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Comprehensive spectral analysis of Cyg X-1 using RXTE data

Research in Astronomy and Astrophysics 2012年第10期12卷 1427-1438页

作者： rizwan Shahid Ranjeev Misra S.N.A.Jaaffrey Department of Physics M.L.Sukhadia UniversityUdaipur-313001India Inter University Centre for Astronomy and Astrophysics Pune-411007India

We analyze a large number （〉 500） of pointed Rossi X-Ray Timing Explorer （RXTE） observations of Cyg X- 1 and model the spectrum of each one. A subset of the observations for which there is a simultaneous reliable measure of the hardness ratio by the All Sky Monitor shows that the sample covers nearly all the spectral shapes of Cyg X-1. Each observation is fitted with a generic empirical model consisting of a disk black body spectrum, a Comptonized component whose input photon shape is the same as the disk emission, a Gaussian to represent the iron line and a reflection feature. The relative strength, width of the iron line and the reflection parameter are in general correlated with the high energy photon spectral index F. This is broadly consistent with a geometry where for the hard state （low F ~ 1.7） there is a hot in- ner Comptonizing region surrounded by a truncated cold disk. The inner edge of the disk moves inwards as the source becomes softer till finally in the soft state （high F 〉 2.2） the disk fills the inner region and active regions above the disk produce the Comptonized component. However, the reflection parameter shows non-monotonic behavior near the transition region （F ~ 2）, which suggests a more complex geometry or physical state of the reflector. In addition, the inner disk temperature, during the hard state, is on average higher than in the soft one, albeit with large scatter. These inconsistencies could be due to limitations in the data and the empirical model used to fit them. The flux of each spectral component is well correlated with F, which shows that unlike some other black hole systems, Cyg X- 1 does not show any hysteresis be- havior. In the soft state, the flux of the Comptonized component is always similar to the disk one, which confirms that the ultra-soft state （seen in other brighter black hole systems） is not exhibited by Cyg X-1. The rapid variation of the Compton amplifica- tion factor with F naturally explains the absence of spec

关键词： accretion accretion disks -- X-rays: binaries

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pH-triggered cancer-targeting polymers:From extracellular accumulation to intracellular release

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Nano Research 2023年第4期16卷 5155-5168页

作者： rizwan Ullah Khan Jinning Shao Jia-Yu Liao Linghui Qian Institute of Drug Metabolism and Pharmaceutical Analysis Zhejiang Province Key Laboratory of Anti-Cancer Drug ResearchCollege of Pharmaceutical SciencesCancer Center&Hangzhou Institute of Innovative MedicineZhejiang UniversityHangzhou 310058China

Stimuli-responsive polymers are promising to achieve targeted delivery,improved stability during circulation,and controlled release of therapeutic and diagnostic *** them,pH-responsive polymeric nanocarriers have attracted significant attention as pH varies in different body fluids(e.g.,stomach,intestine,and colon)and intracellular organelles(e.g.,endosome,lysosome,and mitochondria)to maintain homeostasis,while distinctive pH changes are also found in certain pathological *** example,the extracellular environment of the tumor is acidic,which can be employed to drive selective *** the internalization process,since most nanocarriers enter cells upon endocytosis where a drop of pH from 6.5 to 5.0 can occur from endosome to lysosome,pH-sensitive groups have been developed for enhanced cargo *** this review,both non-covalent and covalent interactions responsive to pH changes are introduced,with a focus on the structure-property relationship and their applications in cancer targeting and endosomal escape.

关键词： cancer targeting pH-responsive structure-property relationship charge shifting acid-labile linkage

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Morphometry of leaf and shoot variables to assess aboveground biomass structure and carbon sequestration by different varieties of white mulberry(Morus alba L.)

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Journal of Forestry Research 2021年第6期32卷 2291-2300页

作者： Ghulam Ali Bajwa Muhammad Umair Yasir Nawab Zahid rizwan Pakistan Forest Institute Peshawar 25130Pakistan National Textile University Faisalabad 37610Pakistan

Mulberry is economically important and can also play a pivotal role in mitigating greenhouse *** and shoot traits were measured for Morus alba ***,*** ***,*** ***,and *** ***-1 to assess aboveground biomass(AGB)and carbon ***-specific and multivariety allometric AGB models were developed using the equivalent diameter at breast height(EDBH)and plant height(H).The completeharvest method was used to measure leaf and shoot traits and biomass,and the ash method was used to measure organic carbon *** results showed significant(p<0.01)varietal differences in leaf and shoot traits,AGB and carbon ***-1 variety had the greatest leaf density(mean±SE:1828.3±0.3 leaves tree^(-1)),Karyansuban had the largest mean leaf area(185.94±8.95 cm^(2)).A diminishing return was found between leaf area and leaf *** had the highest shoot density per tree(46.6±1.83 shoots tree^(-1)),total shoot length(264.1±2.32 m),dry biomass(16.69±0.58 kg tree^(-1)),carbon sequestration(9.99±0.32 kg tree^(-1))and CO_(2) mitigation(36.67±1.16 kg).The variety-specific AGB models b(EDBH)and b(EDBH)2 showed good fit and reasonable accuracy with a coefficient of determination(R^(2))=0.98-0.99,standard error of estimates(SEE)=0.1125-0.3130 and root mean square error(RMSE)=*** multivariety models bln(EDBH)and(EDBH)0.756 showed good-fitness and accuracy with R^(2)=0.85-0.86,SEE=1.6231-1.6445 and RMSE=*** the basis of these findings,variety Latifolia has good potential for biomass production,and allometric equations based on EDBH can be used to estimate AGB with a reasonable accuracy.

关键词： Allometry Biomass estimation CO_(2)mitigation Moraceae Mulberry Regression models

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Smart CardioWatch System for Patients with Cardiovascular Diseases Who Live Alone

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Computers, Materials & Continua 2021年第2期66卷 1237-1250页

作者： Raisa Nazir Ahmed Kazi Manjur Kolhar Faiza rizwan College of Applied Medical Science Prince Sattam Bin Abdulaziz UniversityWadi Ad Dawaser11990Saudi Arabia Department Computer Science Prince Sattam Bin Abdulaziz UniversityWadi Ad Dawaser11990Saudi Arabia

The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s *** this study,we propose a framework referred to as smart forecasting CardioWatch(SCW)to measure the heart-rate variation(HRV)for patients with myocardial infarction(MI)who live alone or are outside their *** this study,HRV is used as a vital alarming sign for patients with *** performance of the proposed framework is measured using machine learning and deep learning techniques,namely,support vector machine,logistic regression,and decision-tree classification *** results indicated that the analysis of heart rate can help health services that are located remotely from the patient to render timely emergency health ***,taking more cardiac parameters into account can lead to more accurate *** the basis of our findings,we recommend the development of health-related software to aid researchers to develop frameworks,such as SCW,for effective provision of emergency health.

关键词： Forecasting system machine learning algorithms medical forecasting systems medical control systems supervised learning

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An Efficient False-Positive Reduction System for Cerebral Microbleeds Detection

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Computers, Materials & Continua 2021年第3期66卷 2301-2315页

作者： Sitara Afzal Muazzam maqsood Irfan Mehmood Muhammad Tabish Niaz Sanghyun Seo Department of Computer Science COMSATS University IslamabadAttock CampusAttockPakistan Department of Media Design and Technology Faculty of Engineering&InformaticsUniversity of BradfordBradfordBD71AZUK Department of Smart Device Engineering School of Intelligent Mechatronics EngineeringSejong UniversitySeoulSouth Korea School of Computer Art College of Art&TechnologyChung-Ang UniversityAnseong17546South Korea

Cerebral Microbleeds(CMBs)are microhemorrhages caused by certain abnormalities of brain *** can be found in people with Traumatic Brain Injury(TBI),Alzheimer’s disease,and in old individuals having a brain *** research reveals that CMBs can be highly dangerous for individuals having dementia and *** CMBs seriously impact individuals’life which makes it crucial to recognize the CMBs in its initial phase to stop deterioration and to assist individuals to have a normal *** existing work report good results but often ignores false-positive’s perspective for this research *** this paper,an efficient approach is presented to detect CMBs from the Susceptibility Weighted Images(SWI).The proposed framework consists of four main phases(i)making clusters of brain Magnetic Resonance Imaging(MRI)using k-mean classifier(ii)reduce false positives for better classification results(iii)discriminative feature extraction specific to CMBs(iv)classification using a five layers convolutional neural network(CNN).The proposed method is evaluated on a public dataset available for 20 *** proposed system shows an accuracy of 98.9%and a 1.1%false-positive rate *** results show the superiority of the proposed work as compared to existing states of the art methods.

