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Cosmetic evaluation of surgical scars after external dacryocystorhinostomy

International Journal of Ophthalmology(English edition) 2016年第12期9卷 1745-1750页

作者： syed ali raza rtzvi Mohammad Saquib Rakesh Maheshwari Yogesh Gupta Zafr Igbal Purleet Maheshwari Institute of Ophthalmology Jawaharlal Nehru Medical College AMU Aligarh.UP 202002 India Department of Oto-Rhino-Laryngology Jawaharlal Nehru Medical College AMU Aligarh.UP 202002 India Department of Oto-Rhino-Laryngology Era's Lucknow Medical College and Hospital Lucknow.UP 226003 India

AIM： To evaluate the surgical scars of external dacryocystorhinostomy （DCR） cosmetically. METHODS： Totally 50 consecutive cases of primary acquired nasolacrimal duct obstruction （PANDO） were included in the study. Surgical scars were assessed by the patients and two independent observers at 2, 6 and 12wk postoperatively on the basis of visibility of the scars and still photographs respectively and were graded from 0-3. Kappa test was utilised to check the agreement of scar grading between the two observers. Wilcoxan signed ranks test was used to analyse the improvement of scar ***： Thirty-four （68%） patients graded their incision site as very visible （grade 3） at 2wk. At 6 and 12wk, incision site was observed as grade 3 by 7 （14%） and 1 （2%） patients respectively. Photographic evaluation of patients by 2 observers showed an average score of 2.75, 1.94 and 0.94 at 2, 6 and 12wk respectively. Change in scar grading from grade 3 to grade 0 in consecutive follow-up （2, 6 and 12wk） was found to be highly significant both for the patient as well for the observers （P〈0.0001）.CONCLUSION： The external DCR is a highly effective and safe procedure and in view of low percentage of cases who complained of marked scarring in the present study, thus scarring should not be the main ground for deciding the approach to DCR surgery, even in young cosmetically conscious patients.

关键词： cosmetic surgical scar external dacryocystorhinostomy primary acquired nasolacrimal duct obstruction

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“Superimposed”spectral characteristics of fluorophores arising from cross-conjugation hybridization

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Chinese Chemical Letters 2025年第1期36卷 442-446页

作者： Kai An Qinglong Qiao Lovelesh syed ali Abbas Abedi Xiaogang Liu Zhaochao Xu CAS Key Laboratory of Separation Science for Analytical Chemistry Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China University of Chinese Academy of Sciences Beijing 100049China Fluorescence Research Group Singapore University of Technology and DesignSingapore 487372Singapore

The demand for enhanced optical properties in advanced fluorescence technologies has driven research into the structure-property relationship of *** this paper,we use naphthalene fluorophores Na DC-Aze and PhDO-Aze as a case study to emphasize the pivotal role of cross conjugation in tuning the optical structure-property *** DC-Aze and PhDO-Aze,formed by hybridizing two distinct conjugated systems in a single naphthalene molecule,exhibit spectral characteristics from both conjugated *** data and theoretical calculations demonstrate the coexistence of two electron-delocalization systems in a cross-conjugation manner in both Na DC-Aze and *** cross-conjugation fluorophores exhibit high brightness,large Stokes shift,and a broad absorption wavelength range by combining distinct spectral properties from its parent *** spectral properties will be advantageous for certain applications(i.e.,panchromatic absorption in organic solar cells,and fluorophores compatible with a wide range of excitation wavelengths).

关键词： Fluorophore Cross conjugation Absorption Emission Naphthalene

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Recent developments in MQL machining of aeronautical materials:A comparative review

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Chinese Journal of Aeronautics 2025年第1期38卷 43-69页

作者： syed Hammad ali Yu YAO Bangfu WU Biao ZHAO Wenfeng DING Muhammad JAMIL Ahmar KHAN Asra BAIG Qi LIU Dongdong XU National Key Laboratory of Science and Technology on Helicopter Transmission Nanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Mechanical Engineering NED University of Engineering and TechnologyKarachi 75270Pakistan Centre for Precision Manufacturing University of StrathclydeGlasgow G11XQUK School of Mechanical Engineering Tongji UniversityShanghai 200092China

