Solution-processed light-induced multilevel non-volatile wearable memory device based on CsPbBr perovskite.

Despite the recent advancements in memory devices, the quest for building materials with low power consumption is still on, with the ultimate focus on the durability of the system and reliability and reproducibility of its performance. Halide perovskites (HPs), which have several intriguing photoelectrical traits, have recently been utilized for memory applications; one of the highlights of these materials is the ionic-motion-based fast switching in their crystal structure. In this work, a CsPbBr film is applied as a switching layer to implement memory devices with a flexible Al/CsPbBr/ITO-PET structure.

Eco-friendly surface modification approach to develop thin film nanocomposite membrane with improved desalination and antifouling properties.

Introduction: Nanomaterials aggregation within polyamide (PA) layer of thin film nanocomposite (TFN) membrane is found to be a common issue and can negatively affect membrane filtration performance. Thus, post-treatment on the surface of TFN membrane is one of the strategies to address the problem.

Objective: In this study, an eco-friendly surface modification technique based on plasma enhanced chemical vapour deposition (PECVD) was used to deposit hydrophilic acrylic acid (AA) onto the PA surface of TFN membrane with the aims of simultaneously minimizing the PA surface defects caused by nanomaterials incorporation and improving the membrane surface hydrophilicity for reverse osmosis (RO) application.

A review on synergistic coexisting pollutants for efficient photocatalytic reaction in wastewater remediation.

With the tremendous development of the economy and industry, the pollution of water is becoming more serious due to the excessive chemical wastes that need to remove thru reduction or oxidation reactions. Simultaneous removal of dual pollutants via photocatalytic redox reaction has been tremendously explored in the last five years due to effective decontamination of pollutants compared to a single pollutants system. In a photocatalysis mechanism, the holes in the valence band can remarkably promote the oxidation of a pollutant.

Advanced biokinetic and hydrodynamic modelling to support and optimize the design of full-scale high rate algal ponds.

High rate algal ponds (HRAP) are known for their suitability to treat wastewater and to produce microalgal biomass, which can be converted into bioproducts. However, full-scale application of HRAP is still limited to few cases, and design procedures are not consolidated or standardized. In this study, a demonstrative-scale HRAP system for secondary wastewater treatment to be implemented in India (treatment capacity of 50 m·d) has been designed combining conventional dimensioning techniques and advanced modelling tools.

A novel sampling-based visual topic models with computational intelligence for big social health data clustering.

Twitter is a popular social network for people to share views or opinions on various topics. Many people search for health topics through Twitter; thus, obtaining a vast amount of social health data from Twitter is possible. Topic models are widely used for social health-care data clustering.

A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework.

Background: Early and automated detection of carotid plaques prevents strokes, which are the second leading cause of death worldwide according to the World Health Organization. Artificial intelligence (AI) offers automated solutions for plaque tissue characterization. Recently, solo deep learning (SDL) models have been used, but they do not take advantage of the tandem connectivity offered by AI's hybrid nature.

Classification of COVID-19 by using supervised optimized machine learning technique.

In recent two years, covid-19 diseases is the most harmful diseases in entire world. This disease increase the high mortality rate in several developed countries. Earlier identification of covid-19 symptoms can avoid the over illness or death.

Hyperparameter Optimization for Transfer Learning of VGG16 for Disease Identification in Corn Leaves Using Bayesian Optimization.

One of the world's most widely grown crops is corn. Crop loss due to diseases has a major economic effect, putting the food supply in jeopardy. In many parts of the world, lack of infrastructure still slows disease diagnosis.

Recent Progress and Challenges in Hollow Fiber Membranes for Wastewater Treatment and Resource Recovery.

Membrane processes have been extensively employed in diverse applications, specifically in industrial wastewater treatment. The technological development in membrane processes has rapidly advanced and accelerated beyond its common principle and operation. Tremendous efforts have been made in the advancement of membrane materials, fabrication method, membrane modification and integration with other technologies that can augment the existing membrane processes to another level.

Ten Fast Transfer Learning Models for Carotid Ultrasound Plaque Tissue Characterization in Augmentation Framework Embedded with Heatmaps for Stroke Risk Stratification.

Only 1-2% of the internal carotid artery asymptomatic plaques are unstable as a result of >80% stenosis. Thus, unnecessary efforts can be saved if these plaques can be characterized and classified into symptomatic and asymptomatic using non-invasive B-mode ultrasound. Earlier plaque tissue characterization (PTC) methods were machine learning (ML)-based, which used hand-crafted features that yielded lower accuracy and unreliability.

Computational fluid dynamics-based disease transmission modeling of SARS-CoV-2 Intensive Care Unit.

Covid-19 has become one of the most severe diseases causing acute respiratory problems and has killed millions of people worldwide. It was declared as the ongoing pandemic by the World Health Organization. It is an infectious virus which can be transmitted by sneezing, coughing and exhalation of air by any infected person.

Application of a polymer-magnetic-algae based nano-composite for the removal of methylene blue - Characterization, parametric and kinetic studies.

The potential ability of synthesized PPy-FeO-SW nano-composite to remove Methylene Blue (MB) from synthetic textile dye solution was investigated under batch conditions. Through parametric studies, the influence of process parameters namely solution pH, on the effective performance of nano-composite was studied. PPy - FeO- SW nano-composite removed 99.

Identifying the natural compound Catechin from tropical mangrove plants as a potential lead candidate against 3CL from SARS-CoV-2: An integrated approach.

