An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

A Photoluminescent Ag10Cu6 Cluster Stablized by a PNNP Ligand and Phenylacetylides Selectively and Reversibly Senses Ammonia in Air and Water

A photoluminescent bimetallic cluster [Ag₁₀Cu₆(bdppthi)₂(C≡CPh)₁₂(MeOH)₂(H₂O)](ClO₄)₄ ( 1 , bdppthi=N,N’-bis(diphenylphosphanylmethyl)-tetrahydroimidazole} was synthesized from the PNNP type ligand bdppthi generated in-situ. Upon excitation at 365 nm, 1 exhibited strong phosphorescent emission at 630 nm, which was selectively quenched by NH₃ in air or water. The sensing of NH₃ was rapid and recoverable, with detection limits of 53 ppm (v/v) in N₂ and 21 μmol/L (0.36 ppm, w/w) for NH₃ ⋅ H₂O in water. Cluster 1 could potentially serve as a bifunctional chemical sensor for the efficient detection of ammonia in waste-gas and waste-water.     

基于随机光栅的可调谐随机光纤激光器

提出一种基于随机光栅与高反射布拉格光栅(FBG)相结合的可调谐随机光纤激光器。利用980nm泵浦光源泵浦一段7m长的掺铒光纤(EDF)进行增益放大,由随机光栅提供随机反馈。随机光栅长7cm,具有约10000个折射率修改点,这些点由飞秒激光逐点写入,并沿光纤方向随机分布,两点相邻间隔小于10μm。同时,利用中心波长为1548nm的高反射FBG来组成半开放腔结构,实现了随机激光的输出。实验测得的泵浦阈值功率仅为18mW,斜率效率高达13.2%,并通过改变FBG的中心波长,实现了输出激光波长的可调谐,调谐范围为4.45nm(1548.04~1552.49nm)。得益于半开放式激光腔的设计和EDF的高增益,整个系统具有阈值低、效率高、结构简单等优点。     

用标准件对梯度磁场定标

就标准厚度卡片在霍尔传感器的定标方面的应用作了有益的探讨。在纵向测量微小长度时,霍尔片处于磁场边缘位置,其对磁场的梯度更大,即灵敏度更高,且靠中心位置的线性更好。     

A precise sensor fault detection technique using statistical techniques for wireless body area networks

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.     

Voltammetric Determination of Isoniazid Drug in Various Matrix by Using CuOx Decorated MW‐CNT Modified Glassy Carbon Electrode

Copper oxide decorated multi‐walled carbon nanotube (MWCNT) modified glassy carbon electrode (GCE) was prepared for determination of isoniazid (INZ) in various matrices. The electrochemical behavior of INZ was tested with the aid of Cyclic Voltammetry (CV) and quantitative experiments were performed by using Linear Sweep Voltammetry (LSV). Morphological and structural characterization of the modified electrode was performed by utilizing Scanning Electron Microscopy (SEM), X‐Ray Photoelectron Spectroscopy (XPS) while electrochemical characterization was performed by using CV and Electrochemical Impedance spectroscopy (EIS). The proposed sensor exhibited well defined anodic peak at 0.30 V for INZ at pH 6.0 medium. Under the optimum conditions, a linear relation between INZ concentration and peak current was observed in the range of 2.0×10^?7 to 5.0×10^?5 M. Limit of detection was calculated as 1.0×10^?8 M and repeatability and accuracy was found as 5.60 % and 91.0 % for 5.0 10^?7 M INZ by using 3 successive measurement, respectively. Then, the analytic performance of the electrode developed was tested by analyzing commercial tablets, artificial human serum and urine samples. The results indicated that satisfactory recoveries was observed for all issue.     

Influences of magnetic fields on current–voltage characteristics of gold-DNA-gold structure with variable gaps

Achieving highly sensitive magnetic sensors by means of Metal-DNA-Metal (MDM) structure is a key issue. DNA, being a genetic information carrier in living cells reveals tunable semiconducting response in the presence of external electric and magnetic fields, which is promising for molecular electronics. The influence of magnetic fields up to 1200 mT on the current–voltage (I–V) behavior of Gold-DNA-Gold (GDG) structure having variable gap sizes from 20–50 μm are reported in this work. These structures were fabricated using UV lithography, DC magnetron sputtering and thermal evaporation techniques. DNA strands were extracted from Boesenbergia rotunda plant via standard protocol. The acquired I–V characteristics display the semiconducting diode nature of DNA in GDG structures. The potential barrier for all the structures exhibit an increasing trend with the increase of externally imposed magnetic field irrespective of variable gap sizes. Furthermore, the potential barrier in GDG junction at higher magnetic field strengths (>1000 mT) is found to be considerably enhanced. This enhancement in the junction barrier height at elevated magnetic fields is attributed to the reduction of carrier mobility and augmentation of resistance. The achieved admirable features of magnetic sensitivity suggest the viability of using these GDG sandwiches as a prospective magnetic sensor.     

光纤布拉格光栅的无源温度补偿

分析了通过施加应变补偿光纤布拉格光栅(FBG)中心波长随温度漂移的原理，给出了一种新型的无源温度补偿的方法和相应的实验结果。该方法采用了两种不同热膨胀系数的金属，对光栅先施加预应变。在0-60℃范围内，中心波长仅偏移了0．02nm。     

DISPERSION COMPENSATION CFBG IN100km 10Gbit／s RECIRCULATING SYSTEMS

A 10Gbit/s recirculating system is configured with Chirped Fiber Bragg Grating (CFBG) for the dispersion compensation. For the first time, the transmission distance in the loop reaches 1000km with bit error rate of 10-9. The effect of the group delay ripple of the fiber grating is also investigated in the recirculating systems, and it is shown that the transmission distance is limited to 4 cycles (4×167.1km ) in the loop with the power penalty fluctuation below 1.0dB. Thus the group delay ripple should be reduced to allow for the wavelength drift of±5GHz. At the end of this letter, the principles are given for designing long haul recirculating systems with dispersion compensation CFBG.     

平面阵列波导光栅波导模式参量的分析

用周期波导的方法分析平面阵列波导光栅(AWG)的本征方程及波导模式参数,结果表明波导传播常数是带状分布的,与波导间隔有关。分析结果对器件的优化设计有一定的指导意义。