|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Crosstalk of liver immune cells and cell death mechanisms in different murine models of liver injury and its clinical relevance显示文摘BACKGROUND: Liver inflammation or hepatitis is a result of pluripotent interactions of cell death molecules, cytokines, chemokines and the resident immune cells collectively called as microenvironment. The interplay of these inflammatory mediators and switching of immune responses during hepatotoxic, viral, drug-induced and immune cell-mediated hepatitis decide the fate of liver pathology. The present review aimed to describe the mechanisms of liver injury, its relevance to human liver pathology and insights for the future therapeutic interventions.DATA SOURCES: The data of mouse hepatic models and relevant human liver diseases presented in this review are systematically collected from Pub Med, Science Direct and the Web of Science databases published in English. RESULTS: The hepatotoxic liver injury in mice induced by the metabolites of CCl4, acetaminophen or alcohol represent necrotic cell death with activation of cytochrome pathway, formation of reactive oxygen species(ROS) and mitochondrial damage. The Fas or TNF-α induced apoptotic liver injury was dependent on activation of caspases, release of cytochrome c and apoptosome formation. The Con A-hepatitis demonstrated the involvement of TRAIL-dependent necrotic/necroptotic cell death with activation of RIPK1/3. The α-Gal Cer-induced liver injury was mediated by TNF-α. The LPS-induced hepatitis involved TNF-α, Fas/Fas L, and perforin/granzyme cell death pathways. The MHV3 or Poly(I:C) induced liver injury was mediated by natural killer cells and TNF-α signaling. The necrotic ischemia-reperfusion liver injury was mediated byhypoxia, ROS, and pro-inflammatory cytokines; however, necroptotic cell death was found in partial hepatectomy. The crucial role of immune cells and cell death mediators in viral hepatitis(HBV, HCV), drug-induced liver injury, non-alcoholic fatty liver disease and alcoholic liver disease in human were discussed.CONCLUSIONS: The mouse animal models of hepatitis provide a parallel approach for the study of human liver pathology. Blocking or stimulating the pathways associated with liver cell death could unveil the novel therapeutic strategies in the management of liver diseases. | Hilal Ahmad Khan Muhammad Zishan Ahmad Junaid Ali Khan Muhammad Imran Arshad | 2017 | Hepatobiliary & Pancreatic Diseases International2017，16，3： | 24 |
| 2 | Synergistic antibacterial effect of honey and Herba Ocimi Basilici against some bacterial pathogens显示文摘OBJECTIVE: To evaluate the antibacterial activity of the combination of different honey brands and methanolic fraction of Herba Ocimi Basilici using agar well diffusion assay. METHODS: The antibacterial activity was determined against thirteen pathogenic bacterial clinical isolates including six gram negative(Klebsiella pneumonia, Pseudomonas aeroginosa, Escherichia coli, Salmonella typhi, Salmonella typhimirium, Xanthomonas campestris) and six gram positive strains(Enterococcus faecalis faecalis, Bacillus subtilis, Staphylococcus aureus, Clostridium perfringens type C, Clostridium perfringens type D, Clostridium chauvoei). Agar well diffusion method was used while zones of inhibition were measured with vernier scale. RESULTS: At higher concentration, all the honey brands showed good to significant activity. The highest activity was observed for Hamdard brand honey(27.60±0.40) against Enterococcus faecalis. CONCLUSION: These results revealed that combinations of plant extracts of Herba Ocimi Basilici with honey can be used for the development of potent and novel antibacterial agents. | Ali Talha Khalil Imran Khan Kafeel Ahmad Yusra Ali Khan Momin Khan Muhammad Jaseem Khan | 2013 | Journal of Traditional Chinese Medicine2013，33，6： | 4 |
| 3 | Mechanical strength of wheat grain varieties influenced by moisture content and loading rate显示文摘Mechanical shear resistance of wheat grain is a significant concern for the designers and researchers related to the design of threshing,handling and processing machinery of the field crops.The grain mechanical properties directly affect the machine geometry and its operational parameters.The present study was carried out to determine the shear resistance of five wheat varieties(Locally names;TD-02,Sindhu-1105,Benazir,China and SKD-118)influenced by moisture content(16.7%,18.7%and 19.5%)and loading rate(3 mm/s,6 mm/s and 9 mm/s).However,some physio-dimensional properties(length,width,thickness,slenderness ratio,surface area and sphericity)were obtained at different moisture contents.The results