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Energy Engineering 2024年第4期121卷 849-867页

作者： Mousumi Basu Chitralekha Jena Baseem Khan ahmed ali Department of Power Engineering Jadavpur UniversityJadavpurIndia School of Electrical Engineering KIIT UniversityBhubaneswarIndia Department of Electrical and Computer Engineering Hawassa UniversityHawassaEthiopia Department of Electrical and Electronic Engineering Technology Faculty of Engineering and the Built EnvironmentUniversity of JohannesburgJohannesburgSouth Africa

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

关键词： Micro-grid distributed energy resources demand response program uncertainty outage

Theories behind Bacillus Calmette-Guerin failure in high-risk non-muscle-invasive bladder cancer and update on current management

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Cancer Pathogenesis and Therapy 2024年第2期2卷 74-80页

作者： Hanna Maroof Louise Paramore ahmed ali Department of Urology Frimley Park HospitalPortsmouth RdFrimleyCamberley GU167UJUnited Kingdom

Bladder cancer encapsulates a wide spectrum of disease severities,with non-muscle invasive bladder cancer(NMIBC)representing an entirely different entity from muscle-invasive disease.Bacillus Calmette-Guerin(BCG)is one of the most successful intravesical treatment methods for patients diagnosed.However,a considerable pro-portion of patients fail to respond to BCG treatment.Given the propensity for recurrence in patients with high-risk bladder cancer,these patients present with surgical dilemmas.There is currently no gold standard for salvage treatment post-BCG failure or unified definition as to what that means.In this review,we discuss the mechanisms of action and pathophysiology of BCG,potential theories behind BCG failure,and the scope of novel treatments forthis surgical conundrum.

关键词： Cystectomy Hyperthermia Induced Immunotherapy Mycobacterium bovis Non-muscle-invasive bladder cancer

Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1539-1562页

作者： Samar M.Alqhtani Toufique A.Soomro Faisal Bin Ubaid ahmed ali Muhammad Irfan Abdullah A.Asiri Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer Science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries.Magnetic resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain images.MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders.Typically,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention.However,early diagnosis of brain tumors is intricate,necessitating the use of computerized methods.This research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain tumors.The proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third step.The final step involves classification using the Support Vector Machine(SVM)classifier.The classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)database.The proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of 0.957.Additionally,this method exhibits a shorter processing time of 0.44 s compared to existing approaches.The performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and DSC.To enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classification method.

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

Single nucleotide polymorphism within chromosome 8q24 is associated with prostate cancer development in Saudi Arabia

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Asian Journal of Urology 2024年第1期11卷 26-32页

作者： Awad Elsid Osman Sahar Alharbi Atif ali ahmed Asim ali Elbagir Pathology and Clinical Laboratory Management Department(PCLM) King Fahad Medical CityRiyadhSaudi Arabia Department of Pathology and Laboratory Medicine University of Missouri at Children's Mercy HospitalKansas CityMOUSA

Objective: Genome-wide association studies have demonstrated that single nucleotide polymorphisms (SNPs) are important risk factors for the development of prostate cancer (PCa). Preliminary studies have suggested that the incidence of PCa in Saudi males is low but is probably familial or genetically related.Methods: To identify any possible association of SNP with PCa development in Saudi patients, we investigated a group of SNPs in Saudi PCa patients (n=85) and compared the outcomes to healthy normal controls (n=115) and nodular hyperplasia patients (n=120). DNA was extracted from paraffin-embedded formalin fixed tissue or whole blood from both patients’ groups and healthy control group. A total of thirteen SNPs were genotyped using TaqMan® minor groove binder polymerase chain reaction assay.Results: The rs16901979A, s629242T and rs1447295A alleles were found at significantly higher frequency in PCa patients than controls (p< 0.05). The rs16901979 CA genotype was found at significantly greater frequency in PCa patients than in healthy controls (43% vs. 14%, odds ratio=4.6, p=0.0001) and benign hyperplasia group (43% vs. 25%, odds ratio=2.2, p=0.009).Conclusion: Our study has highlighted the association of rs16901979 SNP with PCa in Saudi males. Such findings have important implications in the PCa diagnosis and in screening unaffected family members of Saudi patients.

