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The microbiology of infected pancreatic necrosis

Hepatobiliary & Pancreatic Diseases International 2018年第5期17卷 456-460页

作者： Nicholas G.Mowbray bassam ben-ismaeil Mohammed Hammoda Guy Shingler Bilal Al-Sarireh Swansea University Medical School Singleton Park Campus Abertawe Bro-Morgannwg University Health Board Public Health Wales Microbiology ABM Morriston Hospital Abertawe Bro-Morgannwg University Health Board Department of Surgery Morriston Hospital

Background: Acute pancreatitis(AP) continues to cause significant morbidity and mortality, especially when it leads to infected pancreatic necrosis(IPN). Modern treatment of IPN frequently involves prolonged courses of antibiotics in combination with minimally invasive therapies. This study aimed to update the existing evidence base by identifying the pathogens causing IPN and therefore aid future selection of empirical antibiotics. Methods: Clinical data, including microbiology results, of consecutive patients with IPN undergoing minimally invasive necrosectomy at our institution between January 2009 and July 2016 were retrospectively reviewed. Results: The results of 40 patients(22 males and 18 females, median age 60 years) with IPN were reviewed. The etiology of AP was gallstones, alcohol, dyslipidemia and unknown in 31, 2, 2 and 5 patients, respectively. The most frequently identified microbes in microbiology cultures were Enterococcus faecalis and faecium(22.5% and 20.0%) and Escherichia coli(20.0%). In 19 cases the cultures grew multiple organisms. The antibiotics with the least resistance amongst the microbiota were teicoplanin(5.0%), linezolid(5.6%), ertapenem(6.5%), and meropenem(7.4%). Conclusion: The carbapenem antibiotics, ertapenem and meropenem provide good antimicrobial cover against the common, mainly enteral, microorganisms causing IPN. Culture and sensitivity results of acquired samples should be regularly reviewed to adjust prescribing and monitor for emergence of resistance.

关键词： Acute pancreatitis Pancreatic abscess Pancreatic necrosis Infected pancreatic necrosis Antibiotics Intra-abdominal infection

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Nasal flap preservation in endoscopic dacryocystorhinostomy for nasolacrimal duct obstruction

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International Journal of Ophthalmology(English edition) 2024年第9期17卷 1633-1638页

作者： Marianne Romanos Charbel Medawar Souheil Hallit bassam Romanos School of Medicine and Medical Sciences Holy Spirit University of KaslikP.O.Box 446JouniehLebanon Department of Ophtalmology Eye and Ear Hospital InternationalNaccacheLebanon Applied Science Research Center Applied Science Private UniversityAmman 11937Jordan

AIM:To compare surgical outcomes between the conventional endoscopic dacryocystorhinostomy(DCR)and a modified endoscopic DCR for the treatment of nasolacrimal duct obstruction(NLDO),and evaluate factors associated with the surgical success ***:Medical records of patients who underwent primary DCR surgery between January 2016 and July 2020 at the Otorhinolaryngology Department of Eye and Ear International Hospital,Lebanon were ***:The study group consisted of 50 consecutive modified endoscopic DCR and the control group consisted of 138 consecutive conventional endoscopic *** success rates at 1y were 98.0%(49 out of 50)for modified DCR,significantly higher compared to 84.8%(117/138)for the conventional DCR;there was no significant difference in the success rate throughout the years in terms of both surgical *** modified surgery vs traditional[adjusted odds ratio(aOR)=14.96]and having an adjunctive septoplasty surgery vs not(aOR=3.99)were significantly associated with higher odds of ***:Mucosal flap preservation and apposition shows significant improvement in the surgical success ***,there is no statistically significant difference found in terms of complication rate and mean operative time between the conventional and the modified techniques.

关键词： nasolacrimal duct obstruction endoscopic dacryocystorhinostomy mucosal flap

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曲面边界黏性绕流的湍流模型改进方法研究

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力学学报 2024年第1期56卷 58-69页

作者：唐聃戴绍仕谷慧群 bassam A.Younis 哈尔滨工程大学船舶工程学院哈尔滨150001 加利福尼亚大学戴维斯分校美国加利福尼亚州戴维斯95616

多尺度旋涡现象广泛地存在于工程领域的湍流中.研究湍流的重要方法是大涡模拟,但大涡模拟中的过度耗散问题是曲面边界、多尺度旋涡模拟所面临的主要困难.为了克服过度耗散的缺陷,使大曲率曲面边界的多尺度涡流脉动特性预报更准确,文章... 详细信息

