Exploring strong controlled partial metric type spaces: Analysis of fixed points and theoretical contributions.

This study involves the generalization of partial metric spaces and strong controlled metric type spaces through the introduction of the notion of strong controlled partial metric type spaces. This research pursues a dual objective: firstly, to scrutinize fixed points related to contractions of the Kannan type within the framework of strong controlled partial metric type spaces, encompassing both linear and nonlinear contractions; secondly, to furnish illustrative examples and applications that underscore the consequential implications of our theoretical contributions.

Molecularly imprinted polymer composite membranes: From synthesis to diverse applications.

This review underscores the fundamentals of MIP-CMs and systematically summarizes their synthetic strategies and applications, and potential developments. MIP-CMs are widely acclaimed for their versatility, finding applications in separation, filtration, detection, and trace analysis, as well as serving as scaffolds in a range of analytical, biomedical and industrial contexts. Also characterized by extraordinary selectivity, remarkable sensitivity, and outstanding capability to bind molecules, those membranes are also cost-effective, highly stable, and configurable in terms of recognition and, therefore, inalienable in various application fields.

Analysis of a stochastic epidemic model incorporating the Ornstein-Uhlenbeck process.

This article aims to analyze a stochastic epidemic model (Susceptible-exposed-undetected infected-detected infected (reported -recovered) assuming that the transmission rate at which people undetected become detected is perturbed by the Ornstein-Uhlenbeck process. Our first objective is to prove that the stochastic model has a unique positive global solution by constructing a nonnegative Lyapunov function. Afterward, we provide a sufficient criterion to prove the existence of an ergodic stationary distribution of the mode by constructing a suitable series of Lyapunov functions.

Electrophoretic deposition of polyvinyl alcohol, C-H NRs along with moringa on an SS substrate for orthopedic implant applications.

Metals are commonly used in bone implants due to their durability and load-bearing capabilities, yet they often suffer from biofilm growth and corrosion. To overcome these challenges, implants with enhanced biocompatibility, bioactivity, and antimicrobial properties are preferred. Stainless steel (SS) implants are widely favored in orthopedics for their mechanical strength and cost-effectiveness.

Adaptive fixed-time TSM for uncertain nonlinear dynamical system under unknown disturbance.

For nonlinear systems subjected to external disturbances, an adaptive terminal sliding mode control (TSM) approach with fixed-time convergence is presented in this paper. The introduction of the fixed-time TSM with the sliding surface and the new Lemma of fixed-time stability are the main topics of discussion. The suggested approach demonstrates quick convergence, smooth and non-singular control input, and stability within a fixed time.

Tailoring NiCoCu layered double hydroxide with Ag-citrate/polyaniline/functionalized SWCNTs nanocomposites for supercapacitor applications.

Supercapacitors have substantially altered the landscape of sophisticated energy storage devices with their exceptional power density along with prolonged cyclic stability. On the contrary, their energy density remains low, requiring research to compete with conventional battery storage devices. This study addresses the disparities between energy and power densities in energy storage technologies by exploring the integration of layered double hydroxides (LDH) and highly conductive materials to develop an innovative energy storage system.

Four port tri-circular ring MIMO antenna with wide-band characteristics for future 5G and mmWave applications.

MIMO (Multiple-Input-Multiple-Output) antenna systems are promising for fifth-generation (5G) networks, offering lower latency and higher data rates. These systems utilize millimeter-wave (mmWave) frequency bands for efficient transmission and reception of multiple data simultaneously, enhancing overall efficiency and performance. This article presents a compact size, wide band tri-circular ring mmWave MIMO antenna with suitable performance characteristics for next-generation communication systems.

Real-Time Diagnosis System of COVID-19 Using X-Ray Images and Deep Learning.

The novel coronavirus named COVID-19 has quickly spread among humans worldwide, and the situation remains hazardous to the health system. The existence of this virus in the human body is identified through sputum or blood samples. Furthermore, computed tomography (CT) or X-ray has become a significant tool for quick diagnoses.

Positive Effect of Kinesiotape on 1 km Run Performance in University-Level Males: A Cross-Sectional Study.

Introduction: The kinesiotape (KT) method is used to exert a positive effect on muscular, nervous, and organ systems, recognizing the importance of muscle movement. It is widely applied in runners for performance enhancement. However, there is no scientific background to use it as a running speed modulator.

Inline Skating as an Additional Activity for Alpine Skiing: The Role of the Outside Leg in Short Turn Performance.

The complexity of skiing movements urges recreational alpine skiers and competitors to undertake many specific skill trainings not only during the season but also during the off-season using alternative sports. In AS, the role of the outside leg is crucial for successful turn performance. By measuring kinematic and kinetic parameters, we could define whether there is an objective similarity of the role and the movements of the outside leg while performing a turn in AS to those in the most used additional activity, IS.

