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Open Journal of Air Pollution 2024年第3期13卷 73-86页

作者： Hilal k. al-Shidi Hameed Sulaiman Department of Educational Studies University of Technology and Applied Sciences Khasab Oman Department of Biology Sultan Qaboos University Muscat Oman

Particulate matter (PM10) deposited as road dust is considered an important source of contamination from atmosphere. However, there are limited studies on the toxicity of road dust as such on different organisms. This study evaluates the toxicity of road dust using different extraction scenarios on Daphnia magna and Artemia salina as aquatic organisms and also on Prosopis cineraria and Vachellia tortilis as local plant species. Chemical analysis of different extracts shows considerable amount of trace metals, however the trace metals in the dust extract associated with suspended sediment were not absorbed by the receptors. On the other hand, the concentration of trace metals in the artificial mixture was found bioavailable and absorbed causing a high percentage of mortality. In the plant assay, significant difference was obtained in the germination percentage between the control and three different extraction exposures in both plant species. The mean root length of P. cineraria and V. tortilis were higher in 20% and 50% extracts than the control probably due to the availability of nutrients from the dust extract. Interestingly however, the seedling vigor index was the opposite with higher index in the control and lower in dust extracts that contain heavy metals.

关键词： Road Dust Heavy Metals Toxicity Bioavailability Holding Time

An Inventory of Some Relatively Large Marine Mammals, Reptiles, and Fishes Sighted, Caught, By-Caught, or Stranded in the Mediterranean Coast of the Gaza Strip-Palestine

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Open Journal of Ecology 2023年第2期13卷 119-153页

作者： Abdel Fattah N. Abd Rabou k.mal E. Elk.hlout k.mal J. Elnabris Adel J. Attallah Jehad Y. Salah Mohammed A. Aboutair Waleed M. Thabit Sahar k. Serri Hassan G. Abu Hatab Sameeh M. Awadalah Wajdi M. Saqallah Mok.les S. alhawajri tariq k. al-sammak Bashar S. Jarayseh Sinaa A. Ababsa Daoud I. al-Hali Aysha A. Rafeea Doaa S. Ghattas Huda E. Abu Amra Israa M. Jaber Nedal A. Fayyad Ashraf A. Shafei Inas A. Abd Rabou Othman A. Abd Rabou Mohammed A. Abd Rabou Mazen T. Abualtayef Mohammed R. al-Agha Yousif k. Ibrahim Rimel M. Benmessaoud Mourad M. Cherif Hashem A. Madk.ur Department of Biology and Biotechnology Faculty of Science Islamic University of Gaza Gaza Strip Palestine Department of Marine Sciences Faculty of Science Islamic University of Gaza Gaza Strip Palestine Directorate General of Fisheries Ministry of Agriculture Gaza Strip Palestine Environmental Education Center Beit Jala Palestine Wildlife Documenter and Photographer Kafr Kanna Palestine Qimmah Secondary School Jerusalem Palestine k.mal al-Ohood Primary School for Girls North Gaza Education Directorate Gaza Strip Palestine Department of Biology Faculty of Science Al-Aqsa University Gaza Strip Palestine Department of Nursing and Health Sciences University College of Applied Sciences Gaza Strip Palestine Department of Journalism and Media Islamic University of Gaza Gaza Strip Palestine Department of GIS University College of Applied Sciences Gaza Strip Palestine Department of Environmental Engineering Faculty of Engineering Islamic University of Gaza Gaza Palestine Department of Environment and Earth Sciences Faculty of Science Islamic University of Gaza Gaza Palestine Water and Environment Quality Authority Gaza Strip Palestine National Institute of Agronomy of Tunisia Tunis Tunisia National Institute of Marine Sciences and Technologies (INSTM) La Goulette Port Tunis Tunisia National Institute of Oceanography and Fisheries Hurghada Egypt

The Mediterranean Sea is home to an interesting biodiversity. The current cumulative and descriptive study aims to enumerate some relatively large marine mammals, reptiles, and fishes that have been spotted, caught, by-caught, or stranded on the coast of the Gaza Strip, Palestine, which extends about 42 k. along the Mediterranean Sea. This 20-year study from 2003 to 2022 relied much on frequent field visits, meetings, and discussions with stak.holders, following local media sites and social media pages, and photography. The study recorded at least 26 giants or relatively large marine organisms on the Mediterranean coast of the Gaza Strip, Palestine. Certainly, the coming years may bring other marine organisms of relatively large sizes. Marine mammals included three species of cetaceans with the Fin Whale (Balaenoptera physalus) being the largest mammal and even the largest animal ever recorded in this study. Marine reptiles included three species of sea turtles, the largest of which is the Leatherback.Sea Turtle (Dermochelys coriacea), which is in fact the world’s largest sea turtle. The bony fishes were represented by ten species, the largest of which was the Ocean Sunfish (Mola mola), which is the largest bony fish in the world. The cartilaginous fishes included ten species with the largest specimens encountered were the Shortfin Shark.(Isurus oxyrinchus), Bluntnose Sixgill Shark.(Hexanchus griseus), Scalloped Hammerhead Shark.(Sphyrna lewini), and Giant Devil Ray (Mobula mobular). Seabirds were not included in the study. The alexandria Pompano (alectis alexandrinus) and the Silver-Cheek.d Toadfish (Lagocephalus sceleratus), which are bony fishes, appear to be the relatively smallest marine organisms recorded here. In conclusion, the role of the various parties must be coordinated to ensure the sustainability of human activities and their compatibility with the task.of conserving local marine biota, including the gigantic or relatively large ones.

