An Obstacle-Free and Power Efficient Deployment Algorithm for Wireless Sensor Networks

[[abstract]]This paper proposes a robot-deployment algorithm that overcomes unpredicted obstacles and employs full-coverage deployment with a minimal number of sensor nodes. Without the location information, node placement and spiral movement policies are proposed for the robot to deploy sensors efficiently to achieve power conservation and full coverage, while an obstacle surrounding movement policy is proposed to reduce the impacts of an obstacle upon deployment. Simulation results reveal that the proposed robot-deployment algorithm outperforms most existing robot-deployment mechanisms in power conservation and obstacle resistance and therefore achieves a better deployment performance.[[notice]]補正完

Variability of morphology in beat-to-beat photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment

We investigated the beat-to-beat fluctuation of the photoplethysmography (PPG) waveform. The motivation is that morphology variability extracted from the arterial blood pressure (ABP) has been found to correlate with baseline condition and short-term surgical outcome of the patients undergoing liver transplant surgery. Numerous interactions of physiological mechanisms regulating the cardiovascular system could underlie the variability of morphology. We used the unsupervised manifold learning algorithm, Dynamic Diffusion Map, to quantify the multivariate waveform morphological variation. Due to the physical principle of light absorption, PPG waveform signals are more susceptible to artifact and are nominally used only for visual inspection of data quality in clinical medical environment. But on the other hand, the noninvasive, easy-to-use nature of PPG grants a wider range of biomedical application, which inspired us to investigate the variability of morphology information from PPG waveform signal. We developed data analysis techniques to improve the performance and validated with the real-life clinical database

Mechanical regulation of cancer cell apoptosis and autophagy: Roles of bone morphogenetic protein receptor, Smad1/5, and p38 MAPK

AbstractMechanical forces induced by interstitial fluid flow in and surrounding tissues and by blood/lymphatic flow in vessels may modulate cancer cell invasion and metastasis and anticancer drug delivery. Our previous study demonstrated that laminar flow-induced shear stress induces G2/M arrest in tumor cells. However, whether shear stress modulates final cell fate remains unclear. In this study, we investigated the role of flow-induced shear stress in modulating the survival of four human tumor cell lines, i.e., Hep3B hepatocarcinoma cells, MG63 osteosarcoma cells, SCC25 oral squamous carcinoma cells, and A549 carcinomic alveolar basal epithelial cells. Laminar shear stress (LSS) ranging from 0.5 to 12dyn/cm2 induced death of these four tumor cell lines. In contrast to LSS at 0.5dyn/cm2, oscillatory shear stress (OSS) at 0.5±4dyn/cm2 cannot induce cancer cell death. Both LSS and OSS had no effect on human normal hepatocyte, lung epithelial, and endothelial cells. Application of LSS to these four cell lines increased the percentage of cells stained positively for annexin V–FITC, with up-regulations of cleaved caspase-8, -9, and -3, and PARP. In addition, LSS also induced Hep3B cell autophagy, as detected by acidic vesicular organelle formation, LC3B transformation, and p62/SQSTM1 degradation. By transfecting with small interfering RNA, we found that the shear-induced apoptosis and autophagy are mediated by bone morphogenetic protein receptor type (BMPR)-IB, BMPR-specific Smad1 and Smad5, and p38 mitogen-activated protein kinase in Hep3B cells. Our findings provide insights into the molecular mechanisms by which shear stress induces apoptosis and autophagy in tumor cells

Effectiveness and minimum effective dose of app-based mobile health interventions for anxiety and depression symptom reduction: Systematic review and meta-analysis

