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| 1 | 药用植物内生菌对作物生长及氧化应激的作用(英文)显示文摘目的:探讨药用植物内生菌的多样性及其在种子生长和氧化应激中的作用。方法:从三种药用植物(Caralluma acutangula、Rhazya stricta和Moringa peregrina)中提取内生菌;基于18S r DNA测序和系统发育分析鉴定分离得到的内生菌株;以正常和矮化突变体水稻品系为对照,比较不同浓度的内生菌培养滤液(CF)对水稻种子的发芽和生长的影响;通过气相色谱-质谱分析CF中的有效活性成分。结论:从药用植物中共获得10种内生菌,包括茎点霉属6株、链格孢属2株、双极霉属1株和枝孢霉属1株。CF表现出剂量依赖性的生长刺激和抑制作用。与对照和其他内生菌相比,100%的茎点霉菌CF显著促进了水稻种子的发芽和生长;双极霉中的吲哚乙酸含量最高,并表现出比其更高的自由基清除和抗脂质过氧化活性;双极霉菌和茎点霉菌的类黄酮和酚类成分较高。综上所述,药用植物中存在内生菌株,其可以用于改善作物生长和减轻氧化应激。 | Abdul Latif KHAN Syed Abdullah GILANI Muhammad WAQAS Khadija AL-HOSNI Salima AL-KHIZIRI Yoon-Ha KIM Liaqat ALI Sang-Mo KANG Sajjad ASAF Raheem SHAHZAD Javid HUSSAIN In-Jung LEE Ahmed AL-HARRASI | 2017 | Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)2017，18，2： | 6 |
| 2 | Experimental Investigation of Immiscible Supercritical Carbon Dioxide Foam Rheology for Improved Oil Recovery显示文摘This paper presents the rheological behaviour of supercritical CO_2(s CO_2) foam at reservoir conditions of 1 500 psi and 80 °C. Different commercial surfactants were screened and utilized in order to generate a fairly stable CO_2 foam. Mixed surfactant system was also introduced to generate strong foam. Foam rheology was studied for some specific foam qualities using a high pressure high temperature(HPHT) foam loop rheometer. A typical shear thinning behaviour of the foam was observed and a significant increase in the foam viscosity was noticed with the increase of foam quality until 85%. A desired high apparent viscosity with coarse texture was found at 85% foam quality. Foam visualization above 85% showed an unstable foam due to extremely thin lamella which collapsed and totally disappeared in the loop rheometer. Below 5_2%, a non-homogenous and unstable foam was found having low viscosity with some liquid accumulation at the bottom of the circulation loop. This research has demonstrated rheology of s CO_2 foams at different qualities at HPHT to obtain optimal foam quality region for immiscible CO_2 foam co-injection process. | Shehzad Ahmed Khaled Abdalla Elraies Jalal Foroozesh Siti Rohaida Bt Mohd Shafian Muhammad Rehan Hashmet Ivy Chai Ching Hsia Abdullah Almansour | 2017 | Journal of Earth Science2017，28，5： | 5 |
| 3 | Correlations among oligonucleotide repeats, nucleotide substitutions, and insertion-deletion mutations in chloroplast genomes of plant family Malvaceae显示文摘The co-occurrence of mutational events including substitutions and insertions—deletions(InDels)with oligonucleotide repeats has previously been reported for a limited number of prokaryotic,eukaryotic,and organelle genomes.In this study,the correlations among these mutational events in chloroplast genomes of species in the eudicot family Malvaceae were investigated.This study also reported chloroplast genome sequences of Hibiscus mutabilis,Malva parvifJora,and Malvastrum coromandelianum.These three genomes and 16 other publicly available chloroplast genomes from 12 genera of Malvaceae were used to calculate the correlation coefficients among the mutational events at干amily,subfamily,and genus levels.In these comparisons,chloroplast genomes were pairwise aligned to record the substitutions and the InDels in mutually exclusive,250 nucleotide long bins.Taking one among the two genomes as a reference,the coordinate positions of oligonucleotide repeats in the reference genome were recorded.The extent of correlations among repeats,substitutions,and InDels was calculated and categorized as follows:very weak(0.1-0.19),weak(0.20-0.29),moderate(0.30-0.39),and strong(0.4-0.69).The extent of correlations ranged 0.201-0.6 between^InDels and single-nucleotide polymorphism(SNP),'0.182-0.513 between“InDels and repeat,”and 0.055-0.403 between“SNPs and repeats.”At family-and subfamily-level comparisons,88%-96%of the repeats showed co-occurrence with SNPs,whereas at the genus level,23%-86%of the repeats co-occurred with SNPs in same bins.Our findings support the previous hypothesis suggesting the use of oligonucleotide repeats as a proxy for finding the mutational hotspots. | Abdullah Furrukh Mehmood Iram Shahzadi Zain Ali Madiha Islam Muhammad Naeem Bushra Mirza Peter JLockhart Ibrar Ahmed Mohammad Tahir Waheed | 2021 | Journal of Systematics and Evolution2021，59，2： | 1 |
