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Sero-Prevalence and Risk factors of Contagious Bovine Pleuropneumonia (CBPP) in Afgoye District Lower Shabelle Region, Somalia

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Open Journal of Veterinary Medicine 2024年第2期14卷 11-20页

作者： Ahmed Mohamed Ahmed Sumaya Hassan Ali Abdisalam Mohamed Ali Abdirazack Saleban Osman Binti Abubakar Mohamed Abdifatah Mohamud Ibar Shafii abdullahi Mohamed Mohamed Abdelrahman Mohamed Ahmed Ali Omar Zakaria ibrahim Issack College of Veterinary Medicine Abrar University Mogadishu Somalia Faculty of Veterinary Medicine and Animal Husbandry Somali National University Mogadishu Somalia Faculty of Veterinary Science Benadir University Mogadishu Somalia

Contagious bovine Pleuropneumonia (CBPP) is an infectious and highly contagious respiratory disease of cattle and water buffalo, caused by the Mycoplasma mycoides subspecies mycoides. It induces significant economic losses and leads to a severe livestock production problem, negatively influencing people’s livelihoods of affected countries. In Somalia, there is no updated data on the prevalence and distribution of the disease. Hence, a descriptive cross-sectional study was conducted from September 2022 to June 2023 in different villages under the Afgoye District of lower Shabelle region, Somalia. The main purpose of this study is to assess the sero-prevalence and identify the associated risk factors for the occurrence of the disease. In this study, villages, age, sex, breed, and body condition were considered as risk factors. A total of 90 blood samples were collected and tested in the laboratory using the Anti-CBPP Elisa kit test. Out of 90 serum samples from herd cattle, 32 were positive, resulting in an overall prevalence of 35.5%. In addition, we found a statistically significant variation between the prevalence of the disease and factors such as sex, age, body condition and breeds. In summary, the overall prevalence of Contagious bovine pleuropneumonia in this study area is worth to be considered because there is a low quality of health care and less awareness of the Contagious bovine Pleuropneumonia effects on herds, which warrants the official authorities to act and follow appropriate preventive and control measures to reduce the incidence of the disease and generate appropriate controlling and prevention measures in all regions of Somalia.

关键词： Contagious Bovine Pleuropneumonia Sero-Prevalence Cattle Somalia Mycoplasma Cross Sectional Study

Preserving the Ozone Layers: Battling Illegal Trade in Ozone-Depleting Substances

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Atmospheric and Climate Sciences 2024年第3期14卷 287-298页

作者： ibrahim Badawi Seattle Law School Seattle University Seattle USA

The depletion of the ozone layer, a vital shield protecting the Earth from harmful ultraviolet (UV) radiation, is now a worldwide environmental concern. Human activities, particularly the release of ozone depleting substances (ODS), have led to the thinning of this protective layer over recent decades. Simultaneously, illegal trade has emerged as a global challenge, giving rise to economic issues, losses of tax revenue, heightened criminal activities, health risks, and environmental hazards. The depletion of the ozone layer, a critical shield protecting the Earth from harmful ultraviolet (UV) radiation, has become a global environmental concern. This paper delves into the legal dimensions surrounding ozone-depleting substances (ODS), their impact on the ozone layer, and the subsequent risk of skin cancer. As countries navigate international agreements, domestic regulations, and enforcement mechanisms, the intricate interplay between legal frameworks and the health implications of ozone layer depletion comes to the forefront. The paper highlights particular instances of illegal trade in ozone depleting substances, drawing from data reported by the parties to the Montreal Protocol. Notably, China stands out as a significant source of contraband ODS, with other countries such as Bulgaria, Lithuania, Poland, and France reporting numerous cases. Analyzing these case instances offers insights into the efficacy of legal frameworks and enforcement measures. The paper offers a comprehensive set of recommendations to strengthen global control and enforcement against the illegal trade of ozone depleting substances. These recommendations span diverse aspects such as production monitoring, customs collaboration, mutual verification, cross-border agreements, public-private partnerships, international cooperation, detection equipment, global regulatory standards, resource allocation, public awareness campaigns, alternative substance development, and controlling the trade at its so

关键词： Ozone-Depleting Substances Illegal Trade Montreal Protocol Environmental Protection Ozone Layers Climate Change

A Hybrid Classification and Identification of Pneumonia Using African Buffalo Optimization and CNN from Chest X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2497-2517页

作者： Nasser Alalwan Ahmed I.Taloba Amr Abozeid Ahmed ibrahim Alzahrani Ali H.Al-Bayatti Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Information System Department Faculty of Computers and InformationAssiut UniversityAssiutEgypt Mathematics Department Faculty of ScienceAl-Azhar UniversityCairoEgypt Cyber Technology Institute(CTI) De Montfort UniversityLeicesterUK

