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Experimental evaluation of Candonocypris novaezelandiae(Crustacea:Ostracoda) in the biocontrol of Schistosomiasis mansoni transmission

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Asian Pacific Journal of Tropical Biomedicine 2013年第4期3卷 267-272页

作者： Fouad Yousif Sherif Hafez samia el bardicy Menerva Tadros Hoda Abu Taleb Department of Environmental Research and Medical Malacology Theodor Bilharz Research InstituteWarrak El Hadar.Imbaba.Egypt Department of Plant Protection Faculty of AgricultureAin Shams UniversityCairoEgypt Department of Environmental Research and Medical Malacology.Theodor Bilharz Research Institute Warrak El Hadar.Imbaba.Egypt

Objective:To test Candonocypris novaezelandiae(Baird)(***),sub-class Ostracoda,obtained from the Nile,Egypt for its predatory activity on snail,Biomphalaria alexandrina(***),intermediate host of Schistosoma mansoni(***)and on the free-living larval stages of this parasite(miracidia and cercariae).Methods:The predatory activity of *** was determined on *** snail(several densities of eggs,newly hatched and juveniles).This activity was also determined on *** miracidia and cercariae using different volumes of water and different numbers of *** was also tested for its effect on infection of snails and on the cercarial ***:*** was found to feed on the eggs,newly hatched and juvenile snails,but with significant reduction in the consumption in the presence of other diet like the blue green algae(Nostoc muscorum).This ostracod also showed considerable predatory activity on the free-living larval stages of *** which was affected by certain environmental factors such as volume of water,density of *** and number of larvae of the ***:The presence of this ostracod in the aquatic habitat led to significant reduction of snail population,infection rate of snails with schistosme miracidia as well as of cercarial production from the infected *** may suggest that introducing *** into the habitat at schistosome riskv sites could suppress the transmission of the disease.

关键词： Candonocypris novaezelandiae Schistosoma mansoni Biomphalaria alexandrina Biological control Schistosomiasis

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

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Computers, Materials & Continua 2024年第1期78卷 873-897页

作者： Shereen K.Refaay samia A.Ali Moumen T.el-Melegy Louai A.Maghrabi Hamdy H.el-Sayed Faculty of Computers and Artificial Intelligence Sohag UniversitySohag82524Egypt Faculty of Engineering Assiut UniversityAssiut711745Egypt College of Engineering University of Business and TechnologyJeddah23411Saudi Arabia

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s *** studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor *** paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial *** proposed algorithms lack algorithm-specific parameters and metaphorical *** proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned *** proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing *** compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)*** efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base *** experimental results were compared with those obtained using the Jaya optimization *** proposed algorithms exhibited the best *** proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base sta

关键词： Wireless sensor networks Rao algorithms optimization LEACH PEAGSIS

A Robust Approach for Multi Classification-Based Intrusion Detection through Stacking Deep Learning Models

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Computers, Materials & Continua 2024年第6期79卷 4845-4861页

作者： samia Allaoua Chelloug Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Intrusion detection is a predominant task that monitors and protects the network ***,many datasets have been published and investigated by researchers to analyze and understand the problem of intrusion prediction and *** particular,the Network Security Laboratory-Knowledge Discovery in Databases(NSL-KDD)is an extensively used benchmark dataset for evaluating intrusion detection systems(IDSs)as it incorporates various network traffic *** is worth mentioning that a large number of studies have tackled the problem of intrusion detection using machine learning models,but the performance of these models often decreases when evaluated on new *** has led to the utilization of deep learning techniques,which have showcased significant potential for processing large datasets and therefore improving detection *** that reason,this paper focuses on the role of stacking deep learning models,including convolution neural network(CNN)and deep neural network(DNN)for improving the intrusion detection rate of the NSL-KDD *** base model is trained on the NSL-KDD dataset to extract significant *** the base models have been trained,the stacking process proceeds to the second stage,where a simple meta-model has been trained on the predictions generated from the proposed base *** combination of the predictions allows the meta-model to distinguish different classes of attacks and increase the detection *** experimental evaluations using the NSL-KDD dataset have shown the efficacy of stacking deep learning models for intrusion *** performance of the ensemble of base models,combined with the meta-model,exceeds the performance of individual *** stacking model has attained an accuracy of 99%and an average F1-score of 93%for the multi-classification ***,the training time of the proposed ensemble model is lower than the training time of benchmark techniques,demonstrating its efficien

