A microprocessor-based dual slope phase meter

A dual-slope phase meter has been designed and tested to investigate its limitations. The design does not require a time standard; it offers good resolution, relative simplicity, low sensitivity to changes of internal circuit parameters, and microprocessor compatibility. The idea is based on a single-slope approach demonstrated by W.T. Davis (1986), but several disadvantages of the system have been eliminated. The main problem with the system, relating to the error due to the finite time of sampling, is discussed     

Electrochemical Formation of Polypyrrole-carboxymethylcellulose Conducting Polymer Composite Films

1.IntroductionConjugated polymers such as polypyrrole(PPY),polyaniline,polythiophene and polyphenylene etc.whichexhibit significant level of electrical conductivity andhence are termed as conducting polymers,have gotversatile promising applications in the field of energystorage[1],sensors[2],electronic and optical devices[3]andso on.Many researches have been conducted to pro-duce composites or blends of conducting polymer filmswith some insulating polymers in order to overcome thedrawbacks su…     

Pregnancy by Assisted Reproductive Technology Is Associated with Shorter Telomere Length in Neonates

Telomere length (TL) influences the development of lifestyle-related diseases, and neonatal TL may influence their prevalence. Various factors have been reported to affect neonatal TL. Although the fetus is exposed to multiple conditions in utero, the main factors affecting the shortening of neonatal TL are still not known. In this study, we sought to identify factors that influence fetal TL. A total of 578 mother-newborn pairs were included for TL analysis. TL was measured in genomic DNA extracted from cord blood samples using quantitative PCR. The clinical factors examined at enrollment included the following intrauterine environmental factors: maternal age, assisted reproductive technology (ART) used, body mass index (BMI), gestational diabetes mellitus (GDM), maternal stress, smoking, alcohol consumption, preterm delivery, small-for-gestational-age, neonatal sex, and placental weight. Univariate and multivariate regression analyses were used to verify the relationship between neonatal TL and these clinical factors. The median neonatal TL to single-copy gene ratio was 1.0. Pregnancy with ART was among the 11 factors associated with shorter neonatal TL. From multiple regression analysis, we determined that neonatal TL was significantly shorter for pregnancies in the ART group than in the other groups. We conclude that pregnancy with ART is associated with shorter neonatal TL.     

Review on Zinc Oxide Nanoparticles: Antibacterial Activity and Toxicity Mechanism

Nano-Micro Letters - Antibacterial activity of zinc oxide nanoparticles (ZnO-NPs) has received significant interest worldwide particularly by the implementation of nanotechnology to synthesize...     

Structurally Diverse Histone Deacetylase Photoreactive Probes: Design,Synthesis, and Photolabeling Studies in Live Cells and Tissue

Histone deacetylase (HDAC) activity is modulated in vivo by post-translational modifications and formation of multiprotein complexes. Novel chemical tools to study how these factors affect engagement of HDAC isoforms by HDAC inhibitors (HDACi) in cells and tissues are needed. In this study, a synthetic strategy to access chemically diverse photoreactive probes (PRPs) was developed and used to prepare seven novel HDAC PRPs 9 – 15 . The class I HDAC isoform engagement by PRPs was determined in biochemical assays and photolabeling experiments in live SET-2, HepG2, HuH7, and HEK293T cell lines and in mouse liver tissue. Unlike the HDAC protein abundance and biochemical activity against recombinant HDACs, the chemotype of the PRPs and the type of cells were key in defining the engagement of HDAC isoforms in live cells. Our findings suggest that engagement of HDAC isoforms by HDACi in vivo may be substantially modulated in a cell- and tissue-type-dependent manner.     

Blockchain-Enabled EHR Framework for Internet of Medical Things

The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most healthcare services within IoMT are constructed under a centralized platform outsourced in the cloud. Therefore, it is appealing to design a decentralized, auditable and secure EHR system that guarantees absolute access control for the patients while ensuring privacy and security. Using the features of blockchain including decentralization, auditability and immutability, we propose a secure EHR framework which is mainly maintained by the medical centers. In this framework, the patients’ EHR data are encrypted and stored in the servers of medical institutions while the corresponding hash values are kept on the blockchain. We make use of security primitives to offer authentication, integrity and confidentiality of EHR data while access control and immutability is guaranteed by the blockchain technology. The security analysis and performance evaluation of the proposed framework confirms its efficiency.     

Diffusion Based Channel Gains Estimation in WSN Using Fractional Order Strategies

In this study, it is proposed that the diffusion least mean square (LMS) algorithm can be improved by applying the fractional order signal processing methodologies. Application of Caputo’s fractional derivatives are considered in the optimization of cost function. It is suggested to derive a fractional order variant of the diffusion LMS algorithm. The applicability is tested for the estimation of channel parameters in a distributed environment consisting of randomly distributed sensors communicating through wireless medium. The topology of the network is selected such that a smaller number of nodes are informed. In the network, a random sleep strategy is followed to conserve the transmission power at the nodes. The proposed fractional order modified diffusion LMS algorithms are applied in the two configurations of combine-then-adapt and adapt-then-combine. The average squared error performance of the proposed algorithms along with its traditional counterparts are evaluated for the estimation of the Rayleigh channel parameters. A mathematical proof of convergence is provided showing that the addition of the nonlinear term resulting from fractional derivatives helps adjusts the autocorrelation matrix in such a way that the spread of its eigenvalues decreases. This increases the convergence as well as the steady state response even for the larger step sizes. Experimental results are shown for different number of nodes and fractional orders. The simulation results establish that the accuracy of the proposed scheme is far better than its classical counterparts, therefore, helps better solves the channel gains estimation problem in a distributed wireless environment. The algorithm has the potential to be applied in other applications related to learning and adaptation.     

Detection Avoidance and Priority-Aware Target Tracking for UAV Group Reconnaissance Operations

In this paper, we present a novel approach for stationary target tracking in reconnaissance operations with a small UAV group. A reconnaissance mission has multiple competing requirements, such as short scan time and repetitive scanning of the entire area, target recognition, and target tracking. Especially in real-world military reconnaissance scenarios, different types of targets with hostile characteristics exist. The UAVs must scan and track the targets while avoiding detection by enemies. Although small UAVs are unlikely to be detected, they become prone to detection if their path is predictable. To meet these competitive requirements, we propose an attractive pheromone-based cooperative path planning method that makes path prediction almost impossible by ensuring a random path selection mechanism. To avoid detection during target tracking, we implement a new discrete-time tracking scheme with random time intervals and random path planning for multiple UAVs. The proposed model enables a UAV group to sporadically scan the entire area, quickly locate the targets, and simultaneously track the targets based on their priority. In addition, it offers a mechanism that permits the command and control center to balance between reconnaissance and target tracking operations to meet every mission requirement.