An illness known as pneumonia causes inflammation in the *** there is so much information available fromvarious X-ray images,diagnosing pneumonia has typically proven *** improve image quality and speed up the diagnosis of pneumonia,numerous approaches have been *** date,several methods have been employed to identify *** Convolutional Neural Network(CNN)has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and ***,these methods are complex,inefficient,and imprecise to analyze a big number of *** this paper,a new hybrid method for the automatic classification and identification of Pneumonia from chest X-ray images is *** proposed method(ABOCNN)utilized theAfrican BuffaloOptimization(ABO)algorithmto enhanceCNNperformance and *** Weinmed filter is employed for pre-processing to eliminate unwanted noises from chest X-ray images,followed by feature extraction using the Grey Level Co-Occurrence Matrix(GLCM)*** features are then selected from the dataset using the ABO algorithm,and ultimately,high-performance deep learning using the CNN approach is introduced for the classification and identification of *** results on various datasets showed that,when contrasted to other approaches,the ABO-CNN outperforms them all for the classification *** proposed method exhibits superior values like 96.95%,88%,86%,and 86%for accuracy,precision,recall,and F1-score,respectively.

关键词： African buffalo optimization convolutional neural network pneumonia X-ray

Deciphering resistancemechanisms and novel strategies to overcome drug resistance in ovarian cancer:a comprehensive review

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Oncology Research 2024年第5期32卷 831-847页

作者： EFFAT ALEMZADEH LEILA ALLAHQOLI AFROOZ MAZIDIMORADI ESMAT ALEMZADEH FAHIMEH GHASEMI HAMID SALEHINIYA ibrahim ALKATOUT Infectious Diseases Research Center Birjand University of Medical SciencesBirjandIran Department of Midwifery Ministry of Health and Medical EducationTehranIran Student Research Committee Shiraz University of Medical SciencesShirazIran Department of Biotechnology Faculty of MedicineBirjand University of Medical SciencesBirjandIran Cellular and Molecular Research Center Birjand University of Medical SciencesBirjandIran Social Determinants of Health Research Center Birjand University of Medical SciencesBirjandIran Kiel School of Gynaecological Endoscopy Campus KielUniversity Hospitals Schleswig-HolsteinKielGermany

Ovarian cancer is among the most lethal gynecological cancers,primarily due to the lack of specific symptoms leading to an advanced-stage diagnosis and resistance to *** resistance(DR)poses the most significant challenge in treating patients with existing *** Food and Drug Administration(FDA)has recently approved three new therapeutic drugs,including two poly(ADP-ribose)polymerase(PARP)inhibitors(olaparib and niraparib)and one vascular endothelial growth factor(VEGF)inhibitor(bevacizumab)for maintenance ***,resistance to these new drugs has ***,understanding the mechanisms of DR and exploring new approaches to overcome them is crucial for effective *** this review,we summarize the major molecular mechanisms of DR and discuss novel strategies to combat DR.

关键词： Chemotherapy Drug resistance mechanisms Ovarian cancer PARP inhibitors VEGF inhibitor

Comparison of vergence mechanisms between university students with good and poor sleep quality

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International Journal of Ophthalmology(English edition) 2024年第2期17卷 353-358页

作者： Pui Juan Woi Joyce Yi Ling Lu Mohd Izzuddin Hairol Wan Nur Amirah ibrahim Optometry and Vision Science Programme Center for Community Health Studies(ReaCH)Faculty of Health SciencesUniversiti Kebangsaan MalaysiaKuala Lumpur 50300Malaysia Centre of Optometry Studies Faculty of Health SciencesUniversiti Teknologi MARASelangor BranchPuncak Alam CampusSelangor 42300Malaysia

AIM:To compare the vergence mechanisms between good and poor sleepers in university ***:A total of 64 university students were recruited in this *** validated Malay version of Pittsburgh Sleep Quality Index questionnaire(PSQI-M)was used to measure the participants’sleep quality over the past *** were categorized as good sleepers(n=32)and poor sleepers(n=32)based on the PSQI-M *** and fusional vergences were measured at distance and ***-Whitney U test was used to compare heterophoria,negative fusional vergence(NFV),and positive fusional vergence(PFV)at distance and near between good and poor *** correlation analysis was used to study the relationship between PSQI-M score and PFV at ***:Both distance and near heterophorias were not significantly different between good and poor sleepers(P>0.05).There was a difference in distance PFV(P0.05).Distance PFV was negatively correlated with PSQI-M score(rs=-0.33,P<0.05).CONCLUSION:University students with poor sleep quality demonstrates a reduced ability to maintain fusion with increasing convergence demand at *** quality assessment during binocular vision examination in university students is recommended.

