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Portraying Diabetic Foot Ulcers: Comparative Evaluation of Diabetic Foot Infections versus Diabetic Foot Ulcers

Advances in Infectious Diseases（传染病进展） 2024年第2期 297页

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Advances in Infectious Diseases 2024年第2期14卷 297-309页

作者： Jamal Wadi al Ramahi Leen Sharqawi Sarah al-Najafi Eman Awwad haya m. al-obaidi Abdel Hafez mohammad Sara Nofal Dina Riyadh al-Janabi Ibrahim Zuhair Hamza Jamal al-masaeid mohammed al-Ithawi Dina Rasheed Bellal O. al-Far Osama al-Izi Qutaiba al-Bustanji School of medicine The University of Jordan Amman Jordan Department of the Internal medicine The Specialty Hospital Amman Jordan Department of Pharmacy The Specialty Hospital Amman Jordan Department of the medical Al Khalidi Hospital Amman Jordan Department of Pharmacy Jordan Hospital Amman Jordan Department of Internal medicine Jordan Hospital Amman Jordan Department of General Surgery Jordan Hospital Amman Jordan

Background: Confusion often arises in caring for diabetic foot infections and ulcers, especially with antimicrobials;we aim to shed light on this entity and alert healthcare workers to its stewardship. methods: Records were reviewed between February 2016 and September 2023. Data for patients diagnosed with diabetes and foot ulcers, infected or not, were examined following ICD 9 search terms. Records for patients were included if they were prediabetic/diabetic adults with foot ulcers, more than 18 years old, and on antidiabetic treatment. Patients were excluded if they insulin resistant, with normal HgbA1c levels, wheel-chair dependent, bed-bound, non-diabetic patients, diabetic patients who had vascular lower limb surgery earlier to ulcers, diabetic patients who had aortocoronary bypass, deep venous thrombosis within six months, malignancy, and severe clinical depression. A modified IWGDF/IDSA guidelines definitions for DFI and DFU was considered. Statistical analysis was done using R programming. Statistical methods were employed as appropriate, and a significant P-value was considered for P Results: most characteristics were well balanced between DFI and DFU, on imaging osteomyelitis and tissue swelling were significantly more in DFI. Endovascular radiological procedures showed angiograms to be considerably more in DFI, while angioplasty was more in DFU, in addition to smoking. Bacteremia was uncommon, and swab cultures were mostly polymicrobial in both ulcers;no clear association with blood bacteria was detected with the polymicrobial growth, though few were concordant. Antimicrobials prescribed for both ulcers were not statistically different except for carbapenems, which were more in DFI (P Conclusion: Attention should be paid to best practices while caring for diabetic ulcers. These include swab culture interpretations, the use of antimicrobials, and plan management according to DFI or DFU to utilize either local care or combination with antimicrobials.

关键词： Diabetic Foot Ulcers Diabetic Limb Amputation Antimicrobials Stewardship Broad-Spectrum Antimicrobials in Diabetic Foot Ulcers

Experimental and computational study of annealed nickel sulfide quantum dots for catalytic and antibacterial activity

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Nano materials Science 2024年第3期6卷 355-364页

作者： muhammad Ikram Sawaira moeen ali Haider Anwar Ul-Hamid haya alhummiany Hamoud H.Somaily Souraya Goumri-Said mohammed Benali Kanoun Solar Cell Applications Research Lab Department of PhysicsGovernment College University LahoreLahore54000PunjabPakistan Department of Clinical Sciences Faculty of Veterinary and Animal SciencesMuhammad Nawaz ShareefUniversity of Agriculture66000MultanPunjabPakistan Core Research Facilities King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Department of Physics Faculty of ScienceUniversity of JeddahP.O.Box 13151Jeddah21493Saudi Arabia Department of Physics Faculty of ScienceKing Khalid UniversityP.O.Box 9004AbhaSaudi Arabia Physics Department College of Science and General StudiesAlfaisal UniversityP.O.Box 50927Riyadh11533Saudi Arabia Department of mathematics and Sciences College of Humanities and SciencesPrince Sultan UniversityP.O.Box 66833Riyadh11586Saudi Arabia

