The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

    The present study was conducted in order to focus on the effect of the addition of Carnitine and Niacin on some blood serum parameters of Common Carp Cyprinus Carpio. 48 fish carp mean weight 44.13 gm were distributed randomly on four feeding treatments (12 fish each) with replicates (6 fish each) in 8 glass aquaria. Treatments were as follows: fish were fed on basic diet without any addition and conducted as control (T1); addition of 200 mg Carnitine/ Kg diet, (T2) addition of 28 mg Niacin/Kg diet (T3), addition of a mixture of 200 mg Carnitine and 28 mg Niacin/ Kg diet as (T4). The experiment was conducted for 70 days and the results showed an increase in the Cholesterol concentration of T1 (187.6 mg/ 100 ml) and differed s

Dried imported blood worms Chironomus reparius was used to motivate the growth of young carp Cyprinus carpio L ., as fish powder was partial and total replaced by blood worms which is a component of the fodder of the common carp fish. Results have shown that blood worm partial replacement treatment surpasses the imported fish powder. Rates of growth motivation of this treatment have been higher than both the control and total replacement processes. Results have shown significant differences in the weight of the fish in the partial replacement of the fish powder by the blood worms.

Interleukin-38 (IL-38), an inflammatory cytokine discovered in recent years, has been implicated in the pathogenesis of systemic lupus erythematosus (SLE). IL-38 is encoded by the IL1F10 (interleukin 1 family member 10) gene. Genetic variants of this gene have been associated with susceptibility to a number of autoimmune and inflammatory diseases, while their association with SLE risk has not been explored. In this case–control study, two novel variants of the 5 prime untranslated region (5′UTR) of the IL1F10 gene, rs3811050 C/T and rs3811051 T/G, were investigated

Amis: NAFLD is considered to be the most common cause of liver conditions worldwide. Also, it is a primary reason that leads to coronary artery diseases, limiting blood flow to the heart. Therefore, This study aimed to evaluate the serum level of Nesfatin-1 and its ability to indicate the prognosis of CAD in patients with NAFLD. Material & Methods: one-hundred eighty Individuals were enrolled in the study, including In both genders, blood was collected from each Individual and sent to the laboratory for biochemical tests. Findings: Data from the current study showed a significant increase in Nesfatin-1 in the CAD group and a significant decrease in Nesfatin-1 in the NAFLD group compared to the control group. In addition, there w