关键词： binocular vision vergence sleep quality university students

Distribution characteristics and removal rate of antibiotics and antibiotic resistance genes in different treatment processes of two drinking water plants

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Frontiers of Environmental Science & Engineering 2024年第9期18卷 143-152页

作者： Jun Wang Mingtao Huang Bolin Li Hassan ibrahim Mohamed Huanjie Song Gezi Li Ying Yu Han Zhang Weimin Xie School of Resource and Environmental Engineering Wuhan University of TechnologyWuhan 430070China Wuhan Lingang Economic and Technological Development Zone Service Industry Development Investment Group Co.Ltd. Wuhan 430040China Civil Engineering Department Faculty of EngineeringAssiut UniversityAssiut 71516Egypt Changjiang Basin Ecology Environment and Monitoring and Scientific Research Center Changjiang Basin Ecology and Environment AdministrationMinistry of Ecological EnvironmentWuhan 430010China

Emerging pollutants,such as antibiotics and antibiotic-resistance genes,are becoming increasingly important sources of safety and health *** water safety,which is closely related to human health,should receive more attention than natural water body ***,minimal research has been performed on the efficacy of existing treatment processes in water treatment plants for the removal of antibiotics and antibiotic resistance *** address this research gap,this study detected and analyzed six main antibiotics and nine antibiotic resistance genes in the treatment processes of two drinking water plants in *** were collected over three months and then detected and analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry and fluorescence *** total concentrations of antibiotics and antibiotic resistance genes in the influent water of the two water plants were characterized as December>March>*** precipitation and filtration processes of the Zou Maling Water Plant and Yu Shidun Water Plant successfully removed the *** ozone-activated carbon process increased the removal rate of most antibiotics to 100%.However,a large amount of antibiotic resistance gene residues remained in the effluents of the two water *** experiments demonstrated that the existing ozone-activated carbon processes could not effectively remove antibiotic resistance *** study provides a reference for the optimization of drinking water treatment processes for antibiotics and antibiotic resistance gene removal.

关键词： Antibiotics Antibiotics resistance genes Water treatment process unit Spatiotemporal distribution Removal efficacy

A Hybrid Model for Improving Software Cost Estimation in Global Software Development

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Computers, Materials & Continua 2024年第1期78卷 1399-1422页

作者： Mehmood Ahmed Noraini B.ibrahim Wasif Nisar Adeel Ahmed Muhammad Junaid Emmanuel Soriano Flores Divya Anand Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit RajaBatu Pahat86400Malaysia Department of Computer Science COMSATS University Wah Cantt CampusIslamabad47010Pakistan Department of Information Technology The University of HaripurKhyber Pakhtunkhwa22620Pakistan Engineering Research Innovation Group Universidad Europea del AtlanticoSantander39011Spain

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert *** models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate *** addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation ***,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost *** study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these *** proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry *** article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost *** the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing *** findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

关键词： Artificial neural networks COCOMO II cost drivers global software development linear regression software cost estimation

Quantification of Silicon (SI) and Silicon Dioxide (SiO₂) from the Nafud Desert-Al-Qassim Region, Kingdom of Saudi Arabia Using XRD Analysis

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Advances in Materials Physics and Chemistry 2024年第5期14卷 67-75页

作者： Nagwa ibrahim Mohamed Department of Physics College of Science Qassim University Buraydah Saudi Arabia

This research was conducted in the Qassim region, Kingdom of Saudi Arabia. The goal of this research is to determine the percentage of silicon in the Rub al-Khali desert. Samples were collected from four cities located in the Al-Qassim Region of Saudi Arabia (Uyun Al-Jawa, Al-Fuwailiq, Al-Sulaibiya, and Al-Qawara), from three distinct depths (the earth’s surface, 50 cm, and 100 cm). The percentages of silicon in these places vary between the highest value for silicon dioxide, which is 74.47 m/m%, and 34.8 m/m% for silicon in Al-Qawara city at a depth of 100 cm. We used an x-ray fluorescence (XRF) instrument to evaluate the samples. There are high percentage of both silica and silicon in the Nafud desert. Studies have shown that these ratios can help investors benefit from an element of Silicon and silicon dioxide, so the sands of the Nafud desert is sufficient for extracting Silicon and silica in huge quantities. This may transform the Kingdom into a leading country in the global computer technology industry that depends on silicon extracted from the desert sands, the most important of which are microcomputer data processing devices.

关键词： Silica Sand Dispersive X-Ray Fluorescence (EDXRF) Analyzer Solar Cells Nafud Desert Al-Qawwarh

Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan ibrahim M.Mehedi Shaikh Abdul Latif Md.Masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence