Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreAdvanced drug delivery systems offer undeniable benefits for drug delivery. In the past three decades, new methods have been proposed to develop a novel carriers for drug delivery. Nowadays, the major goal is to maximize therapeutic benefit while minimizing side effects. Drug delivery technique is clearly shifting from the micro to nanoscale. Nano-drug delivery systems (NDDSs) are the most promising approach utilized to improve the accuracy of drug delivery and the efficacy of drugs.In this narrative review article, we evaluate how delivery challenges associated with commercial marketed products and discuss newer DDS is being carried out to overcome these challenges .Different colloidal carrier systems such as carbon nanotube ,li
... Show Morethin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness
تم في هذا البحث استخدام المحفز الجديد المصنع من تحميل دقائق البلاتين النانوية على سطح الصفائح النانوية للكرافين كمحفز ضوئي واختباره لدراسة التجزئة الضوئية لملوثات المياه وازالتها بشكل نهائي من مصادر المياه لما لها من تأثير سلبي على البيئة. حيث تم استخدام صبغة البروموفينول الأزرق كمثال على أحد الملوثات. في البدء تم التأكد من تحضير المحفز بالطريقة المستخدمة في طريقة العمل من خلال تشخيصه باستخدام عدد من ا
... Show Moreتم في هذا البحث استخدام المحفز الجديد المصنع من تحميل دقائق البلاتين النانوية على سطح الصفائح النانوية للكرافين كمحفز ضوئي واختباره لدراسة التجزئة الضوئية لملوثات المياه وازالتها بشكل نهائي من مصادر المياه لما لها من تأثير سلبي على البيئة. حيث تم استخدام صبغة البروموفينول الأزرق كمثال على أحد الملوثات. في البدء تم التأكد من تحضير المحفز بالطريقة المستخدمة في طريقة العمل من خلال تشخيصه باستخدام عدد من ا
... Show MorePerennial biofuel and cover crops systems are important for enhancing soil health and can provide numerous soil, agricultural, and environmental benefits. The study objective was to investigate the effects of cover crops and biofuel crops on soil hydraulic properties relative to traditional management for claypan soils. The study site included selected management practices: cover crop (CC) and no cover crop (NC) with corn/soybean rotation, switchgrass (SW), and miscanthus (MI). The CC mixture consisted of cereal rye, hairy vetch, and Austrian winter pea. The research site was located at Bradford Research Center in Missouri, USA, and was implemented on a Mexico silt loam. Intact soil cores (76‐mm diam. by 76‐mm long) were taken from the
... Show MoreThis paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for