Identifying genetic susceptibility loci associated with human coronary artery disease.

Coronary artery disease (CAD) is a multigenic condition influenced by both nature and nurture (60% to 40%). Prognosis of CAD is based on familial patterns. This study examined and analyzed the susceptibility of CAD to genetic variants in various Pakistani families.

Talent management intervention towards performance outcomes of Jordanian telecommunication companies: mediating role of perceived organizational support.

Background: Grounding on the Resource-Based View (RBV) and organization support theory (OST), this study examines the effect of talent management practice (TMP) on perceived organizational support (POS), organizational performance (OP), and employee performance (EP) within the Jordanian telecom sector, with a specific focus on the mediating effect of POS's between TMP-EP and OP relationship.

Methods: This study uses a cross-sectional method to collect data from 397 personnel at three Jordanian telecom enterprises. The Smart-PLS application assisted with structural equation modeling, which was used to examine the data.

Csec-net: a novel deep features fusion and entropy-controlled firefly feature selection framework for leukemia classification.

Leukemia, a life-threatening form of cancer, poses a significant global health challenge affecting individuals of all age groups, including both children and adults. Currently, the diagnostic process relies on manual analysis of microscopic images of blood samples. In recent years, machine learning employing deep learning approaches has emerged as cutting-edge solutions for image classification problems.

An optimized dynamic attribute-based searchable encryption scheme.

Cloud computing liberates enterprises and organizations from expensive data centers and complex IT infrastructures by offering the on-demand availability of vast storage and computing power over the internet. Among the many service models in practice, the public cloud for its operation cost saving, flexibility, and better customer support popularity in individuals and organizations. Nonetheless, this shift in the trusted domain from the concerned users to the third-party service providers pops up many privacy and security concerns.

IoT-based framework for optimizing energy efficiency and reliability in acoustic sensor networks using mobile sinks.

In today's world, there is an increasing demand for environmental monitoring, surveillance, and oceanographic research, which poses challenges in improving energy efficiency and data transfer reliability in Acoustic Sensor Networks. Existing methods face hurdles due to limited energy resources and unreliable data transmission. We propose a Reliable and Energy-Efficient Framework with Sink Mobility (REEFSM) to address these issues.

SentinelFusion based machine learning comprehensive approach for enhanced computer forensics.

In the rapidly evolving landscape of modern technology, the convergence of blockchain innovation and machine learning advancements presents unparalleled opportunities to enhance computer forensics. This study introduces SentinelFusion, an ensemble-based machine learning framework designed to bolster secrecy, privacy, and data integrity within blockchain systems. By integrating cutting-edge blockchain security properties with the predictive capabilities of machine learning, SentinelFusion aims to improve the detection and prevention of security breaches and data tampering.

NeuroHealth guardian: A novel hybrid approach for precision brain stroke prediction and healthcare analytics.

Stroke is a severe illness, that requires early stroke detection and intervention, as this would help prevent the worsening of the condition. The research is done to solve stroke prediction problem, which may be divided into a number of sub-problems such as an individual's predisposition to develop stroke. To attain this objective, a multiturn dataset consisting of various health features, such as age, gender, hypertension, and glucose levels, takes a central role.

Unveiling the nexus between perceived overqualification and knowledge hiding: Moderated mediation analysis of job crafting and job boredom.

Purpose: Grounding on relative deprivation theory, this study aimed to investigate the relationship between perceived overqualification (POQ) and knowledge hiding. Furthermore, this study investigated the mediating role of job boredom and the moderating effect of job crafting.

Design: /Methodology/Approach: This study employs Hayes' PROCESS model to analyze data obtained from 374 employees working in the hospitality and tourism industry.

Enhancing gain and isolation of a quad-element MIMO antenna array design for 5G sub-6 GHz applications assisted with characteristic mode analysis.

This paper presents a novel quad-element array with multiple inputs and multiple outputs (MIMO) designed for 5th generation sub-6 GHz applications. The MIMO system achieves a wide impedance bandwidth, high gain, and high isolation among its components, representing significant advancements in sub-6 GHz antenna applications. The single element, an elliptical resonator with a circular slot, is fed by a 50 Ω microstrip feedline, achieves a broad characteristic bandwidth from 3.

Phytogenic-Mediated Zinc Oxide Nanoparticles Using the Seed Extract of and Its Integrated Potency against Multidrug Resistant Bacteria.

In the current research study, zinc oxide nanoparticles (ZnO-NPs) were synthesized via a green synthesis technique using the seed extract of . The study further intended to evaluate the potential synergistic effects of ZnO-NPs with antibiotics against multidrug resistant (MDR) bacteria. It was observed that seed extracts obtained by -hexane and methanolic solvents revealed the presence of constituents, such as tannins, flavonoids, and terpenoids.

Exploring the Impact of Artificial Intelligence on Global Health and Enhancing Healthcare in Developing Nations.

Background: Artificial intelligence (AI), which combines computer science with extensive datasets, seeks to mimic human-like intelligence. Subsets of AI are being applied in almost all fields of medicine and surgery.

Aim: This review focuses on the applications of AI in healthcare settings in developing countries, designed to underscore its significance by comprehensively outlining the advancements made thus far, the shortcomings encountered in AI applications, the present status of AI integration, persistent challenges, and innovative strategies to surmount them.

