Biomedical and Health Sciences
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We propose AcuGRL, a graph representation learning-based framework that models the relationships between acupoints and disease phenotypes as a heterogeneous graph. This framework incorporates a domain knowledge-guided scheme to capture both the structural and semantic features of the network, generating effective embeddings for downstream tasks. Additionally, we integrate micro-level genetic targets with macro-level disease phenotypes to further enhance network connectivity and provide richer contextual information.
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The proper evaluation of food freshness is critical to ensure safety, quality along with customer satisfaction in the food industry. While numerous datasets exists for individual food items,a unified and comprehensive dataset which encompass diversified food categories remained as a significant gap in research. This research presented UC-FCD, a novel dataset designed to address this gap.
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101 Views
We developed a control framework for an ankle-powered prosthesis that is based on a neuromusculoskeletal model driven by muscle synergies, aimed at mimicking human motor control strategies during cyclic movements.Refer to recent publication for more details on the research goals and methodology [1]. The personalized muscle synergy model computes muscle excitations at each timestamp of every trial using sensory information: gait phase was calculated using real-time ground reaction forces information, speed information was measured from the instrumented treadmill.In this study, both the gait
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28 Views
This dataset includes stress relaxation and performance test results conducted on a steerable catheter to evaluate and validate its viscoelastic properties using a quasilinear viscoelastic (QLV) beam model. Both datasets consist of raw bending moment measurements from a load cell and processed curvature data derived from stereo images.
The relaxation test data provides insights into viscoelastic behavior by illustrating the relationship between moment and curvature across multiple loading levels. This data is used to identify the parameters of the QLV beam model.
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This dataset includes long-term symptom prevalence data for 27 physical and mental health symptoms associated with Long COVID, extracted from 136 studies spanning up to three years. Key symptoms include fatigue, joint pain, myalgia, respiratory issues (dyspnea, cough), sensory impairments (anosmia, ageusia), neurological symptoms (brain fog), and mental health challenges (anxiety, depression, insomnia).
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74 Views
Background: Vascular grafts are mainly composed of synthetic materials, but are prone to thrombosis and intimal hyperplasia at small diameters. Decellularized plant scaffolds have emerged that provide promising alternatives for tissue engineering. We previously developed robust, endothelialized small-diameter vessels from decellularized leatherleaf viburnum. This is the first study to precondition and analyze plant-based vessels under physiological fluid flow and pressure waveforms.
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132 Views
All the healthcare facilites in this dataset were collected from the MOH 2018 list of Uganda healthcare facilites (https://library.health.go.ug/sites/default/files/resources/National%20Health%20Facility%20MasterLlist%202017.pdf) Additional features were scraped using the Google Maps API and additionally from some of the websites of the healthcare facilities themselves.
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In order to train a neural network to predict bone drilling force, we build this dataset. The force data in this dataset come from two sources. The first source is the physics model-calculated force data obtained based on physical cutting laws validated by researchers in this field. Since this cutting process can be simulated by programs, the data volume is almost unlimited. The second source is sensor-recorded force data, which reflect the actual bone drill force imposed on the drill bit during operations but are limited by the utilized equipment and the complexity of experiments.
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129 Views
This dataset provides a comprehensive collection of maternal health data, focusing on key health indicators throughout pregnancy. It includes essential details such as the mother’s age, gravida (number of pregnancies), weight, height, blood pressure, gestational age, and fetal health status. In addition to these primary metrics, the dataset captures important medical test results, including anemia, blood sugar levels, and fetal heart rate, providing a thorough overview of both maternal and fetal well-being.
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115 Views