Minimum quantity lubrication(MQL),as a new sustainable and eco-friendly alternative cooling/lubrication technology that addresses the limitations of dry and wet machining,utilizes a small amount of lubricant or coolant to reduce friction,tool wear,and heat during cutting *** technique has witnessed significant developments in recent years,such as combining MQL with other sustainable techniques to achieve optimum results,using biodegradable lubricants,and innovations in nozzle designs and delivery *** review presents an in-depth analysis of machining characteristics(e.g.,cutting forces,temperature,tool wear,chip morphology and surface integrity,etc.)and sustainability characteristics(e.g.,energy consumption,carbon emissions,processing time,machining cost,etc.)of conventional MQL and hybrid MQL techniques like cryogenic MQL,Ranque-Hilsch vortex tube MQL,nanofluids MQL,hybrid nanofluid MQL and ultrasonic vibration assisted MQL in machining of aeronautical ***,the latest research and developments are analyzed and summarized in the field of MQL,and provide a detailed comparison between each technique,considering advantages,challenges,and limitations in practical *** addition,this review serves as a valuable source for researchers and engineers to optimize machining processes while minimizing environmental impact and operational ***,the potential future aspects of MQL for research and industrial execution are discussed.

关键词： Aerospace materials Minimum Quantity Lubrication(MQL) Cryogenic Nanofluid Grinding Milling Sustainability

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Ultrasonic vibration-assisted cutting of titanium alloys:A state-of-the-art review

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Chinese Journal of Aeronautics 2025年第1期38卷 3-42页

作者： Ahmar KHAN Xin WANG Biao ZHAO Wenfeng DING Muhammad JAMIL Aqib Mashood KHAN syed Hammad ali Sadam HUSSAIN Jiong ZHANG Raj DAS National Key Laboratory of Science and Technology on Helicopter Transmission Nanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Mechanical Engineering College of EngineeringCity University of Hong KongHong Kong 999077China Centre for Additive Manufacturing School of EngineeringAerospace Engineering and AviationRMIT UniversityVictoria 3083Australia

The remarkable ability of titanium alloys to preserve their superior physical and chemical characteristics when subjected to extreme conditions significantly enhances their importance in the aerospace,military,and medical ***,conventional machining of titanium alloys leads to elevated tool wear,development of surface defects,and reduced machining efficiency due to their low heat conductivity,and chemical *** issues can be somewhat counteracted by integrating ultrasonic vibration in the conventional machining of titanium alloys and also enhance *** review article offers a holistic evaluation of the influence of ultrasonic vibration-assisted milling and turning on cutting forces,temperature,tool wear,and surface integrity,encompassing surface morphology,surface roughness,surface residual stress,surface hardness,and surface tribological properties during titanium alloys ***,it investigates the sustainability aspect that has not been previously *** on the performance of ultrasonic-assisted cutting revealed several advantages,including decreased cutting forces and cutting temperature,improved tool life,and a better-machined surface during ***,the sustainability factor is improved due to minimized energy consumption and residual *** conclusion,the key challenges and future prospects in the ultrasonic-assisted cutting of titanium alloys are also *** review article provides beneficial knowledge for manufactur-ers and researchers regarding ultrasonic vibration-assisted cutting of titanium alloy and will play an important role in achieving sustainability in the industry.

关键词： Ultrasonic vibration-assisted cutting Titanium alloys Material removal mechanism Machinability Sustainability

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Deep Learning and Artificial Intelligence-Driven Advanced Methods for Acute Lymphoblastic Leukemia Identification and Classification: A Systematic Review

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Computer Modeling in Engineering & Sciences 2025年第2期142卷 1199-1231页

作者： syed Ijaz Ur Rahman Naveed Abbas Sikandar ali Muhammad Salman Ahmed Alkhayat Jawad Khan Dildar Hussain Yeong Hyeon Gu Department of Computer Science Islamia CollegePeshawar25120Pakistan Department of Information Technology The University of HaripurHaripur22620Pakistan College of Technical Engineering The Islamic UniversityNajaf100986Iraq School of Computing Gachon UniversitySeongnam13120Republic of Korea Department of AI and Data Science Sejong UniversitySeoul05006Republic of Korea

