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Journal of Pharmaceutical Analysis 2017年第4期7卷 258-264页

作者： Umar J.Pandit Gowhar A.Naikoo Mehraj Ud Din Sheikh gulzar a.khan K.K.Raj S.N.Limaye Department of Chemistry Dr. Harisingh Gour UniversitySagarM.P.India Department of Mathematics and Sciences College of Arts and Applied SciencesDofar UniversitySalalahOman

An electrochemically pretreated silver macroporous(Ag MP) multiwalled carbon nanotube modified glassy carbon electrode(PAN-Ag MP-MWCNT-GCE) was fabricated for the selective determination of an antihyperlipidimic drug, pitavastatin(PST). The fabricated electrochemical sensor was characterized by cyclic voltammetry(CV) and electrochemical impedance spectroscopy(EIS). The fabricated electrode was employed in quantifying and determining PST through differential pulse adsorptive stripping voltammetry(DPAdSV) and CV. The electrode fabrication proceeded with remarkable sensitivity to the determination of PST. The effect of various optimized parameters such as pH, scan rate(ν), accumulation time(t_(acc)), accumulation potential(U_(acc))and loading volumes of Ag MP-MWCNT suspension were investigated to evaluate the performance of synthesized electrochemical sensor and to propose a simple, accurate, rapid and economical procedure for the quantification of PST in pharmaceutical formulations and biological fluids. A linear response of PST concentration in the range 2.0×10^(-7)–1.6×10^(-6)M with low detection(LOD) and quantification(LOQ) limits of 9.66 ± 0.04 nM and 32.25 ± 0.07 nM, respectively, were obtained under these optimized conditions.

关键词： Pitavastatin Electrochemical sensor Adsorptive stripping voltammetry Biological fluids Pharmaceutical formulations

Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas khan Sajid Iqbal Yonis gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

Risk factors and outcomes of peptic ulcer bleed in a Pakistani population:A single-center observational study

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World Journal of Gastrointestinal Pharmacology and Therapeutics 2024年第3期15卷 1-9页

作者： Nazish Butt Muhammad Tayyab Usmani Nimrah Mehak Saba Mughal Fakhar Ali Qazi-Arisar Ghulam Mohiuddin gulzar khan Department of Gastroenterology Jinnah Postgraduate Medical CentreKarachi 75505SindhPakistan National Institute of Liver&GI Diseases Dow University of Health SciencesKarachi 75330SindhPakistan School of Public Health Dow University of Health SciencesKarachi 75330SindhPakistan

BACKGROUND Peptic ulcer disease(PUD)remains a significant healthcare burden,contributing to morbidity and mortality worldwide.Despite advancements in therapies,its prevalence persists,particularly in regions with widespread nonsteroidal antiinflammatory drugs(NSAIDs)use and Helicobacter pylori infection.AIM To comprehensively analyse the risk factors and outcomes of PUD-related upper gastrointestinal(GI)bleeding in Pakistani population.METHODS This retrospective cohort study included 142 patients with peptic ulcer bleeding who underwent upper GI endoscopy from January to December 2022.Data on demographics,symptoms,length of stay,mortality,re-bleed,and Forrest classification was collected.RESULTS The mean age of patients was 53 years,and the majority was men(68.3%).Hematemesis(82.4%)and epigastric pain(75.4%)were the most common presenting symptoms.Most patients(73.2%)were discharged within five days.The mortality rates at one week and one month were 10.6%and 14.8%,respectively.Re-bleed within 24 h and seven days occurred in 14.1%and 18.3%of patients,respectively.Most ulcers were Forrest class(FC)Ⅲ(72.5%).Antiplatelet use was associated with higher mortality at 7 and 30 d,while alternative medications were linked to higher 24-hour re-bleed rates.NSAID use was associated with more FCⅢulcers.Re-bleed at 24 h and 7 d was strongly associated with one-week or one-month mortality.CONCLUSION Antiplatelet use and rebleeding increase the risk of early mortality in PUD-related upper GI bleeding,while alternative medicines are associated with early rebleeding.

