Changes in morphological traits, anatomical and molecular alterations caused by gamma-rays and zinc oxide nanoparticles in spinach (Spinacia oleracea L.) plant.

Spinach seeds were irradiated with gamma-rays after that soaked in zinc oxide nanoparticles (ZnO-NPs) at 0.0, 50, 100 and 200 ppm for twenty-four hours at room temperature. Vegetative plant growth, photosynthetic pigments, and proline contents were investigated.

Efficient training of spiking neural networks with temporally-truncated local backpropagation through time.

Directly training spiking neural networks (SNNs) has remained challenging due to complex neural dynamics and intrinsic non-differentiability in firing functions. The well-known backpropagation through time (BPTT) algorithm proposed to train SNNs suffers from large memory footprint and prohibits backward and update unlocking, making it impossible to exploit the potential of locally-supervised training methods. This work proposes an efficient and direct training algorithm for SNNs that integrates a locally-supervised training method with a temporally-truncated BPTT algorithm.

Machine Learning-Based Unobtrusive Intake Gesture Detection via Wearable Inertial Sensors.

Dietary patterns can be the primary reason for many chronic diseases such as diabetes and obesity. State-of-the-art wearable sensor technologies can play a critical role in assisting patients in managing their eating habits by providing meaningful statistics on critical parameters such as the onset, duration, and frequency of eating. For an accurate yet fast food intake recognition, this work presents a novel Machine Learning (ML) based framework that shows promising results by leveraging optimized support vector machine (SVM) classifiers.

Plant stem tissue modeling and parameter identification using metaheuristic optimization algorithms.

Bio-impedance non-invasive measurement techniques usage is rapidly increasing in the agriculture industry. These measured impedance variations reflect tacit biochemical and biophysical changes of living and non-living tissues. Bio-impedance circuit modeling is an effective solution used in biology and medicine to fit the measured impedance.

Parameter Estimation of Two Spiking Neuron Models With Meta-Heuristic Optimization Algorithms.

The automatic fitting of spiking neuron models to experimental data is a challenging problem. The integrate and fire model and Hodgkin-Huxley (HH) models represent the two complexity extremes of spiking neural models. Between these two extremes lies two and three differential-equation-based models.

A flexible capacitive photoreceptor for the biomimetic retina.

Neuromorphic vision sensors have been extremely beneficial in developing energy-efficient intelligent systems for robotics and privacy-preserving security applications. There is a dire need for devices to mimic the retina's photoreceptors that encode the light illumination into a sequence of spikes to develop such sensors. Herein, we develop a hybrid perovskite-based flexible photoreceptor whose capacitance changes proportionally to the light intensity mimicking the retina's rod cells, paving the way for developing an efficient artificial retina network.

Programmable constant phase element realization with crossbar arrays.

Introduction: Constant Phase Elements (CPEs) have been widely used in many applications due to the extra degree of freedom, which offers new responses and behaviors.

Objectives: This paper proposes a new programmable CPE realization using resistive crossbar arrays. By programming the resistive devices, different CPEs can be obtained.

Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems.

Various hypotheses of information representation in brain, referred to as neural codes, have been proposed to explain the information transmission between neurons. Neural coding plays an essential role in enabling the brain-inspired spiking neural networks (SNNs) to perform different tasks. To search for the best coding scheme, we performed an extensive comparative study on the impact and performance of four important neural coding schemes, namely, rate coding, time-to-first spike (TTFS) coding, phase coding, and burst coding.

Zero Valent Iron Nanoparticle-Loaded Nanobentonite Intercalated Carboxymethyl Chitosan for Efficient Removal of Both Anionic and Cationic Dyes.

A zero valent iron-loaded nano-bentonite intercalated carboxymethyl chitosan (nZVI@nBent-CMC) composite was fabricated and characterized by FT-IR, TEM, TEM-EDX, XRD, BET surface area, and zeta potential measurements. The as-fabricated nZVI@nBent-CMC composite exhibited excellent removal efficiency for both anionic Congo red (CR) dye and cationic crystal violet (CV) dye. The maximum uptake capacities of CR and CV onto the nZVI@nBent-CMC composite were found to be 884.

Toward the Optimal Design and FPGA Implementation of Spiking Neural Networks.

The performance of a biologically plausible spiking neural network (SNN) largely depends on the model parameters and neural dynamics. This article proposes a parameter optimization scheme for improving the performance of a biologically plausible SNN and a parallel on-field-programmable gate array (FPGA) online learning neuromorphic platform for the digital implementation based on two numerical methods, namely, the Euler and third-order Runge-Kutta (RK3) methods. The optimization scheme explores the impact of biological time constants on information transmission in the SNN and improves the convergence rate of the SNN on digit recognition with a suitable choice of the time constants.

Unsupervised Adaptive Weight Pruning for Energy-Efficient Neuromorphic Systems.

To tackle real-world challenges, deep and complex neural networks are generally used with a massive number of parameters, which require large memory size, extensive computational operations, and high energy consumption in neuromorphic hardware systems. In this work, we propose an unsupervised online adaptive weight pruning method that dynamically removes non-critical weights from a spiking neural network (SNN) to reduce network complexity and improve energy efficiency. The adaptive pruning method explores neural dynamics and firing activity of SNNs and adapts the pruning threshold over time and neurons during training.