Automatic detection of Leukemia or blood cancer is one of the most challenging tasks that need to be addressed in the healthcare *** of white blood cells(WBCs)in the blood or bone marrow microscopic slide images play a crucial part in early identification to facilitate medical *** Acute Lymphocytic Leukemia(ALL),the most preferred part of the blood or marrow is to be analyzed by the experts before it spreads in the whole body and the condition becomes *** researchers have done a lot of work in this field,to demonstrate a comprehensive analysis few literature reviews have been published focusing on various artificial intelligence-based techniques like machine and deep learning detection of *** systematic review has been done in this article under the PRISMA guidelines which presents the most recent advancements in this *** image segmentation techniques were broadly studied and categorized from various online databases like Google Scholar,Science Direct,and PubMed as image processing-based,traditional machine and deep learning-based,and advanced deep learning-based models were *** Neural Networks(CNN)based on traditional models and then the recent advancements in CNN used for the classification of ALL into its subtypes.A critical analysis of the existing methods is provided to offer clarity on the current state of the ***,the paper concludes with insights and suggestions for future research,aiming to guide new researchers in the development of advanced automated systems for detecting life-threatening diseases.

关键词： Acute lymphoblastic bone marrow segmentation classification machine learning deep learning convolutional neural network

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Decoding molecular mechanisms:brain aging and Alzheimer's disease

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Neural Regeneration Research 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay ali syed Hammad Qaiser Mohammad Uzair Khalid Al-Regaiey Roaa Khallaf Lubna Abdullah Mohammed Albassam Imdad Kaleem Xueyi Wang Ran Wang Mehwish SBhatti Shahid Bashir Atta-ur-Rahman School of Applied Biosciences(ASAB) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological Sciences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Physiology College of MedicineKing Saud UniversityRiyadhSaudi Arabia Department of Neurology Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Mental Health Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Biosciences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Psychiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Institute of Hebei Medical University ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuroscience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for *** aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as Alzheimer's *** these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging *** these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect *** review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of Alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly Alzheimer's disease.

关键词： Alzheimer’s disease brain aging cognitive health dementia molecular mechanisms neuronal activity neuroplasticity neurotransmission

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Intelligent Islanding Detection of Multi-distributed Generation Using Artificial Neural Network Based on Intrinsic Mode Function Feature

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Journal of Modern Power Systems and Clean Energy 2020年第3期8卷 511-520页

作者： Samuel Admasie syed Basit ali Bukhari Teke Gush raza Haider Chul Hwan Kim Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwonSouth Korea U.S.-Pakistan Center for Advanced Studies in Energy(USPCAS-E) National University of Sciences and Technology(NUST)H-12 IslamabadPakistan Department of Electrical Engineering Balochistan University of Engineering and TechnologyKhuzdar 89100Pakistan

The integration of distributed energy resources(DERs) into distribution networks is becoming increasingly important, as it supports the continued adoption of renewable power generation, combined heat and power plants, and storage systems. Nevertheless, inadvertent islanding operation is one of the major protection issues in distribution networks connected to DERs. This study proposes an intelligent islanding detection method(IIDM) using an intrinsic mode function(IMF)feature-based grey wolf optimized artificial neural network(GWO-ANN). In the proposed IIDM, the modal voltage signal is pre-processed by variational mode decomposition followed by Hilbert transform on each IMF to derive highly involved features. Then, the energy and standard deviation of IMFs are employed to train/test the GWO-ANN model for identifying the islanding operations from other non-islanding events. To evaluate the performance of the proposed IIDM, various islanding and non-islanding conditions such as faults, voltage sag, linear and nonlinear load and switching, are considered as the training and testing datasets. Moreover, the proposed IIDM is evaluated under noise conditions for the measured voltage signal. The simulation results demonstrate that the proposed IIDM is capable of differentiating between islanding and non-islanding events without any sensitivity under noise conditions in the test signal.

