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| 1 | Type Ⅰ and type Ⅱ Helicobacter pylori infection status and their impact on gastrin and pepsinogen level in a gastric cancer prevalent area显示文摘BACKGROUND Type I Helicobacter pylori(H.pylori)infection causes severe gastric inflammation and is a predisposing factor for gastric carcinogenesis.However,its infection status in stepwise gastric disease progression in this gastric cancer prevalent area has not been evaluated;it is also not known its impact on commonly used epidemiological gastric cancer risk markers such as gastrin-17(G-17)and pepsinogens(PGs)during clinical practice.AIM To explore the prevalence of type I and type II H.pylori infection status and their impact on G-17 and PG levels in clinical practice.METHODS Thirty-five hundred and seventy-two hospital admitted patients with upper gastrointestinal symptoms were examined,and 523 patients were enrolled in this study.H.pylori infection was confirmed by both 13C-urea breath test and serological assay.Patients were divided into non-atrophic gastritis(NAG),nonatrophic gastritis with erosion(NAGE),chronic atrophic gastritis(CAG),peptic ulcers(PU)and gastric cancer(GC)groups.Their serological G-17,PG I and PG II values and PG I/PG II ratio were also measured.RESULTS A total H.pylori infection rate of 3572 examined patients was 75.9%,the infection rate of 523 enrolled patients was 76.9%,among which type I H.pylori infection accounted for 72.4%(291/402)and type II was 27.6%;88.4%of GC patients were H.pylori positive,and 84.2%of them were type I infection,only 11.6%of GC patients were H.pylori negative.Infection rates of type I H.pylori in NAG,NAGE,CAG,PU and GC groups were 67.9%,62.7%,79.7%,77.6%and 84.2%,respectively.H.pylori infection resulted in significantly higher G-17 and PG II values and decreased PG I/PG II ratio.Both types of H.pylori induced higher G-17 level,but type I strain infection resulted in an increased PG II level and decreased PG I/PG II ratio in NAG,NAGE and CAG groups over uninfected controls.Overall PG I levels showed no difference among all disease groups and in the presence or absence of H.pylori;in stratified analysis,its level was increased in GC and PU patients in H.pylori and type I H.pylori-positive groups.CONCLUSION Type I H.pylori infection is the major form of infection in this geographic region,and a very low percentage(11.6%)of GC patients are not infected by H.pylori.Both types of H.pylori induce an increase in G-17 level,while type I H.pylori is the major strain that affects PG I and PG IIs level and PG I/PG II ratio in stepwise chronic gastric disease.The data provide insights into H.pylori infection status and indicate the necessity and urgency for bacteria eradication and disease prevention in clinical practice. | Lin Yuan Jun-Bo Zhao Ying-Lei Zhou Ya-Bin Qi Qiong-Ya Guo Hai-Hui Zhang Muhammad Noman Khan Ling Lan Chang-He Jia Yan-Rui Zhang Song-Ze Ding | 2020 | World Journal of Gastroenterology2020，26，25： | 29 |
| 2 | Gastric mucosal precancerous lesions in Helicobacter pyloriinfected pediatric patients in central China:A single-center,retrospective investigation显示文摘BACKGROUND Helicobacter pylori(H.pylori)infects about 50%of the world population and is the major cause of chronic gastritis,peptic ulcers,and gastric cancer.Chronic H.pylori infection induces gastric mucosal precancerous lesions mostly in adulthood,and it is debatable whether these pathological conditions can occur in childhood and adolescents as well.Since this is a critical issue to determine if intervention should be offered for this population group,we investigated the gastric mucosal precancerous lesions in pediatric patients in an area in central China with a high prevalence of H.pylori and gastric cancer.AIM To investigate the relationship of H.pylori infection and gastric mucosal precancerous lesions in children and adolescents in central China.METHODS We screened 4258 ward-admitted children and adolescent patients with upper gastrointestinal symptoms,and finally enrolled 1015 pediatric patients with H.pylori infection and endoscopic and histological data.H.pylori infection status was determined by rapid urease test and histopathological examination.Both clinical and pathological data were collected and analyzed retrospectively.Occurrence of gastric mucosal precancerous lesions,inflammatory activity and degree of inflammatory cell infiltration between H.pylori-positive and-negative groups were compared.RESULTS Among the 1015 eligible children and adolescents,the overall H.pylori infection rate was 84.14%(854/1015).The infection rate increased with age.The incidence of gastric mucosal precancerous lesions in H.pylori-infected children was 4.33%(37/854),which included atrophic gastritis(17 cases),intestinal metaplasia(11 cases)and dysplasia(9 cases).In H.pylori-negative patients,only 1 atrophic gastritis case[0.62%,(1/161)]was found(P<0.05).Active inflammation in H.pyloriinfected patients was significantly higher than that in non-infected patients,and the H.pyloriinfected group showed more severe lymphocyte and neutrophil granulocyte infiltration(P<0.001).In addition,endoscopy revealed that the most common findings in H.pylori-positive patients were antral nodularity,but in H.pylori-negative patients only superficial gastritis was observed.CONCLUSION In children and adolescents,gastric mucosal precancerous lesions occurred in 4.33%of H.pyloriinfected patients in central China.These cases included atrophic gastritis,intestinal metaplasia,and dysplasia.The data revealed an obvious critical issue requiring future investigation and intervention for this population group. | Miao Yu Jing Ma Xiao-Xia Song Qiao-Qiao Shao Xue-Chun Yu Muhammad Noman Khan Ya-Bin Qi Ruo-Bing Hu Pei-Ru Wei Wei Xiao Bai-Ling Jia Yan-Bo Cheng Ling-Fei Kong Chuan-Liang Chen Song-Ze Ding | 2022 | World Journal of Gastroenterology2022，28，28： | 2 |
