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Post-hepatectomy liver failure:A timeline centered review

Hepatobiliary & Pancreatic Diseases International 2023年第6期22卷 554-569页

作者： Mohamed Bekheit Lisa Grundy Ahmed KA Salih Petru Bucur Eric Vibert mudassar Ghazanfar Department of Surgery NHS GrampianForesterhill Health CampusAshgrove RoadAB252ZN AberdeenUK Institute of Medical Sciences Medical SchoolForesterhill Health CampusAshgrove RoadAB252ZN AberdeenUK Hépatica Integrated Center of HPB CareElite HospitalAgriculture RoadAlexandriaEgypt Department of Surgery University Hospital ToursVal de la Loire 37000France Centre Hépatobiliaire Paul Brousse Hospital12 Paul Valliant Couturier94804 VillejuifFrance

Background: Post-hepatectomy liver failure(PHLF) is a leading cause of postoperative mortality after liver surgery. Due to its significant impact, it is imperative to understand the risk stratification and preventative strategies for PHLF. The main objective of this review is to highlight the role of these strategies in a timeline centered way around curative resection. Data sources: This review includes studies on both humans and animals, where they addressed PHLF. A literature search was conducted across the Cochrane Library, Embase, MEDLINE/Pub Med, and Web of Knowledge electronic databases for English language studies published between July 1997 and June 2020. Studies presented in other languages were equally considered. The quality of included publications was assessed using Downs and Black’s checklist. The results were presented in qualitative summaries owing to the lack of studies qualifying for quantitative analysis. Results: This systematic review with 245 studies, provides insight into the current prediction, prevention, diagnosis, and management options for PHLF. This review highlighted that liver volume manipulation is the most frequently studied preventive measure against PHLF in clinical practice, with modest improvement in the treatment strategies over the past decade. Conclusions: Remnant liver volume manipulation is the most consistent preventive measure against PHLF.

关键词： Post-hepatectomy liver failure Liver neoplasms Prediction Prevention Management

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Influence of Hartmann Number on Convective Flow of Maxwell Fluid between Two Hot Parallel Plates through Porous Medium Subject to Arbitrary Shear Stress at the Boundary

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Journal of Applied Mathematics and Physics 2022年第1期10卷 160-171页

作者： Adnan Ahmad Zaib Un Nisa mudassar Nazar Muhammad imran Asjad Mushtaq Ahmad Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan Department of Mathematics University of Education Lahore Multan Campus Multan Pakistan School of Mathematical Sciences University of Science and Technology of China Hefei China Department of Mathematics University of Management and Technology Lahore Pakistan

Natural convection flow of unsteady Maxwell fluid with the effects of constant magnetic force in the course of a porous media is investigated in this research work. Fluid motion between a channel of parallel plates is tempted by time dependent shear stress applied on one plate. The governing partial differential equations of a model under consideration are transformed into ordinary differential equations by Laplace transform method and then solved for temperature and velocity fields. The obtained results for temperature fields are expressed in terms of complementary error function. The influences of involved parameters likes Hartmann number, Grashf number, Prandlt number and porosity parameter, on temperature and velocity profiles are shown graphically. There is no such result regarding Maxwell fluid in the existing literature.

关键词： Natural Convection Maxwell Fluid Hot Parallel Plates MHD Porous Media Shear Stress

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Edge-Computing with Graph Computation:A Novel Mechanism to Handle Network Intrusion and Address Spoofing in SDN

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Computers, Materials & Continua 2020年第12期65卷 1869-1890页

作者： Rashid Amin mudassar Hussain Mohammed Alhameed Syed Mohsan Raza Fathe Jeribi Ali Tahir University of Engineering and Technology TaxilaPakistan University of Wah Wah CanttPakistan Jazan University JazanSaudi Arabia Abasyn University Islamabad IslamabadPakistan

Software Defined Networking(SDN)being an emerging network control model is widely recognized as a control and management *** model provides efficient techniques to control and manage the enterprise *** emerging paradigm is edge computing in which data processing is performed at the edges of the network instead of a central *** data processing at the edge nodes reduces the latency and bandwidth *** SDN,the controller is a single point of *** security issues related to the traditional network can be solved by using SDN central management and *** Spoofing and Network Intrusion are the most common *** attacks severely degrade performance and *** propose an edge computing-based mechanism that automatically detects and mitigates those *** this mechanism,an edge system gets the network topology from the controller and the Address Resolution Protocol(ARP)traffic is directed to it for further *** such,the controller is saved from unnecessary processing related to addressing *** propose a graph computation based method to identify the location of an attacker or intruder by implementing a graph difference *** using the correct location information,the exact attacker or intruder is blocked,while the legitimate users get access to the network *** proposed mechanism is evaluated in a Mininet simulator and a POX *** results show that it improves system performance in terms of attack mitigation time,attack detection time,and bandwidth requirements.

