist pronation and wrist supination. Those patterns were classied by an articial neural network, which received as inputs the EMG signal features extracted by an autoregressive model. The minimum number of pairs of electrodes and their best positioning for detection, processing and classication were also investigated. To do so, five pairs of electrodes (two on the biceps - long head (B1) and short head (B2) - and three on the triceps - long head (T1), medium head (T2) and lateral head(T3) and one pair of electrodes (on plexo brachial) configuration were considered. Isometric and isotonic contractions were analyzed for each one of those two configurations. The EMG signals were studied in several combinations for each type of contraction. The results show that the configurations using two pairs of electrodes (positioned on B2 and T1) and three pairs of electrodes (positioned on B2, T1 and T2 or B2, T1 and T3), provided accuracy as good as 100%, for the EMG pattern recognition process.</p> <p><strong>Resumo em Português - Metodologia para Classicação de Sinais EMG no Controle de Membros Artificiais</strong></p> <p>Um dos grandes desafios atuais das pesquisas envolvendo o aperfeiçoamento de membros artificiais, é que esses possam ser controlados de maneira mais natural possível pelos pacientes. Neste sentido, os processos envolvendo a aquisição e a manipulação das informações de controle provenientes do paciente, têm merecido especial atenção. Dentre as diversas técnicas de controle possíveis, uma das que tem alcançado melhores resultados utiliza a atividade eletromiográfica resultante de contrações voluntárias de determinados grupos musculares. Numa tentativa de contribuir para aquelas pesquisas, foi desenvolvido um sistema de processamento de sinais eletromiográficos (EMG), capaz de fornecer entradas de controle para uma prótese com quatro graus de liberdade. Para tal, sinais EMG provenientes dos grupos musculares tríceps e bíceps foram classificados em quatro padrões distintos: flexão e extensão do cotovelo, pronação e supinação do punho. A classificação dos padrões foi feita através de uma rede neural artifical que recebe como entrada as características dos sinais eletromiográficos, extraídas através de um modelo autoregressivo. Outro objetivo desta pesquisa foi buscar o número mínimo de pares de eletrodos e os sítios mais adequados para a detecção, processamento e classificação satisfatória dos movimentos executados. Foram feitas análises considerando 5 pares de eletrodos, sendo dois sobre o bíceps - na cabeça longa (B1) e na cabeça curta (B2) - e três sobre o tríceps - na cabeça longa (T1), na cabeça medial (T2) e na cabeça lateral (T3); e um par de eletrodos sobre o plexo braquial. Os experimentos foram realizados considerando-se contrações isométricas e isotônicas. Aqueles sinais foram analisados em diversas combinações, para cada tipo de contração, numa tentativa de se encontrar aquela que apresentasse melhores resultados. Os resultados mostraram que as combinações envolvendo o uso de dois pares de eletrodos posicionados sobre os sítios B2 e T1; e três pares de eletrodos posicionados sobre os sítios B2, T1 e T2 ou B2, T1 e T3 apresentaram melhores performances, com taxas de acerto de até 100%.</p>
Recognition and Management of Early Mobilization in ICUs : Practice Patterns in China
ClinicalTrials.gov study NCT02804516. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Regulation of Pattern Recognition Receptors by the Apolipoprotein A-I Mimetic Peptide 4F
GEO Series GSE36933. Homo sapiens. 16 samples. Type: Expression profiling by array.
Effect of pattern recognition receptor LE (PGRP-LE) overexpression in Dredd mutant Drosophila enterocytes
GEO Series GSE278928. Drosophila melanogaster. 10 samples. Type: Expression profiling by high throughput sequencing.
Expression of the RNA recognition motif protein RBP10 promotes a bloodstream-form transcript pattern in Trypanosoma brucei
GEO Series GSE29176. Trypanosoma brucei. 11 samples. Type: Expression profiling by array.
RNA-seq analysis of immune responses from human blood monocyte dendritic cells from 3 donors stimulated with 5 pattern recognition receptor (PRR) ligands along with their pairwise and triplet combinat
GEO Series GSE134874. Homo sapiens. 242 samples. Type: Expression profiling by high throughput sequencing.
A soybean pattern recognition receptor conferring broad-spectrum pathogen and pest resistance regulates expression of several NLR receptor proteins
GEO Series GSE226254. Glycine max. 36 samples. Type: Expression profiling by high throughput sequencing.
Microglial pattern recognition via IL-33 promotes synaptic refinement in developing corticothalamic circuits in mice (scRNAseq)
GEO Series GSE218427. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
ATAC-seq analysis of immune responses from bone marrow derived dendritic cells stimulated with 7 pattern recognition receptor (PRR) ligands along with their pairwise and triplet combinations
GEO Series GSE134867. Mus musculus. 36 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Ping Flood Attack Pattern Recognition on Internet of Things Network Dataset
<p><strong>Ping Flood Attack Pattern Recognition using K-Means Algorithm in Internet of Things (IoT) Network</strong> <br> <em>status: on repository</em></p> <p>Abstract — This work investigates ping flood attack pattern recognition on Internet of Things (IoT) network. Experiments are conducted on WiFi communication with three different scenarios: normal traffic, attack traffic, and normal-attack combination traffic to create normal dataset, attack dataset, and normal attack (combined) dataset. The datasets are grouped into two clusters i.e.: (i) normal cluster and (ii) attack cluster. Clustering results using implemented K-Means algorithm show the average number of packets on the cluster of attack in total is 95,931 packets, and the average packets on normal cluster in total is 4,068 packets.</p> <p>Accuracy level of the clustering results then is calculated using confusion matrix equation. Based on the confusion matrix calculation, accuracy of clustering using implemented K-Means algorithm was 99.94%. The true negative rate reaches up to 98.62%, true positive rate is 100%, the false negative rate is 0%, and the false positive rate reaches 1.38%.</p>
Microglial pattern recognition via IL-33 promotes synaptic refinement in developing corticothalamic circuits in mice (ATACseq)
GEO Series GSE218424. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Microglial pattern recognition via IL-33 promotes synaptic refinement in developing corticothalamic circuits in mice (FOS ChIP-seq)
GEO Series GSE218425. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Microglial pattern recognition via IL-33 promotes synaptic refinement in developing corticothalamic circuits in mice (bulk RNA-seq)
GEO Series GSE218369. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Gene expression study reveals compromised Pattern Recognition Receptors and Interferon Signaling in fullterm Low birth Weight newborns
GEO Series GSE29807. Homo sapiens. 12 samples. Type: Expression profiling by array.
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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.