N, P Dual-Doped Carbons as Metal-Free Catalysts for Hydrogenation.

The activation of molecule hydrogen (H) by metal-free catalysts is always a challenge in the field of catalysis. Herein, a series of N, P dual-doped carbon catalysts were constructed by the pyrolysis of chitosan and phytic acid and utilized as metal-free catalysts for the hydrogenation of nitrobenzene. The characterization indicated that the doping of phosphorus atoms not only formed the species with catalytic activity for hydrogenation reaction but also promoted the doping of N.

Probabilistic Estimation of Cadence and Walking Speed From Floor Vibrations.

Objective: This research aims to extract human gait parameters from floor vibrations. The proposed approach provides an innovative methodology on occupant activity, contributing to a broader understanding of how human movements interact within their built environment.

Methods And Procedures: A multilevel probabilistic model was developed to estimate cadence and walking speed through the analysis of floor vibrations induced by walking.

Probabilistic detection of impacts using the PFEEL algorithm with a Gaussian Process Regression Model.

Methods for identifying human activity have a wide range of potential applications, including security, event time detection, intelligent building environments, and human health. Current methodologies typically rely on either wave propagation or structural dynamics principles. However, force-based methods, such as the probabilistic force estimation and event localization algorithm (PFEEL), offer advantages over wave propagation methods by avoiding challenges such as multi-path fading.

Probabilistic Force Estimation and Event Localization (PFEEL) algorithm.

Localization of human activity using floor vibrations has gained attention in recent years. In human health technologies, floor vibrations have been recently used to estimate gait parameters to predict a patients' health status. Various methodologies such as using the characteristics of wave traveling (algorithms based on time of arrival) or the properties of structures (Force Estimation and Event Localization, FEEL, algorithm) have been investigated to localize the impact, fall, or step events.

Correction: Liu et al. Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM. 2019, , 3720.

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Walking speed measurement technology: A review.

Purpose Of Review: This article presents an overview of the main technologies used to estimate gait parameters, focusing on walking speed (WS).

Recent Findings: New wearable and environmental technologies to estimate WS have been developed in the last five years. Wearable technologies refer to sensors attached to parts of the patient's body that capture the kinematics during walking.

Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM.

Human falls are the premier cause of fatal and nonfatal injuries among older adults. The health outcome of a fall event is largely dependent on rapid response and rescue of the fallen elder. Being able to provide an accurate and fast fall detection will dramatically improve the health outcomes of the older population and reduce the associated healthcare cost after a fall.

Energy-Efficient Heterogeneous Wireless Sensor Deployment with Multiple Objectives for Structural Health Monitoring.

Heterogeneous wireless sensor networks (HWSNs) are widely adopted in structural health monitoring systems due to their potential for implementing sophisticated algorithms by integrating a diverse set of devices and improving a network's sensing performance. However, deploying such a HWSN is still in a challenge due to the heterogeneous nature of the data and the energy constraints of the network. To respond to these challenges, an optimal deployment framework in terms of both modal information quality and energy consumption is proposed in this study.