关键词： Software Defined Networking(SDN) edge computing Address Resolution Protocol(ARP) ARP inspection security graph difference

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Malaria Parasite Detection Using a Quantum-Convolutional Network

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Computers, Materials & Continua 2022年第3期70卷 6023-6039页

作者： Javaria Amin Muhammad Almas Anjum Abida Sharif mudassar Raza Seifedine Kadry Yunyoung Nam University of Wah Wah CanttPakistan National University of Technology(NUTECH) IslamabadPakistan COMSATS University Islamabad Vehari CampusVehariPakistan COMSATS University Islamabad Wah CampusPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Malaria is a severe illness triggered by parasites that spreads via mosquito *** underdeveloped nations,malaria is one of the top causes of mortality,and it is mainly diagnosed through ***-assisted malaria diagnosis is difficult owing to the fine-grained differences throughout the presentation of some uninfected and infected ***,in this study,we present a new idea based on the ensemble quantum-classical framework for malaria *** methods comprise three core steps:localization,segmentation,and *** the first core step,an improved FRCNN model is proposed for the localization of the infected malaria ***,the RGB localized images were converted into YCbCr channels to normalize the image intensity ***,the actual lesion region was segmented using a histogram-based color thresholding *** segmented images were employed for classification in two different *** the first method,a CNN model is developed by the selection of optimum layers after extensive experimentation,and the final computed feature vector is passed to the softmax layer for classification of the infection/non-infection of themicroscopicmalaria ***,a quantum-convolutionalmodel is employed for informative feature extraction from microscopicmalaria images,and the extracted feature vectors are supplied to the softmax layer for ***,classification results were analyzed from two different models and concluded that the quantum-convolutional model achieved maximum accuracy as compared to *** proposed models attain a precision rate greater than 90%,thereby proving that these models performed better than the existing models.

关键词： Quantum convolutional RGB YCbCr histogram Malaria

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Deep Learning with a Novel Concoction Loss Function for Identification of Ophthalmic Disease

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Computers, Materials & Continua 2023年第9期76卷 3763-3781页

作者： Sayyid Kamran Hussain Ali Haider Khan Malek Alrashidi Sajid Iqbal Qazi mudassar Ilyas Kamran Shah Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering Faculty of Computer ScienceLahore Garrison UniversityLahore54000Pakistan Department of Computer Science Applied CollegeUniversity of TabukTabukSaudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl Hofuf31982Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl HofufSaudi Arabia

As ocular computer-aided diagnostic(CAD)tools become more widely accessible,many researchers are developing deep learning(DL)methods to aid in ocular disease(OHD)*** eye diseases like cataracts(CATR),glaucoma(GLU),and age-related macular degeneration(AMD)are the focus of this study,which uses DL to examine their *** imbalance and outliers are widespread in fundus images,which can make it difficult to apply manyDL algorithms to accomplish this analytical *** creation of efficient and reliable DL algorithms is seen to be the key to further enhancing detection *** the analysis of images of the color of the retinal fundus,this study offers a DL model that is combined with a one-of-a-kind concoction loss function(CLF)for the automated identification of *** study presents a combination of focal loss(FL)and correntropy-induced loss functions(CILF)in the proposed DL model to improve the recognition performance of classifiers for biomedical *** is done because of the good generalization and robustness of these two types of losses in addressing complex datasets with class imbalance and *** classification performance of the DL model with our proposed loss function is compared to that of the baseline models using accuracy(ACU),recall(REC),specificity(SPF),Kappa,and area under the receiver operating characteristic curve(AUC)as the evaluation *** testing shows that the method is reliable and efficient.

