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185 results for “Health Monitoring”
Influence of gonadectomy on muscle health in micro- and partial-gravity environments in rats (Estrous Cycle Monitoring)
Gonadal hormones, such as testosterone and estradiol, modulate muscle size and strength in males and females. However, the influence of sex hormones on muscle strength in micro- and partial-gravity environments (e.g., the Moon or Mars) is not fully understood. The purpose of this study was to determine the influence of gonadectomy (castration/ovariectomy) on progression of muscle atrophy in both micro- and partial-gravity environments in male and female rats. Male and female Fischer rats (n equals 120) underwent castration/ovariectomy (CAST/OVX) or sham surgery (SHAM) at 11 weeks of age. After 2 weeks of recovery, rats were exposed to hindlimb unloading (0g), partial weight bearing at 40% of normal loading (0.4g, Martian gravity), or normal loading (1.0g) for 28 days. In males, CAST did not exacerbate body weight loss or other metrics of musculoskeletal health. In females, OVX animals tended to have greater body weight loss and greater gastrocnemius loss. Within 7 days of exposure to either microgravity or partial gravity, females had detectable changes to estrous cycle, with greater time spent in low-estradiol phases diestrus and metestrus (∼47% in 1g vs. 58% in 0g and 72% in 0.4g animals, P equals 0.005). We conclude that in males testosterone deficiency at the initiation of unloading has little effect on the trajectory of muscle loss. In females, initial low estradiol status may result in greater musculoskeletal losses. This study derives results from Estrous Cycle Monitoring (Cytology).
Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics
This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.
Rotor health monitoring combining spin tests and data-driven anomaly detection methods
Health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications. These efforts are focused on developing high temperature, wireless, low cost, and durable products. In an effort to address technical issues concerning health monitoring, this article considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating turbine engine-like-disk to detect the disk faults and assess its structural integrity. The experimental results composed at a range of rotational speeds from tests conducted at the NASA Glenn Research Center’s Rotordynamics Laboratory are evaluated and integrated into multiple data-driven anomaly detection techniques to identify faults and anomalies in the disk. In summary, this study presents a select evaluation of online health monitoring of a rotating disk using high caliber capacitive sensors and demonstrates the capability of the in-house spin system.
Propulsion Health Monitoring of a Turbine Engine Disk using Spin Test Data
On line detection techniques to monitor the health of rotating engine components are becoming increasingly attractive options to aircraft engine companies in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenging feature to easily implement, especially, in the presence of scattered loading conditions, crack size, component geometry and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini cracks before any catastrophic event occurs. These techniques go further to evaluate materials' discontinuities and other anomalies that have grown to the level of critical defects which can lead to failure. Generally, health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications [1-5]. These efforts are focused on developing high temperature, wireless, low cost and durable products.Therefore, in an effort to address the technical issues concerning health monitoring of a rotor disk, this paper considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating engine-like-disk-to predict the disk faults and assess its structural integrity. The experimental results collected at a range of rotational speeds from tests conducted at the NASA Glenn Research Center's Rotordynamics Laboratory will be evaluated using multiple data-driven anomaly detection techniques [6-9] to identify anomalies in the disk. This study is expected to present a select evaluation of online health monitoring of a rotating disk using these high caliber sensors and test the capability of the in-house spin system.
Dataset for building the dashboard for monitoring oral health services in Primary Health Care in Brazil
<p>It is an unprecedented digital technology that provides indicators of oral health, calculated using data from the Sistema de Informação em Saúde para a Atenção Básica (SISAB) from 2016 onwards, at the municipal, state, regional, and national disaggregation levels. The monitoring dashboard was set up in the following stages: the creation of spreadsheets for mapping the data source; configuration files for the extracted SISAB data to calculate the indicators; scripts to orchestrate automated extraction; storage of calculated indicators in an analytical database hosted on Google Cloud; and double validation (manual and automated). Within the panel, accessible via URL, the 53 previously validated indicators from the dimensions of "Provision and Management of Oral Health Services" were made available for the free access in graphs, maps, and tables that allow for geographic, temporal, population size, and Human Development Index comparisons. The dashboard proves to be a valuable tool for the qualification and use of SISAB data. Automating information and its periodic dissemination will promote the culture of monitoring, making it a daily practice for oral health professionals, reducing the fragmentation of health information, and expanding the evaluative capacity of managers and healthcare professionals in Primary Health Care.</p> <p>Access the dashboard: <a href="https://lookerstudio.google.com/u/0/reporting/86c09403-f4a0-4625-ad1f-239daa77f6a2/page/p_jdtr4yn74c">Dashboard_oral health</a></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
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DANDI Archive for NWB datasets
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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.