| 3 | Synthesis of yttrium and cerium doped ZnO nanoparticles as highly inexpensive and stable photocatalysts for hydrogen evolution显示文摘Yttrium and cerium co-doped ZnO nanoparticles were synthesized by combustion route and characterized using X-ray diffraction(XRD),scanning electron microscopy(SEM),Brunauer-Emmett-Teller(BET),energy dispersive spectroscopy(EDS),X-ray photoelectron spectroscopy(XPS),UV-visible diffuse reflectance spectroscopy(UV-vis DRS),photoluminescence(PL)and electrochemical impedance spectroscopy(EIS)techniques.The introduction of yttrium ions has efficiently increased the relative percentage of Ce^(3+)ions in ZnO.Yttrium and cerium co-doped ZnO shows efficient photo activity for hydrogen evolution(10.61 mmol/((g·h))higher than previously reported optimal value for rare earth codoped ZnO photocatalysts.This remarkably increased hydrogen evolution can be ascribed to the synergy between electronic anchoring effect of Y^(3+)/Y^(2+)and Ce^(4+)/Ce^(3+)redox couples.This report presents new idea for the synthesis of efficient photocatalyst using economical route and ion anchoring effect.The hydrogen evolution was also tested using Na_(2)S and Na_(2)SO_(3)as electron donors under visible light illumination.The synthesized photocatalysts also exhibit high stability. | Irshad Ahmad Muhammad Shoaib Akhtar Mian Faisal Manzoor Muhammad Wajid Muhammad Noman Ejaz Ahmed Mukhtar Ahmad Waheed Qamar Khan Anwar M.Rana | 2021 | Journal of Rare Earths2021，39，4： | 2 |
| 4 | Numerical investigation of modal and fatigue performance of a horizontal axis tidal current turbine using fluid-structure interaction显示文摘The tidal power has the potential to play a vital role in a sustainable energy future.The main objective of this paper is to investigate the performance and fatigue life of tidal current turbine(TCT)using fluid structure interaction(FSI)modeling.The performance of TCT was predicted using Ansys CFX.The performance curve,pressure distribution on the blade,and velocity streamline were visualized for eight repetitive analyses at different tip speed ratio.The hydrodynamic load calculated from CFD analysis was transferred to FEA model for investigation of the structural response of TCT.Modal analysis was performed to examine the mode shapes and natural frequencies of TCT.The fatigue analysis were performed and number of cycles and safety factor at different equivalent alternating stresses were investigated.The results of the simulation confirm that the turbine has a maximum value of the coefficient of performance atλ=5,the turbine operating frequency is not close to its natural frequency,and it is safe under the applied fatigue loads with a high factor of safety. | Habib Ullah Muzamil Hussain Naseem Abbas Hassaan Ahmad Mohammed Amer Muhammad Noman | 2019 | Journal of Ocean Engineering and Science2019，4，4： | 1 |
| 5 | Image magnification using adaptive interpolation by pixel level data-dependent geometrical shapes显示文摘 | Muhammad Sajjad Naveed Khattak Noman Jafri | 2007 | International Journal of Computer Science and Engineering2007，1，2： | 1 |
| 6 | Resource efficient connectivity restoration algorithm for mobile sensoractor networks显示文摘 | Noman H Muhammad I | 2012 | EURASIP Journal on Wireless Communications and Networking2012，347，1： | 1 |
| 7 | Interobserver reliability between pediatric radiologists and residents in ultrasound evaluation of intraventricular hemorrhage in premature infants显示文摘BACKGROUND Germinal matrix intraventricular hemorrhage(IVH)may contribute to significant morbidity and mortality in premature infants.Timely identification and grading of IVH affect decision-making and clinical outcomes.There is possibility of misinterpretation of the ultrasound appearances,and the interobserver variability has not been investigated between radiology resident and board-certified radiologist.AIM To assess interobserver reliability between senior radiology residents performing bedside cranial ultrasound during on-call hours and pediatric radiologists.METHODS From June 2018 to June 2020,neonatal cranial ultrasound examinations were performed in neonatal intensive care unit.Ultrasound findings were recorded by the residents performing the ultrasound and the pediatric attending radiologists.RESULTS In total,200 neonates were included in the study,with a mean gestational age of 30.9 wk.Interobserver agreement for higher grade(Grade III&IV)IVH was excellent.There was substantial agreement for lower grade(Grade I&II)IVH.CONCLUSION There is strong agreement between radiology residents and pediatric radiologists,which is higher for high grade IVHs. | Muhammad Danish Barakzai Ayimen Khalid Zara Za Sheer Faheemullah Khan Naila Nadeem Noman Khan Kiran Hilal | 2022 | World Journal of Radiology2022，14，11： | 0 |