关键词： Deep learning multi-classification focal loss CNN eye disease

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3D Semantic Deep Learning Networks for Leukemia Detection

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Computers, Materials & Continua 2021年第10期69卷 785-799页

作者： Javaria Amin Muhammad Sharif Muhammad Almas Anjum Ayesha Siddiqa Seifedine Kadry Yunyoung Nam mudassar Raza University of Wah Wah CanttPakistan COMSATS University Islamabad Wah CampusPakistan National University of Technology(NUTECH) IJP Road IslamabadPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

White blood cells(WBCs)are a vital part of the immune system that protect the body from different types of bacteria and *** cell growth destroys the body’s immune system,and computerized methods play a vital role in detecting abnormalities at the initial *** this research,a deep learning technique is proposed for the detection of *** proposed methodology consists of three *** I uses an open neural network exchange(ONNX)and YOLOv2 to localize *** localized images are passed to Phase II,in which 3D-segmentation is performed using deeplabv3 as a base network of the pre-trained Xception *** segmented images are used in Phase III,in which features are extracted using the darknet-53 model and optimized using Bhattacharyya separately criteria to classify *** proposed methodology is validated on three publically available benchmark datasets,namely ALL-IDB1,ALL-IDB2,and LISC,in terms of different metrics,such as precision,accuracy,sensitivity,and dice *** results of the proposed method are comparable to those of recent existing methodologies,thus proving its effectiveness.

关键词： YOLOv2 darknet53 Bhattacharyya separately criteria ONNX

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Resolution beyond classical limits with spatial frequency heterodyning

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Chinese Optics Letters 2006年第3期4卷 148-151页

作者： A.mudassar A.R.Harvey A.H.Greenaway J.D.C.Jones School of Engineering and Physical Sciences Heriot-Watt UniversityUK

A technique for coherent imaging based on spatial frequency heterodyning is described. Three images corresponding to three physical measurements are recorded. For the first measurement, a scene is simply illuminated with a coherent beam and for measurements 2 and 3, the scene is projected with cosine and sine fringes, respectively. Due to spatial frequency heterodyning, upper and lower side hand information falls in the pass band of the imager. These bands are separated and correct phases and positions are assigned to these bands in the spatial frequency domain. An extension of bandwidth is achieved in the frequency domain and the inverse frequency domain data then give a high resolution coherent image.

关键词： Resolution beyond classical limits with spatial frequency heterodyning

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Projection of future streamflow of the Hunza River Basin,Karakoram Range(Pakistan)using HBV hydrological model

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Journal of Mountain Science 2018年第10期15卷 2218-2235页

作者： Ayaz Fateh ALI XIAO Cun-de ZHANG Xiao-peng Muhammad ADNAN mudassar IQBAL Garee KHAN State Key Laboratory of Cryospheric Science Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Land Surface and Resource Ecology Beijing Normal UniversityBeejing 100875China Key Laboratory of land Surface Process and Climate Change in Cold and Arid Regions Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 73o000China Department of Earth Sciences Karakoram International UniversityGilgit 15100Pakistan

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could

关键词： HBV Light model Hydrological modeling Hunza River Upper Indus Basin Snow and glacier-melt

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Improved Shark Smell Optimization Algorithm for Human Action Recognition

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Computers, Materials & Continua 2023年第9期76卷 2667-2684页

作者： Inzamam Mashood Nasir mudassar Raza Jamal Hussain Shah Muhammad Attique Khan Yun-Cheol Nam Yunyoung Nam Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Architecture Joongbu UniversityGoyang10279South Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma *** effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video *** Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature *** accuracy and effectiveness of these models continue to be the biggest challenge in this *** this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted *** proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search *** proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of *** local optimal features are selected,a global search is conducted to further optimize these *** proposed iSSO algorithm is employed on nine(9)selected CNN *** CNN models are selected based on their top-1 and top-5 accuracy in ImageNet *** evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.

关键词： Action recognition improved shark smell optimization convolutional neural networks machine learning

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Design of a gap tunable flux qubit with FastHenry

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Chinese Physics B 2016年第12期25卷 179-182页

作者： Naheed Akhtar 郑亚锐 mudassar Nazir 吴玉林邓辉郑东宁朱晓波 Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of Sciences

In the preparations of superconducting qubits, circuit design is a vital process because the parameters and layout of the circuit not only determine the way we address the qubits, but also strongly affect the qubit coherence properties. One of the most important circuit parameters, which needs to be carefully designed, is the mutual inductance among different parts of a superconducting circuit. In this paper we demonstrate how to design a gap-tunable flux qubit by layout design and inductance extraction using a fast field solver FastHenry. The energy spectrum of the gap-tunable flux qubit shows that the measured parameters are close to the design values.

关键词： superconducting circuit Josephson junction flux qubit FastHenry

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