关键词： Microbleeds detection false-positive deep learning CNN

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Genotoxicity of ferric oxide nanoparticles in Raphanus sativus：Deciphering the role of signaling factors,oxidative stress and cell death

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Journal of Environmental Sciences 2016年第9期28卷 49-62页

作者： Quaiser Saquib Mohammad Faisal Abdulrahman A.Alatar Abdulaziz A.Al-Khedhairy Mukhtar Ahmed Sabiha M.Ansari Hend A.Alwathnani Mohammad K.Okla Sourabh Dwivedi Javed Musarrat Shelly Praveen Shams T.Khan rizwan Wahab maqsood A.Siddiqui Javed Ahmad Zoology Department College of Sciences King Saud University P.O. Box 245S Riyadh 114S1 Saucli Arabia A.R. Al-Jeraisy Chair for DNA Research Zoology Department College of Sciences King Saud University P.O. Box 2455 Riyadh 11451Saudi Arabia Department of Botany & Microbiology College of Sciences King Saucl University P.O. Box 2455 Riyaclh 11451 Saudi Arabia Department of Agricultural Microbiology Faculty of Agricultural Sciences Aligarh Muslim University AIigarh 202002 India Baba Ohulam Shah Badshah Uniuersity Rajouri 185131Jammu and Kashmir India Division of Plant Pathology Indian Agricultural Research Institute New Delhi 110012 India

We have studied the genotoxic and apoptotic potential of ferric oxide nanoparticles（Fe_2O_3-NPs） in Raphanus sativus（radish）.Fe_2O_3-NPs retarded the root length and seed germination in *** sections of treated roots showed subcellular localization of Fe_2O_3-NPs,along with the appearance of damaged mitochondria and excessive *** cytometric analysis of Fe_2O_3-NPs（1.0 mg/m L） treated groups exhibited 219.5%,161%,120.4% and 161.4% increase in intracellular reactive oxygen species（ROS）,mitochondrial membrane potential（ΔΨm）,nitric oxide（NO） and Ca2＋influx in radish protoplasts.A concentration dependent increase in the antioxidative enzymes glutathione（GSH）,catalase（CAT）,superoxide dismutase（SOD） and lipid peroxidation（LPO） has been *** assay showed a concentration dependent increase in deoxyribonucleic acid（DNA） strand breaks in Fe_2O_3-NPs treated *** cycle analysis revealed 88.4% of cells in sub-G1 apoptotic phase,suggesting cell death in Fe_2O_3-NPs（2.0 mg/m L） treated *** together,the genotoxicity induced by Fe_2O_3-NPs highlights the importance of environmental risk associated with improper disposal of nanoparticles（NPs） and radish can serve as a good indicator for measuring the phytotoxicity of NPs grown in NP-polluted environment.

关键词： Ferric oxide nanoparticles Nanotoxicity DNA damage Apoptosis Oxidative stress Phytotoxicity

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Artificial Intelligence-Based Semantic Segmentation of Ocular Regions for Biometrics and Healthcare Applications

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Computers, Materials & Continua 2021年第1期66卷 715-732页

作者： rizwan Ali Naqvi Dildar Hussain Woong-Kee Loh Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea School of Computational Science Korea Institute for Advanced Study(KIAS)Seoul02455Korea Department of Software Gachon UniversitySeongnam13120Korea

Multiple ocular region segmentation plays an important role in different applications such as biometrics,liveness detection,healthcare,and gaze ***,segmentation techniques focus on a single region of the eye at a *** the number of obvious advantages,very limited research has focused on multiple regions of the ***,accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur,ghost effects low resolution,off-angles,and unusual ***,the available segmentation methods cannot address these *** this paper,to address the accurate segmentation of multiple eye regions in unconstrainted scenarios,a lightweight outer residual encoder-decoder network suitable for various sensor images is *** proposed method can determine the true boundaries of the eye regions from inferior-quality images using the high-frequency information flow from the outer residual encoder-decoder deep convolutional neural network(called ORED-Net).Moreover,the proposed ORED-Net model does not improve the performance based on the complexity,number of parameters or network *** proposed network is considerably lighter than previous state-of-theart *** experiments were performed,and optimal performance was achieved using SBVPI and UBIRIS.v2 datasets containing images of the eye *** simulation results obtained using the proposed OREDNet,with the mean intersection over union score(mIoU)of 89.25 and 85.12 on the challenging SBVPI and UBIRIS.v2 datasets,respectively.