| 8 | Hyperspectral anomaly detection:a performance comparison of existing techniques显示文摘Anomaly detection in Hyperspectral Imagery(HSI)has received considerable attention because of its potential application in several areas.Numerous anomaly detection algorithms for HSI have been proposed in the literature;however,due to the use of different datasets in previous studies,an extensive performance comparison of these algorithms is missing.In this paper,an overview of the current state of research in hyperspectral anomaly detection is presented by broadly dividing all the previously proposed algorithms into eight different categories.In addition,this paper presents the most comprehensive comparative analysis to-date in hyperspectral anomaly detection by evaluating 22 algorithms on 17 different publicly available datasets.Results indicate that attribute and edge-preserving filtering-based detection(AED),local summation anomaly detection based on collaborative representation and inverse distance weight(LSAD-CR-IDW)and local summation unsupervised nearest regularized subspace with an outlier removal anomaly detector(LSUNRSORAD)perform better as indicated by the mean and median values of area under the receiver operating characteristic(ROC)curves.Finally,this paper studies the effect of various dimensionality reduction techniques on anomaly detection.Results indicate that reducing the number of components to around 20 improves the performance;however,any further decrease deteriorates the performance. | Noman Raza Shah Abdur Rahman M.Maud Farrukh Aziz Bhatti Muhammad Khizer Ali Khurram Khurshid Moazam Maqsood Muhammad Amin | 2022 | International Journal of Digital Earth2022，15，1： | 0 |
| 9 | Suggestion Mining from Opinionated Text of Big Social Media Data显示文摘:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services.The increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making process.To overcome this challenge,extracting suggestions from opinionated text is a possible solution.In this study,the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’reviews.A classification using a word-embedding approach is used via the XGBoost classifier.The two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews.F1,precision,recall,and accuracy scores are calculated.The results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%.Moreover,the results revealed that suggestion keywords and phrases are the predominant features for suggestion extraction.Thus,this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews. | Youseef Alotaibi Muhammad Noman Malik Huma Hayat Khan Anab Batool Saif ul Islam Abdulmajeed Alsufyani Saleh Alghamdi | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 10 | Reimagining safe lithium applications in the living environment and its impacts on human,animal,and plant system显示文摘Lithium's(Li)ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry.Li enigmatic entry into the terrestrial food chain raises many questions and uncertainties that may pose a grave threat to living biota.We examined the leverage existing published articles regarding advances in global Li resources,interplay with plants,and possible involvement with living organisms,especially humans and animals.Globally,Li concentration(<10 e300 mg kg1)is detected in agricultural soil,and their pollutant levels vary with space and time.High mobility of Li results in higher accumulation in plants,but the clear mechanisms and specific functions remain unknown.Our assessment reveals the causal relationship between Li level and biota health.For example,lower Li intake(<0.6 mM in serum)leads to mental disorders,while higher intake(>1.5 mM in serum)induces thyroid,stomach,kidney,and reproductive system dysfunctions in humans and animals.However,there is a serious knowledge gap regarding Li regulatory standards in environmental compartments,and mechanistic approaches to unveil its consequences are needed.Furthermore,aggressive efforts are required to define optimum levels of Li for the normal functioning of animals,plants,and humans.This review is designed to revitalize the current status of Li research and identify the key knowledge gaps to fight back against the mountainous challenges of Li during the recent digital revolution.Additionally,we propose pathways to overcome Li problems and develop a strategy for effective,safe,and acceptable applications. | Noman Shakoor Muhammad Adeel Muhammad Arslan Ahmad Muhammad Zain Usman Waheed Rana Arsalan Javaid Fasih Ullah Haider Imran Azeem Pingfan Zhou Yuanbo Li Ghulam Jilani Ming Xu Jorg Rinklebe Yukui Rui | 2023 | Environmental Science and Ecotechnology2023，，3： | 0 |
| 11 | Feasibility and physics potential of detecting ^(8)B solar neutrinos at JUNO显示文摘The Jiangmen Underground Neutrino Observatory(JUNO)features a 20 kt multi-purpose underground liquid scintillator sphere as its main detector.Some of JUNO's features make it an excellent location for^8B solar neutrino measurements,such as its low-energy threshold,high energy resolution compared with water Cherenkov detectors,and much larger target mass compared with previous liquid scintillator detectors.In this paper,we present a comprehensive assessment of JUNO's potential for detecting^8B solar neutrinos via the neutrino-electron elastic scattering process.A reduced 2 MeV threshold for the recoil electron energy is found to be achievable,assuming that the intrinsic radioactive background^(238)U and^(232)Th in the liquid scintillator can be controlled to 10^(-17)g/g.With ten years of data acquisition,approximately 60,000 signal and 30,000 background events are expected.This large sample will enable an examination of the distortion of the recoil electron spectrum that is dominated by the neutrino flavor transformation in the dense solar matter,which will shed new light on the inconsistency between the measured electron spectra and the predictions of the standard three-flavor neutrino oscillation framework.IfDelta m^(2)_(21)=4.8times10^(-5);(7.5times10^(-5))eV^(2),JUNO can provide evidence of neutrino oscillation in the Earth at approximately the 3sigma(2sigma)level by measuring the non-zero signal rate variation with respect to the solar zenith angle.Moreover,JUNO can simultaneously measureDelta m^2_(21)using^8B solar neutrinos to a precision of 20% or better,depending on the