This research investigates the hydrothermal synthesis and annealing duration effects on nickel sulfide(NiS_(2) quantum dots(QDs)for catalytic decolorization of methylene blue(mB)dye and antimicrobial *** size increased with longer annealing,reducing catalytic ***–vis,XRD,TEm,and FTIR analyses probed optical structural,morphological,and vibrational *** confirmed NiS2's anorthic structure,with crystallite size growing from 6.53 to 7.81 nm during extended ***–Vis exhibited a bathochromic shift,reflecting reduced band gap energy(Eg)in NiS_(2).TEm revealed NiS_(2)QD formation,with agglomerated QD average size increasing from 7.13 to 9.65 nm with prolonged *** NiS_(2) showed significant mB decolorization(89.85%)in acidic *** NiS_(2) QDs demonstrated notable antibacterial activity,yielding a 6.15mm inhibition zone against Escherichia coli(***)compared to ***-principles computation supported a robust interaction between mB and NiS_(2),evidenced by obtained adsorption *** study highlights the nuanced relationship between annealing duration,structural changes,and functional properties in NiS_(2)QDs,emphasizing their potential applications in catalysis and antibacterial interventions.

关键词： NiS_(2) antibacterial quantum dots dye degradation DFT

Surface modification techniques of membranes to improve their antifouling characteristics:recent advancements and developments

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Frontiers of Chemical Science and Engineering 2023年第12期17卷 1837-1865页

作者： muhammad Tawalbeh haya aljaghoub muhammad Qasim Amani al-Othman Sustainable and Renewable Energy Engineering Department University of SharjahSharjah 27272United Arab Emirates Sustainable Energy&Power Systems Research Centre RISEUniversity of SharjahSharjah 27272United Arab Emirates Industrial Engineering and Engineering management Department University of SharjahSharjah 27272United Arab Emirates Department of Chemical and Biological Engineering American University of SharjahSharjah 26666United Arab Emirates materials Science and Engineering Program College of Arts and SciencesAmerican University of SharjahSharjah 26666United Arab Emirates

Extensive research efforts are currently devoted to developing and improving conventional technologies for water treatment. membrane-based water treatment technologies are among the most preferred options due to their commercial success, simple operation, low energy and space requirements, and high separation efficiency. Despite the advances made in membrane-based technologies, fouling remains a critical challenge. Fouling occurs upon the accumulation of unwanted impurities on the membrane surface and within the membrane pores which results in a significant decline in the membrane permeate flux. To alleviate the operational challenges from fouling, surface modification to develop antifouling membranes appears to be an effective technique. A comprehensive review of the surface modification techniques for the development of antifouling membranes is provided in this paper. Chemical surface modification techniques (grafting and plasma treatment), physical modification techniques (blending, coating, adsorption, and thermal treatment), and combined physical and chemical modification techniques have been discussed. moreover, the challenges related to surface modification and the future research directions are addressed.

关键词： fouling antifouling membrane surface modification membrane pretreatment

Hybrid metaheuristics with Deep Learning Enabled Automated Deception Detection and Classification of Facial Expressions

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Computers, materials & Continua 2023年第6期75卷 5433-5449页

作者： haya alaskar Department of Computer Sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl KharjSaudi Arabia

Automatic deception recognition has received considerable atten-tion from the machine learning community due to recent research on its vast application to social media,interviews,law enforcement,and the *** analysis-based techniques for automated deception detection have received increasing *** study develops a new self-adaptive population-based firefly algorithm with a deep learning-enabled automated deception detection(SAPFF-DLADD)model for analyzing facial ***-tially,the input video is separated into a set of video ***,the SAPFF-DLADD model applies the mobileNet-based feature extractor to produce a useful set of *** long short-term memory(LSTm)model is exploited for deception detection and *** the final stage,the SAPFF technique is applied to optimally alter the hyperparameter values of the LSTm model,showing the novelty of the *** experimental validation of the SAPFF-DLADD model is tested using the miami University Deception Detection Database(mU3D),a database comprised of two classes,namely,truth and *** extensive comparative analysis reported a better performance of the SAPFF-DLADD model compared to recent approaches,with a higher accuracy of 99%.