showed that the shear resistance reduced by increasing the moisture content and loading rate.The average shear resistance decreased from 10.45 N to 3.74 N for 3-9 mm/s loading rate at moisture content of 16.7%to 19.5%.Thus,the maximum correlation(r=0.905)of shear resistance obtained at 16.7%,whereas minimum correlation(r=0.692)obtained at 19.5%.The shear resistance of wheat grain was highly significant(p<0.05)at 9 mm/s for 19.5%.Shear resistance decreased with an increase in the moisture content in the grain whereas deformation is increasing with the increase of moisture content.However,the maximum bulk density of wheat grain obtained at 19.5%for SKD-118,while the minimum obtained at 16.7%for TD-02.It is recommended that the design and modification of wheat grain processing equipment should be executed on the physio-mechanical properties of grain varieties. | Yaoming Li Farman Ali Chandio Zheng Ma Imran Ali Lakhiar Abdul Razaque Sahito Fiaz Ahmad Irshad Ali Mari Umer Farooq Muhammad Suleman | 2018 | International Journal of Agricultural and Biological Engineering2018，11，4： | 4 |
| 4 | Slippery Photothermal Trap for Outstanding Deicing Surfaces显示文摘Ice accumulation is a safety and operational threat in power lines,wind turbines,and transportations.Surfaces having both passive anti-icing and active deicing functionalities are very rare.Here,we report a self-cleaning slippery photothermal trap,which is icephobic passively and deice the surfaces actively by converting sun light to heat at the ice-substrate interface.The photothermal trap consists of three layers:a candle soot layer act as solar radiation absorber,a magnetic iron oxide Fe_(3)O_(4) nanoparticles layer act as heat spreader for lateral dispersal of sun light,and Room Temperature Vulcanized(RTV)insulation to reduce the transverse heat loss.Upon illumination under microsolar 300,the temperature of the surface increased by 40℃ within 200 s.The heat confinement at the magnetic Fe_(3)O_(4) na-noparticles layer leads to rapid increase of the surface temperature,ice start to melt and silicone lubricant facilitates the ice removal.The slippery photothermal trap removed the frozen droplet(10 fiL)within 40 s upon the illumination of sun light and the frozen droplet was completely converted into water after 7 min illumination of solar light at-20℃.The developed slippery photothermal trap also melted the fully frost covered layer within 100 s at-20℃ under sunlamp.The average defrosted length(25 mm)was also observed by irradiation of laser light for 45 s.The self-cleaning slippery photothermal coating showed outstanding deicing performance at subzero temperature for long term due to the infusion of silicone oil into the nanostructures and same chemical composition with binder. | Muhammad Imran Jamil Qiongyan Wang Amjad Ali Munir Hussain Tariq Aziz Xiaoli Zhan Qinghua Zhang | 2021 | Journal of Bionic Engineering2021，18，3： | 3 |
| 5 | Text Sentiment Analysis Using Frequency-Based Vigorous Features显示文摘Sentiment Analysis, an un-abating research area in text mining, requires a computational method for extracting useful information from text. In recent days, social media has become a really rich source to get information about the behavioral state of people(opinion) through reviews and comments. Numerous techniques have been aimed to analyze the sentiment of the text, however, they were unable to come up to the complexity of the sentiments. The complexity requires novel approach for deep analysis of sentiments for more accurate prediction. This research presents a three-step Sentiment Analysis and Prediction(SAP) solution of Text Trend through K-Nearest Neighbor(KNN). At first, sentences are transformed into tokens and stop words are removed. Secondly, polarity of the sentence, paragraph and text is calculated through contributing weighted words, intensity clauses and sentiment shifters. The resulting features extracted in this step played significant role to improve the results. Finally, the trend of the input text has been predicted using KNN classifier based on extracted features. The training and testing of the model has been performed on publically available datasets of twitter and movie reviews. Experiments results illustrated the satisfactory improvement as compared to existing solutions. In addition, GUI(Hello World) based text analysis framework has been designed to perform the text analytics. | Abdul Razzaq Muhammad Asim Zulqrnain Ali Salman Qadri Imran Mumtaz Dost Muhammad Khan Qasim Niaz | 2019 | China Communications2019，16，12： | 2 |
