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Cardiovascular disease (CVD) is the single leading cause of global mortality and is projected to remain so. Cardiac arrhythmia is a very common type of CVD and may indicate an increased risk of stroke or sudden cardiac death. The ECG is the most widely adopted clinical tool to diagnose and assess the risk of arrhythmia. ECGs measure and display the(More)
Sensitive to apoptosis gene (SAG) is a novel RING finger protein that has been shown to be involved in protection against apoptotic cell death induced by oxidative stress in various cell types. As SAG has been previously shown to be expressed in the heart, we assessed its role in cardiac myocytes exposed to ischaemic stress. SAG expression was enhanced by(More)
Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing(More)
Artificial neural networks (ANNs) are a promising machine learning technique in classifying non-linear electrocardiogram (ECG) signals and recognizing abnormal patterns suggesting risks of cardiovascular diseases (CVDs). In this paper, we propose a new reusable neuron architecture (RNA) enabling a performance-efficient and cost-effective silicon(More)
To date, cardiovascular disease (CVD) is the leading cause of global death. The Electrocardiogram (ECG) is the most widely adopted clinical tool that measures the electrical activities of the heart from the body surface. However, heart rhythm irregularities cannot always be detected on a standard resting ECG machine, since they may not occur during an(More)
Continued rapid progress in the development of embedded motion sensing enables wearable devices that provide fundamental advances in the capability to monitor and classify human motion, detect movement disorders, and estimate energy expenditure. With this progress, it is becoming possible to provide, for the first time, evaluation of outcomes of(More)
Real-time, fine-grained power consumption information enables energy optimization and adaptation for operating systems and applications. Due to the high cost associated with dedicated power sensors, however, most computers do not have the ability to measure disaggregated power consumption at a component or subsystem level. We present DiPART (Disaggregated(More)
The aim of this study was to identify an effective flavonoid that could improve the intracellular accumulation of ritonavir in human brain-microvascular endothelial cells (HBMECs). An in vivo experiment on Sprague-Dawley rats was then designed to further determine the flavonoid's impact on the pharmacokinetics and tissue distribution of ritonavir. In the(More)
Peptide toxins from venomous animals are natural resources with diverse biological functions and therapeutic potential towards human diseases. For venomous scorpions, many valuable peptide toxins have been discovered from Buthidae scorpions, but few works were done about non-buthidae scorpions. Here, we cloned and characterized the first disulfide-bridged(More)
Farmland monitoring is of great significance in precision agriculture. In this paper, we design a wireless sensor network to monitor farmland information, including air temperature and humidity, light intensity, soil moisture, soil PH value, and the growth of crops. We carry out an experiment in the cornfield of Hongzehu farm. It shows that the monitoring(More)