关键词： Deception detection facial cues deep learning computer vision hyperparameter tuning

Intelligent machine Learning Based EEG Signal Classification model

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Computers, materials & Continua 2022年第4期71卷 1821-1835页

作者： mesfer al Duhayyim haya mesfer alshahrani Fahd N.al-Wesabi mohammed Abdullah al-Hagery Anwer mustafa Hilal Abu Sarwar Zaman Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

In recent years,Brain-Computer Interface(BCI)system gained much popularity since it aims at establishing the communication between human brain and *** systems are applied in several research areas such as neuro-rehabilitation,robots,exoeskeletons,***(EEG)is a technique commonly applied in capturing brain *** is incorporated in BCI systems since it has attractive features such as noninvasive nature,high time-resolution output,mobility and *** classification process is highly essential in decision making process and it incorporates different processes namely,feature extraction,feature selection,and *** this motivation,the current research paper presents an Intelligent Optimal Fuzzy Support Vector machine-based EEC recognition(IOFSVm-EEG)model for BCI *** Component Analysis(ICA)technique is applied onto the proposed IOFSVm-EEG model to remove the artefacts that exist in EEG signal and to retain the meaningful EEG ***,Common Spatial Pattern(CSP)-based feature extraction technique is utilized to derive a helpful set of feature vectors from the preprocessed EEG ***,OFSVm method is applied in the classification of EEG signals,in which the parameters involved in FSVm are optimally tuned using Grasshopper Optimization algorithm(GOA).In order to validate the enhanced EEG recognition outcomes of the proposed IOFSVm-EEG model,an extensive set of experiments was *** outcomes were examined under distinct *** experimental results highlighted the enhanced performance of the presented IOFSVm-EEG model over other state-of-the-art methods.

关键词： Brain computer interface EEG recognition human computer interface machine learning parameter tuning FSVm

Development of Non-ABO Red Blood Cell alloantibodies in Patient Undergoing allogeneic Haematopoietic Stem Cell Transplant

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Case Reports in Clinical medicine 2024年第5期13卷 162-170页

作者： Ahmed alsuhaibani Khalid Batarfi Ahmed alharbi haya alwasel Abdullah alenazi Abdulmohsen alotaibi Jalal Hassan Rayyan alotaibi Hajer Aziz Nourah alharethi Sara alobaidi maram.alonayzan Sanad alharthi majd alanazi Sarah alotaibi Ahmed Shareefi Bandar alqahtani Department of Laboratory and Pathology King Abdulaziz Medical City of National Guard Riyadh Saudi Arabia

alloantibodies that are non ABO alloimmunization to protein antigens happens only after exposure, in contrast to ABO isohaemagglutinins, which are present naturally, even in the absence of prior exposure. It is recognized that while non-ABO RBC antibodies are less common than ABO antibodies, they generate essentially the same issues that lead to unfavorable clinical results. If non-ABO alloantibodies are identified early on, these issues related complications may be avoided This call for an in-depth understanding of the recipient and donor’s ABO-Rh grouping, antibody screening, and the phenotype of certain antigens. Equally important, the temporal association time between transplantation and hemolysis can help identify the underlying mechanism of hemolysis and direct appropriate management. Therefore, for that, it is crucial to identify the etiology of post-HSCT anemia for prevention and therapy, in addition to a thorough grasp of the mechanism of anemia in non-ABO-incompatible HSCT and the temporal link between HSCT and anemia. Finding the cause of post-HSCT anemia is essential for prevention and therapy, in addition to a thorough grasp of the mechanism of anemia in non-ABO-incompatible HSCT and the temporal link between HSCT and anemia. Therefore, for that, it is crucial to identify the etiology of post-HSCT anemia. In this case report review, we would like to highlight the vital role of transfusion medicine services and stem cell clinical teams in paying particular attention to the clinical significance of non-ABO alloantibodies involved to avoid causing overt hemolysis of incompatible donor RBCs or delayed erythropoiesis. Considering the fact that some of the Haematopoietic stem cell transplant centers do not give an attention to the other non-ABO RBC antigens.

关键词： Haematopoietic Stem Cell Transplant (HSCT) Non-ABO Red Blood Cell Antibodies alloantibodies

Deep Learning Empowered Cybersecurity Spam Bot Detection for Online Social Networks

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Computers, materials & Continua 2022年第3期70卷 6257-6270页

作者： mesfer al Duhayyim haya mesfer alshahrani Fahd Nal-Wesabi mohammed alamgeer Anwer mustafa Hilal mohammed Rizwanullah Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Cybersecurity encompasses various elements such as strategies,policies,processes,and techniques to accomplish availability,confidentiality,and integrity of resource processing,network,software,and data from *** this scenario,the rising popularity of Online Social Networks(OSN)is under threat from spammers for which effective spam bot detection approaches should be *** studies have developed different approaches for the detection of spam bots in *** those techniques primarily concentrated on hand-crafted features to capture the features of malicious users while the application of Deep Learning(DL)models needs to be *** this motivation,the current research article proposes a Spam Bot Detection technique using Hybrid DL model abbreviated as *** proposed SBD-HDL technique focuses on the detection of spam bots that exist in *** technique has different stages of operations such as pre-processing,classification,and parameter ***,SBD-HDL technique hybridizes Graph Convolutional Network(GCN)with Recurrent Neural Network(RNN)model for spam bot classification *** order to enhance the detection performance of GCN-RNN model,hyperparameters are tuned using Lion Optimization algorithm(LOA).Both hybridization of GCN-RNN and LOA-based hyperparameter tuning process make the current work,a first-of-its-kind in this *** experimental validation of the proposed SBD-HDL technique,conducted upon benchmark dataset,established the supremacy of the technique since it was validated under different measures.

