Reliable relay assisted communications for IoT based fall detection.

Robust wireless communication using relaying system and Non-Orthogonal Multiple Access (NOMA) will be extensively used for future IoT applications. In this paper, we consider a fall detection IoT application in which elderly patients are equipped with wearable motion sensors. Patient motion data is sent to fog data servers via a NOMA-based relaying system, thereby improving the communication reliability. We analyze the average signal-to-interference-plus-noise (SINR) performance of the NOMA-based relaying system, where the source node transmits two different symbols to the relay and destination node by employing superposition coding over Rayleigh fading channels. In the amplify-and-forward (AF) based relaying, the relay re-transmits the received signal after amplification, whereas, in the decode-and-forward (DF) based relaying, the relay only re-transmits the symbol having lower NOMA power coefficient. We derive closed-form average SINR expressions for AF and DF relaying systems using NOMA. The average SINR expressions for AF and DF relaying systems are derived in terms of computationally efficient functions, namely Tricomi confluent hypergeometric and Meijer's G functions. Through simulations, it is shown that the average SINR values computed using the derived analytical expressions are in excellent agreement with the simulation-based average SINR results.

Junction Temperature Optical Sensing Techniques for Power Switching Semiconductors: A Review.

Recent advancements in power electronic switches provide effective control and operational stability of power grid systems. Junction temperature is a crucial parameter of power-switching semiconductor devices, which needs monitoring to facilitate reliable operation and thermal control of power electronics circuits and ensure reliable performance. Over the years, various junction temperature measurement techniques have been developed, engaging both non-optical and optical-based methods, highlighting their advancements and challenges. This review focuses on several optical sensing-based junction temperature measuring techniques used for power-switching devices such as metal-oxide-semiconductor field-effect transistors (MOSFETs) and insulated-gate bipolar transistors (IGBTs). A comprehensive summary of recent developments in infrared camera (IRC), thermal sensitive optical parameter (TSOP), and fiber Bragg grating (FBG) temperature sensing techniques is provided, shedding light on their merits and challenges while providing a few possible future solutions. In addition, calibration methods and remedies for obtaining accurate measurements are discussed, thus providing better insight and directions for future research.

Performance Analysis of IRS-Assisted THz Communication Systems over α-µ Fading Channels with Pointing Errors.

In this paper, we analyze the performance of an intelligent reflecting surface (IRS)-aided terahertz (THz) wireless communication system with pointing errors. Specifically, we derive closed-form analytical expressions for the upper bounded ergodic capacity and approximate expression of the outage probability. We adopt an α-µ fading channel model for our analysis that is experimentally demonstrated to be a good fit for THz small-scale fading statistics, especially in indoor communication scenarios. In the proposed analysis, the statistical distribution of the α-µ fading channel is used to derive analytical expressions for the ergodic capacity and outage probability. Our proposed analysis considers not only the IRS reflected channels, but also the direct channel between the communication nodes. The results of the derived analytical expressions are validated through Monte Carlo simulations. Through simulations, it has been noticed that pointing errors degrade the performance of the IRS-assisted THz wireless communication system which can be compensated by deploying an IRS having a large number of reflecting elements.

Reliable and cost-efficient protection scheme for 5G fronthaul/backhaul network.

One of the challenges for Mobile Network Operators (MNO) in 5G deployment is to ensure reliability in the various sections of the network as the new services and applications, for instance, video on demand, telemedicine, online learning, smart transportation and augmented reality require not only high bandwidth but also demand uninterrupted service. However, this reliability requires substantial investment. Therefore, MNO only deploys protection or backup resources in the network unless it is cost-effective. The study aims to present a reliable and low-cost protection scheme based on an Ultra-Dense Wavelength Division Multiplexing Passive Optical Network (UDWDM PON) for the transport layer of the 5G network, i.e., for the fronthaul/backhaul section. We have evaluated the Capital Expenditure (CAPEX) cost of UDWDM PON with and without protection in a dense urban area. We also measure the figure of merit between the cost and reliability of the system and, subsequently, confirm that the proposed protection scheme can achieve system reliability up to four nines with very low additional CAPEX investment. Finally, the efficacy of the proposed protection scheme is also demonstrated through simulation experiments.

On the Physical Layer Security of Federated Learning Based IoMT Networks.

