Cardiovascular disease (CVD) remains the leading cause of mortality in women. Estimating cardiovascular risk using prediction models is essential for guiding preventive strategies. Despite progress, conventional risk models still omit critical women-specific factors, limiting their accuracy. Precision medicine, supported by artificial intelligence, provides a framework to integrate these overlooked determinants. This approach may help close existing gaps in cardiovascular risk prediction. Sex-specific biomarkers that contribute to overall cardiovascular risk can be incorporated into risk assessment tools to improve prevention strategies, early detection, and personalized intervention. The integration of imaging-derived variables enh

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad

This study aimed to explore The Degree of Practicing of the Sixth Primary Social Studies’ Teachers in Iraq for the Principles of Active Learning from their Point of view

The study society consisted of 230 male and femalesocial studiesteachers’ subjects for the sixth primary grade in Al-Anbar General Directorate of Education. 160 of them were selected to represent the sample of the study with a percent of (70%) from the original society. To achieve the aims of the study, the researchers prepared a questionnaire consisting of (43) items which represented the active learning principles. The validity and stability of the tool were verified. The researchers used the descriptive approach to suit the objectives of this study. &

The aim of the research was to prepare the fields and items for safe environment scale form professional basketball players and coaches’ point of view. The researchers used the descriptive method on professional athletes of players and coaches from (11) clubs; for the pilot study (21) athletes were selected and for the building sample (103) athletes, and standardization sample (101) athletes from the participants in the Iraqi league (2018-2019). The scale of the safe environment was concluded with (6) fields and (52) items. The researchers came up with the safe environment scale from the point of view of professional basketball players and coaches. Finally the researchers recommended paying attention to providing safe environment for athl

تصف هذه الدراسة تطوير تقنية سهلة ورخيصة ودقيقة وسريعة لقياس 4-اثيل فينول وتنطوي الطريقة الأولية على تحويل -3 نيترو انيلين إلى ملح ديازونيوم ثم التفاعل مع 4 - إثيل فينول في وسط قلوي.المعقد المتكون هو أصفر اللون وله امتصاص عند اعلى طول موجي عند 426 nm. ويتبع قانون بير في مدى خطي قدره 5-12 μg mL-1 مع معامل ارتباط قدره 0.994 وامتصاص مولاري 6.0024x10^3  L.mol-1.cm-1  وتم استُخدِام تقنية نقطة السحابة لقياس كميات قليلة جدا من الفينول باس