Epileptic seizure detection from electroencephalogram (EEG) signals using linear graph convolutional network and DenseNet based hybrid framework

A clinical condition known as epilepsy occurs when the brain's regular electrical activity is disturbed, resulting in a rapid, aberrant, and excessive discharge of brain neurons. The electroencephalogram (EEG) signal is the measurement of electrical activity received from the nerve cells of the cerebral cortex to make precise diagnoses of disorders, which is made crucial attention for treating epilepsy patients in recent years. The concentration on grid-like data has been a significant drawback of existing deep learning-based automatic epileptic seizure detection algorithms from raw EEG signals; nevertheless, physiological recordings frequently have irregular and unordered structures, making it challenging to think of them as a matrix. In order to take advantage of the implicit information that exists in seizure detection, graph neural networks have received a lot of attention. These networks feature interacting nodes connected by edges whose weights can be either dictated by temporal correlations or anatomical junctions. To address this limitation, a novel hybrid framework is proposed for epileptic seizure detection by using linear graph convolution neural network (LGCN) and DenseNet. When compared to previous deep learning networks, DenseNet achieves the model's higher computational accuracy and memory efficiency by reducing the vanishing gradient problem and enhancing feature propagation in each of its layers. The Stockwell transform (S-transform) is used to preprocess from the raw EEG signal and then group the resulting matrix into time-frequency blocks as inputs for the LGCN to use for feature selection and after the Densenet uses for classification. The proposed hybrid framework outperforms the state-of-the-art in seizure detection tasks, achieving 98% accuracy and 98.60% specificity in extensive experiments on the publicly available CHB-MIT EEG dataset

Case Study on CFD investigation of dense phase pneumatic conveying at a pipeline enlargement

Pneumatic conveying is being widely used by industry for their conveying system and the most critical problem that the system has is the corrosion of the pipeline. Some of the many engineers has develop a solution order to reduce the corrosion rate of the pipeline that is to increase the diameter of the pipe with objective to reduce the flow velocities as the flow velocities contribute the most in corroding the pipeline. By using Fluent 6.3.26 simulation program, ‘Eulerian’ Computational Fluid Dynamic (CFD) model, simulating the movement of the particles is possible and by varying the three different pipeline geometry; single bore, abrupt step, and gradual step, constructed using Gambit 2.4.6 from a pipe bore of 75-100 mm. The flow behaviour of plug of material passing through the pipeline is investigated. With 5x10-3 s time step, the solid volume fractions is recorded at 0.01 s of flow time at the point of enlargement and visualised throughout the pipe. Supported by 5 m/s air flow, the plug movement is illustrated showing that there is a potential of stagnant zone formation with the abrupt step enlargement geometry, and on the other hand, the gradual step shows a smooth dispersed particle flow without any potential of stagnant zone formation

قواعد نفي الحرج وأثرها زمن وباء كورونا: دراسة تأصيلية مقاصدية فقهية

الأهداف: يهدف هذا البحث لبيان أثر قواعد التيسير، ورفع الحرج في الأحكام الفقهية زمن فيروس كورونا. المنهجية: اتبع الباحث في ذلك المنهج الاستقرائي باستقراء أقوال المذاهب والفقهاء في كل مسألة، والمنهج المقارن، بمقارنة أقوالهم وأدلتهم والترجيح بينها. النتائج: خلص هذا البحث إلى أن لقواعد الشريعة الفقهية الكلية المتضمنة للتيسير ورفع الحرج، أثرا عظيما في إصدار الأحكام الفقهية زمن المستجدات والنوازل المعاصرة، ومنها فيروس كورونا، حيث كان لها مدخل عظيم في تسهيل كثير من الأحكام الفقهية على الناس، ورفع المشقة عنهم، وهي مع ذلك لم تخرج تلك الأحكام بذلك عن نطاق الحق وموافقة الشرع، إذ الشرع أصلا جاء لجلب مصالح العباد، ودفع المفاسد عنهم، وظهر ذلك جليا في التخفيف في طهارة مريض كورونا وصلاته، وتيسير أمور عبادات الناس ومعاملاتهم. التوصيات: يوصي البحث بالتعريف بمنهج الشريعة الإسلامية في التيسير، ودفع الحرج من خلال المحاضرات والمؤتمرات الدولية، والتعريف بالأحكام الفقهية أثناء النوازل، مستصحبين روح الشريعة الإسلامية في التخفيف والتيسير ، مما يؤكد كونها شريعة ربانية صالحة لكل زمان ومكان وظرف

Lund -Mackay staging for rhinosinusitis, correlation between computed tomography scan score and intraoperative findings

Objective: We have conducted this study to evaluate the accuracy of Lund – Mackay scoring system for rhinosinusitis with regards to time lag between dates of both CT scan and operation. Methods: A total of 120 rhinosinusitis patients, divided into three groups according to time lag between date of performing sinuses CT scan and date of surgery. Group A, the time lag was more than 8 weeks, in group B the time lag was 2-8 weeks, and group C, the time lag was less than two weeks. All patients underwent endoscopic sinus surgery; rhinosinusitis was staged using Lund – Mackay system and compared intraoperative findings using the same scoring system. Results: There was a significant difference in staging score in group A, and in group B although the difference was not statistically significant, it was scientifically noticed, in group C there was no difference between the preoperative and intraoperative scores. Conclusion: The correlation between Lund – Mackay staging and intraoperative finding in endoscopic sinus surgery depends on the time lag between scan date and surgery date, the shorter the time lag the better the correlation

Effect of Using New Technology Vehicles on the World’s Environment and Petroleum Resources

Nowadays the trend toward the use of transportation technologies which are clean and less dependent on fossil fuel is highly increased. That is because of the fast depletion of oil reserves in the world, on the other hand the growth of developing nations into industrialized one’s will increase the demand on the energy sector , in which transportation occupy a large percent of it. This increase of transportation sector will affect the environment as a result of greenhouse gases. In this paper the use of several types of clean energy vehicles is demonstrated compared with classical internal combustion engine one’s, with statistical demonstration and the energy conversion chain, also the impact of hybrid vehicles on the petroleum reserves and consumption rates will be discussed using some mathematical equations

Performance evaluation of logarithmic spiral search and selective mechanism based arithmetic optimizer for parameter extraction of different photovoltaic cell models.