Internet of Medical Things (IoMT) connects different medical devices, health sensors and hospital records to data platforms using wireless communications. Federated Learning (FL) is an emerging collaborative learning technique that can be beneficial for IoMT due to reduced communication overhead and enhanced security. This paper provides an overview of different architectures used in FL and potential approaches for FL based IoMT. We also discuss how Physical Layer Security (PLS) can be used for efficient privacy preservation of data in FL based IoMT. We highlight the recent work in this area and major research challenges related to PLS assisted FL in IoMT. We also provide a case study demonstrating that clustering of IoMT devices (such that a single device in each cluster acts as a cluster head) enhances the secrecy rate of the FL based IoMT network as compared to its non-clustered counterpart. Finally, we also discuss future opportunities and open research questions related to PLS assisted FL in IoMT.

Design and Analysis of an O+E-Band Hybrid Optical Amplifier for CWDM Systems.

Broadband amplification in the O+E-band is very desirable nowadays as a way of coping with increasing bandwidth demands. The main issue with doped fiber amplifiers working in this band such as the bismuth-doped fiber amplifier is that they are costly and not widely available. Therefore, a wideband and flat-gain hybrid optical amplifier (HOA) covering the O+E-band based on a parallel combination of a praseodymium-doped fiber amplifier (PDFA) and a semiconductor optical amplifier (SOA) is proposed and demonstrated through numerical simulations. The praseodymium-doped fiber (PDF) core is pumped using a laser diode with a power of 500 mW that is centered at a wavelength of 1030 nm. The SOA is driven by an injection current of 60 mA. The performance of the HOA is analyzed by the optimization of various parameters such as the PDF length, Pr3+ concentration, pump wavelength, and injection current. A flat average gain of 24 dB with a flatness of 1 dB and an output power of 9.6 dBm is observed over a wavelength range of 1270-1450 nm. The noise figure (NF) varies from a minimum of 4 dB to a maximum of 5.9 dB for a signal power of 0 dBm. A gain reduction of around 4 dB is observed for an O-band signal at a wavelength of 1290 nm by considering the up-conversion effect. The transmission performance of the designed HOA as a pre-amplifier is evaluated based on the bit-error rate (BER) analysis for a coarse wavelength-division multiplexing (CWDM) system of eight on-off keying (OOK)-modulated channels, each having a data rate of 10 Gbps. An error-free transmission over 60 km of standard single-mode fiber (SMF) is achieved for different data rates of 5 Gbps, 7.5 Gbps, and 10 Gbps.

A Comprehensive Review of Performance of Next-Generation Sequencing Platforms.

Background: Next-generation sequencing methods have been developed and proposed to investigate any query in genomics or clinical activity involving DNA. Technical advancement in these sequencing methods has enhanced sequencing volume to several billion nucleotides within a very short time and low cost. During the last few years, the usage of the latest DNA sequencing platforms in a large number of research projects helped to improve the sequencing methods and technologies, thus enabling a wide variety of research/review publications and applications of sequencing technologies. Objective: The proposed study is aimed at highlighting the most fast and accurate NGS instruments developed by various companies by comparing output per hour, quality of the reads, maximum read length, reads per run, and their applications in various domains. This will help research institutions and biological/clinical laboratories to choose the sequencing instrument best suited to their environment. The end users will have a general overview about the history of the sequencing technologies, latest developments, and improvements made in the sequencing technologies till now. Results: The proposed study, based on previous studies and manufacturers' descriptions, highlighted that in terms of output per hour, Nanopore PromethION outperformed all sequencers. BGI was on the second position, and Illumina was on the third position. Conclusion: The proposed study investigated various sequencing instruments and highlighted that, overall, Nanopore PromethION is the fastest sequencing approach. BGI and Nanopore can beat Illumina, which is currently the most popular sequencing company. With respect to quality, Ion Torrent NGS instruments are on the top of the list, Illumina is on the second position, and BGI DNB is on the third position. Secondly, memory- and time-saving algorithms and databases need to be developed to analyze data produced by the 3rd- and 4th-generation sequencing methods. This study will help people to adopt the best suited sequencing platform for their research work, clinical or diagnostic activities.

Performance Enhancement of Ytterbium-Doped Fiber Amplifier Employing a Dual-Stage In-Band Asymmetrical Pumping.