| 6 | Anxiolytic potential of ursolic acid derivative-a stearoyl glucoside isolated from Lantana camara L.(verbanaceae)显示文摘Objective:To investigate the anxiolytic activity of newly isolated compound by our lab called ursolic acid stearoyl glucoside(UASG) from the leaves of Lantana camam(L camam).Methods: Column chromatography was used to isolate UASG.Anxiolytic potential was experimentally proved and demonstrated through Elevated plus-maze,Open field and light and dark test. Results:The UASG showed marked increased in time spent(%) and number of frequent movements made by animals in open arm of elevated plus-maze apparatus.In light and dark model,UASG produced marked increase in time spent by animal,number of crossing and reduced duration of immobility in light box.Conclusions:UASG showed significant increase in number of rearing,assisted rearing and number of square crossed in open field established test model.UASG showed its anxiolytic effect in dose dependent manner. | Imran Kazmi Muhammad Afzal Babar Ali Zoheir A.Damanhouri Aftab Ahmaol Firoz Anwar | 2013 | Asian Pacific Journal of Tropical Medicine2013，6，6： | 2 |
| 7 | Effective age of information in real-time wireless feedback control systems显示文摘Ultra-reliable and low-latency communication(URLLC)is one of the most important scenarios in forthcoming fifth generation(5 G)cellular networks to ensure timely exchange of information and realize real-time wireless control.In URLLC,timely information update needs to be guaranteed since control performance,e.g.,control cost and stability,is directly determined by timely control information update.In this paper,we introduce an effective age of information(EAoI)to evaluate the timeliness of information update in control process.We consider the control process with two phases:sensor to controller phase and controller to actuator phase.We adopt first-generate-first-serve(FGFS)M/M/1/1→M/M/1/2 and FGFS M/M/1/1~*→M/M/1/2~*tandem queuing models to represent control process and we use finitestate Markov chains to describe control information updates.By studying state transitions,we calculate the average EAoI for both tandem queuing models.More importantly,we analyze throughput of wireless control systems and its relationship with average EAoI,which provides a guideline for URLLC system design in real-time feedback control systems.Simulation results show the advantage of using EAoI. | Bo CHANG Burak KIZILKAYA Liying LI Guodong ZHAO Zhi CHEN Muhammad Ali IMRAN | 2021 | Science China(Information Sciences)2021，64，2： | 2 |
| 8 | TLR4 polymorphisms and disease susceptibility显示文摘 | Mamoona Noreen Muhammad Ali A. Shah Sheeba Murad Mall Shazia Choudhary Tahir Hussain Iltaf Ahmed Syed Fazal Jalil Muhammad Imran Raza | 2012 | Inflammation Research2012，，3： | 2 |
| 9 | A Study of Cellular Neural Networks with Vertex-Edge Topological Descriptors显示文摘The CellularNeuralNetwork(CNN)has various parallel processing applications,image processing,non-linear processing,geometric maps,highspeed computations.It is an analog paradigm,consists of an array of cells that are interconnected locally.Cells can be arranged in different configurations.Each cell has an input,a state,and an output.The cellular neural network allows cells to communicate with the neighbor cells only.It can be represented graphically;cells will represent by vertices and their interconnections will represent by edges.In chemical graph theory,topological descriptors are used to study graph structure and their biological activities.It is a single value that characterizes the whole graph.In this article,the vertex-edge topological descriptors have been calculated for cellular neural network.Results can be used for cellular neural network of any size.This will enhance the applications of cellular neural network in image processing,solving partial differential equations,analyzing 3D surfaces,sensory-motor organs,and modeling biological vision. | Sadia Husain Muhammad Imran Ali Ahmad Yasir Ahmad Kashif Elahi | 2022 | Computers, Materials & Continua2022，，2： | 1 |
| 10 | Breeding for pre-harvest sprouting resistance in bread wheat under rainfed conditions显示文摘Pre-harvest sprouting in wheat is the germination of seeds within the spikes when rains occur after or during grain ripening, which occurs commonly in the barani tract of Pakistan. Therefore, 10 cultivars and five advanced lines of spring bread wheat were evaluated for pre-harvest sprouting resistance. After natural rainfall,seeds were immediately collected from the wet spikes and tested for germinating ability. Three different germination tests were applied to hand-threshed seed:(1) spikes threshed on the day of sampling and germination tested immediately,(2) spikes threshed on the day of sampling and germination tested 1 week later, and(3) spikes threshed 