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Neurological diseases caused by coronavirus infection of the respiratory airways

Brain Science Advances 2020年第4期6卷 324-343页

作者： Waqas Ahmed Adeel Khan Wish Hal Sundar Humaira Naseem Wanghao Chen Jia Feng samran durrani Lukui Chen Department of Neurosurgery Neuroscience CenterCancer CenterIntegrated Hospital of Traditional Chinese MedicineSouthern Medical UniversityGuangzhou 510310GuangdongChina School of Medicine Southeast UniversityNanjing 210009JiangsuChina School of Biological Science and Medical Engineering Southeast UniversityNanjing 210009JiangsuChina Department of Medicine Dow University of Health SciencesKarachiSindhPakistan Department of General Surgery Allied Hospital FaisalabadPunjabPakistan

Infections of the central nervous system(CNS)infections are critical problems for public health.They are caused by several different organisms,including the respiratory coronaviruses(Co Vs).Co Vs usually infect the upper respiratory tract causing the common cold.However,in infants,and in elderly and immunocompromised persons,they can also affect the lower respiratory tract causing pneumonia and various syndromes of respiratory distress.Co Vs also have neuroinvasive capabilities because they can spread from the respiratory tract to the CNS.Once infection begins in the CNS cells,it can cause various CNS problems such as status epilepticus,encephalitis,and long-term neurological disease.This neuroinvasive properties of Co Vs may damage the CNS as a result of misdirected host immune response,which could be associated with autoimmunity in susceptible individuals(virus-induced neuro-immunopathology)or associated with viral replication directly causing damage to the CNS cells(virus-induced neuropathology).In December 2019,a new disease named COVID-19 emerged which is caused by Co Vs.The significant clinical symptoms of COVID-19 are related to the respiratory system,but they can also affect the CNS,causing acute cerebrovascular and intracranial infections.We describe the possible invasion routes of coronavirus in this review article,and look for the most recent findings associated with the neurological complications in the recently published literature.

关键词： human coronavirus respiratory viral infection neuroinvasion CNS infection neurological diseases COVID-19

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Supporting tuberculosis program in active contact tracing:a case study from Pakistan

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Infectious Diseases of Poverty 2022年第2期11卷 72-76页

作者： Babar Tasneem Shaikh Ahmed Khan Laghari Sulaiman durrani Alina Chaudhry Nabeela Ali Integrated Health System Strengthening and Service Delivery(IHSS-SD)Activity JSI Research&Training Institute Inc.Mezzanine FloorThe Grand Hotel Street 1Sector E-11/1Islamabad 44000Pakistan

Tuberculosis(TB)is on the rise in Pakistan and there could be multiple reasons including poverty,difficulty in access to TB treatment services,non-compliance with treatment,social stigma etc.According to the TB program managers,limited treatment and testing sites for tuberculosis and lack of trained human resources play a major role in compromising TB management.A major lacuna in the TB control program is the absence of active contact tracing strategy.This is essential for a disease where positive cases are known to be able to infect a further 10-15 individuals in a year.Tackling tuberculosis in Pakistan has been beleaguered by funding challenges and other systems’bottlenecks such as lack of skilled human resources and insufficient supply of medicines,despite the fact that disease burden is one of the highest in the world.Although it is a notifiable disease,active case finding,contact tracing and reporting is notoriously low throughout the country.Access to diagnostics and treatment facilities has been limited and stigma attached to the disease remains deeply entrenched among the communities.Researchers have shown that enhanced and active approaches to contact investigation effectively identifies additional patients with TB among household contacts at a relatively modest cost.USAID’s Integrated Health Systems Strengthening and Service Delivery Activity extended support to the Health Departments of Sindh and Khyber Pakhtunkhwa provinces.In collaboration with the two provincial TB programs,community based active contact tracing was conducted on 17,696 individuals,based on the index cases.Among the contacts traced,243 cases were diagnosed as drug sensitive or drug resistant TB.Awareness sessions were conducted to sensitize people on the various aspects of disease and importance of getting tested.The project also supported establishing three satellite Programmatic Management of Drug Resistant Tuberculosis(PMDT)sites for drug resistant TB treatment,enhancing the programs’diagnostic and testing capacity.