关键词： Semantic segmentation ocular regions biometric for healthcare sensors deep learning

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A review on the generation, determination and mitigation of Urban Heat Island

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Journal of Environmental Sciences 2008年第1期20卷 120-128页

作者： rizwan Ahmed Memon DENNIS Y.C. Leung LIU Chunho Department of Mechanical Engineering the University of Hong Kong Hong Kong China.

Urban Heat Island （UHI） is considered as one of the major problems in the 21st century posed to human beings as a result of urbanization and industrialization of human civilization. The large amount of heat generated from urban structures, as they consume and re-radiate solar radiations, and from the anthropogenic heat sources are the main causes of UHI. The two heat sources increase the temperatures of an urban area as compared to its surroundings, which is known as Urban Heat Island Intensity （UHII）. The problem is even worse in cities or metropolises with large population and extensive economic activities. The estimated three billion people living in the urban areas in the world are directly exposed to the problem, which will be increased significantly in the near future. Due to the severity of the problem, vast research effort has been dedicated and a wide range of literature is available for the subject. The literature available in this area includes the latest research approaches, concepts, methodologies, latest investigation tools and mitigation measures. This study was carded out to review and summarize this research area through an investigation of the most important feature of UHI. It was concluded that the heat re-radiated by the urban structures plays the most important role which should be investigated in details to study urban heating especially the UHI. It was also concluded that the future research should be focused on design and planning parameters for reducing the effects of urban heat island and ultimately living in a better environment.

关键词： urban heat island (UHI) urbanization temperature rise mitigation

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An efficient deep learning-assisted person re-identification solution for intelligent video surveillance in smart cities

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Frontiers of Computer Science 2023年第4期17卷 83-96页

作者： Muazzam maqsood Sadaf YASMIN Saira GILLANI Maryam BUKHARI Seungmin RHO Sang-Soo YEO Department of Computer Science COMSATS University IslamabadAttock CampusAttock 43600Pakistan Department of Computer Science Bahria UniversityLahore 54600Pakistan Department of Industrial Security Chung-Ang UniversitySeoul 06974Republic of Korea Department of Computer Engineering Mokwon UniversityDaejeon 35349Republic of Korea

Innovations on the Internet of Everything(IoE)enabled systems are driving a change in the settings where we interact in smart units,recognized globally as smart city ***,intelligent video-surveillance systems are critical to increasing the security of these smart *** precisely,in today’s world of smart video surveillance,person re-identification(Re-ID)has gained increased consideration by *** researchers have designed deep learningbased algorithms for person Re-ID because they have achieved substantial breakthroughs in computer vision *** this line of research,we designed an adaptive feature refinementbased deep learning architecture to conduct person *** the proposed architecture,the inter-channel and inter-spatial relationship of features between the images of the same individual taken from nonidentical camera viewpoints are focused on learning spatial and channel *** addition,the spatial pyramid pooling layer is inserted to extract the multiscale and fixed-dimension feature vectors irrespective of the size of the feature ***,the model’s effectiveness is validated on the CUHK01 and CUHK02 *** compared with existing approaches,the approach presented in this paper achieves encouraging Rank 1 and 5 scores of 24.6% and 54.8%,respectively.

关键词： Internet of Everything(IoE) visual surveillance systems big data security systems person re-identification(Re-ID) deep learning

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Optimization of Steel Bar Manufacturing Process Using Six Sigma

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Chinese Journal of Mechanical Engineering 2016年第2期29卷 332-341页

作者： NAEEM Khawar ULLAH Misbah TARIQ Adnan maqsood Shahid AKHTAR Rehman NAWAZ Rashid HUSSAIN Iftikhar Department of Industrial Engineering University of Engineering and Technology(UET) Peshawar

Optimization of a manufacturing process results in higher productivity and reduced wastes. Production parameters of a local steel bar manufacturing industry of Pakistan is optimized by using six Sigma-Define, measure, analyze, improve, and controlmethodology. Production data is collected and analyzed. After analysis, experimental design result is used to identify significant factors affecting process performance. The significant factors are controlled to optimized level using two-level factorial design method. A regression model is developed that helps in the estimation of response under multi variable input values. Model is tested, verified, and validated by using industrial data collected at a local steel bar manufacturing industry of Peshawar（Khyber Pakhtunkhwa, Pakistan）. The sigma level of the manufacturing process is improved to 4.01 from 3.58. The novelty of the research is the identification of the significant factors along with the optimum levels that affects the process yield, and the methodology to optimize the steel bar manufacturing process.

关键词： steel bar manufacturing industry six sigma yield sigma level design of experiments

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