1 week after sampling and germination test immediately after threshing. Seeds and spikes kept for 1 week were place on blotting paper at room temperature.Cultivars BARS-09, 09 FJ17, Doukkala-12, NARC-09 and Ouassou-20 exhibited higher sprouting resistance while other genotypes were susceptible to pre-harvest sprouting in each of the three tests. A diallel crossing was conducted with six susceptible and two resistant genotypes to assess the genetic behavior of pre-harvest sprouting resistance.The combining ability(CA) demonstrated a higher proportion of additive genetic effects for sprouting resistance, because of higher variance of general and specific CA for both parameters under study. Doukkala-12 and BARS-09 showed increased pre-harvest sprouting resistance in their F1 descendants. | Muhammad ZEESHAN Waheed ARSHAD Muhammad Imran KHAN Shiraz ALI Ali NAWAZ Amina BATOOL Muhammad TARIQ Muhammad Imran AKRAM Muhammad Amjad ALI | 2018 | Frontiers of Agricultural Science and Engineering2018，5，2： | 1 |
| 11 | Machine Learning Based Psychotic Behaviors Prediction from Facebook Status Updates显示文摘With the advent of technological advancements and the widespread Internet connectivity during the last couple of decades,social media platforms(such as Facebook,Twitter,and Instagram)have consumed a large proportion of time in our daily lives.People tend to stay alive on their social media with recent updates,as it has become the primary source of interactionwithin social circles.Although social media platforms offer several remarkable features but are simultaneously prone to various critical vulnerabilities.Recent studies have revealed a strong correlation between the usage of social media and associated mental health issues consequently leading to depression,anxiety,suicide commitment,and mental disorder,particularly in the young adults who have excessively spent time on socialmedia which necessitates a thorough psychological analysis of all these platforms.This study aims to exploit machine learning techniques for the classification of psychotic issues based on Facebook status updates.In this paper,we start with depression detection in the first instance and then expand on analyzing six other psychotic issues(e.g.,depression,anxiety,psychopathic deviate,hypochondria,unrealistic,and hypomania)commonly found in adults due to extreme use of social media networks.To classify the psychotic issues with the user’s mental state,we have employed different Machine Learning(ML)classifiers i.e.,Random Forest(RF),Support Vector Machine(SVM),Naïve Bayes(NB),and K-Nearest Neighbor(KNN).The used ML models are trained and tested by using different combinations of features selection techniques.To observe themost suitable classifiers for psychotic issue classification,a cost-benefit function(sometimes termed as‘Suitability’)has been used which combines the accuracy of the model with its execution time.The experimental evidence argues that RF outperforms its competitor classifiers with the unigram feature set. | Mubashir Ali Anees Baqir Hafiz Husnain Raza Sherazi Asad Hussain Asma Hassan Alshehri Muhammad Ali Imran | 2022 | Computers, Materials & Continua2022，，8： | 1 |
| 12 | TLR4 polymorphisms and disease susceptibility显示文摘 | Mamoona Noreen Muhammad Ali A. Shah Sheeba Murad Mall Shazia Choudhary Tahir Hussain Iltaf Ahmed Syed Fazal Jalil Muhammad Imran Raza | 2012 | Inflammation Research2012，，3： | 1 |
| 13 | Temperature trends and elevation dependent warming during 1965-2014 in headwaters of Yangtze River, Qinghai Tibetan Plateau显示文摘The understanding of temperature trends in high elevation mountain areas is an integral part of climate change research and it is critical for assessing the impacts of climate change on water resources including glacier melt, degradation of soils, and active layer thickness. In this study, climate changes were analyzed based on trends in air temperature variables(Tmax, Tmin, Tmean), and Diurnal Temperature Range(DTR) as well as elevation-dependent warming at annual and seasonal scales in the Headwaters of Yangtze River(HWYZ), Qinghai Tibetan Plateau. The Base Period(1965-2014) was split into two subperiods;Period-Ⅰ(1965-1989) and Period-Ⅱ(1990-2014) and the analysis was constrained over two subbasins;Zhimenda and Tuotuohe. Increasing trends were found in absolute changes in temperature variables during Period-Ⅱ as compared to Period-Ⅰ.Tmax, Tmin, and Tmean had significant increasing trends for both sub-basins. The highest significant trends in annual time scale were observed in Tmin(1.15℃ decade-1) in Tuotuohe and 0.98℃ decade-1 in Zhimenda sub-basins. In Period-Ⅱ, only the winter season had the highest magnitudes