central value,and to sub-percent precision using reactor antineutrinos.A comparison of these two measurements from the same detector will help understand the current mild inconsistency between the value of Delta m^2_(21)reported by solar neutrino experiments and the KamLAND experiment. | Angel Abusleme Thomas Adam Shakeel Ahmad Sebastiano Aiello Muhammad Akram Nawab Ali Fengpeng An Guangpeng An Qi An Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste Andrej Babic Wander Baldini Andrea Barresi Eric Baussan Marco Bellato Antonio Bergnoli Enrico Bernieri David Biare Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Max Buesken Mario Buscemi Jose Busto Ilya Butorov Anatael Cabrera Hao Cai Xiao Cai Yanke Cai Zhiyan Cai Antonio Cammi Agustin Campeny Chuanya Cao Guofu Cao Jun Cao Rossella Caruso Cédric Cerna Jinfan Chang Yun Chang Pingping Chen Po-An Chen Shaomin Chen Shenjian Chen Xurong Chen Yi-Wen Chen Yixue Chen Yu Chen Zhang Chen Jie Cheng Yaping Cheng Alexander Chepurnov Davide Chiesa Pietro Chimenti Artem Chukanov Anna Chuvashova Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Salvatore Costa Flavio Dal Corso Christophe De La Taille Jiawei Deng Zhi Deng Ziyan Deng Wilfried Depnering Marco Diaz Xuefeng Ding Yayun Ding Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Georgy Donchenko Jianmeng Dong Damien Dornic Evgeny Doroshkevich Marcos Dracos Frédéric Druillole Shuxian Du Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Lukas Fajt Donghua Fan Lei Fan Can Fang Jian Fang Marco Fargetta Anna Fatkina Dmitry Fedoseev Vladko Fekete Li-Cheng Feng Qichun Feng Richard Ford Andrey Formozov Amélie Fournier Haonan Gan Feng Gao Alberto Garfagnini Alexandre Göttel Christoph Genster Marco Giammarchi Agnese Giaz Nunzio Giudice Franco Giuliani Maxim Gonchar Guanghua Gong Hui Gong Oleg Gorchakov Yuri Gornushkin Marco Grassi Christian Grewing Maxim Gromov Vasily Gromov Minghao Gu Xiaofei Gu Yu Gu Mengyun Guan Nunzio Guardone Maria Gul Cong Guo Jingyuan Guo Wanlei Guo Xinheng Guo Yuhang Guo Paul Hackspacher Caren Hagner Ran Han Yang Han Miao He Wei He Tobias Heinz Patrick Hellmuth Yuekun Heng Rafael Herrera Daojin Hong YuenKeung Hor Shaojing Hou Yee Hsiung Bei-Zhen Hu Hang Hu Jianrun Hu Jun Hu Shouyang Hu Tao Hu Zhuojun Hu Chunhao Huang Guihong Huang Hanxiong Huang Qinhua Huang Wenhao Huang Xingtao Huang Yongbo Huang Jiaqi Hui Wenju Huo Cédric Huss Safeer Hussain Antonio Insolia Ara Ioannisian Daniel Ioannisyan Roberto Isocrate Kuo-Lun Jen Xiaolu Ji Xingzhao Ji Huihui Jia Junji Jia Siyu Jian Di Jiang Xiaoshan Jiang Ruyi Jin Xiaoping Jing Cécile Jollet Jari Joutsenvaara Sirichok Jungthawan Leonidas Kalousis Philipp Kampmann Li Kang Michael Karagounis Narine Kazarian Amir Khan Waseem Khan Khanchai Khosonthongkee Patrick Kinz Denis Korablev Konstantin Kouzakov Alexey Krasnoperov Svetlana Krokhaleva Zinovy Krumshteyn Andre Kruth Nikolay Kutovskiy Pasi Kuusiniemi Tobias Lachenmaier Cecilia Landini Sébastien Leblanc Frederic Lefevre Liping Lei Ruiting Lei Rupert Leitner Jason Leung Demin Li Fei Li Fule Li Haitao Li Huiling Li Jiaqi Li Jin Li Kaijie Li Mengzhao Li Nan Li Nan Li Qingjiang Li Ruhui Li Shanfeng Li Shuaijie Li Tao Li Weidong Li Weiguo Li Xiaomei Li Xiaonan Li Xinglong Li Yi Li Yufeng Li Zhibing Li Ziyuan Li Hao Liang Hao Liang Jingjing Liang Jiajun Liao Daniel Liebau Ayut Limphirat Sukit Limpijumnong Guey-Lin Lin Shengxin Lin Tao Lin Jiajie Ling Ivano Lippi Fang Liu Haidong Liu Hongbang Liu Hongjuan Liu Hongtao Liu Hu Liu Hui Liu Jianglai Liu Jinchang Liu Min Liu Qian Liu Qin Liu Runxuan Liu Shuangyu Liu Shubin Liu Shulin Liu Xiaowei Liu Yan Liu Alexey Lokhov Paolo Lombardi Claudio Lombardo Kai Loo Chuan Lu Haoqi Lu Jingbin Lu Junguang Lu Shuxiang Lu Xiaoxu Lu Bayarto Lubsandorzhiev Sultim Lubsandorzhiev Livia Ludhova Fengjiao Luo Guang Luo Pengwei Luo Shu Luo Wuming Luo Vladimir Lyashuk Qiumei Ma Si Ma Xiaoyan Ma Xubo Ma Jihane Maalmi Yury Malyshkin Fabio Mantovani Francesco Manzali Xin Mao Yajun Mao Stefano MMari Filippo Marini Sadia Marium Cristina Martellini Gisele Martin-Chassard Agnese Martini Davit Mayilyan Axel Müller Ints Mednieks Yue Meng Anselmo Meregaglia Emanuela Meroni David Meyhöfer Mauro Mezzetto Jonathan Miller Lino Miramonti Salvatore Monforte Paolo Montini Michele Montuschi Nikolay Morozov Pavithra Muralidharan Massimiliano Nastasi Dmitry VNaumov Elena Naumova Igor Nemchenok Alexey Nikolaev Feipeng Ning Zhe Ning Hiroshi Nunokawa Lothar Oberauer Juan Pedro Ochoa-Ricoux Alexander Olshevskiy Domizia Orestano Fausto Ortica Hsiao-Ru Pan Alessandro Paoloni Nina Parkalian Sergio Parmeggiano Teerapat Payupol Yatian Pei Nicomede Pelliccia Anguo Peng Haiping Peng Frédéric Perrot Pierre-Alexandre Petitjean Fabrizio Petrucci Luis Felipe Piñeres Rico Oliver Pilarczyk Artyom Popov Pascal Poussot Wathan Pratumwan Ezio Previtali Fazhi Qi Ming Qi Sen Qian Xiaohui Qian Hao Qiao Zhonghua Qin Shoukang Qiu Muhammad Rajput Gioacchino Ranucci Neill Raper Alessandra Re Henning Rebber Abdel Rebii Bin Ren Jie Ren Taras Rezinko Barbara Ricci Markus Robens Mathieu Roche Narongkiat Rodphai Aldo Romani Bedřich Roskovec Christian Roth Xiangdong Ruan Xichao Ruan Saroj Rujirawat Arseniy Rybnikov Andrey Sadovsky Paolo Saggese Giuseppe Salamanna Simone Sanfilippo Anut Sangka Nuanwan Sanguansak Utane Sawangwit Julia Sawatzki Fatma Sawy Michaela Schever Jacky Schuler Cédric Schwab Konstantin Schweizer Dmitry Selivanov Alexandr Selyunin Andrea Serafini Giulio Settanta Mariangela Settimo Muhammad Shahzad Vladislav Sharov Gang Shi Jingyan Shi Yongjiu Shi Vitaly Shutov Andrey Sidorenkov FedorŠimkovic Chiara Sirignano Jaruchit Siripak Monica Sisti Maciej Slupecki Mikhail Smirnov Oleg Smirnov Thiago Sogo-Bezerra