关键词： Mediterranean Sea Marine Biodiversity Marine Mammals Sea Turtles Bony Fishes Cartilaginous Fishes Gaza Strip Palestine

A Pioneering Approach to the Synthesis of Silver Nanoparticles

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Journal of Materials Science and Chemical Engineering 2024年第7期12卷 14-22页

作者： Wasan A. al-Dulaimi Zeena M. al-Azzawi Emad k. al-Shak.rchi Physics Department College of Science Al-Nahrain University Baghdad Iraq

Our research introduces a groundbreak.ng chemical reduction method for synthesizing silver nanoparticles, mark.ng a significant advancement in the field. The nanoparticles were meticulously characterized using various techniques, including optical analysis, structural analysis, transmission electron microscopy (TEM), and field-emission scanning electron microscope (FESEM). This thorough process instills confidence in the accuracy of our findings. The results unveiled that the silver nanoparticles had a diameter of less than 20 nm, a finding of great importance. The absorption spectrum decreased in the peak.wavelength range (405 - 394 mm) with increasing concentrations of Ag nanoparticles in the range (1 - 5%). The XRD results indicated a cubic crystal structure for silver nanoparticles with the lattice constant (a = 4.0855 Å), and Miller indices were (111), (002), (002), and (113). The simulation on the XRD pattern showed a face center cubic phase with space group Fm-3m, providing valuable insights into the structure of the nanoparticles.

关键词： Chemical Reduction Method UV-VIS Absorption Spectrometer Field-Emission Scanning Electron Microscope (FESEM) Transmission Electron Microscopy (TEM)

Room and cryogenic deformation behavior of AZ61 and AZ61-xCaO(x=0.5,1 wt.%)alloy

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Journal of Magnesium and alloys 2024年第5期12卷 1996-2009页

作者： Umer Masood Chaudry Hafiz Muhammad Rehan tariq Nooruddin Ansari Soo Yeol Lee Tea-Sung Jun Department of Mechanical Engineering Incheon National UniversityIncheon 22012Republic of Korea Research Institute for Engineering and Technology Incheon National UniversityIncheon 22012Republic of Korea Department of Materials Science&Engineering Chungnam National UniversityDaejeon 34134Republic of Korea

This study investigates the influence of CaO(0.5,1(wt.%))alloying on the microstructural evolution,texture development and deformation behavior of AZ61 magnesium *** uniaxial tension tests at room(RT)and cryogenic(CT,-150℃)temperature were performed to investigate the twinability and dislocation behavior and its consequent effect on flow stress,ductility and strain hardening *** results showed that the AZ61-1CaO exhibited superior strength/ductility synergy at RT with a yield strength(YS)of 223 MPa and a ductility of 23% as compared to AZ61(178 MPa,18.5%)and AZ61-0.5CaO(198 MPa,21%).Similar trend was witnessed for all the samples during CT deformation,where increase in the YS and decrease in ductility were *** Mtex tools based in-grain misorientation axis(IGMA)analysis of RT deformed samples revealed the higher activities of prismatic slip in AZ61-CaO,which led to superior ***,subsequent EBSD analysis of CT deformed samples showed the increased fraction of fine{10-12}tension twins and nucleation of multiple{10-12}twin variants caused by higher local stress concentration at the grain boundaries,which imposed the strengthening by twin-twin ***,the detailed investigations on strengthening contributors showed that the dislocation strengthening has the highest contribution towards strength in all samples.

关键词： Magnesium Twinning Twinning variant EBSD Cryogenic deformation

Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi al-MEk.LAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network.CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation k.owledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

Accelerated Particle Swarm Optimization algorithm for Efficient Cluster Head Selection in WSN

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Computers, Materials & Continua 2024年第6期79卷 3585-3629页

作者： Imtiaz Ahmad tariq Hussain Babar Shah altaf Hussain Iqtidar ali Farman ali Institute of Computer Sciences and Information Technology The University of AgriculturePeshawarPakistan School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhouChina College of Technological Innovation Zayed UniversityDubaiUnited Arab Emirates School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063South Korea