The imperative shift towards renewable energy sources, driven by environmental concerns and climate change, has cast a spotlight on solar energy as a clean, abundant, and cost-effective solution. To harness its potential, accurate modeling of photovoltaic (PV) systems is crucial. However, this relies on estimating elusive parameters concealed within PV models. This study addresses these challenges through innovative parameter estimation by introducing the logarithmic spiral search and selective mechanism-based arithmetic optimization algorithm (Ls-AOA). Ls-AOA is an improved version of the arithmetic optimization algorithm (AOA). It combines logarithmic search behavior and a selective mechanism to improve exploration capabilities. This makes it easier to obtain accurate parameter extraction. The RTC France solar cell is employed as a benchmark case study in order to ensure consistency and impartiality. A standardized experimental framework integrates Ls-AOA into the parameter tuning process for three PV models: single-diode, double-diode, and three-diode models. The choice of RTC France solar cell underscores its significance in the field, providing a robust evaluation platform for Ls-AOA. Statistical and convergence analyses enable rigorous assessment. Ls-AOA consistently attains low RMSE values, indicating accurate current-voltage characteristic estimation. Smooth convergence behavior reinforces its efficacy. Comparing Ls-AOA to other methods strengthens its superiority in optimizing solar PV model parameters, showing that it has the potential to improve the use of solar energy

Comprehensive comparison of cloud-based NGS data analysis and alignment tools

Next-Generation Sequencing (NGS) is very helpful for conducting DeoxyriboNucleic Acid (DNA) Sequencing. DNA sequencing is the process for determining the order (sequence) of the main chemical bases in the DNA. Analyzing human DNA sequencing is important for determining the possibility that a person will develop certain diseases, and/or the ability to respond to medication. However, the NGS process is a complicated and resource-hungry technical process. To solve this dilemma, the majority of NGS software systems are deployed as cloud-based services distributed over cloud-based platforms. Cloud-based platforms provide promising solutions for the computationally intensive tasks required by the NGS data analysis. This work provides a comprehensive investigation of cloud-based NGS data analysis and alignment tools, both the commercial and the open-source tools. We also discuss in detail the main features and setup requirements for each tool, and then compare and contrast between them. Moreover, we extensively analyze and classify the studied NGS data analysis and alignment tools to help NGS biomedical researchers and clinicians in finding appropriate tools for their work, while understanding the similarities and the differences between them

Metachromatic leukodystrophy associated with choledochal cysts and gallbladder papillomatosis

Metachromatic Leukodystrophy (MLD) is an autosomal recessive lysosomal storage disease caused by the deficiency of the enzyme arylsulfatase A which is responsible for the desulfation of cerebroside sulfate, a myelin glycolipid. Accumulation of these sulfatides in the macrophages of various tissues causes a wide spectrum of presentations including central and peripheral nervous system dysfunction and gallbladder abnormalities. We report a case of a 6-year old girl with infantile Metachromatic Leukodystrophy who was found to have elevated liver enzymes, biliary markers and total and direct bilirubin during work-up for unexplained high-grade fever. Imaging showed dilated intra and extra hepatic biliary tree, markedly expanded CBD by dense content and multiple variable sized filling defects with narrowing in between. The dense content was confirmed to be mucosal papillomatosis with hyperplastic epithelium. To the authors' knowledge, obstructive extra-hepatic biliary tree polypoid masses and cystic dilation with metachromatic leukodystrophy have not previously been reported. Keywords: Metachromatic leukodystrophy, Gallbladder papillomatosis, Choledochal cyst

Automatic Generation Control of a Hybrid PV-Reheat Thermal Power System Using RIME Algorithm

This study focuses on the automatic generation control (AGC) system, which is crucial for maintaining balance between power generation and demand in power systems. The implementation of the AGC system needs to be more precise due to the increasing uncertainty surrounding renewable energy sources (RESs) and changes in demand. The objective of this study is to investigate the AGC functions in a two-area hybrid power system that combines a PV system with a reheat thermal system. To improve system performance, we utilize a proportional-integral (PI) controller. We utilized a recently developed optimization method, RIME, for tuning controller parameters. This technique has not been studied before in AGC processes. Furthermore, the optimization procedure utilizes a modified version of the integral of time-multiplied absolute error (ITAE) objective function. The study compares the performance of the RIME-tuned PI controller under various scenarios, including changes in thermal system load, load variations in both areas, and robustness considerations, with well-known techniques in the literature, such as the black widow optimization algorithm (BWOA), the salp swarm algorithm (SSA), the shuffled frog leaping algorithm (SFLA), the firefly algorithm (FA) and the genetic algorithm (GA). Our comparative study demonstrates that the proposed controller outperforms state-of-the-art approaches in terms of overshoot values and damping durations for both system frequency and tie-line power changes. The study provides valuable information on the effectiveness of the RIME-tuned PI controller in controlling AGC processes in complex hybrid power systems