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Antibacterial Characterization of Silver Nanoparticles against *** ATCC-15224

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Journal of Materials Science & Technology 2008年第2期24卷 192-196页

作者： M.Raffi f.hussain T.M.Bhatti J.I.Akhter A.Hameed M.M.Hasan Department of Chemical and Materials Engineering Pakistan Institute of Engineering and Applied Sciences(PIEAS)Islamabad-45650Pakistan Department of Microbiology Faculty of Biological SciencesQuaid-i-Azam UniversityIslamabadPakistan Central Analytical facility Division Pakistan Institute of Nuclear Science and Technology(PINSTECH)Islamabad-45650Pakistan Physics Division Pakistan Institute of Nuclear Science and Technology(PINSTECH)Islamabad-45650Pakistan

Silver nanoparticles of mean size 16 nm were synthesized by inert gas condensation （IGC） method. Crystalline structure, morphology and nanoparticles size estimation were conducted by X-ray diffraction （XRD） and transmission electron microscopy （TEM）. Antibacterial activity of these silver nanoparticles as a function of particles concentration against gram-negative bacterium Escherichia coli （E. coli） was carried out in liquid as well as solid growth media. Scanning electron microscopy （SEM） and TEM studies showed that silver nanoparticles after interaction with *** have adhered to and penetrated into the bacterial cells. Antibacterial properties of silver nanoparticles are attributed to their total surface area, as a larger surface to volume ratio of nanoparticles provides more efficient means for enhanced antibacterial activity.

关键词： Silver Nanoparticles Antibacterial Electron microscopy

Dementia in military and veteran populations:a review of risk factors—traumatic brain injury,post-traumatic stress disorder,deployment,and sleep

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Military Medical Research 2022年第3期9卷 351-364页

作者： Zara Raza Syeda f.hussain Suzanne ftouni Gershon Spitz Nick Caplin Russell G.foster Renata S.M.Gomes Research and Innovation Blind Veterans UK12-14 Harcourt StreetLondonW1H 4HDUK BRAVO VICTOR Research12-14 Harcourt StreetLondonW1H 4HDUK Circadian Therapeutics OxfordOX11BYUK School of Psychological Sciences Monash University18 Innovation WalkClayton CampusWellington RoadMelbourneVIC3800Australia Sleep&Circadian Neuroscience Institute(SCNi) Nuffield Department of Clinical NeurosciencesSir William Dunn School of PathologyOxford Molecular Pathology InstituteUniversity of OxfordSouth Parks RoadOxfordOX13RFUK Northern Hub for Veterans and Military families Research Department of NursingMidwifery and HealthFaculty of Health and Life SciencesNorthumbria UniversityNewcastleNE77XAUK

The military population face a unique set of risk factors that may increase the risk of being diagnosed with *** brain injury(TBI)and post-traumatic stress disorder(PTSD)have a higher prevalence in this group in comparison to the civilian *** delving into the individual relationships between TBI and dementia,and PTSD and dementia,we are able to better explore dementia in the military and veteran *** there are some inconsistencies in results,the TBI-dementia association has become more widely ***-tosevere TBI has been found to increase the risk of being diagnosed with Alzheimer’s disease.A correlation between PTSD and dementia has been established,however,whether or not it is a causal relationship remains *** such as blast,combat and chemical exposure may occur during a deployment,along with TBI and/or PTSD diagnosis,and can impact the risk of ***,there is a lack of literature exploring the direct effects of deployment on dementia *** problems have been observed to occur in those following TBI,PTSD and *** sleep has been associated with possible dementia *** limited studies have focused on the link between sleep and dementia in military and veteran populations,sleep is a valuable factor to study due to its association and interconnection with other military/veteran *** review aims to inform of various risk factors to the cognitive health of military members and veterans:TBI,PTSD,deployment,and sleep.

关键词： Dementia Alzheimer’s disease Traumatic brain injury Post-traumatic stress disorder Military Veteran Deployment Sleep

Traumatic brain injury and sight loss in military and veteran populations–a review

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Military Medical Research 2022年第1期9卷 71-85页

作者： Syeda f.hussain Zara Raza Andrew T.G.Cash Thomas Zampieri Robert A.Mazzoli Randy H.Kardon Renata S.M.Gomes Research&Innovation Blind Veterans UK12-14 Harcourt StreetLondon W1H 4HDUK. Bravo Victor Research12-14 Harcourt StreetLondon W1H 4HDUK Blinded Veterans Association 1101 King StreetSuite 300AlexandriaVirginia 22314USA Department of Ophthalmology Madigan Army Medical Center9040 Jackson AvenueTacomaWashington 98431USA lowa City VA Health Care System and Iowa City VA Center for the Prevention and Treatment of Visual Loss Iowa CityIowa 52246USA department of Ophthalmology and Visual Sciences The University of IowaIowa CityIowa 52242USA Northern Hub for Veterans and Military families Research Department of NursingMidwifery and HealthFaculty of Health and Life SciencesNorthumbria UniversityNewcastle NE77XAUK.