Julanan Songwadhana Boonrucksar Soonthornthum Albert Sotnikov Ondrej Sramek Warintorn Sreethawong Achim Stahl Luca Stanco Konstantin Stankevich DušanŠtefánik Hans Steiger Jochen Steinmann Tobias Sterr Matthias Raphael Stock Virginia Strati Alexander Studenikin Gongxing Sun Shifeng Sun Xilei Sun Yongjie Sun Yongzhao Sun Narumon Suwonjandee Michal Szelezniak Jian Tang Qiang Tang Quan Tang Xiao Tang Alexander Tietzsch Igor Tkachev Tomas Tmej Konstantin Treskov Andrea Triossi Giancarlo Troni Wladyslaw Trzaska Cristina Tuve Stefan van Waasen Johannes van den Boom Guillaume Vanroyen Nikolaos Vassilopoulos Vadim Vedin Giuseppe Verde Maxim Vialkov Benoit Viaud Cristina Volpe Vit Vorobel Lucia Votano Pablo Walker Caishen Wang Chung-Hsiang Wang En Wang Guoli Wang Jian Wang Jun Wang Kunyu Wang Lu Wang Meifen Wang Meng Wang Ruiguang Wang Siguang Wang Wei Wang Wenshuai Wang Xi Wang Xiangyue Wang Yangfu Wang Yaoguang Wang Yi Wang Yifang Wang Yuanqing Wang Yuman Wang Zhe Wang Zheng Wang Zhimin Wang Zongyi Wang Apimook Watcharangkool Lianghong Wei Wei Wei Yadong Wei Liangjian Wen Christopher Wiebusch Steven Chan-Fai Wong Bjoern Wonsak Diru Wu Fangliang Wu Qun Wu Wenjie Wu Zhi Wu Michael Wurm Jacques Wurtz Christian Wysotzki Yufei Xi Dongmei Xia Yuguang Xie Zhangquan Xie Zhizhong Xing Benda Xu Donglian Xu Fanrong Xu Jilei Xu Jing Xu Meihang Xu Yin Xu Yu Xu Baojun Yan Xiongbo Yan Yupeng Yan Anbo Yang Changgen Yang Huan Yang Jie Yang Lei Yang Xiaoyu Yang Yifan Yang Haifeng Yao Zafar Yasin Jiaxuan Ye Mei Ye Ugur Yegin Frédéric Yermia Peihuai Yi Xiangwei Yin Zhengyun You Boxiang Yu Chiye Yu Chunxu Yu Hongzhao Yu Miao Yu Xianghui Yu Zeyuan Yu Chengzhuo Yuan Ying Yuan Zhenxiong Yuan Ziyi Yuan Baobiao Yue Noman Zafar Andre Zambanini Pan Zeng Shan Zeng Tingxuan Zeng Yuda Zeng Liang Zhan Feiyang Zhang Guoqing Zhang Haiqiong Zhang Honghao Zhang Jiawen Zhang Jie Zhang Jingbo Zhang Peng Zhang Qingmin Zhang Shiqi Zhang Tao Zhang Xiaomei Zhang Xuantong Zhang Yan Zhang Yinhong Zhang Yiyu Zhang Yongpeng Zhang Yuanyuan Zhang Yumei Zhang Zhenyu Zhang Zhijian Zhang Fengyi Zhao Jie Zhao Rong Zhao Shujun Zhao Tianchi Zhao Dongqin Zheng Hua Zheng Minshan Zheng Yangheng Zheng Weirong Zhong Jing Zhou Li Zhou Nan Zhou Shun Zhou Xiang Zhou Jiang Zhu Kejun Zhu Honglin Zhuang Liang Zong Jiaheng Zou | 2021 | Chinese Physics C2021，45，2： | 0 |
| 12 | Identification and Visualization of Spatial and Temporal Trends in Textile Industry显示文摘The research volume increases at the study rate,causing massive text corpora.Due to these enormous text corpora,we are drowning in data and starving for information.Therefore,recent research employed different text mining approaches to extract information from this text corpus.These proposed approaches extract meaningful and precise phrases that effectively describe the text’s information.These extracted phrases are commonly termed keyphrases.Further,these key phrases are employed to determine the different fields of study trends.Moreover,these key phrases can also be used to determine the spatiotemporal trends in the various research fields.In this research,the progress of a research field can be better revealed through spatiotemporal bibliographic trend analysis.Therefore,an effective spatiotemporal trend extraction mechanism is required to disclose textile research trends of particular regions during a specific period.This study collected a diversified dataset of textile research from 2011–2019 and different countries to determine the research trend.This data was collected from various open access journals.Further,this research determined the spatiotemporal trends using quality phrasemining.This research also focused on finding the research collaboration of different countries in a particular research subject.The research collaborations of other countries’researchers show the impact on import and export of those countries.The visualization approach is also incorporated to understand the results better. | Umair Yousaf Muhammad Asif Shahbaz Ahmed Noman Tahir Azeem Irshad Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi Habib Hamam | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 13 | Augmenting IoT Intrusion Detection System Performance Using Deep Neural Network显示文摘Due to their low power consumption and limited computing power,Internet of Things(IoT)devices are difficult to secure.Moreover,the rapid growth of IoT devices in homes increases the risk of cyber-attacks.Intrusion detection systems(IDS)are commonly employed to prevent cyberattacks.These systems detect incoming attacks and instantly notify users to allow for the implementation of appropriate countermeasures.Attempts have been made in the past to detect new attacks using machine learning and deep learning techniques,however,these efforts have been unsuccessful.In this paper,we propose two deep learning models to automatically detect various types of intrusion attacks in IoT networks.Specifically,we experimentally evaluate the use of two Convolutional Neural Networks(CNN)to detect nine distinct types of attacks listed in the NF-UNSW-NB15-v2 dataset.To accomplish this goal,the network stream data were initially converted to twodimensional images,which were then used to train the neural network models.We also propose two baseline models to demonstrate the performance of the proposed models.Generally,both models achieve high accuracy in detecting the majority of these nine attacks. | Nasir Sayed Muhammad Shoaib Waqas Ahmed Sultan Noman Qasem Abdullah M.Albarrak Faisal Saeed | 2023 | Computers, Materials & Continua2023，，1： | 0 |
