Intrusion detection in metaverse environment internet of things systems by metaheuristics tuned two level framework.

Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure.

New Evidence for Scop. Extracts Application in Gastrointestinal Ailments.

Background/objectives: Scop. is traditionally used for treatment of various gastrointestinal ailments. In this study, we investigated the phytochemical profile and biological activities of leaves, bark and flowers extracts of Methods: Phytochemical analysis was performed using HPLC.

The Comparison of Classical Statistical and Machine Learning Methods in Prediction of Thrombosis in Patients with Acute Myeloid Leukemia.

Thrombosis is one of the most frequent complications of cancer, with a potential impact on morbidity and mortality, particularly those with acute myeloid leukemia (AML). Therefore, effective thrombosis prevention is a crucial aspect of cancer management. However, preventive measures against thrombosis may carry inherent risks and complications.

Introducing the Concept of Hypertensive Heart Disease to Improve Hypertensive Left Ventricular Hypertrophy.

Background: Among the organ damage mediated by hypertension, cardiac lesions hold significant importance. Numerous authors focus on hypertensive heart disease (HHD) rather than exclusively on left ventricular hypertrophy (LVH).

Objective: This narrative review aims to assess the incorporation of the concept of 'hypertensive heart disease' (HHD) in hypertension (HTN) guidelines.

Exploring the Interplay of Handgrip Neuromuscular, Morphological, and Psychological Characteristics in Tactical Athletes and General Population: Gender- and Occupation-Based Specific Patterns.

Background/objectives: The correlation of handgrip strength (HGS) and morphological characteristics with Big Five personality traits is well documented. However, it is unclear whether these relationships also exist in highly trained and specialized populations, such as tactical athletes, and whether there are specific differences compared to the general population. This study aimed to explore the interplay of handgrip neuromuscular, morphological, and psychological characteristics in tactical athletes and the general population of both genders.

Ozone/Thiosulfate-Assisted Leaching of Cu and Au from Old Flotation Tailings.

The growing demand for metal production promotes the search for alternative sources and novel modalities in metallurgy. Flotation tailings are an important secondary mineral resource; however, they might pose a potential environmental threat due to containing toxic metals. Therefore, proper leaching reagent selection is required.

Endurance Sports and Atrial Fibrillation: A Puzzling Conundrum.

The confirmed benefits of regular moderate exercise on cardiovascular health have positioned athletes as an illustration of well-being. However, concerns have arisen regarding the potential predisposition to arrhythmias in individuals engaged in prolonged strenuous exercise. Atrial fibrillation (AF), the most common heart arrhythmia, is typically associated with age-related risks but has been documented in otherwise healthy young and middle-aged endurance athletes.

Treatment of idiopathic scoliosis with conservative methods based on exercises: a systematic review and meta-analysis.

Introduction: This systematic review and meta-analysis aimed to systematically assess the effect size of conservative methods based on exercise for respondents with idiopathic scoliosis.

Methods: This study was developed in accordance with the PRISMA guidelines. The PubMed, Cochrane Library, Web of Science, and Google Scholar databases were searched in May 2023.

Sensory Deprivation in the Elderly Population of the Republic of Serbia: Sociodemographic Factors as Key to Understanding Sensory Challenges.

Background: Sensory impairments, notably hearing loss (68% in those aged 70+) and vision loss (24%-50%), are prevalent in older individuals. We investigated the correlation between visual and hearing impairments in older adults, considering sociodemographic factors, mental health, and social support.

Methods: The study is part of The Serbian 2019 National Health Survey, conducted in 2019.

What is in a label: Effects of labeling on the preference for plant-based products.

Our study investigated the effects of three labels on the preference for plant-based products: plant-based, vegan, and Lenten, referring to products appropriate to consume during religious fasting. We conducted two preregistered experiments to measure the effects of labeling on product preference (Study 1, N = 290) and actual tasting preferences (Study 2, N = 251) in a predominantly meat-eating European society (Serbia). We did not find statistically significant effects of labels on the preference for plant-based products in Study 1.

The trend in national childhood immunization program coverage throughout Serbian communities in Kosovo and Metohija from 2003 to 2022: pre-COVID-19 period vs. COVID-19 pandemic.

Background: The childhood immunization coverage in Serbian communities in Kosovo after the 1999 armed conflict has not been investigated. The study purpose was to evaluate the trend of immunization coverage with vaccines from the national childhood immunization program in Serbian communities in Kosovo and Metohija from 2003 to 2022.

Methods: Data were retrieved from the annual reports of the Public Health Institute of Kosovska Mitrovica received through notifications from the primary health centers where vaccines are being administered.

Machine learning classification meets migraine: recommendations for study evaluation.

The integration of machine learning (ML) classification techniques into migraine research has offered new insights into the pathophysiology and classification of migraine types and subtypes. However, inconsistencies in study design, lack of methodological transparency, and the absence of external validation limit the impact and reproducibility of such studies. This paper presents a framework of six essential recommendations for evaluating ML-based classification in migraine research: (1) group homogenization by clinical phenotype, attack frequency, comorbidity, therapy, and demographics; (2) defining adequate sample size; (3) quality control of collected and preprocessed data; (4) transparent training, testing, and performance evaluation of ML models, including strategies for data splitting, overfitting control, and feature selection; (5) interpretability of results with clinical relevance; and (6) open data and code sharing to facilitate reproducibility.