War and combat exposure pose great risks to the vision *** recently,vision related deficiencies and impairments have become common with the increased use of powerful explosive devices and the subsequent rise in incidence of traumatic brain injury(TBI).Studies have looked at the effects of injury severity,aetiology of injury and the stage at which visual problems become *** was little discrepancy found between the frequencies or types of visual dysfunctions across blast and non-blast related groups,however complete sight loss appeared to occur only in those who had a blast-related ***,the more severe the injury,the greater the likelihood of specific visual disturbances occurring,and a study found total sight loss to only occur in cases with greater *** of mild TBI(mTBI)is *** able to identify a potential TBI via visual symptoms may offer a new avenue for diagnosis.

关键词： Traumatic brain injury Visual impairment Military Veteran

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可压缩壁湍流的广义雷诺比拟

可压缩壁湍流的广义雷诺比拟

A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

中国力学大会——2013

作者：张又升毕卫涛 f.hussain 佘振苏北京大学工学院湍流与复杂系统国家重点实验室 Department of Mechanical Engineering Texas Tech UniversityLubbockTexas 79409-1021USA

基于结构系综动力学系统相似性的思想提出了称为广义雷诺比拟(GRA)的理论,广泛适用于各种流动类型(圆管,槽道和边界层),普朗特数,壁面温度及压力梯度(对于边界层,要求满足准一维流动近似)。GRA用"广义总焓"来表达可压缩壁湍流雷诺平均...

基于结构系综动力学系统相似性的思想提出了称为广义雷诺比拟(GRA)的理论,广泛适用于各种流动类型(圆管,槽道和边界层),普朗特数,壁面温度及压力梯度(对于边界层,要求满足准一维流动近似)。GRA用"广义总焓"来表达可压缩壁湍流雷诺平均的能量方程,与雷诺平均的动量方程相似,由此建立了温度和速度平均场的新的定量关系。GRA关于平均温度和平均速度的关系将Walz方程推广到非绝热壁和有压力梯度的情形。对于脉动场,

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Computers, Materials & Continua 2024年第8期80卷 2099-2119页

作者： Tajmal hussain Jungpyo Hong Jongwon Seok Department of Information and Communication Engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational *** technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing *** this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing ***,features are extracted by the VGG19 convolutional ***,after processing through the GAP layer,the extracted features are fed to the SVM classifier for *** this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the *** outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%f1-score for the NEU-CLS ***,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%f1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.

关键词： Smart manufacturing steel defect detection deep learning CNN

Hordedane diterpenoid phytoalexins restrict fusarium graminearum infection but enhance Bipolaris sorokiniana colonization of barley roots

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Molecular Plant 2024年第8期17卷 1307-1327页

作者： Yaming Liu Dario Esposto Lisa K.Mahdi Andrea Porzel Pauline Stark Hidayat hussain Anja Scherr-Henning Simon Isfort Ulschan.Bathe Ivan f.Acosta Alga Zuccaro Gerd U.Balcke Alain Tissier Department of Cell and Metabolic Biology Leibniz Institute of Plant BiochemistryHalleGermany Institute for Plant Sciences Cluster of Excellence on Plant Sciences(CEPLAS)Cologne BiocenterUniversity of CologneCologneGermany Department of Bioorganic Chemistry Leibniz Institute of Plant BiochemistryHalleGermany Max Planck Institute for Plant Breeding Research CologneGermany Horticultural Sciences University of FloridaGainesvilleFLUSA.

Plant immunity is a multilayered process that includes recognition of patterns or effectors from pathogens to elicit defense *** include the induction of a cocktail of defense metabolites that typically restrict pathogen ***,we investigate the interaction between barley roots and the fungal pathogens Bipolaris sorokiniana(Bs)and fusarium graminearum(fg)at the metabolite *** identify hordedanes,a previously undescribed set of labdane-related diterpenoids with antimicrobial properties,as critical players in these *** of barley roots by Bs and fg elicits hordedane synthesis from a 60o-kb gene *** reconstruction of the biosynthesis pathway in yeast and Nicotiana benthamiana produced several hordedanes,including one of the most functionally decorated products 19-β-hydroxy-hordetrienoic acid(19-OH-HTA).Barley mutants in the diterpene synthase genes of this cluster are unable to produce hordedanes but,unexpectedly,show reduced Bs *** contrast,colonization by fusarium graminearum,another fungal pathogen of barley and wheat,is 4-fold higher in the mutants completely lacking ***,19-OH-HTA enhances both germination and growth of Bs,whereas it inhibits other pathogenic fungi,including *** of microscopy and transcriptomics data suggest that hordedanes delay the necrotrophic phase of *** together,these results show that adapted pathogens such as Bs can subvert plant metabolic defenses to facilitate root colonization.

