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A selective approach to the surgical management of periampullary cancer patients and its outcome

Hepatobiliary & Pancreatic Diseases International 2014年第6期13卷 628-633页

作者： Omar j Shah irfan Robbani Parveen Shah Sadaf A Bangri irfan j khan Mohammad Y Bhat Manmohan Singh Departments of Surgical Gastroenterology Sher-i-Kashmir Institute of Medical Sciences Srinagar Kashmir India Radiodiagnosis & Imaging Sher-i-Kashmir Institute of Medical Sciences Srinagar Kashmir India Pathology Sher-i-Kashmir Institute of Medical Sciences Srinagar Kashmir India Departments of Surgical Gastroenterology Sher-i-Kashmir Institute of Medical Sciences Srinagar Kashmir India Departments of Surgical Gastroenterology Sher-i-Kashmir Institute of Medical Sciences Srinagar Kashmir India

BACKGROUND： Pancreaticoduodenectomy is a high risk, complex, technically challenging operation associated with significant perioperative morbidity and mortality. This study on the surgical management of periampullary cancer patients is based on our experience in a period of nearly 13 years. METHODS： The study was conducted on two groups of patients： group A included 42 patients who were treated between january 2000 and September 2005 and group B included 134 patients who were treated between October 2005 to October 2012. Preoperative, intraoperative and postoperative details of all these patients were collected, tabulated and analyzed to assess the impact of the selective approach introduced in the department with effect from October 2005. RESULTS： Intraoperative details revealed highly significant differences in the management of the two groups of patients in respect of operative time （250.4 vs 126.6 minutes; P〈0.001）, operative blood loss （1070.2 vs 414.9 mL; P〈0.001） and intraoperative blood transfusion （1A vs 0.2 units; P〈0.001）. Variations between the two groups in the frequency of complications were found to be statistically insignificant. However, the difference between the two groups in the overall morbidity of patients （47.6% vs 26.1%; P=0.009） and the length of their hospital stay （11.8 vs 7.8 days; P〈0.001） were significant. CONCLUSION： A selective approach applied to the surgical management of periampullary cancer patients is a step in the right direction.

关键词： pancreaticoduodenectomy superior approach technique Whipple's operation

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Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

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journal of Magnesium and Alloys 2024年第4期12卷 1518-1528页

作者： Annayath Maqbool Abdul Khalad Noor Zaman khan Department of Mechanical Engineering National Institute of Technology SrinagarJ&K 190006India Department of Mechanical Engineering Indian Institute of TechnologyHyderabadSangareddyTelangana 502284India School of Engineering Deakin UniversityVictoria 3216Australia

The corrosion rate is a crucial factor that impacts the longevity of materials in different *** undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion ***,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still *** current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 *** Taguchi L27 design of experiments was used for the experimental *** addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion *** shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified *** study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

关键词： Corrosion rate Friction stir processing Virtual sample generation Particle swarm optimization Machine learning Graphical user interface

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A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

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Computers, Materials & Continua 2024年第3期78卷 3805-3823页

作者： Shaha Al-Otaibi Rahim khan Hashim Ali Aftab Ahmed khan Amir Saeed jehad Ali Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Abdul Wali Khan University MardanMardan23200Pakistan Department of Computer Science and IT UET PeshawarJalozai Campus PeshawarPeshawar24240Pakistan Department of AI Convergence Network Ajou UniversitySuwon16499South Korea

The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server *** IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority ***,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are *** paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other ***,Media Access Control(MAC)address and Advance Encryption Scheme(AES)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline ***,TA shares a list of authentic devices,i.e.,server S_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication ***,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT ***,proposed authentication and existing state-of-the-art approaches have been s

关键词： Internet of things authenticity security location communication

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Dynamical study of varicella-zoster virus model in sense of Mittag-Leffler kernel

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International journal of Biomathematics 2024年第3期17卷 153-183页

作者： Qura Tul Ain Aziz khan Thabet Abdeljawad j.F.Gomez-Aguilar Saleem Riaz Department of Mathematics Guizhou University GuiyangGuizhou 550025P.R.China Department of Mathematics and Sciences Prince Sultan University P.O.Bor 66833 11586 RiyadhSaudi Arabia Department of Medical Research China Medical University Taichung 40402Taiwan CONACyT-Tecnologico Nacional de Mécico/CENIDET Interior Internado Palmira S/N Col.Palmira C.P.62490CuernavacaMorelosMécico IConsejo Academico Universidad Virtual CNCIMonterreyMécico School of Automation Northwestern Polytechnical University 170072 Xian P.R.China

The primary varicella-zoster virus(VzV)infection that causes chickenpox(also known as varicella),spreads quickly among people and,in severe circumstances,can cause to fever and *** this paper,the Mittag-Leffler fractional operator is used to examine the mathematical representation of the *** fractional-order differential equations are created in terms of the disease's dynamical analysis such as S:Susceptible,V:Vaccinated,E:Exposed,I:Infectious and R:*** derive the existence criterion,positive solution,Hyers-Ulam stability,and boundedness of results in order to examine the suggested fractional-order model's ***,some numerical examples for the VzV model of various fractional orders are shown with the aid of the generalized Adams-Bashforth-Moulton approach to show the viability of the obtained results.