Sex-Specific Associations Between Lifestyle Factors and Sick Leave in the Serbian Working Population: Findings from the National Health Survey.

: Sick leave is influenced by various modifiable lifestyle factors and sex differences. This study investigates the associations between body mass index, fruit and vegetable consumption, physical activity, smoking, and alcohol consumption and sick leave among Serbia's working population, with emphasis on sex differences. : Data from the 2019 National Health Survey of Serbia were analyzed, involving a sample of 4652 individuals.

Optimized deep learning networks for accurate identification of cancer cells in bone marrow.

Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans to diagnose bone cancer. Manual methods are labor-intensive and may need specialized knowledge. As a result, creating an automated process for distinguishing between malignant and healthy bone is essential.

Sentiment classification for insider threat identification using metaheuristic optimized machine learning classifiers.

This study examines the formidable and complex challenge of insider threats to organizational security, addressing risks such as ransomware incidents, data breaches, and extortion attempts. The research involves six experiments utilizing email, HTTP, and file content data. To combat insider threats, emerging Natural Language Processing techniques are employed in conjunction with powerful Machine Learning classifiers, specifically XGBoost and AdaBoost.

Monitoring the Impact of Artificial Structure on Hydrogeological Environment: A Case Study of Hydraulic Tunnel at Pirot Hydropower Plant.

Artificial objects, particularly tunnels used for water transport under pressure, impact the geological and hydrogeological environment to a greater or lesser extent, and it is vital to assess their contributions to groundwater quality. Although tunnels are typically lined with concrete, their interaction with the hydrogeological environment intensifies over time. In this study, the detailed spatiotemporal monitoring of all hydrogeological features within the potential influence zone of the hydraulic tunnel of the Pirot Hydropower Plant has been conducted in order to determine the degree of interaction between the artificial object and the natural environment in real time, and to assess the correlation between monitored parameters.

Agreement and Sensitivity of the Acceleration-Velocity Profile Derived via Local Positioning System.

Sprint performance is commonly assessed via discrete sprint tests and analyzed through kinematic estimates modeled using a mono-exponential equation, including estimated maximal sprinting speed (MSS), relative acceleration (TAU), maximum acceleration (MAC), and relative propulsive maximal power (PMAX). The acceleration-velocity profile (AVP) provides a simple summary of short sprint performance using two parameters: MSS and MAC, which are useful for simplifying descriptions of sprint performance, comparison between athletes and groups of athletes, and estimating changes in performance over time or due to training intervention. However, discrete testing poses logistical challenges and defines an athlete's AVP exclusively from the performance achieved in an isolated testing environment.

Intrusion detection using metaheuristic optimization within IoT/IIoT systems and software of autonomous vehicles.

The integration of IoT systems into automotive vehicles has raised concerns associated with intrusion detection within these systems. Vehicles equipped with a controller area network (CAN) control several systems within a vehicle where disruptions in function can lead to significant malfunctions, injuries, and even loss of life. Detecting disruption is a primary concern as vehicles move to higher degrees of autonomy and the possibility of self-driving is explored.

System and method to diagnose conjunctivitis in the eye of a user.

This Proposed work explores how machine learning can be used to diagnose conjunctivitis, a common eye ailment. The main goal of the study is to capture eye images using camera-based systems, perform image pre-processing, and employ image segmentation techniques, particularly the UNet++ and U-net models. Additionally, the study involves extracting features from the relevant areas within the segmented images and using Convolutional Neural Networks for classification.

Uncovering pathways towards sustainable transportation: Investigating factors influencing societal acceptance of end-of-life vehicle management in Indonesia.

Addressing the critical environmental challenge of end-of-life vehicle (ELV) management in Indonesia's transportation industry, this study investigates the complex interplay between societal factors and technical adoption. We use a comprehensive survey and path analysis to investigate the relationships between demographic characteristics (gender, age, income and education) and ELV acceptance, revealing complex preferences and concerns across several population groups. Comparative analyses with previous research reveal gender-specific inequities and age-related problems, emphasizing the importance of customized measures.

Proposal of a Modified Classification of Hypertensive Crises: Urgency, Impending Emergency, and Emergency.

Systemic arterial hypertension (HTN) is the main cause of morbidity and mortality, and HTN crises contribute significantly to an unfavourable clinical course. For decades, HTN crises have been dichotomized into hypertensive emergency (HTN-E) and hypertensive urgency (HTN-U). The main difference between the two is the presence of acute hypertension-mediated organ damage (HMOD) - if HMOD is present, HTN crisis is HTN-E; if not, it is HTN-U.

The impact of sociodemographic and health aspects on cognitive performance in the older adult population in the republic of Serbia.

The aim of this study was to investigate how sociodemographic and health factors contribute cognitive abilities in the older population of the Republic of Serbia, using data from the 2019 national health survey. The study included 3,743 participants, of whom 2,061 (55.1%) were women and 1,682 (44.

Unraveling symptom interplay: a network analysis of procrastination in gifted students.

Background: This study explores the intricate web of symptoms experienced by academically gifted high school students, focusing on procrastination, rumination, perfectionism, and cognitive flexibility. The well-being of these gifted adolescents remains a pivotal concern, and understanding the dynamics of these symptoms is vital.

Methods: A diverse sample of 207 academically gifted high school students from Mashhad, Iran, participated in this study.