| 14 | R-IDPS: Real Time SDN-Based IDPS System for IoT Security显示文摘The advent of the latest technologies like the Internet of things(IoT)transforms the world from a manual to an automated way of lifestyle.Meanwhile,IoT sector open numerous security challenges.In traditional networks,intrusion detection and prevention systems(IDPS)have been the key player in the market to ensure security.The challenges to the conventional IDPS are implementation cost,computing power,processing delay,and scalability.Further,online machine learning model training has been an issue.All these challenges still question the IoT network security.There has been a lot of research for IoT based detection systems to secure the IoT devices such as centralized and distributed architecture-based detection systems.The centralized system has issues like a single point of failure and load balancing while distributed system design has scalability and heterogeneity hassles.In this study,we design and develop an agent-based hybrid prevention system based on software-defined networking(SDN)technology.The system uses lite weight agents with the ability to scaleup for bigger networks and is feasible for heterogeneous IoT devices.The baseline profile for the IoT devices has been developed by analyzing network flows from all the IoT devices.This profile helps in extracting IoT device features.These features help in the development of our dataset that we use for anomaly detection.For anomaly detection,support vector machine has been used to detect internet control message protocol(ICMP)flood and transmission control protocol synchronize(TCP SYN)flood attacks.The proposed system based on machine learning model is fully capable of online and offline training.Other than detection accuracy,the system can fully mitigate the attacks using the software-defined technology SDN technology.The major goal of the research is to analyze the accuracy of the hybrid agent-based intrusion detection systems as compared to conventional centralized only solutions,especially under the flood attack conditions generated by the distributed denial of service(DDoS)attacks.The system shows 97%to 99%accuracy in simulated results with no false-positive alarm.Also,the system shows notable improvement in terms of resource utilization and performance under attack scenarios. The R-IDPS is scalable, and thesystem is suitable for heterogeneous IoT devices and networks. | Noman Mazhar Rosli Saleh Reza Zaba Muhammad Zeeshan M.Muzaffar Hameed Nauman Khan | 2022 | Computers, Materials & Continua2022，，11： | 0 |
| 15 | Lifetime Prediction of LiFePO_(4) Batteries Using Multilayer Classical-Quantum Hybrid Classifier显示文摘This article presents a multilayer hybrid classical-quantum classifier for predicting the lifetime of LiFePO_(4) batteries using early degradation data.The multilayer approach uses multiple variational quantum circuits in cascade,which allows more parameters to be used as weights in a single run hence increasing accuracy and provides faster cost function convergence for the optimizer.The proposed classifier predicts with an accuracy of 92.8%using data of the first four cycles.The effectiveness of the hybrid classifier is also presented by validating the performance using untrained data with an accuracy of 84%.We also demonstrate that the proposed classifier outperforms traditional machine learning algorithms in classification accuracy.In this paper,we show the application of quantum machine learning in solving a practical problem.This study will help researchers to apply quantum machine learning algorithms to more complex real-world applications,and reducing the gap between quantum and classical computing. | Muhammad Haris Muhammad Noman Hasan Abdul Basit Shiyin Qin | 2021 | Journal of Quantum Computing2021，3，3： | 0 |
| 16 | Electrical control strategy for an ocean energy conversion system显示文摘Globally abundant wave energy for power generation attracts ever increasing attention. Because of non-linear dynamics and potential uncertainties in ocean energy conversion systems, generation productivity needs to be increased by applying robust control algorithms. This paper focuses on control strategies for a small ocean energy conversion system based on a direct driven permanent magnet synchronous generator (PMSG). It evaluates the performance of two kinds of control strategies, i.e., traditional field-oriented control (FOC) and robust adaptive control. The proposed adaptive control successfully achieves maximum velocity and stable power production, with reduced speed tracking error and system response time. The adaptive control also guarantees global system stability and its superiority over FOC by using a non-linear back-stepping control technique offering a better optimization solution. The robustness of the ocean energy conversion system is further enhanced by investigating the Lyapunov method and the use of a DC-DC boost converter. To overcome system complexity, turbine-generator based power take-off (PTO) is considered. A Matlab/Simulink study verifies the advantages of a non-linear control strategy for an Oscillating Water Column (OWC) based power generation system. | Muhammad Noman Guojie Li Keyou Wang Bei Han | 2021 | Protection and Control of Modern Power Systems2021，6，1： | 0 |