关键词： Non variceal bleed Mortality Re-bleed Forrest classification Antiplatelets Alternative medicines

An Energy-Efficient Mobile Agent-Based Data Aggregation Scheme for Wireless Body Area Networks

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Computers, Materials & Continua 2022年第3期70卷 5929-5948页

作者： gulzar Mehmood Muhammad Zahid khan Muhammad Fayaz Mohammad Faisal Haseeb Ur Rahman Jeonghwan Gwak Department of Computer Science&Information Technology University of MalakandChakdara Dir Lower23021Pakistan Department of Computer Science University of Central AsiaNarynKyrgyzstan Department of Software Korea National University of TransportationChungju27469Korea Department of Biomedical Engineering Korea National University of TransportationChungju27469Korea Department of AI Robotics Engineering Korea National University of TransportationChungju27469Korea Department of IT and Energy Convergence(BK21 FOUR) Korea National University of TransportationChungju27469Korea

Due to the advancement in wireless technology and miniaturization,Wireless Body Area Networks(WBANs)have gained enormous popularity,having various applications,especially in the healthcare sector.WBANs are intrinsically resource-constrained;therefore,they have specific design and development requirements.One such highly desirable requirement is an energy-efficient and reliable Data Aggregation(DA)mechanism for WBANs.The efficient and reliableDAmay ultimately push the network to operate without much human intervention and further extend the network lifetime.The conventional client-serverDAparadigm becomes unsuitable and inefficient for WBANs when a large amount of data is generated in the network.Similarly,in most of the healthcare applications(patient’s critical conditions),it is highly important and required to send data as soon as possible;therefore,reliable data aggregation in WBANs is of great concern.To tackle the shortcomings of the client-serverDAparadigm,theMobile Agent-Basedmechanismproved to be a more workable solution.In aMobile Agent-Based mechanism,a taskspecific mobile agent(code)traverses to the intended sources to gather data.Thesemobile agents travel on a predefined path called itinerary;however,planning a suitable and reliable itinerary for a mobile agent is also a challenging issue inWBANs.This paper presents a new Mobile Agent-Based DA scheme for WBANs,which is energy-efficient and reliable.Firstly,in the proposed scheme,the network is divided into clusters,and cluster-heads are selected.Secondly,a mobile agent is generated from the base station to collect the required data from cluster heads.In the case,if any fault occurs in the existing itinerary,an alternate itinerary is planned in real-time without compromising the network performance.In our simulation-based validation,we have found that the proposed system delivers significantly improved fault-tolerance and reliability with energy-efficiency and extended network lifetime in WBANs.

关键词： WBANs mobile-agent data aggregation reliability

Connective tissue growth factor expression hints at aggressive nature of colorectal cancer

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World Journal of Gastroenterology 2022年第5期28卷 547-569页

作者： Ishrat Parveiz Bhat Tahseen Bilal Rather Irfan Maqbool Gowhar Rashid Kulsum Akhtar gulzar A Bhat Fazl Q Parray Besina Syed Ishrat Younas khan Mohsin Kazi Muhammad D Hussain Mudassar Syed Department of Clinical Biochemistry Sher-I-Kashmir Institute of Medical SciencesSrinagar 190011Jammu and KashmirIndia Department of General Surgery Sher-I-Kashmir Institute of Medical SciencesSrinagar 190011Jammu and KashmirIndia Department of Pathology Sher-I-Kashmir Institute of Medical SciencesSrinagar 190011Jammu and KashmirIndia Department of Pharmaceutics College of PharmacyKing Saud UniversityPO Box 2457Riyadh 11451Saudi Arabia Department of Pharmaceutical and Biomedical Sciences California Health Sciences UniversityCaliforniaCA 93612United States

BACKGROUND Connective tissue growth factor(CTGF)is a mediator of transforming growth factor-beta signaling and plays a key role in connective tissue remodeling,inflammatory processes and fibrosis in various illnesses including cancer.AIM To investigate the role of CTGF in colorectal cancer(CRC)progression and to compare the CTGF expression with different clinicopathological parameters.METHODS Real-time polymerase chain reaction,immunohistochemistry and Western blotting was performed to evaluate the CTGF expression and the results were statistically analyzed against the clinicopathological variables of patient data using STATA software version 16.RESULTS CTGF expression levels in tumor specimens were significantly higher than their paired normal specimens.The higher protein expression levels showed a significant association with smoking,staging,tumor grade,invasion depth,necrosis of tumor tissue,and both lymphovascular and perineural invasion.As per the cox regression model and classification tree analysis,tumor-nodemetastasis stage and perineural invasion were important predictors for CTGF expression and prognosis of CRC patients.Survival analysis indicated that CTGF overexpression was associated with poorer overall and disease-free survival.CONCLUSION Expression of CTGF was increased in CRC and was linked with poor overall and disease-free survival of CRC patients.These findings support prior observations and thus CTGF may be a possible prognostic marker in CRC.