关键词： Intrusion detection multi classification deep learning stacking NSL-KDD

Polio in Gaza:Another disastrous outcome of the Gaza conflict,2023-2024

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Asian Pacific Journal of Tropical Medicine 2024年第9期17卷 381-383页

作者： Zuhair Dardona Mounia Amane samia Boussaa Microbial Biotechnologies Agro sciences and Environment Laboratory(BioMAgE)Faculty of Sciences SemlaliaCadi Ayyad UniversityMarrakeshMoroccoGovernmental Medical ServicesGazaPalestine ISPITS-Higher Institute of Nursing and Health Techniques Ministry of HealthMarrakechMorocco ISPITS-Higher Institute of Nursing and Health Techniques Ministry of HealthRabatMorocco

On October 7th,2023,a devastating conflict erupted between Gaza and Israel,causing around 40000 deaths and over 90000 *** war has displaced more than 1.9 million people,who now live in overcrowded tent camps facing severe shortages of clean water,sanitation,fuel,electricity,and *** rely on international aid and resort to unsafe methods for basic needs[1].The Gaza Strip,a tiny coastal area of just 365 square kilometers with 2.3 million residents,is one of the world's most densely populated *** burdened by inadequate infrastructure,the ongoing war has worsened conditions,caused the collapse of sewage and water systems and severely disrupted daily *** devastation has created a breeding ground for infectious diseases,especially among the displaced people living in overcrowded camps[2,3].

关键词： injuries Israel resort

Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

Self-supported copper-based gas diffusion electrodes improve the local CO_(2)concentration for efficient electrochemical CO_(2)reduction

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Frontiers of Chemical Science and Engineering 2024年第3期18卷 51-62页

作者： Azeem Mustafa Bachirou Guene Lougou Yong Shuai Zhijiang Wang Haseeb-ur-Rehman samia Razzaq Wei Wang Ruming Pan Jiupeng Zhao Key Laboratory of Aerospace Thermophysics of MIIT Harbin Institute of TechnologyHarbin150001China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin150001China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin150001China Mechanical Engineering Department University of Engineering and TechnologyTaxila47050Pakistan School of Aerospace Mechanical and Mechatronics EngineeringUniversity of SydneySydney2006Australia

electrochemical CO_(2)reduction is a sustainable approach in green chemistry that enables the production of valuable chemicals and fuels while mitigating the environmental impact associated with CO_(2)*** its several advantages,this technology suffers from an intrinsically low CO_(2)solubility in aqueous solutions,resulting in a lower local CO_(2)concentration near the electrode,which yields lower current densities and restricts product *** diffusion electrodes(GDEs),particularly those with tubular architectures,can solve these issues by increasing the local CO_(2)concentration and triple-phase interface,providing abundant electroactive sites to achieve superior reaction *** this study,robust and self-supported Cu flow-through gas diffusion electrodes(FTGDEs)were synthesized for efficient formate production via electrochemical CO_(2)*** were further compared with traditional Cu electrodes,and it was found that higher local CO_(2)concentration due to improved mass transfer,the abundant surface area available for the generation of the triple-phase interface,and the porous structure of Cu FTGDEs enabled high formate Faradaic efficiency(76%)and current density(265 mA¸cm^(−2))at–0.9 V *** hydrogen electrode(RHE)in 0.5 mol·L^(−1)*** combined phase inversion and calcination process of the Cu FTGDEs helped maintain a stable operation for several *** catalytic performance of the Cu FTGDEs was further investigated in a non-gas diffusion configuration to demonstrate the impact of local gas concentration on the activity and performance of electrochemical CO_(2)*** study demonstrates the potential of flow-through gas-diffusion electrodes to enhance reaction kinetics for the highly efficient and selective reduction of CO_(2),offering promising applications in sustainable electrochemical processes.