| 17 | Short-Term Wind Energy Forecasting Using Deep Learning-Based Predictive Analytics显示文摘Wind energy is featured by instability due to a number of factors,such as weather,season,time of the day,climatic area and so on.Furthermore,instability in the generation of wind energy brings new challenges to electric power grids,such as reliability,flexibility,and power quality.This transition requires a plethora of advanced techniques for accurate forecasting of wind energy.In this context,wind energy forecasting is closely tied to machine learning(ML)and deep learning(DL)as emerging technologies to create an intelligent energy management paradigm.This article attempts to address the short-term wind energy forecasting problem in Estonia using a historical wind energy generation data set.Moreover,we taxonomically delve into the state-of-the-art ML and DL algorithms for wind energy forecasting and implement different trending ML and DL algorithms for the day-ahead forecast.For the selection of model parameters,a detailed exploratory data analysis is conducted.All models are trained on a real-time Estonian wind energy generation dataset for the first time with a frequency of 1 h.The main objective of the study is to foster an efficient forecasting technique for Estonia.The comparative analysis of the results indicates that Support Vector Machine(SVM),Non-linear Autoregressive Neural Networks(NAR),and Recurrent Neural Network-Long-Term Short-Term Memory(RNNLSTM)are respectively 10%,25%,and 32%more efficient compared to TSO’s forecasting algorithm.Therefore,RNN-LSTM is the best-suited and computationally effective DL method for wind energy forecasting in Estonia and will serve as a futuristic solution. | Noman Shabbir Lauri Kütt Muhammad Jawad Oleksandr Husev Ateeq Ur Rehman Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi | 2022 | Computers, Materials & Continua2022，，7： | 0 |
| 18 | Inclined magnetic field and variable viscosity effects on bioconvection of Casson nanofluid slip flow over non linearly stretching sheet显示文摘In pursuit of improved thermal transportation,the slip flow of Casson nanofluid is considered in the existence of an inclined magnetic field and radiative heat flux flow over a nonlinear stretching sheet.The viscosity of the fluid is considered as a function of temperature along with the convective thermal boundary condition.Numerical solutions are obtained via Runge-Kutta along with the shooting technique method for the chosen boundary values problem.To see the physical insights of the problem,some graphs are plotted for various flow and embedded parameters on temperature function,micro-organism distribution,velocity,and volume fraction of nanoparticles.A decline is observed in the velocity and the temperature for Casson fluid.Thermophoresis and Brownian motion incremented the temperature profile.It is also found that thermal transportation can be enhanced in the presence of nanoparticles and the bioconvection of microorganisms.Present results are useful in the various sectors of engineering and for heat exchangers working in various technological processors.The main findings of the problem are validated and compared with those in the existing literature as a limiting case. | Noman Sarwar Muhammad Imran Asjad Sajjad Hussain Md.Nur Alam Mustafa Inc | 2022 | Propulsion and Power Research2022，11，4： | 0 |
| 19 | Sub-percent precision measurement of neutrino oscillation parameters with JUNO显示文摘JUNO is a multi-purpose neutrino observatory under construction in the south of China.This publication presents new sensitivity estimates for the measurement of the △m_(31)^(2),△m_(21)^(2),sin^(2)θ_(12),and sin^(2)θ_(13) oscillation parameters using reactor antineutrinos,which is one of the primary physics goals of the experiment.The sensitivities are obtained using the best knowledge available to date on the location and overburden of the experimental site,the nuclear reactors in the surrounding area and beyond,the detector response uncertainties,and the reactor antineutrino spectral shape constraints expected from the TAO satellite detector.It is found that the △m_(21)^(2) and sin^(2)θ_(12) oscillation parameters will be determined to 0.5%precision or better in six years of data collection.In the same period,the △m_(31)^(2) parameter will be determined to about 0.2%precision for each mass ordering hypothesis.The new precision represents approximately an order of magnitude improvement over existing constraints for these three parameters. | Angel Abusleme Thomas Adam Shakeel Ahmad Rizwan Ahmed Sebastiano Aiello Muhammad Akram Abid Aleem 安丰鹏 安琪 Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste 白伟东 Nikita Balashov Wander Baldini Andrea Barresi Davide Basilico Eric Baussan Marco Bellato Antonio Bergnoli Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Jose Busto Ilya Butorov Anatael Cabrera Barbara Caccianiga 蔡浩 蔡啸 蔡严克 蔡志岩 Riccardo Callegari Antonio Cammi Agustin Campeny 曹传亚 曹国富 曹俊 Rossella Caruso Cédric Cerna Chi Chan 常劲帆 Yun Chang 陈国明 陈平平 Po-An Chen 陈少敏 Xurong Chen 陈义学 陈羽 陈志源 陈梓康 程捷 程雅苹 Yu Chin Cheng Alexey Chetverikov Davide Chiesa Pietro Chimenti Artem Chukanov Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Flavio Dal Corso Olivia Dalager Christophe De La Taille 邓智 邓子艳 Wilfried Depnering Marco Diaz Xuefeng Ding 丁雅韵 Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Dmitry Dolzhikov Georgy Donchenko 董建蒙 Evgeny Doroshkevich Marcos Dracos Frédéric Druillole 杜然 杜书先 Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Donghua Fan 樊磊 方建 方文兴 Marco Fargetta Dmitry Fedoseev 费政勇 Li-Cheng Feng 冯启春 Richard Ford Amélie Fournier 甘浩男 高峰 Alberto Garfagnini Arsenii Gavrikov Marco Giammarchi Nunzio Giudice Maxim Gonchar 龚光华 宫辉 Yuri Gornushkin Alexandre Göttel Marco Grassi Vasily Gromov 顾旻皓 谷肖飞 古宇 关梦云 管宇铎 Nunzio Guardone 郭聪 郭竞渊 郭万磊 Xinheng Guo 郭宇航 Paul Hackspacher Caren Hagner 韩然 Yang Han 何苗 Wei He Tobias Heinz Patrick Hellmuth 衡月昆 Rafael Herrera 贺远强 侯少静 Yee Hsiung Bei-Zhen Hu 胡航 Jianrun Hu 胡俊 胡守扬 胡涛 胡宇翔 胡焯钧 黄桂鸿 黄翰雄 黄凯旋 黄文昊 Xin Huang 黄性涛 黄永波 惠加琪 霍雷 霍文驹 Cédric Huss Safeer Hussain Ara Ioannisian Roberto Isocrate Beatrice Jelmini Ignacio Jeria 季筱璐 贾慧慧 贾俊基 蹇司玉 蒋荻 蒋炜 江晓山 荆小平 Cécile Jollet