Background: The majorities of statin-treated patients, in whom low-density lipoprotein cholesterol (LDL-C) targets have been achieved, have had recurrent cardiovascular events (CVE) with an absolute rate remain even higher among patients with disorders of insulin resistance, metabolic syndrome (MetS) and type2 diabetes mellitus (T2DM) as compared to patients devoid of these conditions.Objectives: Provide updated key messages of lipid and lipoprotein abnormalities as indicator for cardiovascular disease (CVD) risk in patients with T2DM and obesity, as well as the current evidence-based treatment targets and interventions to reduce this risk.Key messages: The Residual Risk Reduction Initiative (R3I) emphasized atherogenic dyslipidemia (AD)

 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, K_oc, of 147 L/kg which is more moveable than XXXX, and another one

Abstract

The current study presents numerical investigation of the fluid (air) flow characteristics and convection heat transfer around different corrugated surfaces geometry in the low Reynolds number region (Re<1000). The geometries are included wavy, triangle, and rectangular. The effect of different geometry parameters such as aspect ratio and number of cycles per unit length on flow field characteristics and heat transfer was estimated and compared with each other. The computerized fluid dynamics package (ANSYS 14) is used to simulate the flow field and heat transfer, solve the governing equations, and extract the results. It is found that the turbulence intensity for rectangular extended surface was larg

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

The process involved isolating E. faecium from the gut of honeybees, screening the bacterium for bacteriocin-like inhibitory substance (BLIS), evaluating its impact on the expression of the mexA gene in multidrug-resistant (MDR) P. aeruginosa, and determining the role of bacteriocin in treating infected wounds in mice through histopathological examination. After evaluating the best circumstances for producing BLIS, it was discovered that glucose was a superior carbon source and yeast extract was the best source of nitrogen. The pH was found to be 5, the ideal incubation time was 72 hours, and ammonium sulfate salt was used for partial purification at 80% saturation. The identification of MDR P. aeruginosa isolates from pus infection

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

Abstract

The present search addressed the "strategic Vigilance and their impact in Organizational success "Where has the objective of strategic Vigilance and Organizational success of increasing importance at the present time, for being fairly modern topics, which have a tremendous impact on the success of organizations.                                                                  &

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