多尺度旋涡现象广泛地存在于工程领域的湍流中.研究湍流的重要方法是大涡模拟,但大涡模拟中的过度耗散问题是曲面边界、多尺度旋涡模拟所面临的主要困难.为了克服过度耗散的缺陷,使大曲率曲面边界的多尺度涡流脉动特性预报更准确,文章采用正则化变分多尺度模型(RVM)改进了壁面自适应涡黏模型(WALE)中的亚格子模型,并采用C++语言在Open FOAM开源平台实现了计算代码编译.文章以经典圆柱黏性绕流作为曲面边界黏性绕流的代表,讨论了改进的大涡模型(MWALE)中滤波算子对亚临界雷诺数(Re=4.0×10^(4))波算子阶数(n)敏感.四阶滤波算子(n=2)能准确地预报圆柱壁面的平均涡量及尾流瞬时涡量分布、再循环旋涡长度和速度剖面,而二阶滤波算子(n=1)无法准确地预测分离区和尾流区内脉动速度剖面,因此在强压力梯度区四阶滤波算子预测的压力分布、脉动升阻力与实验结果吻合的更好,能更准确地捕捉到多尺度旋涡结构.

关键词：多尺度涡流改进的大涡模型滤波算子圆柱绕流

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Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq bassam SaleemAllah Almogadwy M.A.Khan Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

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Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq bassam SaleemAllah Almogadwy Muhammad Adnan Khan Muhammad Hasnain Azam Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

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Phishing Attacks Detection Using EnsembleMachine Learning Algorithms

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Computers, Materials & Continua 2024年第7期80卷 1325-1345页

作者： Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Marwan Abu-Zanona bassam Mohammad Elzaghmouri Farah H.Zawaideh Mouiad Fadeil Alawneh Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26110Jordan Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjloun26767Jordan

Phishing,an Internet fraudwhere individuals are deceived into revealing critical personal and account information,poses a significant risk to both consumers and web-based *** indicates a persistent rise in phishing ***,these fraudulent schemes are progressively becoming more intricate,thereby rendering them more challenging to ***,it is imperative to utilize sophisticated algorithms to address this *** learning is a highly effective approach for identifying and uncovering these harmful *** learning(ML)approaches can identify common characteristics in most phishing *** this paper,we propose an ensemble approach and compare it with six machine learning techniques to determine the type of website and whether it is normal or not based on two phishing *** that,we used the normalization technique on the dataset to transform the range of all the features into the same *** findings of this paper for all algorithms are as follows in the first dataset based on accuracy,precision,recall,and F1-score,respectively:Decision Tree(DT)(0.964,0.961,0.976,0.968),Random Forest(RF)(0.970,0.964,0.984,0.974),Gradient Boosting(GB)(0.960,0.959,0.971,0.965),XGBoost(XGB)(0.973,0.976,0.976,0.976),AdaBoost(0.934,0.934,0.950,0.942),Multi Layer Perceptron(MLP)(0.970,0.971,0.976,0.974)and Voting(0.978,0.975,0.987,0.981).So,the Voting classifier gave the best *** in the second dataset,all the algorithms gave the same results in four evaluation metrics,which indicates that each of them can effectively accomplish the prediction ***,this approach outperformed the previous work in detecting phishing websites with high accuracy,a lower false negative rate,a shorter prediction time,and a lower false positive rate.

关键词： Social engineering attacks phishing attacks machine learning security artificial intelligence

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Will artificial intelligence reach any limit in gastroenterology?

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Artificial Intelligence in Gastroenterology 2024年第2期5卷 1-9页

作者： Joseph Bou Jaoude Rose Al Bacha bassam Abboud Department of Gastroenterology Levant HospitalBeirut 166830Lebanon Department of General Surgery Geitaoui HospitalFaculty of MedicineLebanese UniversityLebanonBeirut 166830Lebanon

Endoscopy is the cornerstone in the management of digestive *** the last few decades,technology has played an important role in the development of this field,helping endoscopists in better detecting and characterizing luminal ***,despite ongoing advancements in endoscopic technology,the incidence of missed pre-neoplastic and neoplastic lesions remains high due to the operator-dependent nature of endoscopy and the challenging learning curve associated with new *** intelligence(AI),an operator-independent field,could be an invaluable *** can serve as a“second observer”,enhancing the performance of endoscopists in detecting and characterizing luminal *** utilizing deep learning(DL),an innovation within machine learning,AI automatically extracts input features from targeted endoscopic *** encompasses both computer-aided detection and computer-aided diagnosis,assisting endoscopists in reducing missed detection rates and predicting the histology of luminal digestive *** applications in clinical gastrointestinal diseases are continuously expanding and evolving the entire digestive *** all published studies,real-time AI assists endoscopists in improving the performance of non-expert gastroenterologists,bringing it to a level comparable to that of *** development of DL may be affected by selection *** have utilized different AI-assisted models,which are *** the future,algorithms need validation through large,randomized ***,AI has no limit to assist endoscopists in increasing the accuracy and the quality of endoscopic ***,practically,we still have a long way to go before standardizing our AI models to be accepted and applied by all gastroenterologists.