关键词： Connective tissue growth factor Quantitative real time polymerase chain reaction Immunohistochemistry Western blotting Colorectal cancer

Conformal Killing Vectors in LRS Bianchi Type Ⅴ Spacetimes

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Communications in Theoretical Physics 2016年第3期65卷 315-320页

作者： Suhail khan Tahir Hussain Ashfaque H.Bokhari gulzar Ali khan Department of Mathematics University of Peshawar Department of Mathematics and Statistics King Fahd University of Petroleum and Minerals

In this note,we investigate conformal Killing vectors(CKVs)of locally rotationally symmetric(LRS)Bianchi type V spacetimes.Subject to some integrability conditions,CKVs up to implicit functions of(t,x)are obtained.Solving these integrability conditions in some particular cases,the CKVs are completely determined,obtaining a classification of LRS Bianchi type V spacetimes.The inheriting conformal Killing vectors of LRS Bianchi type V spacetimes are also discussed.

关键词： Killing LRS 时空矢量保形可积条件旋转对称隐函数

Land-Cover Classification and its Impact on Peshawar’s Land Surface Temperature Using Remote Sensing

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Computers, Materials & Continua 2022年第2期70卷 4123-4145页

作者： Shahab Ul Islam Saifullah Jan Abdul Waheed gulzar Mehmood Mahdi Zareei Faisal Alanazi Department of Computer Science IQRA National UniversityPeshawar25124Pakistan Department of Computer Science City University of Science&Information TechnologyPeshawar25124Pakistan Department of Information Technology Hazara UniversityMansehra21120Pakistan School of Electrical and Computer Engineering Seoul National UniversitySeoul08826Korea Department of Computer Science and Information Technology University of Malakand23021Pakistan Tecnologico de Monterrey School of Engineering and SciencesZapopan45201Mexico Department of Electrical Engineering Prince Sattam Bin Abdulaziz UniversityCollege of EngineeringAl Kharj16278Saudi Arabia

Spatial and temporal informationon urban infrastructure is essential and requires various land-cover/land-use planning and management applications.Besides,a change in infrastructure has a direct impact on other land-cover and climatic conditions.This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature(LST)during the years 1996 and 2019.For this purpose,firstly,satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper)plus and OLI(Operational Land Imager)of 30 m resolution were taken.Secondly,for classification and image processing,remote sensing(RS)applications ENVI(Environment for Visualising Images)and GIS(Geographic Information System)were used.Thirdly,for better visualization and more in-depth analysis of land sat images,pre-processing techniques were employed.For Land use and Land cover(LU/LC)four types of land cover areas were identified-vegetation area,water cover,urbanized area,and infertile land for the years under research.The composition of red,green,and near infra-red bands was used for supervised classification.Classified images were extracted for analyzing the relative infrastructure change.A comparative analysis for the classification of images is performed for SVM(Support Vector Machine)and ANN(Artificial Neural Network).Based on analyzing these images,the result shows the rise in the average temperature from 30.04℃ to 45.25℃.This only possible reason is the increase in the built-up area from 78.73 to 332.78 Area km^(2) from 1996 to 2019.It has also been witnessed that the city’s sides are hotter than the city’s center due to the barren land on the borders.

关键词： Remote sensing temperature extraction urbanization satellite image classification artificial neural network support vector machine LU/LC land surface temperature

Variation in patient dose due to differences in calibration and dosimetry protocols

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Nuclear Science and Techniques 2018年第5期29卷 44-49页

作者： Wazir Muhammad Asad Ullah gulzar khan Tahir Zeb khan Tauseef Jamaal Fawad Ullah Matiullah khan Amjad Hussain Department of Therapeutic Radiology Yale-School of MedicineYale UniversityNew HavenCT 06520-8040USA Heath Physics Division(HPD) Pakistan Institute of Nuclear Science and Technology(PINSTECH)Islamabad 45650Pakistan Department of Physics Abul Wali Khan UniversityMardan 23200Pakistan Pakistan Institute Nuclear Science&Technology(PIEAS) Islamabad 45650Pakistan Department of Physics Kohat University of Science and TechnologyKohat 26000Pakistan Department of Medical Physics CancerCare ManitobaBrandonMB R7A 2B3Canada