关键词： Varicella-zoster virus model Hyers-Ulam stability ABC fractional operator Schauder fix point theory numerical analysis

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Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

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Computers, Materials & Continua 2024年第5期79卷 3333-3353页

作者： Aiman Muhammad Arshad Bilal khan Sadique Ahmad Muhammad Asim Department of Computer Science City University of Science and Information TechnologyPeshawar25000Pakistan EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia School of Computer Science and Technology Guangdong University of TechnologyGuangzhou510006China

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,***, the research on RomanUrdu is not up to the ***, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including j48-Decision Tree (j48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

关键词： Digital forensics author profiling for security AdaBoostM1 random forest ensemble learning

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A Novel Layered Double Hydroxide and Dodecyl Alcohol Assisted PCM Composite with High Latent Heat Storage Capacity and Thermal Conductivity

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journal of Thermal Science 2024年第2期33卷 537-547页

作者： AL-AHMED Amir SARI Ahmet khan Firoz AL-RASHEIDI Masoud Hekimoğlu Gökhan AFZAAL Mohammad A.ALSULAMI Ahmed DAFALLA Hatim SALHI Billel A.ALSULAIMAN Fahad Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Department of Metallurgical and Material Engineering Karadeniz Technical UniversityTrabzon61080Turkey Maths and Natural Sciences Division Higher Colleges of TechnologyP.O.Box 7947SharjahUnited Arab Emirates Department of Mechanical Engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Core Research Facilities King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Membranes and Water Security King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia

Dodecyl alcohol(DDA) is a promising solid-liquid phase change material(PCM) due to its favorable latent heat storage(LHS) ***,the leakage issue of PCM in a melted state during the heating period and low thermal conductivity restricts its utilization potential in thermal energy storage(TES) *** the same context,the present work aims to overcome the leakage issue and improve the thermal conductivity of the *** this in mind,a novel leak-proof layered double hydroxide(LDH)/DDA composite PCM is proposed through a solution-based impregnation *** leak-proof impregnation ratio of the DDA impregnated within the cavities of the synthesized Al/Fe-LDH was determined to be 60%.Detailed morphological,physicochemical,and thermal properties of the fabricated composite were studied by scanning electron microscopy(SEM),Fourier transforms infrared(FTIR) spectroscopy,X-ray diffraction(XRD)spectroscopy,differential scanning calorimetry(DSC),thermalgravimetric analysis(TGA),and thermal cycling *** results show that the LDH/DDA composite has a suitable phase change temperature(about 20℃) for passive solar thermal management of building *** composite PCM showed high LHS enthalpy(about136 j/g),good thermal stability,and cycling LHS *** also showed nearly 152% higher thermal conductivity compared to that of pure DDA,ultimately reducing the melting and solidification time of the pure DDA by 44.9% and 45.5%,respectively.

关键词： dodecyl alcohol layered double hydroxide composite PCM thermal conductivity thermal energy storage(TES)

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Engineering hierarchical quaternary superstructure of an integrated MOF-derived electrode for boosting urea electrooxidation assisted water electrolysis

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Green Energy & Environment 2024年第4期9卷 695-701页

作者： jianjun Tian Changsheng Cao Yingchun He Muhammad Imran khan Xin-Tao Wu Qi-Long Zhu State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of Sciences(CAS)Fuzhou350002China Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108China University of Chinese Academy of Sciences Beijing100049China Research Institute of Sciences and Engineering(RISE) University of SharjahSharjah27272United Arab Emirates

Controllable design of the catalytic electrodes with hierarchical superstructures is expected to improve their electrochemical ***,a self-supported integrated electrode(NiCo-ZLDH/NF)with a unique hierarchical quaternary superstructure was fabricated through a self-sacrificing template strategy from the metal–organic framework(Co-ZIF-67)nanoplate arrays,which features an intriguing well-defined hierarchy when taking the unit cells of the NiCo-based layered double hydroxide(NiCo-LDH)as the primary structure,the ultrathin LDH nanoneedles as the secondary structure,the mesoscale hollow plates of the LDH nanoneedle arrays as the tertiary structure,and the macroscale three-dimensional frames of the plate arrays as the quaternary ***,the distinctive structure of NiCo-ZLDH/NF can not only accelerate both mass and charge transfer,but also expose plentiful accessible active sites with high intrinsic activity,endowing it with an excellent electrochemical performance for urea oxidation reaction(UOR).Specially,it only required the low potentials of 1.335,1.368 and 1.388 V to deliver the current densities of 10,100 and 200 mA cm^(-2),respectively,much superior to those for typical *** NiCo-ZLDH/NF as the bifunctional electrode for both anodic UOR and cathodic HER,an energy-saving electrolysis system was further explored which can greatly reduce the needed voltage of 213 mV to deliver the current density of 100 mA cm^(-2),as compared to the conventional water electrolysis system composed of *** work manifests that it is prospective to explore the hierarchically nanostructured electrodes and the innovative electrolytic technologies for high-efficiency electrocatalysis.