关键词： Artificial intelligence Digestive tract Gastroenterology Gastroscopy Coloscopy

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Low-Density Microplastics in Recreational Parks of Al Ain, United Arab Emirates: Abundance, Composition, and Potential Effects on Soil Health

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Journal of Environmental Protection 2024年第2期15卷 109-123页

作者： Rener De Jesus Ahmed Abuibaid bassam Al-Hindawi Ruwaya AlKendi Department of Biology College of Science United Arab Emirates University Al Ain UAE Department of Chemistry College of Science United Arab Emirates University Al Ain UAE

Microplastics (MPs) have been an emerging concern due to their harmful effects on the ecosystem and are ubiquitous in various habitats, from marine to terrestrial environments. However, studies on the presence of MPs in recreational areas are limited. One of the previous works has reported that urban recreational parks are considered “sinks” for plastic debris, including MPs. In this study, low-density MPs (LD-MPs) in soil samples collected from recreational parks of Al Ain, United Arab Emirates (UAE) were isolated by density flotation method. Results showed that these parks have varying levels of LD-MPs caused by various anthropogenic activities, such as sludge use and application of reclaimed water from wastewater treatment facilities in those areas. These plastic particles were isolated in 87% of the soil samples, with an average concentration of 1550 ± 340 MPs/kg. Predominantly, these comprised large LD-MPs (300 - 5000 μm), with red and blue being the most common colors. Fourier transform infrared (FTIR) spectroscopy identified possible synthetic polymers, including polyethylene and polypropylene. Additionally, a negative correlation was observed between LD-MP concentration and soil pH and moisture content, indicating potential adverse effects on soil health. These findings highlight the need for monitoring and managing microplastic pollution in urban recreational areas to mitigate its ecological impacts.

关键词： Plastic Particles FTIR Analysis Microfibers Soil Pollutants Urban Parks

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赛德西港用于船舶减排的陆上可再生能源供电评估

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哈尔滨工程大学学报（英文版） 2024年第2期23卷 506-524页

作者： Merna Makram Ameen M.bassam Adel A.Tawfik Waleed Yehia Naval Architecture and Marine Eng.Dept. Faculty of EngineeringPort Said UniversityPort Fuad 42526Egypt

Air pollution from shipping is becoming a critical issue,particularly in dense hub port *** proposed solution to minimize ship-based emissions at ports is the implementation of an Onshore Power Supply(OPS)*** allows ships to shut off their auxiliary engines and instead connect to the port *** there have been numerous studies conducted on ports in Europe and the United States,little research has been done on Egyptian ***,this paper aims to investigate the feasibility of implementing OPS at Port Said West Port in Egypt,aligning with Egypt Vision 2030’s goals for addressing climate *** research primarily focuses on analyzing data collected from calling ships to generate socio-economic and cost-effectiveness analyses of *** further enhance the environmental benefits of OPS,the paper proposes the use of solar energy as the OPS electricity *** findings of the study revealed that by relying on the national grid,emissions can be reduced by 28%.Moreover,it is predicted that this reduction could reach 100%if electricity generation is solely based on solar ***,the economic analysis demonstrates promising profitability,with a payback period of approximately two years.

关键词： Onshore power supply Port sustainability Shipping emissions inventory Solar energy Photovoltaic systems

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Using Remote Sensing Data to Delineate the Lineaments for Hydrothermal Mineral Prediction in Heqing Area, Northwest Yunnan Province, China

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Journal of China University of Geosciences 2007年第2期18卷 142-147页

作者： Mansour S Al-Mokredi 胡光道 bassam F Al bassam Faculty of Earth Resources China University of Geosciences

Lineament extraction and analysis is one of the routine work in mapping medium and large areas using remote sensing data, most of which are satellite images. Landsat Enhanced Thematic Mapper （ETM） of 945×1 232 pixels subscene acquired on 21 March 2000 covering the northwestern part of Yunnan Province has been digitally processed using ER Mapper software. This article aims to produce lineament density map that predicts favorable zones for hydrothermal mineral occurrences and quantify spatial associations between the known hydrothermal mineral deposits. In the process of lineament extraction a number of image processing techniques were applied. The extracted lineaments were imported into MapGIS software and a suitable grid of 100 m×100 m was chosen. The Kriging method was used to create the lineament density map of the area. The results show that remote sensing data could be useful to extract the lineaments in the area. These lineaments are closely correlated with the faults obtained through other geological investigation methods. On comparing with field data the lineament-density map identifies two important high prospective zones, where large-scale deposits are already existing. In addition the map highlights unrecognized target areas that require follow up investigation.

关键词： lineament extraction hydrothermal mineral prediction Kriging method Heqing area(China)

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