The performance of doped fiber amplifiers can be enhanced significantly with the help of multi-stage pumping technique provided that various critical parameters of pumps including their optical power and wavelength are optimized. We report the performance enhancement of a ytterbium doped fiber amplifier (YDFA) for a 1.02-1.08 µm spectral region with an optimized design based on a novel dual-stage in-band asymmetrical pumping scheme. By accurately adjusting the optical power and wavelength of pumps in both the stages, a record peak gain of around 62.5 dB and output power of 4.5 W are achieved for a signal wavelength of 1.0329 µm at an optimized length of Ytterbium-doped silica fiber and optimized doping concentration of Yb3+. Moreover, a minimum noise figure (NF) of 4 dB is observed for a signal wavelength of 1.0329 µm at the optimized parameters. Similarly, the effect of using high and low pump powers at the first and the second stage, respectively, on NF of the amplifier is also investigated at different values of signal powers. It is observed that the value of NF increases significantly by using high pump power at the first stage and low pump power at the second stage.

Compound Homozygous Rare Mutations in PLCE1 and HPS1 Genes Associated with Autosomal Recessive Retinitis Pigmentosa in Pakistani Families.

Background: Retinitis pigmentosa (RP) belongs to pigmentary retinopathies, a generic name for all retinal dystrophies with a major phenotypical and genotypical variation, characterized by progressive reduction of photo-receptor functionality of the rod and cone. Global prevalence of RP is ~ 1/4000 and it can be inherited as autosomal dominant (adRP), autosomal recessive (arRP) or X- linked (xlRP). We designed this study to identify causative mutations in Pakistani families affected with arRP. Methods: In 2019, we recruited two unrelated Pakistani consanguineous families affected with progressive vision loss and night blindness from Punjab region. Clinical diagnosis confirmed the; bone spicule pigmentation of the retina, and an altered electroretinogram (EGR) response. Proband and healthy individual from each family were subjected for whole-exome sequencing (WES). Various computational tools were used to analyze the Next Generation Sequencing (NGS) data and to predict the pathogenicity of the identified mutations. Results: WES data analysis highlighted two missense homozygous variants at position c.T1405A (p.S469T) in PLCE1 and c.T11C (p.V4A) in HPS1 genes in proband of both families. Healthy individuals of two families were tested negative for p.S469T and p.V4A mutations. The variant analysis study including molecular dynamic simulations predicted mutations as disease causing. Conclusion: Compound effect of mutations in rarely linked PLCE1 and HPS1 genes could also cause RP. This study highlights the potential application of WES for a rapid and precise molecular diagnosis for heterogeneous genetic diseases such as RP.

Insilico modeling and analysis of small molecules binding to the PHLPP1 protein by molecular dynamics simulation.

The PHLPP (Pleckstrin homology domain leucine-rich repeat protein phosphatases) is a newly discovered group of genes which includes PHLPP1 and PHLPP2 and plays an integral part in several cellular processes like apoptosis, cell signaling cell survival, and cell proliferation etc. Both the activation and deactivation of these genes can have vital role in several ailments like heart diseases, circadian rhythm and most importantly the cancer, hence encouraging the growth of novel therapeutic elements. To give new directions into the development of PHLPP1- targeting drugs, the interaction mechanism between PHLPP1 and five important ligands 4IP, B39, 635, ATP and GTA were investigated through docking and Molecular Dynamics Simulation. It is also noteworthy to be mentioned here that there is no previous crystal structure of PHLPP1 available. The in-silico results can provide potential base for advancements in development of new therapeutic elements targeting different diseases, mainly cancer. In this study, we employed homology modeling technique to develop a high-quality structure model of PHLPP1. The PHLPP1 model was then used in docking interaction analysis and Molecular Dynamics Simulation, to study binding pockets and interactions of PHLPP1 ligands and finding actively contributing residues in binding pocket. In final step, Free Energy Estimation was performed to observe ligand binding's quantitative characteristics.

Computational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene.

Single Nucleotide Polymorphisms (SNPs) are the most common candidate mutations in human beings that play a vital role in the genetic basis of certain diseases. Previous studies revealed that Solute Carrier Family 26 Member 4 (SLC26A4) being an essential gene of the multi-faceted transporter family SLC26 facilitates reflexive movement of Iodide into follicular lumen through apical membrane of thyrocyte. SLC26A4 gene encodes Pendred protein, a membrane glycoprotein, highly hydrophobic in nature, present at the apical membrane of thyrocyte functioning as transporter of iodide for thyroid cells. A minor genetic variation in SLC26A4 can cause Pendred syndrome, a syndrome associated with thyroid glands and deafness. In this study, we performed in-silico analysis of 674 missense SNPs of SLC26A4 using different computational platforms. The bunch of tools including SNPNEXUS, SNAP-2, PhD-SNP, SNPs&GO, I-Mutant, ConSurf, and ModPred were used to predict 23 highly confident damaging and disease causing nsSNPs (G209V, G197R, L458P, S427P, Q101P, W472R, N392Y, V359E, R409C, Q235R, R409P, G139V, G497S, H723R, D87G, Y127H, F667C, G334A, G95R, S427C, R291W, Q383H and E384G) that could potentially alter the SLC26A4 gene. Moreover, protein structure prediction, protein-ligand docking and Molecular Dynamics simulation were performed to confirm the impact of two evident alterations (Y127H and G334A) on the protein structure and function.