关键词： Distributed energy resource(DER) intrinsic mode function(IMF) grey wolf optimized artificial neural network(GWO-ANN) intelligent islanding detection method(IIDM) microgrid

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Empirical Thermal Investigation of Oil-Immersed Distribution Transformer under Various Loading Conditions

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Computer Modeling in Engineering & Sciences 2021年第11期129卷 829-847页

作者： syed ali raza Ahsan Ullah Shuang He Yifeng Wang Jiangtao Li School of Electrical Engineering Xi’an Jiaotong UniversityXi’an710049China

The distribution transformer is the mainstay of the power *** internal temperature study is desirable for its safe operation in the power *** purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading *** achieve this goal,the temperature distribution in the oil,core,and windings are studied at each *** experimental study is performed with a 10/0.38 kV,10 kVA oil–immersed transformer equipped with forty–two PT100 sensors(PTs)for temperature measurement installed inside during its manufacturing *** possible locations for the hottest spot temperature(HST)are considered that made by finite element analysis(FEA)simulation and losses calculations.A resistive load is made to achieve 80%to 120%loading of the test transformer for this *** temperature is measured in each part of the transformer at all provided loading *** is observed that temperature varies with loading throughout the transformer,and a detailed map of temperature is obtained in the whole test *** these results,the HST stays in the critical section of the primary winding at all loading *** work is helpful to understand the complete internal temperature layout and the location of the HST in distribution transformers.

关键词： Distribution transformer direct temperature measurement sensor location loading conditions hottest spot temperature thermal distribution

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Low Impedance Fault Identification and Classification Based on Boltzmann Machine Learning for HVDC Transmission Systems

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 440-449页

作者： Raheel Muzzammel ali raza the Department of Electrical Engineering University of LahoreLahore 54000Pakistan

Identification and classification of DC faults are considered as fundamentals of DC grid protection.A sudden rise of DC fault current must be identified and classified to immediately operate the corresponding interrupting *** this paper,the Boltzmann machine learning(BML)approach is proposed for identification and classification of DC faults using travelling waves generated at fault point in voltage source converter based high-voltage direct current(VSC-HVDC)transmission *** unsupervised way of feature extraction is performed on the frequency spectrum of the travelling *** class logistic regression(BCLR)classifies the HVDC transmission system into faulty and healthy *** proposed technique reduces the time for fault identification and classification because of reduced tagged data with few ***,the faults near or at converter stations are readily identified and *** performance of the proposed technique is assessed via simulations developed in MATLAB/Simulink and tested for pre-fault and post-fault data both at VSC1 and VSC2,***,the proposed technique is supported by analyzing the root mean square error to show practicality and realization with reduced computations.

关键词： Binary class logistic regression(BCLR) Boltzmann machine learning(BML) DC grid protection fault identification and classification voltage source converter based high-voltage direct current(VSC-HVDC)transmission system

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Mathematical Modelling of Rotavirus Disease Through Efficient Methods

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Computers, Materials & Continua 2022年第9期72卷 4727-4740页

作者： ali raza Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan

The design of evolutionary approaches has a vital role in the recent development of scientific *** tackle highly nonlinear complex problems,nonlinear ordinary differential equations,partial differential equations,stochastic differential equations,and many more may called computational *** rotavirus causes may include severe diarrhea,vomiting,and fever leading to rapid *** the report of the World Health Organization(WHO),approximately 600,000 children die worldwide each year,80 percent of whom live in developing *** million children are hospitalized each *** Asia,up to 45 percent of the children hospitalized for diarrhea may be infected with *** rotavirus model is categorized into five-compartment like susceptible(S),breastfeeding(M),vaccinated(V),infected(I),and recovered children(R).Positivity,boundedness,equilibria,reproduction number,and stability results are part of the qualitative analysis of the *** that,the design of the evolutionary approaches on the model predicts the efficiency,visualization,long-term behavior of the disease,and best results of the rotavirus *** the end,evolutionary computations are an appropriate tool for double-checking the qualitative examination of the model.

关键词： Rotavirus disease epidemic model methods comparison analysis

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