Microscopic handcrafted features selection from computed tomography scans for early stage lungs cancer diagnosis using hybrid classifiers.

Lung's cancer is the leading cause of cancer-related deaths worldwide. Recently cancer mortality rate and incidence increased exponentially. Many patients with lung cancer are diagnosed late, so the survival rate is shallow.

Covid19-Mexican-Patients' Dataset (Covid19MPD) Classification and Prediction Using Feature Importance.

Coronavirus disease, Covid19, pandemic has a great effect on human heath worldwide since it was first detected in late 2019. A clear understanding of the structure of the available Covid19 datasets might give the healthcare provider a better understanding of identifying some of the cases at an early stage. In this article, we will be looking into a Covid19 Mexican Patients' Dataset (Covid109MPD), and we will apply number of machine learning algorithms on the dataset to select the best possible classification algorithm for the death and survived cases in Mexico, then we will study the performance of the enhancement of the specified classifiers in term of their features selection in order to be able to predict sever, and or death, cases from the available dataset.

Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria.

The novel coronavirus infectious disease (or COVID-19) almost spread widely around the world and causes a huge panic in the human population. To explore the complex dynamics of this novel infection, several mathematical epidemic models have been adopted and simulated using the statistical data of COVID-19 in various regions. In this paper, we present a new nonlinear fractional order model in the Caputo sense to analyze and simulate the dynamics of this viral disease with a case study of Algeria.

Ensuring data integrity of healthcare information in the era of digital health.

Data integrity continues to be a persistent problem in the current healthcare sector. It ensures that the data is correct and has not even in any manner been improperly changed. Incorrect data might become significant health threats for patients and a big responsibility for clinicians, resulting in problems such as scam, misconduct, inadequate treatment and data theft.

Threshold condition and non pharmaceutical interventions's control strategies for elimination of COVID-19.

In this work we focus on the eradication of the COVID-19 infection with the help of almost Non Pharmaceutical Interventions(NPIs), using mathematical modelling. First the basic reproduction number is investigated. Then, on the basis of sensitivity test of , the most active/sensitive parameters are presented in detail.

Secure and energy-efficient framework using Internet of Medical Things for e-healthcare.

In various fields, the internet of things (IoT) gains a lot of popularity due to its autonomous sensors operations with the least cost. In medical and healthcare applications, the IoT devices develop an ecosystem to sense the medical conditions of the patients' such as blood pressure, oxygen level, heartbeat, temperature, etc. and take appropriate actions on an emergency basis.

Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection.

Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and bleeding) through wireless capsule endoscopy (WCE) is still a key challenge.

Feature enhancement framework for brain tumor segmentation and classification.

Automatic medical image analysis is one of the key tasks being used by the medical community for disease diagnosis and treatment planning. Statistical methods are the major algorithms used and consist of few steps including preprocessing, feature extraction, segmentation, and classification. Performance of such statistical methods is an important factor for their successful adaptation.

An ensemble classification of exudates in color fundus images using an evolutionary algorithm based optimal features selection.

Atomic recognition of the Exudates (EXs), the major symbol of diabetic retinopathy is essential for automated retinal images analysis. In this article, we proposed a novel machine learning technique for early detection and classification of EXs in color fundus images. The major challenge observed in the classification technique is the selection of optimal features to reduce computational time and space complexity and to provide a high degree of classification accuracy.

Movement Activity Determination with Health-related Variables of University Students in Kosice.

Introduction: There is currently a strong scientific evidence about the negative health consequences of physical inactivity. One of the potential tools for promoting physical activity at the institutional level of the Ecological model is to create conditions and settings that would enable pupils, students and employees engage in some form of physical activity. However, physical activities as a subject are being eliminated from the study programs at Slovak universities.

Microscopic abnormality classification of cardiac murmurs using ANFIS and HMM.

Auscultation of heart dispenses identification of the cardiac valves. An electronic stethoscope is used for the acquisition of heart murmurs that is further classified into normal or abnormal murmurs. The process of heart sound segmentation involves discrete wavelet transform to obtain individual components of the heart signal and its separation into systole and diastole intervals.

Retinal imaging analysis based on vessel detection.

With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection.

Report: Nuclei segmentation of leukocytes in blood smear digital images.

The Leukocytes are differentiated from each other on the basis of their nuclei, demanded in many Medical studies, especially in all types of Leukemia by the Hematologists to note the disorder caused by specific type of Leukocyte. Leukemia is a life threatening disease. The work for diagnosing is manually carried out by the Hematologists involving much labor, time and human errors.