BACKGROUND: Mobile health (mHealth) apps offer new opportunities to deliver psychological treatments for mental illness in an accessible, private format. The results of several previous systematic reviews support the use of app-based mHealth interventions for anxiety and depression symptom management. However, it remains unclear how much or how long the minimum treatment dose is for an mHealth intervention to be effective. Just-in-time adaptive intervention (JITAI) has been introduced in the mHealth domain to facilitate behavior changes and is positioned to guide the design of mHealth interventions with enhanced adherence and effectiveness. OBJECTIVE: Inspired by the JITAI framework, we conducted a systematic review and meta-analysis to evaluate the dose effectiveness of app-based mHealth interventions for anxiety and depression symptom reduction. METHODS: We conducted a literature search on 7 databases (ie, Ovid MEDLINE, Embase, PsycInfo, Scopus, Cochrane Library (eg, CENTRAL), ScienceDirect, and ClinicalTrials, for publications from January 2012 to April 2020. We included randomized controlled trials (RCTs) evaluating app-based mHealth interventions for anxiety and depression. The study selection and data extraction process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We estimated the pooled effect size using Hedge g and appraised study quality using the revised Cochrane risk-of-bias tool for RCTs. RESULTS: We included 15 studies involving 2627 participants for 18 app-based mHealth interventions. Participants in the intervention groups showed a significant effect on anxiety (Hedge g=-.10, 95% CI -0.14 to -0.06, I2=0%) but not on depression (Hedge g=-.08, 95% CI -0.23 to 0.07, I2=4%). Interventions of at least 7 weeks\u27 duration had larger effect sizes on anxiety symptom reduction. CONCLUSIONS: There is inconclusive evidence for clinical use of app-based mHealth interventions for anxiety and depression at the current stage due to the small to nonsignificant effects of the interventions and study quality concerns. The recommended dose of mHealth interventions and the sustainability of intervention effectiveness remain unclear and require further investigation

Energy Efficiency Improvement and Cost Saving Opportunities for the Pharmaceutical Industry. An ENERGY STAR Guide for Energy and Plant Managers

The U.S. pharmaceutical industry consumes almost $1 billion in energy annually. Energy efficiency improvement is an important way to reduce these costs and to increase predictable earnings, especially in times of high energy price volatility. There are a variety of opportunities available at individual plants in the U.S. pharmaceutical industry to reduce energy consumption in a cost-effective manner. This Energy Guide discusses energy efficiency practices and energy efficient technologies that can be implemented at the component, process, system, and organizational levels. A discussion of the trends, structure, and energy consumption characteristics of the U.S. pharmaceutical industry is provided along with a description of the major process steps in the pharmaceutical manufacturing process. Expected savings in energy and energy-related costs are given for many energy efficiency measures, based on case study data from real-world applications in pharmaceutical and related facilities worldwide. Typical measure payback periods and references to further information in the technical literature are also provided, when available. The information in this Energy Guide is intended to help energy and plant managers reduce energy consumption in a cost-effective manner while meeting regulatory requirements and maintaining the quality of products manufactured. At individual plants, further research on the economics of the measures?as well as their applicability to different production practices?is needed to assess potential implementation of selected technologies

Strategies for Preventing Drug Recidivism Cycle in Taiwan

Drug abuse is currently a worldwide problem and Taiwan is no exception. Drug abuse is a disease that must be treated on the basis of evidence (United Nations Office on Drugs and Crime 2007; World Health Organisation 2004). In order to reduce the damage caused by drug abuse to the nation, society and people, the government not only developed two anti-drug strategies - that of supply eradication and demand reduction - but since May 1994, has mobilised relevant government departments to take assertive action. Some of the actions include law enforcement enhancement, anti-drug enforcement and drug rehabilitation utilisation. In 2005, new anti-drug programs, such as the sterile needle exchange program and substitution therapy program, were also introduced. The cities implementing the Harm Reduction Program (HR Program) showed lower HIV infection rates in comparison to others without the HR Program. The income and employment conditions of drug addicted patients receiving Methadone Maintenance Treatment have been improved. The future drug policies in Taiwan will focus on drug rehabilitation (treatment), anti-drug actions (prevention) and law enforcement (punishment). The educational system, community recovery and aftercare for drug addicts will also be indispensable (WHO/UNODC/UNAIDS 2004)