Results of a project to calibrate mercury sphygmomanometer blood pressure-measuring devices in Egypt.

Hypertension (HTN) is a common health problem and a major cardiovascular risk factor. Accurate measurement of blood pressure (BP) is mandatory for proper diagnosis and follow-up. The aim of this study was to evaluate the accuracy of mercury sphygmomanometer BP-measuring devices in public hospitals in Cairo, Egypt.

Efficient Acceleration of Stencil Applications through In-Memory Computing.

The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of big data and artificial intelligence. This fact forces new constraints in computer architecture design towards more data-centric principles.

New renal haemodynamic indices can predict worsening of renal function in acute decompensated heart failure.

Aims: Worsening of renal function (WRF) is a common complication in patients with acute decompensated heart failure (ADHF). We aimed to evaluate the role of intrarenal Doppler ultrasound (IRD) in the early prediction of WRF in this patient group.

Methods And Results: Among 90 patients (age: 57.

Biometric Identity Based on Intra-Body Communication Channel Characteristics and Machine Learning.

In this paper, we propose and validate using the Intra-body communications channel as a biometric identity. Combining experimental measurements collected from five subjects and two multi-layer tissue mimicking materials' phantoms, different machine learning algorithms were used and compared to test and validate using the channel characteristics and features as a biometric identity for subject identification. An accuracy of 98.

An Ultra-Area-Efficient 1024-Point In-Memory FFT Processor.

Current computation architectures rely on more processor-centric design principles. On the other hand, the inevitable increase in the amount of data that applications need forces researchers to design novel processor architectures that are more data-centric. By following this principle, this study proposes an area-efficient Fast Fourier Transform (FFT) processor through in-memory computing.

The operating room case-mix problem under uncertainty and nurses capacity constraints.

Surgery is one of the key functions in hospitals; it generates significant revenue and admissions to hospitals. In this paper we address the decision of choosing a case-mix for a surgery department. The objective of this study is to generate an optimal case-mix plan of surgery patients with uncertain surgery operations, which includes uncertainty in surgery durations, length of stay, surgery demand and the availability of nurses.

Colorectal cancers and chlorinated water.

Published reports have revealed increased risk of colorectal cancers in people exposed to chlorinated drinking water or chemical derivatives of chlorination. Oestrogen plays a dual positive functions for diminishing the possibilities of such risk by reducing the entrance, and increasing the excretion, of these chemicals. In addition, there are supplementary measures that could be employed in order to reduce this risk further, such as boiling the drinking water, revising the standard concentrations of calcium, magnesium and iron in the public drinking water and prescribing oestrogen in susceptible individuals.

Emerging role of adipokine apelin in hepatic remodelling and initiation of carcinogensis in chronic hepatitis C patients.

Background: Although accumulating data has implicated a role for the Apelinergic system in cirrhosis, the role of Apelin during different stages of fibrogenesis has not been clarified, whereas no studies have been conducted on its expression in human hepatocellular carcinoma (HCC). This study aimed to elucidate its role in hepatic remodelling and carcinogenesis.

Methods: Immunolocalization of Apelin was compared during different stages of HCV-induced liver disease (n=123).

Lipid profile and hepatic steatosis in hepatitis C infected egyptian survivors of childhood cancer.

Backgound/aim: Studies associating chronic hepatitis C virus (HCV) infection with lipid profile and hepatic steatosis in children and adolescents are scarce. This study investigated lipid profile abnormalities and hepatic steatosis among HCV-infected Egyptian children and adolescents who survived leukemia and lymphoma and evaluated impact on response to antiviral therapy.

Subjects And Methods: Thirty-six leukemia/lymphoma cured children and adolescents (mean age: 12.

Does living in crowded houses offer protection against the development of inflammatory bowel disease?

Introduction: The credibility of the "Hygiene hypothesis" in patients with inflammatory bowel disease has been assessed.

Objective: This survey is aimed at finding an answer for the question: "Does living in crowded or overcrowded houses protect against the development of inflammatory bowel disease?"

Patients And Methods: Asian immigrants to the United Kingdom who attended inflammatory bowel diseases' clinics during the period of the study and who fulfilled Leonard-Jones criteria were asked to complete a questionnaire. The participants were asked to respond to questions on age, sex, their birth rank, diagnosis, & number of brothers, sisters, sons and daughters.

Epidemiology and inflammatory bowel diseases.

The role of alcohol in causing or aggravating the pathogenesis of inflammatory bowel disease is unclear. For finding a conclusive answer for this valuable question we conducted this review. Only two studies were identified that successfully fulfilled our inclusive criteria.

Trends on gastrointestinal bleeding and mortality: where are we standing?

Bleeding from the gastrointestinal tract and its management are associated with significant morbidity and mortality. The predisposing factors that led to the occurrence of these hemorrhagic instances are largely linked to the life style of the affected persons. Designing a new strategy aimed at educating the publics and improving their awareness of the problem could effectively help in eradicating this problem with no associated risks and in bringing the mortality rates down to almost zero.