Jari Joutsenvaara Leonidas Kalousis Philipp Kampmann 康丽 Rebin Karaparambil Narine Kazarian Amina Khatun Khanchai Khosonthongkee Denis Korablev Konstantin Kouzakov Alexey Krasnoperov Nikolay Kutovskiy Pasi Kuusiniemi Tobias Lachenmaier Cecilia Landini Sébastien Leblanc Victor Lebrin Frederic Lefevre 雷瑞庭 Rupert Leitner Jason Leung Daozheng Li 李德民 李飞 李福乐 李高嵩 Huiling Li 李梦朝 李民 李楠 Nan Li 李清江 李茹慧 李瑞 黎山峰 李涛 李腾 李卫东 李卫国 李笑梅 李小男 李兴隆 李仪 李依宸 李玉峰 Zepeng Li 李兆涵 李志兵 李紫源 李宗海 梁浩 梁昊 廖佳军 Ayut Limphirat Guey-Lin Lin 林盛鑫 林韬 凌家杰 Ivano Lippi 刘芳 刘海东 刘昊天 刘宏邦 刘红娟 刘洪涛 Hui Liu 刘江来 刘金昌 刘敏 刘倩 刘钦 Runxuan Liu 刘树彬 刘术林 刘小伟 刘熙文 Yan Liu Yunzhe Liu Alexey Lokhov Paolo Lombardi Claudio Lombardo Kai Loo 陆川 路浩奇 陆景彬 吕军光 路书祥 Bayarto Lubsandorzhiev Sultim Lubsandorzhiev Livia Ludhova Arslan Lukanov Daibin Luo Fengjiao Luo 罗光 罗舒 罗武鸣 罗晓杰 Vladimir Lyashuk 马帮争 马冰 马秋梅 马斯 马骁妍 马续波 Jihane Maalmi 麦景宇 Yury Malyshkin Roberto Carlos Mandujano Fabio Mantovani Francesco Manzali 冒鑫 冒亚军 Stefano M.Mari Filippo Marini Cristina Martellini Gisele Martin-Chassard Agnese Martini Matthias Mayer Davit Mayilyan Ints Mednieks Artur Meinusch 孟月 Anselmo Meregaglia Emanuela Meroni David Meyhö Mauro Mezzetto Jonathan Miller Lino Miramonti Marta Colomer Molla Paolo Montini Michele Montuschi Axel Müller Massimiliano Nastasi Dmitry V.Naumov Elena Naumova Diana Navas-Nicolas Igor Nemchenok Minh Thuan Nguyen Thi 宁飞鹏 宁哲 Hiroshi Nunokawa Lothar Oberauer Juan Pedro Ochoa-Ricoux Alexander Olshevskiy Domizia Orestano Fausto Ortica Rainer Othegraven Alessandro Paoloni Sergio Parmeggiano 裴亚田 Luca Pelicci Nicomede Pelliccia 彭安国 彭海平 彭宇 彭昭缘 Frédéric Perrot Pierre-Alexandre Petitjean Fabrizio Petrucci Oliver Pilarczyk Luis Felipe Piñeres Artyom Popov Pascal Poussot Ezio Previtali 齐法制 祁鸣 钱森 钱小辉 钱圳 乔浩 秦中华 丘寿康 Gioacchino Ranucci Neill Raper Reem Rasheed Alessandra Re Henning Rebber Abdel Rebii Mariia Redchuk 任斌 任杰 Barbara Ricci Mariam Rifai Mathieu Roche Narongkiat Rodphai Aldo Romani Bedřich Roskovec 阮锡超 Arseniy Rybnikov Andrey Sadovsky Paolo Saggese Simone Sanfilippo Anut Sangka Utane Sawangwit Julia Sawatzki Michaela Schever Cédric Schwab Konstantin Schweizer Alexandr Selyunin Andrea Serafini Giulio Settanta Mariangela Settimo Zhuang Shao Vladislav Sharov Arina Shaydurova 石京燕 史娅楠 Vitaly Shutov Andrey Sidorenkov FedorŠimkovic Chiara Sirignano Jaruchit Siripak Monica Sisti Maciej Slupecki Mikhail Smirnov Oleg Smirnov Thiago Sogo-Bezerra Sergey Sokolov Julanan Songwadhana Boonrucksar Soonthornthum Albert Sotnikov OndřejŠrámek Warintorn Sreethawong Achim Stahl Luca Stanco Konstantin Stankevich DušanŠtefánik Hans Steiger Jochen Steinmann Tobias Sterr Matthias Raphael Stock Virginia Strati Alexander Studenikin 苏俊 孙世峰 孙希磊 孙勇杰 孙永昭 孙正阳 Narumon Suwonjandee Michal Szelezniak 唐健 唐强 唐泉 唐晓 Vidhya Thara Hariharan Eric Theisen Alexander Tietzsch Igor Tkachev Tomas Tmej Marco Danilo Claudio Torri Konstantin Treskov Andrea Triossi Giancarlo Troni Wladyslaw Trzaska Alexandros Tsagkarakis Cristina Tuve Nikita Ushakov Vadim Vedin Giuseppe Verde Maxim Vialkov Benoit Viaud Cornelius Moritz Vollbrecht Cristina Volpe Katharina Von Sturm Vit Vorobel Dmitriy Voronin Lucia Votano Pablo Walker 王彩申 Chung-Hsiang Wang 王恩 王国利 王坚 王俊 汪璐 Meifen Wang 王孟 Meng Wang 王瑞光 王思广 王维 王为 王文帅 王玺 王湘粤 王仰夫 王耀光 王毅 王义 王贻芳 王元清 Yuman Wang 王喆 王铮 王志民 Zongyi Wang Apimook Watcharangkool 魏微 魏巍 韦雯露 魏亚东 温凯乐 温良剑 Christopher Wiebusch 黄振辉 Bjoern Wonsak 吴帝儒 吴群 吴智 Michael Wurm Jacques Wurtz Christian Wysotzki 习宇飞 夏冬梅 Xiang Xiao 谢小川 谢宇广 Zhangquan Xie 辛钊 邢志忠 续本达 徐程 徐东莲 徐繁荣 许杭锟 徐吉磊 徐晶 徐美杭 徐音 闫保军 Taylor Yan Wenqi Yan 严雄波 Yupeng Yan 杨长根 杨成峰 Huan Yang 杨洁 杨雷 杨晓宇 Yifan Yang 姚海峰 叶佳璇 叶梅 叶子平 Frédéric Yermia Na Yin 尤郑昀 俞伯祥 余炽业 喻纯旭 余泓钊 于淼 于向辉 于泽源 于泽众 袁岑溪 袁成卓 袁影 袁振雄 岳保彪 Noman Zafar Vitalii Zavadskyi 曾珊 曾婷轩 曾裕达 占亮 张爱强 张斌 张斌婷 张飞洋 Guoqing Zhang 张宏浩 张家梁 张家文 张杰 Jin Zhang 张景波 张金楠 Mohan Zhang 张鹏 张清民 张石其 张澍 张涛 张晓梅 张鑫 张玄同 Xueyao Zhang 张银鸿 张易于 张永鹏 张宇 张圆圆 张玉美 张振宇 张志坚 Fengyi Zhao 赵洁 赵荣 赵润泽 赵书俊 Dongqin Zheng 郑华 郑阳恒 Weirong Zhong 周静 周莉 周楠 周顺 周彤 周详 朱江 朱景森 朱康甫 朱科军 朱志航 庄博 庄红林 宗亮 邹佳恒 | 2022 | Chinese Physics C2022，46，12： | 0 |
| 20 | Physicochemical,rheological and antioxidant profiling of yogurt prepared from non-enzymatically and enzymatically hydrolyzed potato powder under refrigeration显示文摘Evidences show that the storage period greatly affects the quality of yogurt.In this study,three types of yogurt:control yogurt(CY),non-hydrolyzed potato powder yogurt(PPY)and enzymatically hydrolyzed potato powder yogurt(EHPPY)were prepared at 42℃ for 5 h and stored for 28 days at 4℃.The yogurts were evaluated for quality characteristics at different storage periods.Negligible differences in pH values,titratable acidities and viable counts were detected in all three types of yogurt during storage.However,compared to other yogurts,EHPPY exhibited desirable water holding capacity,throughout the storage period.Apart from this,sensory properties and antioxidant activities(2-diphenyl-1-picryl-hydrazyl(DPPH)free radical scavenging activity and ferric reducing antioxidant power(FRAP))of EHPPY were also significantly improved during the storage period.Furthermore,the storage(G’)and loss(G”)modulus of PPY,EHPPY were lower than CY at 4℃ while a hysteresis loop was shown by all yogurts at the temperature range of 4-50℃ indicating higher G’(elasticity)than G”(viscosity).Based on our findings,EHPP could be an important functional ingredient in improving the quality and storage stability of yogurt for its production at an industrial level. | Ishtiaq Ahmad Zhouyi Xiong Hanguo Xiong Rana Muhammad Aadil Nauman Khalid Allah Bakash Jvaid Lakhoo Zia-ud-din Asad Nawaz Noman Walayat Rao Sanaullah Khan | 2023 | Food Science and Human Wellness2023，12，1： | 0 |
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