Biogenic Ag-doped ZnO nanostructures induced cytotoxicity in luminal A and triple-negative human breast cancer cells.

To evaluate the apoptosis-inducing properties of undoped and silver-doped-zinc-oxide nanoparticles (SDZONs) synthesized using against MCF-7 (Luminal-A) and MDA-MB-231 (Triple-negative) breast cancer cell lines. Nanostructures were developed by facile biohydrothermal method and characterized by x-ray diffraction (XRD), Fourier transform infrared (FTIR), and high resolution transmission electron microscopy (HR-TEM). The comparative effect of doping and dose concentration of nanostructures on cytotoxicity was measured using MTT and trypan-blue-exclusion assay.

S-WD-EEMD: A hybrid framework for imbalanced sEMG signal analysis in diagnosis of human knee abnormality.

The diagnosis of human knee abnormalities using the surface electromyography (sEMG) signal obtained from lower limb muscles with machine learning is a major problem due to the noisy nature of the sEMG signal and the imbalance in data corresponding to healthy and knee abnormal subjects. To address this challenge, a combination of wavelet decomposition (WD) with ensemble empirical mode decomposition (EEMD) and the Synthetic Minority Oversampling Technique (S-WD-EEMD) is proposed. In this study, a hybrid WD-EEMD is considered for the minimization of noises produced in the sEMG signal during the collection, while the Synthetic Minority Oversampling Technique (SMOTE) is considered to balance the data by increasing the minority class samples during the training of machine learning techniques.

Numerical simulation for MHD Oldroyd-B fluid flow with melting and slip effect.

This investigation reflects an examination of Oldroyd-B fluid flow over a permeable surface subjected to the effects of melting, slip effect, inclined magnetic field and chemical reactions. The governing equations are resolved using the bvp4c inbuilt MATLAB tool, the arithmetic computation for the momentum, thermal and concentration equations are executed. The results are exhibited graphically.

High rates of nitrogen removal in aerated VFCWs treating sewage through C-N-S cycle.

The efficiency of deep aerated vertical flow constructed wetlands (DA-VFCWs) being operated in Hyderabad, India, was evaluated herein using physicochemical analysis and 16S rRNA amplicon sequencing. The results showed 2-4-fold higher removal rate coefficients for Biochemical oxygen demand (1.32---3.

Enhanced Route navigation control system for turtlebot using human-assisted mobility and 3-D SLAM optimization.

An autonomous, power-assisted Turtlebot is presented in this paper in order to enhance human mobility. The turtlebot moves from its initial position to its final position at a predetermined speed and acceleration. We propose an intelligent navigation system that relies solely on individual instructions.

Bibliometric analysis, physical properties, and experimental evaluation of additives-diesel ternary blends.

The availability of petroleum fuels is being challenged due to high demand and heavy dependence on imports, raising awareness of the need for cleaner alternatives. Urbanization, air quality, economic factors, and emissions limits motivate the search for alternative fuels compatible with compression ignition engines. A comprehensive bibliometric analysis further underscores the escalating worldwide research efforts in this critical domain.

MHD micro polar fluid flow over a stretching surface with melting and slip effect.

Objective of the present analysis is to represent the phenomenon of Heat-mass transfer on MHD micro polar fluids caused by permeable and continuously stretching sheet along with slip impacts fostered in a porous medium. Consequently, the equation of energy includes the term of non-uniform heat source/sink. The equation regarding species concentration in cooperates the terms indicating order of chemical reaction to characterize the chemically reactive species.

Assessment of removal rate coefficient in vertical flow constructed wetland employing machine learning for low organic loaded systems.

Secondary datasets of 42 low organic loading Vertical flow constructed wetlands (LOLVFCWs) were assessed to optimize their area requirements for N and P (nutrients) removal. Significant variations in removal rate coefficients (k) (0.002-0.

Cow-urine emulsified diesel fuel: preparation, stability, and rheological study for diesel engine application.

Water-diesel emulsion fuel has been found as a prominent alternative fuel by various researchers. Alike this technology, cow-urine (Bos indicus urine) emulsified diesel fuel (GMD emulsion) has been explored in this study. Making of homogeneous and stable emulsion is a crucial aspect in this approach while maintaining the diesel standards.

Siamese-Based Architecture for Cross-Lingual Plagiarism Detection in English-Hindi Language Pairs.

The cross-lingual plagiarism detection (CLPD) is a challenging problem in natural language processing. Cross-lingual plagiarism is when a text is translated from any other language and used as it is without proper acknowledgment. Most of the existing methods provide good results for monolingual plagiarism detection, whereas the performances of existing methods for the CLPD are very limited.

Human lower limb activity recognition techniques, databases, challenges and its applications using sEMG signal: an overview.

Human lower limb activity recognition (HLLAR) has grown in popularity over the last decade mainly because to its applications in the identification and control of neuromuscular disorders, security, robotics, and prosthetics. Surface electromyography (sEMG) sensors provide various advantages over other wearable or visual sensors for HLLAR applications, including quick response, pervasiveness, no medical monitoring, and negligible infection. Recognizing lower limb activity from sEMG signals is also challenging owing to the noise in the sEMG signal.

Cyber-Internet Security Framework to Conquer Energy-Related Attacks on the Internet of Things with Machine Learning Techniques.

The Internet of Things (IoT) ushers in a new era of communication that depends on a broad range of things and many types of communication technologies to share information. This new age of communication will be characterised by the following characteristics: Because all of the IoT's objects are connected to one another and because they function in environments that are not protected, it poses a significantly greater number of issues, constraints, and challenges than do traditional computing systems. This is due to the fact that traditional computing systems do not have as many interconnected components.