of Tmax and Tmin0.58℃ decade-1 and 1.26℃ decade-1 in Tuotuohe subbasin, respectively. Elevation dependent warming analysis revealed that Tmax, Tmin and Tmean trend magnitudes increase with the increase of elevations in the middle reaches(4000 m to 4400 m) of the HWYZ during Period-Ⅱ annually. The increasing trend magnitude during Period-Ⅱ, for Tmax, is 1.77, 0.92, and 1.31℃ decade-1, for Tmin 1.20, 1.32 and 1.59℃ decade-1,for Tmean 1.51, 1.10 and 1.51℃ decade-1 at elevations of4066 m, 4175 m and 4415 m respectively in the winter season. Tmean increases during the spring season for> 3681 m elevations during Period-Ⅱ, with no particular relation with elevation dependency for other variables. During the summer season in Period Ⅱ, Tmax, Tmin, Tmean increases with the increase of elevations(3681 m to 4415 m) in the middle reaches of HWYZ. Elevation dependent warming(EDW), the study concluded that magnitudes of Tmin are increasing significantly after the 1990s as compared to Tmax in the HWYZ. It is concluded that the climate of the HWYZ is getting warmer in both sub-basins and the rate of warming was more evident after the 1990s. The outcomes of the study provide an essential insight into climate change in the region and would be a primary index to select and design research scenarios to explore the impacts of climate change on water resources. | Naveed AHMED WANG Gen-xu Adeyeri OLUWAFEMI Sarfraz MUNIR HU Zhao-yong Aamir SHAKOOR Muhammad Ali IMRAN | 2020 | Journal of Mountain Science2020，17，3： | 1 |
| 14 | Structural, electrical, dielectric and magnetic properties of Gd-Sn substituted Sr-hexaferrite synthesized by sol–gel combustion method显示文摘 | Muhammad Naeem Ashiq Sajeela Shakoor Muhammad Najam-ul-Haq Muhammad Farooq Warsi Irshad Ali Imran Shakir | 2015 | Journal of Magnetism and Magnetic Materials2015，，： | 1 |
| 15 | Privacy Protection with Dynamic Pseudonym-Based Multiple Mix-Zones Over Road Networks显示文摘In this research we proposed a strategy for location privacy protection which addresses the issues related with existing location privacy protection techniques. Mix-Zones and pseudonyms are considered as the basic building blocks for location privacy; however, continuously changing pseudonyms process at multiple locations can enhance user privacy. It has been revealed that changing pseudonym at improper time and location may threat to user's privacy. Moreover, certain methods related to pseudonym change have been proposed to attain desirable location privacy and most of these solutions are based upon velocity, GPS position and direction of angle. We analyzed existing methods related to location privacy with mix zones, such as RPCLP, EPCS and MODP, where it has been observed that these methods are not adequate to attain desired level of location privacy and suffered from large number of pseudonym changes. By analyzing limitations of existing methods, we proposed Dynamic Pseudonym based multiple mix zone(DPMM) technique, which ensures highest level of accuracy and privacy. We simulate our data by using SUMO application and analysis results has revealed that DPMM outperformed existing pseudonym change techniques and achieved better results in terms of acquiring high privacy with small number of pseudonym change. | Qasim Ali Arain Zhongliang Deng Imran memon Asma Zubedi Jichao Jiao Aisha Ashraf Muhammad Saad Khan | 2017 | China Communications2017，14，4： | 1 |
| 16 | COVID-19 and comorbidities of hepatic diseases in a global perspective显示文摘The worldwide outbreak of coronavirus disease 2019(COVID-19) has challenged the priorities of healthcare system in terms of different clinical management and infection transmission, particularly those related to hepatic-disease comorbidities. Epidemiological data evidenced that COVID-19 patients with altered liver function because of hepatitis infection and cholestasis have an adverse prognosis and experience worse health outcomes. COVID-19-associated liver injury is correlated with various liver diseases following a severe acute respiratory syndrome-coronavirus type 2(SARS-CoV-2) infection that can progress during the treatment of COVID-19 patients with or without pre-existing liver disease. SARS-CoV-2 can induce liver injury in a number of ways including direct cytopathic effect of the virus on cholangiocytes/hepatocytes, immune-mediated damage, hypoxia, and sepsis. Indeed, immediate cytopathogenic effects of SARSCoV-2 via its potential target, the angiotensin-converting enzyme-2 receptor, which is highly expressed in hepatocytes and cholangiocytes, renders the liver as an extra-respiratory organ with increased susceptibility to pathological outcomes. But, underlying COVID-19-linked