关键词： barley Hordeum vulgare diterpenoid phytoalexins gene cluster pathogenic fungi Bipolaris sorokininiana fusarium graminearum

Intrusion Detection System for Smart Industrial Environments with Ensemble feature Selection and Deep Convolutional Neural Networks

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Intelligent Automation & Soft Computing 2024年第3期39卷 545-566页

作者： Asad Raza Shahzad Memon Muhammad Ali Nizamani Mahmood hussain Shah Dr.AHS Bukhari Postgraduate Centre of Information and Communication Technology Faculty of Engineering and TechnologyUniversity of SindhJamshoro76060Pakistan Newcastle Business School Northumbria UniversityNewcastleNE1UK

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven ***,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the *** signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging ***,there is the need for an IDS which can learn from data and detect new *** Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking *** this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta *** proposed DSNN model was trained and evaluated with the next-generation dataset,TON_*** pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE ***,precision,recall,f1-score,and false positive rates were used to evaluate the performance of the proposed ensemble *** experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML *** addition,the model proposed for IDS has been compared with similar *** proposed DSNN achieved better performance metrics than the other *** proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

关键词： Industrial internet of things smart industrial environment cyber-attacks convolutional neural network ensemble learning

Power swing and voltage collapse identification schemes for correct distance relay operation in power system

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Journal of Central South University 2013年第4期20卷 988-1000页

作者： Ahmad f. Abidin Azah Mohamed hussain Shareef Department of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia

The new techniques were presented for preventing undesirable distance relay maloperation during voltage collapse and power swings in transmission grids. Initially, the work focused on the development of a fast detection of voltage collapse and a three-phase fault at transmission lines by using under impedance fault detector (UIfD) and support vector machine (SVM). Likewise, an intelligent approach was developed to discriminate a fault, stable swing and unstable swing, for correct distance relay operation by using the S-transform and the probabilistic neural network (PNN). To illustrate the effectiveness of the proposed techniques, simulations were carried out on the IEEE 39-bus test system using the PSS/E and MATLAB software.

关键词： under impedance fault detector distance relay fault voltage collapse

CO_2 adsorption using TiO_2 composite polymeric membranes:A kinetic study

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Journal of Environmental Sciences 2015年第9期27卷 163-171页

作者： Sarah Hafeez X.fan Arshad hussain C.f.Martín School of Chemical and Materials Engineering (SCME) National University of Sciences & Technology Institute for Materials and Processes School of Engineering University of Edinburgh University of Aberdeen School of Engineering Fraser Noble Building King's College

CO2is the main greenhouse gas which causes global climatic changes on larger scale. Many techniques have been utilised to capture CO2. Membrane gas separation is a fast growing CO2 capture technique, particularly gas separation by composite membranes. The separation of CO2 by a membrane is not just a process to physically sieve out of CO2 through the controlled membrane pore size. It mainly depends upon diffusion and solubility of gases, particularly for composite dense membranes. The blended components in composite membranes have a high capability to adsorb CO2. The adsorption kinetics of the gases may directly affect diffusion and solubility. In this study, we have investigated the adsorption behaviour of CO2 in pure and composite membranes to explore the complete understanding of diffusion and solubility of CO2 through membranes. Pure cellulose acetate（CA） and cellulose acetatetitania nanoparticle（CA-TiO2） composite membranes were fabricated and characterised using SEM and fTIR analysis. The results indicated that the blended CA-TiO2 membrane adsorbed more quantity of CO2 gas as compared to pure CA membrane. The high CO2 adsorption capacity may enhance the diffusion and solubility of CO2 in the CA-TiO2 composite membrane, which results in a better CO2 separation. The experimental data was modelled by Pseudo first-order, pseudo second order and intra particle diffusion *** to correlation factor R2, the Pseudo second order model was fitted well with experimental data. The intra particle diffusion model revealed that adsorption in dense membranes was not solely consisting of intra particle diffusion.

关键词： Global warming Cellulose acetate Gas adsorption Pseudo order models CO2 Ti O2