关键词： Prostatecancer Saudi Singlenucleotide polymorphism Allele

Multifaceted roles of extracellular RNAs in different diseases

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Military Medical Research 2023年第3期10卷 359-368页

作者： Abdullah Muhammad Sohail Muhammad Babar Khawar ali Afzal ali Hassan Sara Shahzaman ahmed ali Molecular Medicine and Cancer Therapeutics Lab Department of ZoologyFaculty of SciencesUniversity of Central PunjabLahorePakistan Applied Molecular Biology and Biomedicine Lab Department of ZoologyUniversity of NarowalNarowalPakistan

Extracellular RNAs(exRNAs) are novel circulating factors that can be used as biomarkers in various diseases. Their unique and diverse kinds, as well as their role as biomarkers, make them significant biomarkers. There has been immense work carried out since the discovery of exRNAs in circulation and other biological fluids to catalog and determine whether exRNAs may be utilized as indicators for health and illness. In this review, we aim to understand the current state of exRNAs in relation to various diseases and their potential as biomarkers. We will also review current issues and challenges faced in using exRNAs, with clinical and lab trials, that can be used as viable markers for different diseases.

关键词： Extracellular RNAs(exRNAs) Extracellular vehicles(EVs) Cancer Biomarkers Exosomes

Neurosurgical and pharmacological management of dystonia

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World Journal of Psychiatry 2024年第5期14卷 624-634页

作者： ali ahmed Mohamed Steven Faragalla Asad Khan Garrett Flynn Gersham Rainone Phillip Mitchell Johansen Brandon Lucke-Wold Charles E Schmidt College of Medicine Florida Atlantic UniversityBoca RatonFL 33431United States Department of Neurosurgery and Brain Repair University of South FloridaTampaFL 33606United States Department of Neurosurgery University of FloridaGainesvilleFL 32611United States

Dystonia characterizes a group of neurological movement disorders characterized by abnormal muscle movements,often with repetitive or sustained contraction resulting in abnormal posturing.Different types of dystonia present based on the affected body regions and play a prominent role in determining the potential efficacy of a given intervention.For most patients afflicted with these disorders,an exact cause is rarely identified,so treatment mainly focuses on symptomatic alleviation.Pharmacological agents,such as oral anticholinergic administration and botulinum toxin injection,play a major role in the initial treatment of patients.In more severe and/or refractory cases,focal areas for neurosurgical intervention are identified and targeted to improve quality of life.Deep brain stimulation(DBS)targets these anatomical locations to minimize dystonia symptoms.Surgical ablation procedures and peripheral denervation surgeries also offer potential treatment to patients who do not respond to DBS.These management options grant providers and patients the ability to weigh the benefits and risks for each individual patient profile.This review article explores these pharmacological and neurosurgical management modalities for dystonia,providing a comprehensive assessment of each of their benefits and shortcomings.

关键词： Botulinum toxin Magnetic resonance imaging-guided focused ultrasound Surgical ablation Deep brain stimulation Peripheral denervation surgery Antipsychotics

Price Prediction of Seasonal Items Using Time Series Analysis

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Computer Systems Science & Engineering 2023年第7期46卷 445-460页

作者： ahmed Salah Mahmoud Bekhit Esraa Eldesouky ahmed ali ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business domain.There are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal items.This lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series task.We proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based models.Thus,this research tuned a set of well-known predictive models on a real-life dataset.Those models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear regression.Moreover,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are proposed.Then,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined models.The obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

A Deep Learning Ensemble Method for Forecasting Daily Crude Oil Price Based on Snapshot Ensemble of Transformer Model

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Computer Systems Science & Engineering 2023年第7期46卷 929-950页

作者： ahmed Fathalla Zakaria Alameer Mohamed Abbas ahmed ali Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt Mining and Petroleum Department Faculty of EngineeringAl-Azhar UniversityQenaEgypt School of Computer Science and Technology Central South UniversityChangshaHunanChina College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Higher Future Institute for Specialized Technological Studies Cairo3044Egypt

The oil industries are an important part of a country’s economy.The crude oil’s price is influenced by a wide range of variables.Therefore,how accurately can countries predict its behavior and what predictors to employ are two main questions.In this view,we propose utilizing deep learning and ensemble learning techniques to boost crude oil’s price forecasting performance.The suggested method is based on a deep learning snapshot ensemble method of the Transformer model.To examine the superiority of the proposed model,this paper compares the proposed deep learning ensemble model against different machine learning and statistical models for daily Organization of the Petroleum Exporting Countries(OPEC)oil price forecasting.Experimental results demonstrated the outperformance of the proposed method over statistical and machine learning methods.More precisely,the proposed snapshot ensemble of Transformer method achieved relative improvement in the forecasting performance compared to autoregressive integrated moving average ARIMA(1,1,1),ARIMA(0,1,1),autoregressive moving average(ARMA)(0,1),vector autoregression(VAR),random walk(RW),support vector machine(SVM),and random forests(RF)models by 99.94%,99.62%,99.87%,99.65%,7.55%,98.38%,and 99.35%,respectively,according to mean square error metric.