SARS-CoV-2, a member of beta coronaviruses, is a single-stranded, positive-sense RNA virus responsible for the COVID-19 pandemic. With global fatalities of the pandemic exceeding 4.57 million, it becomes crucial to identify effective therapeutics against the virus.

Properties and Performance Verification on Magnetite Polydimethylsiloxane Graphene Array Microwave Sensor.

This paper investigates the use of a Magnetite Polydimethylsiloxane (PDMS) Graphene array sensor in ultra-wide band (UWB) spectrum for microwave imaging applications operated within 4.0-8.0 GHz.

Adsorptive potential of iron oxide based nanocomposite for the sequestration of Congo red from aqueous solution.

The ability of polypyrrole-Iron oxide-seaweed nanocomposite has been tested for the removal of congo red from aqueous solution. The characteristics of nanocomposite after adsorption of Congo red (CR) have been analyzed. FTIR results authorized the involvement of various functional groups in the adsorption of CR.

Effect of Wettability and Uniform Distribution of Reinforcement Particle on Mechanical Property (Tensile) in Aluminum Metal Matrix Composite-A Review.

There is a massive demand for low-weight high strength materials in automotive, space aerospace, and even structural industries in this present engineering world. These industries attract composites only because of their high strength, resistance to wear, and low weight. Among these composites, metal matrix composite finds wide applications due to its elevated properties, excellent resistance property, corrosion resistance, etc.

An Experimental Multi-Target Tracking of AM Radio-Based Passive Bistatic Radar System via Multi-Static Doppler Shifts.

This paper presents a description of recent research and the multi-target tracking in experimental passive bistatic radar (PBR) system taking advantage of numerous non-cooperative AM radio signals via multi-static doppler shifts. However, it raises challenges for use by multiple spatially distributed AM radio illuminators for multi-target tracking in PBR system due to complex data association hypotheses and no directly used tracking algorithm in the practical scenario. To solve these problems, after a series of key array signal processing techniques in the self-developed system, by constructing a nonlinear measurement model, the novel method is proposed to accommodate nonlinear model by using the unscented transformation (UT) in Gaussian mixture (GM) implementation of iterated-corrector cardinality-balanced multi-target multi-Bernoulli (CBMeMBer).

Performance evaluation of polymer-marine biomass based bionanocomposite for the adsorptive removal of malachite green from synthetic wastewater.

In this experimental investigation, feasibility and performance of a polymer hybrid bio-nano composite were evaluated to remove malachite green (MG) under controlled environment conditions. The polymer hybrid bio-nanocomposite was characterized using FTIR, SEM and EDS. The influence of operating variables, namely effect of pH (2-11), nanocomposite dosage (20-100 mg), initial MG concentration (10- 200 mg/L), contact time (10-120 min) and temperature (298-318 K) were explored.

Evaluation of hybrid controllers for space vector modulation-inverter driven permanent magnet synchronous motor-pump assembly.

Many controllers are available in the market for controlling the Permanent Magnet Synchronous Motor (PMSM) drive application, though the most preferably used one is Proportional Integral (PI), controller. However, it is found that the PI and other latest controllers have their own merits and demerits while analyzing their outputs via comparison. Thus it is decided to test the deed of hybrid controllers that can serve a lot better than standalone controllers for precise control applications.

IoT-Enabled Wireless Sensor Networks for Air Pollution Monitoring with Extended Fractional-Order Kalman Filtering.

This paper presents the development of high-performance wireless sensor networks for local monitoring of air pollution. The proposed system, enabled by the Internet of Things (IoT), is based on low-cost sensors collocated in a redundant configuration for collecting and transferring air quality data. Reliability and accuracy of the monitoring system are enhanced by using extended fractional-order Kalman filtering (EFKF) for data assimilation and recovery of the missing information.

Spatial analysis and probabilistic risk assessment of exposure to fluoride in drinking water using GIS and Monte Carlo simulation.

Prevalence of fluorosis is a worldwide public health problem especially in many states of India. It is necessary to find out the fluoride endemic areas to adopt remedial measures to the people on the risk of fluorosis. The target goals of this research were to assess (a) the exposure of fluoride concentration; (b) probabilistic risk assessment, sensitivity analysis, and uncertainty through intake of groundwater among population of Agra City (infants, children and adults) by Crystal Ball software; and (c) spatial distribution of HQ and fluoride concentration.

Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application.

Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting.

Fuzzy segmentation and black widow-based optimal SVM for skin disease classification.

The skin, which has seven layers, is the main human organ and external barrier. According to the World Health Organization (WHO), skin cancer is the fourth leading cause of non-fatal disease risk. In medicinal fields, skin disease classification is a major challenging issue due to inaccurate outputs, overfitting, larger computational cost, and so on.

Free Convective Flow of Hamilton-Crosser Model Gold-water Nanofluid Through a Channel with Permeable Moving Walls.

Background: The present manuscript analyzes the influence of buoyant forces of a conducting time-dependent nanofluid flow through porous moving walls. The medium is also filled with porous materials. In addition to that, uniform heat source and absorption parameters are considered that affect the nanofluid model.

Microbial cellulases - An update towards its surface chemistry, genetic engineering and recovery for its biotechnological potential.

The inherent resistance of lignocellulosic biomass makes it impervious for industrially important enzymes such as cellulases to hydrolyze cellulose. Further, the competitive absorption behavior of lignin and hemicellulose for cellulases, due to their electron-rich surfaces augments the inappropriate utilization of these enzymes. Hence, modification of the surface charge of the cellulases to reduce its non-specific binding to lignin and enhance its affinity for cellulose is an urgent necessity.