关键词： Active contact tracing Community awareness Tuberculosis Pakistan

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超越经典合成氨工艺

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环球科学 2024年第7期 68-75页

作者：杰米·杜拉尼曾欣欣(译) 付先彪(审校) 《化学世界》杂志

如果没有工业合成氨,如今地球上可能就不会有80亿人居住了。这篇来自《科学美国人》德国版的文章再次提醒我们,目前传统的合成氨工艺属于能源密集型技术,需更新迭代。自20世纪初发明以来,哈伯-博施合成氨工艺从根本上改变了粮食生产,进... 详细信息

如果没有工业合成氨,如今地球上可能就不会有80亿人居住了。这篇来自《科学美国人》德国版的文章再次提醒我们,目前传统的合成氨工艺属于能源密集型技术,需更新迭代。自20世纪初发明以来,哈伯-博施合成氨工艺从根本上改变了粮食生产,进而改变了整个世界。这项工艺突破难题,使氮气和氢气合成氨(氨是制造肥料的重要原料)成为了可能。

关键词：合成氨工艺能源密集型突破难题氢气氮气

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A Smart Heart Disease Diagnostic System Using Deep Vanilla LSTM

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Computers, Materials & Continua 2023年第10期77卷 1251-1279页

作者： Maryam Bukhari Sadaf Yasmin Sheneela Naz Mehr Yahya durrani Mubashir Javaid Jihoon Moon Seungmin Rho Department of Computer Science COMSATS University IslamabadAttock CampusAttockPakistan Department of Computer Science COMSATS University IslamabadIslamabadPakistan Department of Computer Science UET TaxilaTaxilaPakistan Department of AI and Big Data Soonchunhyang UniversityAsanKorea Department of Industrial Security Chung-Ang UniversitySeoul06974Korea

Effective smart healthcare frameworks contain novel and emerging solutions for remote disease diagnostics,which aid in the prevention of several diseases including heart-related abnormalities.In this context,regular monitoring of cardiac patients through smart healthcare systems based on Electrocardiogram(ECG)signals has the potential to save many lives.In existing studies,several heart disease diagnostic systems are proposed by employing different state-of-the-art methods,however,improving such methods is always an intriguing area of research.Hence,in this research,a smart healthcare system is proposed for the diagnosis of heart disease using ECG signals.The proposed framework extracts both linear and time-series information on the ECG signals and fuses them into a single framework concurrently.The linear characteristics of ECG signals are extracted by convolution layers followed by Gaussian Error Linear Units(GeLu)and time series characteristics of ECG beats are extracted by Vanilla Long Short-Term Memory Networks(LSTM).Following on,the feature reduction of linear information is done with the help of ID Generalized Gated Pooling(GGP).In addition,data misbalancing issues are also addressed with the help of the Synthetic Minority Oversampling Technique(SMOTE).The performance assessment of the proposed model is done over the two publicly available datasets named MIT-BIH arrhythmia database(MITDB)and PTB Diagnostic ECG database(PTBDB).The proposed framework achieves an average accuracy performance of 99.14%along with a 95%recall value.

关键词： Smart systems deep learning ECG signals heart disease concurrent learning LSTM generalized gated pooling

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A Triplet-Branch Convolutional Neural Network for Part-Based Gait Recognition

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Computer Systems Science & Engineering 2023年第11期47卷 2027-2047页

作者： Sang-Soo Yeo Seungmin Rho Hyungjoon Kim Jibran Safdar Umar Zia Mehr Yahya durrani Department of Computer Engineering Mokwon UniversityDaejeonKorea Department of Industrial Security Chung-Ang UniversitySeoul06974Korea Department of Computer Engineering Semyung UniversityJechun-siKorea Department of Computer Science UET TaxilaTaxilaPakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttockPakistan

Intelligent vision-based surveillance systems are designed to deal with the gigantic volume of videos captured in a particular environment to perform the interpretation of scenes in form of detection,tracking,monitoring,behavioral analysis,and retrievals.In addition to that,another evolving way of surveillance systems in a particular environment is human gait-based surveillance.In the existing research,several methodological frameworks are designed to use deep learning and traditional methods,nevertheless,the accuracies of these methods drop substantially when they are subjected to covariate conditions.These covariate variables disrupt the gait features and hence the recognition of subjects becomes difficult.To handle these issues,a region-based triplet-branch Convolutional Neural Network(CNN)is proposed in this research that is focused on different parts of the human Gait Energy Image(GEI)including the head,legs,and body separately to classify the subjects,and later on,the final identification of subjects is decided by probability-based majority voting criteria.Moreover,to enhance the feature extraction and draw the discriminative features,we have added soft attention layers on each branch to generate the soft attention maps.The proposed model is validated on the CASIA-B database and findings indicate that part-based learning through triplet-branch CNN shows good performance of 72.98%under covariate conditions as well as also outperforms single-branch CNN models.

关键词： Vision-based surveillance systems deep learning triplet-branch CNN gait recognition covariate conditions

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Zika virus,a pathway to new challenges

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Asian Pacific Journal of Tropical Medicine 2016年第7期9卷 606-609页

作者： Zubia Jamil Yasir Waheed Taimoor Zeb durrani Fauji Foundation Hospital Foundation University Medical College Foundation University IslamabadDHA Phase I Liver Clinic Iftikhar Eye Hospital

The current Zika outbreak is largest of its kind with 1.4 million cases in Brazil alone.World Health Organization declared the current outbreak as the public health emergency of international concerns.The major route of Zika virus transmission is mosquito bites.Sexual transmission and monkey bites are also observed in few cases.There is dire need to evaluate the other routes of transmission like blood transfusion,lactation and contact with body fluids.Zika virus is infecting infants,not only causing microcephaly but also creating number of complications resulting in bad outcomes of pregnancy.In Brazil alone,4 000 cases of microcephaly have observed during the current outbreak.The incidence of Guillian-Barre(GB) syndrome is also observed during the current Zika virus outbreak.GB syndrome is acute medical condition leading the patients to death due to weakness of respiratory muscles or can cause the life time disability.There is no anti-viral drug or vaccine available for Zika virus.Zika infection can be prevented by using mosquito repellents,mosquito nets,cooling rooms by air conditions and wearing full sleeves or permethrin treated clothes.The current outbreak of Zika has not only affected the health care but also caused great economic loss.Estimated loss in Latin America and Caribbean is US$3.5 billion.United Nation's sustainable development goal 3.d stresses the strengthening of early warning,risk reduction and management of national and global health risks.The world will keep on facing new challenges in the form of Ebola or Zika;there is strong need to prepare ourselves for any disease outbreak.

关键词： Zika virus Public health emergency Microcephaly Guillian-Barre syndrome Mosquito bites

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Vitamin D Deficiency and Its Relationship with Child-Pugh Class in Patients with Chronic Liver Disease

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Journal of Clinical and Translational Hepatology 2018年第2期6卷 135-140页

作者： Zubia Jamil Sharmin Arif Anum Khan Asghar Aurangzeb durrani Nayyar Yaqoob Department of Medicine Foundation University Medical CollegeIslamabadPakistan Department of Medicine Fauji Foundation HospitalRawalpindiPakistan

Background and Aims:Skeletal manifestation in liver dis-eases represents the minimally scrutinized part of the disease spectrum.Vitamin D deficiency has a central role in developing hepatic osteodystrophy in patients with chronic liver disease.This study aimed to investigate vitamin D levels and their relationship with disease advancement in these patients.Methods:Vitamin D levels were checked in 125 chronic liver disease patients.The patients were classified in three stages according to Child-Pugh score:A,B and C.The relationship of vitamin D levels with Child-Pugh score and other variables in the study was assessed by the contingency coefficient.Correlation and logistic regression analyses were also carried out to find additional predictors of low vitamin D levels.Results:Among the patients,88%had either insufficient or deficient stores of vitamin D,while only 12%had sufficient vitamin D levels(p>0.05).Vitamin D levels were notably related to Child-Pugh class(contingency coefficient=0.5,p<0.05).On univariate and multinomial regression analyses,age,female sex,MELD and Child-Pugh class were predictors of low vitamin D levels.Age,model of end-stage liver disease score and Child-Pugh score were negatively correlated to vitamin D levels(p<0.05).Conclusions:Vitamin D deficiency is notably re-lated to age,female sex and model of end-stage liver disease score,in addition to Child-Pugh class of liver cirrhosis.Vita-min D levels should be routinely checked in patients with ad-vanced liver cirrhosis(Child-Pugh class B and C)and this deficiency must be addressed in a timely manner to improve general well-being of cirrhotic patients.