A Sensor Placement Approach Using Multi-Objective Hypergraph Particle Swarm Optimization to Improve Effectiveness of Structural Health Monitoring Systems.

In this paper, a novel Multi-Objective Hypergraph Particle Swarm Optimization (MOHGPSO) algorithm for structural health monitoring (SHM) systems is considered. This algorithm autonomously identifies the most relevant sensor placements in a combined fitness function without artificial intervention. The approach utilizes six established Optimal Sensor Placement (OSP) methods to generate a Pareto front, which is systematically analyzed and archived through Grey Relational Analysis (GRA) and Fuzzy Decision Making (FDM).

Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed.

The intricate and multifaceted nature of diabetes disrupts the body's crucial glucose processing mechanism, which serves as a fundamental energy source for the cells. This research aims to predict the occurrence of diabetes in individuals by harnessing the power of machine learning algorithms, utilizing the PIMA diabetes dataset. The selected algorithms employed in this study encompass Decision Tree, K-Nearest Neighbor, Random Forest, Logistic Regression, and Support Vector Machine.

Assessment of fall-associated risk factors in the Muslim community-dwelling older adults of Peshawar, Khyber Pakhtunkhwa, Pakistan.

Background: Falls are the third-leading cause of disability among the elderly population worldwide. It is multifactorial, and the occurrence of falls depends on different factors, which can be different from context to context, and individual to individual. Therefore, regular assessment of fall risk factors is required to develop a strategy for fall prevention.

An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce.

Artificial Intelligence (AI) has become essential to Electronic-Commerce technology over the past decades. Its fast growth has changed the way consumers do online shopping. Using the Technology Acceptance Model (TAM) as a theoretical framework, this research examines how AI can be made more effective and profitable in e-commerce and how entrepreneurs can make AI technology to assist in achieving their business goals.

Genetic Investigation of Consanguineous Pakistani Families Segregating Rare Spinocerebellar Disorders.

Spinocerebellar disorders are a vast group of rare neurogenetic conditions, generally characterized by overlapping clinical symptoms including progressive cerebellar ataxia, spastic paraparesis, cognitive deficiencies, skeletal/muscular and ocular abnormalities. The objective of the present study is to identify the underlying genetic causes of the rare spinocerebellar disorders in the Pakistani population. Herein, nine consanguineous families presenting different spinocerebellar phenotypes have been investigated using whole exome sequencing.

A Four Element mm-Wave MIMO Antenna System with Wide-Band and High Isolation Characteristics for 5G Applications.

In this article, we propose a light weight, low profile Multiple Input Multiple Output (MIMO) antenna system for compact 5th Generation (5G) mmwave devices. Using a RO5880 substrate that is incredibly thin, the suggested antenna is made up of circular rings stacked vertically and horizontally on top of one another. The single element antenna board has dimensions of 12 × 12 × 0.

Investigating the Effectiveness of Novel Support Vector Neural Network for Anomaly Detection in Digital Forensics Data.

As criminal activity increasingly relies on digital devices, the field of digital forensics plays a vital role in identifying and investigating criminals. In this paper, we addressed the problem of anomaly detection in digital forensics data. Our objective was to propose an effective approach for identifying suspicious patterns and activities that could indicate criminal behavior.

Enhancing Security and Privacy in Healthcare Systems Using a Lightweight RFID Protocol.

Exploiting Radio Frequency Identification (RFID) technology in healthcare systems has become a common practice, as it ensures better patient care and safety. However, these systems are prone to security vulnerabilities that can jeopardize patient privacy and the secure management of patient credentials. This paper aims to advance state-of-the-art approaches by developing more secure and private RFID-based healthcare systems.

A Compact MIMO Multiband Antenna for 5G/WLAN/WIFI-6 Devices.

This research work presents a compact design of a Multiple-Input Multiple-Output (MIMO) multiband antenna along with high-isolation characteristics. The presented antenna was designed for 3.50 GHz, 5.

Neuroprotective effects of vitamin B1 on memory impairment and suppression of pro-inflammatory cytokines in traumatic brain injury.

Traumatic Brain Injury (TBI) remains one of the prevailing disorders that affect millions of people around the globe. There is a cascade of secondary attributes attached to TBI including excitotoxicity, axonal degeneration, neuroinflammation, oxidative stress, and apoptosis. Neuroinflammation is caused due to the activation of microglia along with pro-inflammatory cytokines.

Real-World Driver Stress Recognition and Diagnosis Based on Multimodal Deep Learning and Fuzzy EDAS Approaches.

Mental stress is known as a prime factor in road crashes. The devastation of these crashes often results in damage to humans, vehicles, and infrastructure. Likewise, persistent mental stress could lead to the development of mental, cardiovascular, and abdominal disorders.

Linking public leadership with project management effectiveness: Mediating role of goal clarity and moderating role of top management support.

Objective: Grounding on social learning theory (SLT), this study examines the effect of public leadership on project management effectiveness (PME). Further, this study examines the mediating role of goal clarity and moderating role of top management support.

Methodology: Hierarchical linear regressions were used to investigate the relationships.