liver disease pathogenesis with abnormal liver function tests(LFTs) is incompletely understood. Hence, we collated COVID-19-associated liver injuries with increased LFTs at the nexus of pre-existing liver diseases and COVID-19, and defining a plausible pathophysiological triad of COVID-19, hepatocellular damage, and liver disease. This review summarizes recent findings of the exacerbating role of COVID-19 in pre-existing liver disease and vice versa as well as international guidelines of clinical care, management, and treatment recommendations for COVID-19 patients with liver disease. | Aqsa Ahmad Syeda Momna Ishtiaq Junaid Ali Khan Rizwan Aslam Sultan Ali Muhammad Imran Arshad | 2021 | World Journal of Gastroenterology2021，27，13： | 1 |
| 17 | China's Foreign Direct Investment in Africa :An overview 显示文摘 | Omar Mohamed Ali Shah Muhammad Imran | 2012 | :793-7972012，，： | 1 |
| 18 | Anomaly Based Camera Prioritization in Large Scale Surveillance Networks显示文摘Digital surveillance systems are ubiquitous and continuously generate massive amounts of data,and manual monitoring is required in order to recognise human activities in public areas.Intelligent surveillance systems that can automatically identify normal and abnormal activities are highly desirable,as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are occurring.This paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition system.The proposed system addresses the limitations of existing manual monitoring surveillance systems using a three-step framework.In the first step,the salient frames are selected from the online video stream using a frame differencing method.A lightweight 3D convolutional neural network(3DCNN)architecture is applied to extract spatio-temporal features from the salient frames in the second step.Finally,the probabilities predicted by the 3DCNN network and the metadata of the cameras are processed using a linear threshold gate sigmoid mechanism to control the priority of the camera.The proposed system performs well compared to state-of-theart violent activity recognition methods in terms of efficient camera prioritisation in large-scale surveillance networks.Comprehensive experiments and an evaluation of activity recognition and camera prioritisation showed that our approach achieved an accuracy of 98%with an F1-score of 0.97 on the Hockey Fight dataset,and an accuracy of 99%with an F1-score of 0.98 on the Violent Crowd dataset. | Altaf Hussain Khan Muhammad Hayat Ullah Amin Ullah Ali Shariq Imran Mi Young Lee Seungmin Rho Muhammad Sajjad | 2022 | Computers, Materials & Continua2022，，2： | 1 |
| 19 | A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification显示文摘Diabetes or Diabetes Mellitus(DM)is the upset that happens due to high glucose level within the body.With the passage of time,this polygenic disease creates eye deficiency referred to as Diabetic Retinopathy(DR)which can cause a major loss of vision.The symptoms typically originate within the retinal space square in the form of enlarged veins,liquid dribble,exudates,haemorrhages and small scale aneurysms.In current therapeutic science,pictures are the key device for an exact finding of patients’illness.Meanwhile,an assessment of new medicinal symbolisms stays complex.Recently,Computer Vision(CV)with deep neural networks can train models with high accuracy.The thought behind this paper is to propose a computerized learning model to distinguish the key precursors of Dimensionality Reduction(DR).The proposed deep learning framework utilizes the strength of selected models(VGG and Inception V3)by fusing the extracated features.To select the most discriminant features from a pool of features,an entropy concept is employed before the classification step.The deep learning models are fit for measuring the highlights as veins,liquid dribble,exudates,haemorrhages and miniaturized scale aneurysms into various classes.The model will ascertain the loads,which give the seriousness level of the patient’s eye.The model will be useful to distinguish the correct class of seriousness of diabetic retinopathy pictures. | Farrukh Zia Isma Irum Nadia Nawaz Qadri Yunyoung Nam Kiran Khurshid Muhammad Ali Imran Ashraf Muhammad Attique Khan | 2022 | Computers, Materials & Continua2022，，2： | 1 |
| 20 | Metal-catalyzed synthesis of ultralong tin dioxide nanobelts: Electrical and optical properties with oxygen vacancy-related orange emission显示文摘 | Faheem K. Butt Chuanbao Cao Tariq Mahmood Faryal Idrees Muhammad Tahir Waheed S. Khan Zulfiqar Ali Muhammad Rizwan M. Tanveer Sajad Hussain Imran Aslam Dapeng Yu | 2014 | Materials Science in Semiconductor Processing2014，，： | 1 |
您所在的机构暂未开通此部分的功能，请联系管理员