关键词： Vitamin D deficiency Liver cirrhosis Osteodystrophy Liver disease Skeletal manifestations

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Photovoltaic yield prediction using an irradiance forecast model based on multiple neural networks

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Journal of Modern Power Systems and Clean Energy 2018年第2期6卷 255-267页

作者： Saad Parvaiz durrani Stefan BALLUFF Lukas WURZER Stefan KRAUTER Paderborn University Bosch Thermotechnik GmbH

In order to develop predictive control algorithms for efficient energy management and monitoring for residential grid connected photovoltaic systems, accurate and reliable photovoltaic(PV) power forecasts are required.A PV yield prediction system is presented based on an irradiance forecast model and a PV model. The PV power forecast is obtained from the irradiance forecast using the PV model. The proposed irradiance forecast model is based on multiple feed-forward neural networks. The global horizontal irradiance forecast has a mean absolute percentage error of 3.4% on a sunny day and 23% on a cloudy day for Stuttgart. PV power forecasts based on the neural network irradiance forecast have performed much better than the PV power persistence forecast model.

关键词： Grid connected photovoltaic(GCPV) Photovoltaic(PV) PV power prediction Irradiance forecast Neural network(NN)

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Ecological Characteristics of Plants of Harboi Rangeland, Kalat, Pakistan

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热带亚热带植物学报 2005年第2期13卷 130-138页

作者： Mufakhirah Jan durrani Farrukh HUSSAIN Saeed-ur-Rehman Department of Botany University of Balochistan Quetta PakistanDepartment of Botany University of Peshawar Peshawar PakistanDepartment of Botany University of Balochistan Quetta Pakistan

The floristic composition, ecological characteristics and ethnoecology of plants of Harboi rangeland (Kalat, Pakistan) were done during 1997 to 1999. There were 202 species that belonged to 45 plant families. Asteraceae, Papilionaceae, Poaceae, Brassicaceae and Lamiaceae were the leading families. Juniperus macropoda was the only tree species while Artemesia maritima, Sophora griffithii, Hertia intermedia, Nepeta juncea, Perovskia abrotanoides, Convolvulus leiocalycinus and Astragalus spp. were the most common shrubs. The dominant life forms were therophyte and hemicryptophyte while nanophylls, microphylls and leptophylls were dominant leaf sizes. The growing season lasts from March to November with two flowering periods. Most, i.e. 83.6% plants flowered during April to June while 63.3% plants bloomed during July to September. Some 145 species had various local uses. They included 129 fodder species, 50 medicinal species, 12 vegetable/fruits species, 7 fuel wood species, 3 species each were used for roof thatching and making herbal tea. Deforestation, over grazing and over collection of medicinal and fuel wood species have led to the degradation of this rangeland. There is need to conserve these resources with the participation of local communities.

关键词：巴基斯坦哈博伊草原植物生态特征

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A Novel Refined Track Initiation Algorithm for Group Targets Based on Group Model

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Chinese Journal of Electronics 2014年第4期23卷 851-856页

作者： GAO Fei REN He WANG Jun Amir Hussain Tariq S. durrani School of Electronic and Information Engineering Beihang University School of Natural Sciences University of Stirling Department of Electronic & Electrical Engineering University of Strathclyde

Traditional refined track initiation methods for group targets have mistakes or loss of tracks when tracking irregular motions, for the reason that they rely on a stable relative position of group members. To solve the problem, a group dynamic model was introduced for proposing a new initiation algorithm and its whole framework. We made a self-adaptive improvement of the group separation on various group radii. After the pre-association of these groups, a state equation derived from the model was used for predictions of group members. Then a relational matrix was defined for refined data associations. Finally tracks were validated by logic-based method. Particular scenarios and Monte Carlo simulations showed that,compared with algorithms based on relative position, this algorithm has better performance on the adaptability to changes of a group structure and the correctness of initiation.

关键词： Group targets Track initiation Group model State equation Data association

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