关键词： Cybersecurity spam bot data classification social networks twitter deep learning

Artificial Intelligence Based Clustering with Routing Protocol for Internet of Vehicles

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Computers, materials & Continua 2022年第3期70卷 5835-5853页

作者： manar Ahmed Hamza haya mesfer alshahrani Fahd Nal-Wesabi mesfer al Duhayyim Anwer mustafa Hilal Hany mahgoub Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

With recent advances made in Internet of Vehicles(IoV)and Cloud Computing(CC),the Intelligent Transportation Systems(ITS)find it advantageous in terms of improvement in quality and interactivity of urban transportation service,mitigation of costs incurred,reduction in resource utilization,and improvement in traffic management *** trafficrelated problems in future smart cities can be sorted out with the incorporation of IoV in *** communication enables the collection and distribution of real-time essential data regarding road network *** this scenario,energy-efficient and reliable intercommunication routes are essential among vehicular nodes in sustainable urban *** this motivation,the current research article presents a new Artificial Intelligence-based Energy Efficient Clustering with Routing(AI-EECR)Protocol for IoV in urban *** proposed AI-EECR protocol operates under three stages namely,network initialization,Cluster Head(CH)selection,and routing *** presented AI-EECR protocol determines the CHs from vehicles with the help of Quantum Chemical Reaction Optimization(QCRO)*** a fitness function with the help of vehicle speed,trust level,and energy level of the *** order to make appropriate routing decisions,a set of relay nodeswas selected usingGroup Teaching Optimization algorithm(GTOA).The performance of the presented AI-EECR model,in terms of energy efficiency,was validated against different aspects and a brief comparative analysis was *** experimental outcomes established that AI-EECR model outperformed the existing methods under different measures.

关键词： Vehicular communication internet of vehicles energy efficient smart transportation smart city urban computing

Intelligent Deep Learning Based Automated Fish Detection model for UWSN

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Computers, materials & Continua 2022年第3期70卷 5871-5887页

作者： mesfer al Duhayyim haya mesfer alshahrani Fahd Nal-Wesabi mohammed alamgeer Anwer mustafa Hilal manar Ahmed Hamza Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

An exponential growth in advanced technologies has resulted in the exploration of Ocean *** has paved the way for new opportunities that can address questions relevant to diversity,uniqueness,and difficulty of marine *** Wireless Sensor Networks(UWSNs)are widely used to leverage such opportunities while these networks include a set of vehicles and sensors to monitor the environmental *** this scenario,it is fascinating to design an automated fish detection technique with the help of underwater videos and computer vision techniques so as to estimate and monitor fish biomass in water *** models have been developed earlier for fish ***,they lack robustness to accommodate considerable differences in scenes owing to poor luminosity,fish orientation,structure of seabed,aquatic plantmovement in the background and distinctive shapes and texture of fishes from different *** this motivation,the current research article introduces an Intelligent Deep Learning based Automated Fish Detection model for UWSN,named IDLAFD-UWSN *** presented IDLAFD-UWSN model aims at automatic detection of fishes from underwater videos,particularly in blurred and crowded ***-UWSN model makes use of mask Region Convolutional Neural Network(mask RCNN)with Capsule Network as a baseline model for fish ***,in order to train mask RCNN,background subtraction process using Gaussianmixturemodel(Gmm)model is *** model makes use of motion details of fishes in video which consequently integrates the outcome with actual image for the generation of fish-dependent candidate ***,Wavelet Kernel Extreme Learning machine(WKELm)model is utilized as a classifier *** performance of the proposed IDLAFD-UWSN model was tested against benchmark underwater video dataset and the experimental results achieved by IDLAFD-UWSN model were promising in comparison with other state-of-the-art methods under differe

关键词： Aquaculture background subtraction deep learning fish detection marine surveillance underwater sensor networks