关键词： CO_(2)electroreduction flow-through delivery hollow fiber structure local concentration formate

Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1981-2004页

作者： Shaik Mahaboob Basha Victor Hugo Cde Albuquerque samia Allaoua Chelloug Mohamed Abd elaziz Shaik Hashmitha Mohisin Suhail Parvaze Pathan Department of electronics and Communication Engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Information Technology Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India Department of Veterinary Clinical Sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

Preparation of Fe-As alloys by mechanical alloying and vacuum hot-pressed sintering:microstructure evolution,mechanical properties,and mechanisms

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Rare Metals 2024年第8期43卷 3876-3892页

作者： Fei Chai Fei-Ping Zhao Zhan Hu Shi-Yi Wen Ben-Hammouda samia Ze-Lin Fu Xin-Ting Lai Yan-Jie Liang Xiao-Bo Min Li-Yuan Chai School of Metallurgy and Environment Central South UniversityChangsha 410083China Chinese National Engineering Research Center for Control&Treatment of Heavy Metal Pollution Institute of Environmental EngineeringCentral South UniversityChangsha 410083HunanChin State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410083China Department of Building Civiland Environmental EngineeringConcordia UniversityMontreal H3G 1M8Canada

Arsenic materials have attracted great attention due to their unique ***,research concerning iron-arsenic(Fe-As) alloys is very scarce due to the volatility of As at low temperature and the high melting point of ***,a new Fe-As alloy was obtained by mechanical alloying(MA) followed by vacuum hot-pressed sintering(VHPS).Moreover,a systematic study was carried out on the microstructural evolution,phase composition,leaching toxicity of As,and physical and mechanical properties of Fe-As alloys with varying weight fractions of As(20%,25%,30%,35%,45%,55%,65%,and 75%).The results showed that pre-alloyed metallic powders(PAMPs) have a fine grain size and specific supersaturated solid solution after MA,which could effectively improve the mechanical properties of Fe-As alloys by VHPS.A high density(> 7.350 g·cm^(-3)),low toxicity,and excellent mechanical properties could be obtained for FeAs alloys sintered via VHPS by adding an appropriate amount of As,which is more valuable than commercial Fe-As *** Fe-25% As alloy with low toxicity and a relatively high density(7.635 g·cm^(-3)) provides an ultra-high compressive strength(1989.19 MPa),while the Fe-65% As alloy owns the maximum Vickers hardness(HVo.5 899.41).After leaching by the toxicity characteristic leaching procedure(TCLP),these alloys could still maintain good mechanical performance,and the strengthening mechanisms of Fe-As alloys before and after leaching were *** in the grain size,micro structure,and phase distribution induced significant differences in the compressive strength and hardness.

关键词： Mechanical alloying Vacuum hot-pressed sintering High-pressure Arsenic-iron alloys Mechanical properties

Impact of the COVID-19 Pandemic on Cancer Patients: Experience of the medical oncology department of CHU HASSAN II Fez.

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Journal of Cancer Therapy 2024年第3期15卷 83-91页

作者： Khadija Hinaje Oumaima Talbi Lamiae Amaadour Karima Oualla Zineb Benbrahim samia Arifi Nawfel Mellas Department of Medical Oncology Hassan II University Hospital University Sidi Mohamed Ben Abdellah Fez Morocco

Introduction: In December 2019, COVID 19 spread worldwide, but did not officially start in MOROCCO until March 02, 2020. Since then, this pandemic has significantly impacted the health status of patients in general and cancer patients in particular. The main objective of our study is to evaluate the prognosis of patients treated for cancer and infected with COVID-19. Material and method: A descriptive study with prospective collection was carried out at the medical oncology department of CHU Hassan II in FEZ over a period of two years, from March 2020 to March 2022. Data was carried out on the software SPSS. Results: One hundred cancer patients tested positive for COVID-19 infection and were collected within our department. The average age was 56 years [22-91]. The sex ratio was 1.2. Patients with breast cancer were the most affected by this infection (34%). The clinical symptomatology was dominated by the respiratory syndrome (45%).The diagnosis was made through thoracic CT scan in 62% of cases. 76% of patients were in a metastatic stage. 96% of patients were undergoing oncological treatment. For symptomatique patients, the standard treatment approach involved using antibiotics in 76% of cases. Evolution was marked by recovery in 79% of patients, with a death rate of 12% in this cancer patient population. Conclusion: COVID-19 infection is particularly severe in cancer patients. Mortality among these patients remains high and is associated with overall patient characteristics. However, anticancer treatments have not shown deleterious effects on the course of COVID-19.

关键词： COVID-19 Cancer. SARS-CoV-2