For precise and accurate patient dose delivery,the dosimetry system must be calibrated properly according to the recommendations of standard dosimetry protocols such as TG-51 and TRS-398. However, the dosimetry protocol followed by a calibration laboratory is usually different from the protocols that are followed by different clinics, which may result in variations in the patient dose.Our prime objective in this study was to investigate the effect of the two protocols on dosimetry measurements.Dose measurements were performed for a Co-60 teletherapy unit and a high-energy Varian linear accelerator with 6 and 15 MV photon and 6, 9, 12, and 15 MeV electron beams, following the recommendations and procedures of the AAPM TG-51 and IAEA TRS-398 dosimetry protocols. The dosimetry systems used for this study were calibrated in a Co-60 radiation beam at the Secondary Standard Dosimetry Laboratory(SSDL) PINSTECH,Pakistan, following the IAEA TRS-398 protocol. The ratio of the measured absorbed doses to water in clinical setting,D_w(TG-51/TRS-398), was 0.999 and 0.997 for 6 and15 MV photon beams,whereas these ratios were 1.013,1.009, 1.003, and 1.000 for 6, 9, 12, and 15 MeV electron beams, respectively. This difference in the absorbed dosesto-water D_w ratio may be attributed mainly due to beam quality(K_Q) and ion recombination correction factor.

关键词： Radiation dosimetry Dosimetry systems calibrations Patient dose Absorbed dose-to-water ratio AAPM TG-51 IAEA TRS-398

Innovative Fungal Disease Diagnosis System Using Convolutional Neural Network

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Computers, Materials & Continua 2022年第12期73卷 4869-4883页

作者： Tahir Alyas Khalid Alissa Abdul Salam Mohammad Shazia Asif Tauqeer Faiz gulzar Ahmed Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Networks and Communications Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of General Education Skyline University CollegeUniversity City of SharjahUAE Higher Colleges of Technology Abu DhabiUAE Department of Enterprise Computing Skyline University CollegeSharjahUAE Department of Computer Science University of South AsiaLahore54000Pakistan

Fungal disease affects more than a billion people worldwide,resulting in different types of fungus diseases facing life-threatening infections.The outer layer of your body is called the integumentary system.Your skin,hair,nails,and glands are all part of it.These organs and tissues serve as your first line of defence against bacteria while protecting you from harm and the sun.The It serves as a barrier between the outside world and the regulated environment inside our bodies and a regulating effect.Heat,light,damage,and illness are all protected by it.Fungi-caused infections are found in almost every part of the natural world.When an invasive fungus takes over a body region and overwhelms the immune system,it causes fungal infections in people.Another primary goal of this study was to create a Convolutional Neural Network(CNN)-based technique for detecting and classifying various types of fungal diseases.There are numerous fungal illnesses,but only two have been identified and classified using the proposed Innovative Fungal Disease Diagnosis(IFDD)system of Candidiasis and Tinea Infections.This paper aims to detect infected skin issues and provide treatment recommendations based on proposed system findings.To identify and categorize fungal infections,deep machine learning techniques are utilized.A CNN architecture was created,and it produced a promising outcome to improve the proposed system accuracy.The collected findings demonstrated that CNN might be used to identify and classify numerous species of fungal spores early and estimate all conceivable fungus hazards.Our CNN-Based can detect fungal diseases through medical images;earmarked IFDD system has a predictive performance of 99.6%accuracy.

关键词： Deep machine learning CNN ReLU skin disease fungal

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

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Computers, Materials & Continua 2021年第2期66卷 1595-1612页

作者： Kashif Iqbal Sagheer Abbas Muhammad Adnan khan Atifa Ather Muhammad Saleem khan Areej Fatima gulzar Ahmad School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Sciences GC UniversityLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Comsats University IslamabadLahore CampusLahore54000Pakistan

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity.Vision-based target detection and object classification have been improved due to the development of deep learning algorithms.Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise,well-engineered,and complete detection of objects,scene or events.The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection.In this study we examined to solve these problems described by(1)extracting region-of-interest in the images(2)vehicle detection based on instance segmentation,and(3)building deep learning model based on the key features obtained from input parking images.We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces.Image augmentation techniques were performed using edge detection,cropping,refined by rotating,thresholding,resizing,or color augment to predict the region of bounding boxes.A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling,training,validating and testing on parking video frames through video-camera.The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6%than previous reported methodologies.Moreover,this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection.The results are verified using Python,TensorFlow,OpenCV computer simulation frameworks.

关键词： Smart parking-lot detection deep convolutional neural network data augmentation region-of-interest object detection