关键词： Deep learning ensemble learning transformer model crude oil price

Pyronaridine combined with diminazene aceturate inhibits Babesia in vitro and in vivo

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Asian Pacific Journal of Tropical Biomedicine 2024年第3期14卷 93-99页

作者： Shimaa Abd El-Salam El-Sayed Mohamed Z.Sayed-ahmed Shaimaa ahmed Awad ali Nourah Alsadaan Nawazish Alam Mahmoud S.Alkhoudary Ikuo Igarashi Mohamed Abdo Rizk National Research Center for Protozoan Diseases Obihiro University of Agriculture and Veterinary MedicineInada-ChoObihiroHokkaido 080-8555Japan Department of Biochemistry and Chemistry of Nutrition Faculty of Veterinary MedicineMansoura UniversityMansoura 35516Egypt Department of Clinical Pharmacy College of PharmacyJazan UniversityJazan 45142Saudi Arabia Medical-Surgical Department College of NursingJouf UniversitySakaka 72388Saudi Arabia Critical Care and Emergency Nursing Faculty of NursingMansoura UniversityEgypt College of Nursing Jouf UniversitySakaka 72388Saudi Arabia Faculty of Pharmacy Mansoura UniversityMansoura 35516DakahliaEgypt Department of Internal Medicine and Infectious Diseases Faculty of Veterinary MedicineMansoura UniversityMansoura 35516Egypt

Objective:To evaluate the combination therapy of pyronaridine tetraphosphate and diminazene aceturate against Babesia in vitro and in vivo.Methods:Bioinformatic analysis was performed using atom pair fingerprints.An in vitro combination test was performed against Babesia bovis and Theileria equi.Moreover,the in vivo chemotherapeutic efficacy of pyronaridine tetraphosphate in combination with diminazene aceturate was investigated against the growth of Babesia microti in mice using a fluorescence inhibitory assay.Results:Pyronaridine tetraphosphate and diminazene aceturate exhibited nearly similar molecular weights.The in vitro combination of pyronaridine tetraphosphate and diminazene aceturate was synergistic on Babesia bovis and additive on Theileria equi.In addition,5 mg/kg pyronaridine tetraphosphate combined with 10 mg/kg diminazene aceturate inhibited Babesia microti growth significantly compared with those observed after treatment with 25 mg/kg diminazene aceturate alone from day 6 post treatment to day 12 post treatment.The combination therapy also normalized the hematological parameters of infected mice.Conclusions:An oral dose of pyronaridine tetraphosphate combined with a subcutaneous dose of diminazene aceturate inhibits Babesia in vitro and in mice,suggesting it might be a new paradigm for the treatment of babesiosis.

关键词： Babesia Pyronaridine tetraphosphate Diminazene aceturate Babesiosis Theileria

Updates on management of gliomas in the molecular age

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World Journal of Clinical Oncology 2024年第2期15卷 178-194页

作者： ali ahmed Mohamed Rakan Alshaibi Steven Faragalla Youssef Mohamed Brandon Lucke-Wold Charles E.Schmidt College of Medicine Florida Atlantic UniversityBoca RatonFL 33431United States Herbert Wertheim College of Medicine Florida International UniversityMiamiFL 33199United States College of Osteopathic Medicine Kansas City UniversityJoplinMO 64804United States Department of Neurosurgery University of FloridaGainesvilleFL 32611United States

Gliomas are primary brain tumors derived from glial cells of the central nervous system,afflicting both adults and children with distinct characteristics and therapeutic challenges.Recent developments have ushered in novel clinical and molecular prognostic factors,reshaping treatment paradigms based on classi-fication and grading,determined by histological attributes and cellular lineage.This review article delves into the diverse treatment modalities tailored to the specific grades and molecular classifications of gliomas that are currently being discussed and used clinically in the year 2023.For adults,the therapeutic triad typically consists of surgical resection,chemotherapy,and radiotherapy.In contrast,pediatric gliomas,due to their diversity,require a more tailored approach.Although complete tumor excision can be curative based on the location and grade of the glioma,certain non-resectable cases demand a chemotherapy approach usually involving,vincristine and carboplatin.Addi-tionally,if surgery or chemotherapy strategies are unsuccessful,Vinblastine can be used.Despite recent advancements in treatment methodologies,there remains a need of exploration in the literature,particularly concerning the efficacy of treatment regimens for isocitrate dehydrogenase type mutant astrocytomas and fine-tuned therapeutic approaches tailored for pediatric cohorts.This review article explores into the therapeutic modalities employed for both adult and pediatric gliomas in the context of their molecular classification.

关键词： Gliomas Chemotherapy Radiotherapy Isocitrate dehydrogenase type mutant Pediatric gliomas Astrocytoma Oligodendroglioma 1p/19q-codeleted