An efficient modular framework for automatic LIONC classification of MedIMG using unified medical language.

Handwritten prescriptions and radiological reports: doctors use handwritten prescriptions and radiological reports to give drugs to patients who have illnesses, injuries, or other problems. Clinical text data, like physician prescription visuals and radiology reports, should be labelled with specific information such as disease type, features, and anatomical location for more effective use. The semantic annotation of vast collections of biological and biomedical texts, like scientific papers, medical reports, and general practitioner observations, has lately been examined by doctors and scientists.

Identification of characteristics frequency and hot-spots in protein sequence of COVID-19 disease.

COVID-19 has threatened the whole world since December 2019 and has also infected millions of people around the globe. It has been transmitted through the SARS CoV-2 virus. Various proteins of the SARS CoV-2 virus have an important role in its interaction with human cells.

Energy, exergy, environmental impact, and economic analyses of evacuated tube compound parabolic concentrator-powered solar thermal domestic water heating system.

In the reported study, a dynamic analytical model is developed to propose the energy, exergy, environmental impact, and economic analyses of the water heating system at Jaipur (India) with an evacuated tube compound parabolic concentrator field of a total area of 81 m. Consequently, the model is used to perform parametric studies to report the effect of operating and meteorological parameters on the productivity and performance of the system. Moreover, the system's performance, environmental impact, and economic aspects have been investigated and compared under different meteorological conditions at four different Rajasthan (India) locations using TMY2 weather data files.

Intelligent Wearable Devices Enabled Automatic Vehicle Detection and Tracking System with Video-Enabled UAV Networks Using Deep Convolutional Neural Network and IoT Surveillance.

The discipline of computer vision is becoming more popular as a research subject. In a surveillance-based computer vision application, item identification and tracking are the core procedures. They consist of segmenting and tracking an object of interest from a sequence of video frames, and they are both performed using computer vision algorithms.

A Liver Damage Prediction Using Partial Differential Segmentation with Improved Convolutional Neural Network.

Background: The liver is one of the most significant and most essential organs in the human body. It is divided into two granular lobes, one on the right and one on the left, connected by a bile duct. The liver is essential in the removal of waste products from human food consumption, the creation of bile, the regulation of metabolic activities, the cleaning of the blood by sensitizing digestive management, and the storage of vitamins and minerals.

Intelligent Diagnostic Prediction and Classification Models for Detection of Kidney Disease.

Kidney disease is a major public health concern that has only recently emerged. Toxins are removed from the body by the kidneys through urine. In the early stages of the condition, the patient has no problems, but recovery is difficult in the later stages.

Zika Virus Prediction Using AI-Driven Technology and Hybrid Optimization Algorithm in Healthcare.

The Zika virus presents an extraordinary public health hazard after spreading from Brazil to the Americas. In the absence of credible forecasts of the outbreak's geographic scope and infection frequency, international public health agencies were unable to plan and allocate surveillance resources efficiently. An RNA test will be done on the subjects if they are found to be infected with Zika virus.

Voting-based 1D CNN model for human lower limb activity recognition using sEMG signal.

Surface electromyography (sEMG) signal classification has many applications such as human-machine interaction, diagnosis of kinesiological studies, and neuromuscular diseases. However, these signals are complicated because of different artifacts added to the sEMG signal during recording. In this study, a multi-stage classification technique is proposed for the identification of distinct movements of the lower limbs using sEMG signals acquired from leg muscles of healthy knee and abnormal knee subjects.

Grey forecasting models based on internal optimization for Novel Corona virus (COVID-19).

Pandemic forecasting has become an uphill task for the researchers on account of the paucity of sufficient data in the present times. The world is fighting with the Novel Coronavirus to save human life. In a bid to extend help to the concerned authorities, forecasting engines are invaluable assets.

Use of 2-methoxyethyl ether and nitromethane as oxygenated additives for performance improvement and emission reduction of CI engine: experimental investigation and numerical simulation.

Diesel engines are playing a vital responsibility in the field of automobile, agriculture, construction, and power generation. In the present world, much research is going on in the field of renewable energy to replace conventional sources of energy. But it is not very easy to replace diesel engines with other sources due to the better power output and reliability.

A state of the art on solar-powered vapor absorption cooling systems integrated with thermal energy storage.

The intermittent nature of solar energy is a dominant factor in exploring well-designed thermal energy storages for consistent operation of solar thermal-powered vapor absorption systems. Thermal energy storage acts as a buffer and moderator between solar thermal collectors and generators of absorption chillers and significantly improves the system performance. Vapor absorption chillers are available in half, single, double, and triple-effect modes of operation and operate at temperatures ranging from 75 to 220 °C to produce a cooling effect with COPs ranging from 0.

Development and applications of an intelligent crow search algorithm based on opposition based learning.

Metaheuristics are proven beneficial tools for solving complex, hard optimization problems. Recently, a plethora of work has been reported on bio inspired optimization algorithms. These algorithms are mimicry of behavior of animals, plants and processes into mathematical paradigms.

Effect of diesel-methanol-nitromethane blends combustion on VCR stationary CI engine performance and exhaust emissions.

The continuous rise in cost of fossil fuels and environmental pollution has attracted research in the area of clean alternative fuels for improving the performance and emission of internal combustion engines. In the present work, methanol and nitromethane were treated as a biofuel and investigations have been made to evaluate the feasibility of replacing diesel with a suitable diesel-methanol-nitromethane blend. For this, experimental investigations were carried out on a VCR diesel engine using diesel-methanol-nitromethane blends to determine the most favorable blending ratio and engine operating parameters for enhancing performance and reduce emissions.