关键词： Hierarchical superstructures Metal–organic frameworks Layered double hydroxides Urea oxidation reaction Hydrogen evolution reaction

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Knowledge‐based deep learning system for classifying Alzheimer's disease for multi‐task learning

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 805-820页

作者： Amol Dattatray Dhaygude Gaurav Kumar Ameta Ihtiram Raza khan Pavitar Parkash Singh Renato RMaaliw III Natrayan Lakshmaiya Mohammad Shabaz Muhammad Attique khan Hany SHussein Hammam Alshazly Department of Data Science University of WashingtonSeattleWashingtonUSA Department of Computer Science&Engineering Parul Institute of TechnologyParul UniversityVadodaraGujaratIndia Department of Computer Science Jamia HamdardDelhiIndia Department of Management Lovely Professional UniversityPhagwaraIndia 5 College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Mechanical Engineering Saveetha School of EngineeringSIMATSChennaiTamil NaduIndia Model Institute of Engineering and Technology JammuJ&KIndia Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Electrical Engineering Department College of EngineeringKing Khalid UniversityAbhaSaudi Arabia Electrical Engineering Department Aswan UniversityAswanEgypt Faculty of Computers and Information South Valley UniversityQenaEgypt

Deep learning has recently become a viable approach for classifying Alzheimer's disease(AD)in medical ***,existing models struggle to efficiently extract features from medical images and may squander additional information resources for illness *** address these issues,a deep three‐dimensional convolutional neural network incorporating multi‐task learning and attention mechanisms is *** upgraded primary C3D network is utilised to create rougher low‐level feature *** introduces a new convolution block that focuses on the structural aspects of the magnetic resonance imaging image and another block that extracts attention weights unique to certain pixel positions in the feature map and multiplies them with the feature map ***,several fully connected layers are used to achieve multi‐task learning,generating three outputs,including the primary classification *** other two outputs employ backpropagation during training to improve the primary classification *** findings show that the authors’proposed method outperforms current approaches for classifying AD,achieving enhanced classification accuracy and other in-dicators on the Alzheimer's disease Neuroimaging Initiative *** authors demonstrate promise for future disease classification studies.

关键词： classification deep learning

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Acoustofluidic separation of prolate and spherical micro-objects

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Microsystems & Nanoengineering 2024年第1期10卷 217-230页

作者： Muhammad Soban khan Mushtaq Ali Song Ha Lee Keun Young jang Seong jae Lee jinsoo Park Department of Mechanical Engineering Chonnam National University77 Yongbong-roBuk-guGwangju 61186Republic of Korea Department of Polymer Engineering The University of Suwon17 Wauan-gilBongdam-eupHwaseongGyeonggi 18323Republic of Korea

Most microfluidic separation techniques rely largely on object size as a separation *** ability to separate micro-objects based on their shape is crucial in various biomedical and chemical ***,we develop an ondemand,label-free acoustofluidic method to separate prolate ellipsoids from spherical microparticles based on traveling surface acoustic wave-induced acoustic radiation force and *** freely rotating non-spherical microobjects were aligned under the progressive acoustic field by the counterrotating radiation torque,and the major axis of the prolate ellipsoids was parallel to the progressive wave *** specific alignment of the ellipsoidal particles resulted in a reduction in the cross-sectional area perpendicular to the wave *** a consequence,the acoustic backscattering decreased,resulting in a decreased magnitude of the radiation *** the variation in radiation force,which depended on the micro-object morphology enabled the acoustofluidic shape-based *** conducted numerical simulations for the wave scattering of spherical and prolate objects to elucidate the working mechanism underlying the proposed method.A series of experiments with polystyrene microspheres,prolate ellipsoids,and peanut-shaped microparticles were performed for *** quantitative analysis of the separation efficiency,we confirmed the high purity and high recovery rate of the proposed acoustofluidic shapebased separation of *** a bioparticle,we utilize Thalassiosira eccentrica to perform shape-based separation,as the species has a variety of potential applications in drug delivery,biosensing,nanofabrication,bioencapsulation and immunoisolation.

关键词： separation spherical rotating

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ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

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Intelligent Automation & Soft Computing 2024年第2期39卷 301-317页

作者： Aiman Muhammad Arshad Bilal khan Khalil khan Ali Mustafa Qamar Rehan Ullah khan Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstanaKazakhstan Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and *** improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and *** evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(j48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are *** findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,*** metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling *** study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and *** results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

关键词： Machine learning author profiling AdaBoostM1 random forest ensemble learning text classification

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