A Strategy for Classification of "Vaginal vs. Cesarean Section" Delivery: Bivariate Empirical Mode Decomposition of Cardiotocographic Recordings.

We propose objective and robust measures for the purpose of classification of "vaginal vs. cesarean section" delivery by investigating temporal dynamics and complex interactions between fetal heart rate (FHR) and maternal uterine contraction (UC) recordings from cardiotocographic (CTG) traces. Multivariate extension of empirical mode decomposition (EMD) yields intrinsic scales embedded in UC-FHR recordings while also retaining inter-channel (UC-FHR) coupling at multiple scales. The mode alignment property of EMD results in the matched signal decomposition, in terms of frequency content, which paves the way for the selection of robust and objective time-frequency features for the problem at hand. Specifically, instantaneous amplitude and instantaneous frequency of multivariate intrinsic mode functions are utilized to construct a class of features which capture nonlinear and nonstationary interactions from UC-FHR recordings. The proposed features are fed to a variety of modern machine learning classifiers (decision tree, support vector machine, AdaBoost) to delineate vaginal and cesarean dynamics. We evaluate the performance of different classifiers on a real world dataset by investigating the following classifying measures: sensitivity, specificity, area under the ROC curve (AUC) and mean squared error (MSE). It is observed that under the application of all proposed 40 features AdaBoost classifier provides the best accuracy of 91.8% sensitivity, 95.5% specificity, 98% AUC, and 5% MSE. To conclude, the utilization of all proposed time-frequency features as input to machine learning classifiers can benefit clinical obstetric practitioners through a robust and automatic approach for the classification of fetus dynamics.

System dynamics of active and passive postural changes: Insights from principal dynamic modes analysis of baroreflex loop.

The baroreflex being a key modulator of cardiovascular control ensures adequate blood pressure regulation under orthostatic stress which otherwise may cause severe hypotension. Contrary to conventional baroreflex sensitivity indices derived across a-priori traditional frequency bands, the present study is aimed at proposing new indices for the assessment of baroreflex drive which follows active (supine to stand-up) and passive (supine to head-up tilt) postural changes. To achieve this, a novel system identification approach of principal dynamic modes (PDM) was utilized to extract data-adaptive frequency components of closed-loop interactions between beat-to-beat interval and systolic blood pressure recorded from 10 healthy humans. We observed that the gain of low-pass global PDM of cardiac arm (:feedback reflex loop, mediated by pressure sensors to adjust heart rate in response to arterial blood pressure), and 0.2 Hz global PDM of mechanical arm (:feed-forward pathways, originating changes in arterial blood pressure in response to heart rate variations) may function as potential markers to distinguish active and passive orthostatic tests in healthy subjects.

Characterisation of ictal and interictal states of epilepsy: A system dynamic approach of principal dynamic modes analysis.

Epilepsy is a brain disorder characterised by the recurrent and unpredictable interruptions of normal brain function, called epileptic seizures. The present study attempts to derive new diagnostic indices which may delineate between ictal and interictal states of epilepsy. To achieve this, the nonlinear modeling approach of global principal dynamic modes (PDMs) is adopted to examine the functional connectivity of the temporal and frontal lobes with the occipital brain segment using an ensemble of paediatric EEGs having the presence of epileptic seizure. The distinct spectral characteristics of global PDMs are found to be in line with the neural rhythms of brain dynamics. Moreover, we find that the linear trends of associated nonlinear functions (ANFs) associated with the 2nd and 4th global PDMs (representing delta, theta and alpha bands) of Fp1-F3 may differentiate between ictal and interictal states of epilepsy. These findings suggest that global PDMs and their associated ANFs may offer potential utility as diagnostic neural measures for ictal and interictal states of epilepsy.