Numerous wireless network. have emerged that can be used for short communication ranges where the infrastructure-based network. may fail because of their installation and *** of them is a sensor network.with embedded sensors work.ng as the primary nodes,termed Wireless Sensor Network.(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering *** have several challenges,including throughput,energy usage,and network.lifetime *** strategies have been applied to get over these *** may,therefore,be thought of as the best way to solve such ***,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network.lifetime,and minimize energy *** paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)*** the help of APSO in the implementation of the WSN,the main methodology of this article has tak.n *** simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 *** sending pack.ts ratio was also raised for all three CH selection scenarios,increasing from 659 to *** number of dead nodes lik.wise dropped for the given combination,falling between 71 and *** network.lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based *** to underwater,WSN can mak. use of the proposed *** overall results have been evaluated and

关键词： Wireless sensor network cluster head selection low energy adaptive clustering hierarchy accelerated particle swarm optimization

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risk.,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** k.y steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models lik. RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Comparative analysis of jet and underlying event properties across various models as a function of charged particle multiplicity at 7 TeV

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Chinese Physics C 2024年第9期48卷 118-125页

作者： Maryam Waqar Haifa I.alrebdi Muhammad Waqas k.S.al-mugren Muhammad Ajaz Department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China

In this study,a comprehensive analysis of jets and underlying events as a function of charged particle multiplicity in proton-proton(pp)collisions at a center-of-mass energy of √s=7 TeV is *** Monte Carlo(MC)event generators,including Pythia8.308,EPOS 1.99,EPOSLHC,EPOS4_(Hydro),and EPOS4_(noHydro),are employed to predict particle *** predictions from these models are compared with experimental data from the CMS *** charged particles are categorized into those associated with underlying events and those link.d to jets,and the analysis is restricted to charged particles with|η|0.25 GeV/*** comparing the MC predictions with CMS data,we find that EPOS4_(Hydro),EPOSLHC,and Pythia8 consistently reproduce the experimental results for all charged particles,underlying events,intrajets,and leading charged *** charged jet rates with p_T^(***)>5 GeV/c,EPOS4_(Hydro)and Pythia8 perform exceptionally *** the case of charged jet rates with p_T^(***)→30 GeV/c,EPOSLHC reproduces satisfactorily good results,whereas EPOS4 Hydro exhibits good agreement with the data at higher charged particle multiplicities compared to the other *** can be attributed to the conversion of energy into flow when"Hydro=on"leading to an increase in *** EPOSLHC model describes the data better owing to the new collective flow effects,correlated flow treatment,and parameterization compared to EPOS ***,the examination of the jet p_T spectrum and normalized charged p_T density reveals that EPOS4_(Hydro),EPOS4_(noHydro),and EPOSLHC exhibit good agreement with the experimental results,whereas Pythia8 and EPOS 1.99 do not perform as well owing to the lack.of correlated flow treatment.

关键词： Monte Carlo models underlying event jets charged particle multiplicity

Developing a Model for Park.nson’s Disease Detection Using Machine Learning algorithms

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Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Park.nson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speak.ng,writing,walk.ng,or performing other basic sk.lls as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Park.nson’s disease and identify related risk.*** research work.d on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),k.Nearest Neighbours(k.N),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,k.N,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Park.nson’s disease(PD) SVM and XGBoost

The optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function

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Petroleum 2024年第1期10卷 68-84页

作者： Firas A.A.al-k.bbawi Independent scholar Livingston Scotland UNITED KINGDOM

The main objective of this study is to develop the optimal semi-analytical modeling for the infiniteconductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function. The available semi-analytical infinite-conductivity models（ICMs） for horizontal well under rectangular bounded reservoir in literature were developed by applying superposition of pressures in space（SPS）. A new instantaneous source function（i.e., instantaneous uniform-flux segmentary source function under bounded reservoir） is derived to be used instead of SPS to develop the optimal semi-analytical *** new semi-analytical ICM is verified with ICM of Schlumberger [1] and with previous semi-analytical ICMs in terms of bottom hole pressure（BHP） profile and inflow rate distribution along the wellbore. The model is also validated with real horizontal wells in terms of inflow rate distribution along the wellbore. The results show that the developed model gives the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir. Besides that, high computationalefficiency and high-resolution of wellbore discretization have been achieved（i.e., wellbore segment number could be tens of hundreds depending on solution requirement）. The results also show that at pseudosteady state（PSS） flow regime, inflow rate distribution along the wellbore by previous semi-analytical ICMs is stabilized U-shaped as performance of inflow rate distribution at late radial flow regime. Therefore, the previous semi-analytical ICMs are incorrectly modeling inflow rate distribution at PSS flow regime due to the negative influence of applying SPS. The optimal semi-analytical ICM is in a general form and real time domain,and can be applicable for 3D horizontal well and 2D vertical fracture well under infinite and rectangular bounded reservoirs, of uniform-flux and infinite-conductivity wellbore conditions at any time of

关键词： Infinite-conductivity model Horizontal well performance Semi-analytical modeling Rectangular bounded reservoir Instantaneous source functions Flow regimes