| 4 | Essential oil composition and nutrient analysis of selected medicinal plants in Sultanate of Oman显示文摘 | Javid Hussain Najeeb Ur Rehman Ahmed Al-Harrasi Liaqat Ali Abdul Latif Khan Muhammad Abdullah Albroumi | 2013 | Asian Pacific Journal of Tropical Disease2013，，6： | 1 |
| 5 | Where Pakistan Stands Among Top Rice Exporting Countries, an Analysis of Competitiveness显示文摘Under the umbrella of WTO, the reduction in trade barriers has forced the policy makers to focus on the export competitiveness. Rice is an important source for foreign exchange earnings for the economy of Pakistan, keeping in mind of this fact, the competitiveness of Pakistan's rice with other major exporters was examined by applying revealed competitive advantage. The domestic consumption trends of rice among the major rice exporting countries were also analyzed in the current study. The results revealed that as compare to other major exporters of rice in the world, Pakistan had high competitive and comparative advantage in the production of rice. The comparison of the movements in comparative advantage indices for Pakistan with the major world rice competitors/exporters showed that Pakistan possessed relatively high comparative and competitive advantages in rice production. The declining domestic per capita consumption of rice and increasing trends in competitiveness for Pakistan clearly revealed the expected potential of higher growth which meant that rice exports from Pakistan could continue to play an important role for the earnings of foreign exchange. In order to exploit the potential benefits of rice exports, we need to strengthen the competitiveness in rice sector of Pakistan. | Muhammad Abdullah Jia Li Sidra Ghazanfar Jaleel Ahmed Imran Khan Mazhir Nadeem Ishaq | 2015 | Journal of Northeast Agricultural University(English Edition)2015，22，2： | 1 |
| 6 | Factors Hindering Pakistani Farmers' Choices Towards Adoption of Crop Insurance显示文摘This study was conducted to analyze the factors that negatively influence Pakistani farmers' willingness to participate in crop insurance. Probit model was applied to identify the significant factors which influenced our dependent variable 'not willing to participate'. The results of the analyses showed that crop insurance premium was the most influencing factor which had positive and significant impact on dependent variable. Similarly dissatisfaction with crop loan insurance scheme, lacking of knowledge about crop insurance, believing of being against Islamic rules and time taking process was also found to be positive and significantly influenced the dependent variable. While limited decision power and limited perils were not found to be significant in the results. | Sidra Ghazanfar Zhang Qi-wen Muhammad Abdullah Jaleel Ahmed Imran Khan Zeeshan Ahmad | 2015 | Journal of Northeast Agricultural University(English Edition)2015，22，2： | 1 |
| 7 | A Neuro-Fuzzy Approach to Road Traffic Congestion Prediction显示文摘The fast-paced growth of artificial intelligence applications provides unparalleled opportunities to improve the efficiency of various systems.Such as the transportation sector faces many obstacles following the implementation and integration of different vehicular and environmental aspects worldwide.Traffic congestion is among the major issues in this regard which demands serious attention due to the rapid growth in the number of vehicles on the road.To address this overwhelming problem,in this article,a cloudbased intelligent road traffic congestion prediction model is proposed that is empowered with a hybrid Neuro-Fuzzy approach.The aim of the study is to reduce the delay in the queues,the vehicles experience at different road junctions across the city.The proposed model also intended to help the automated traffic control systems by minimizing the congestion particularly in a smart city environment where observational data is obtained from various implanted Internet of Things(IoT)sensors across the road.After due preprocessing over the cloud server,the proposed approach makes use of this data by incorporating the neuro-fuzzy engine.Consequently,it possesses a high level of accuracy by means of intelligent decision making with minimum error rate.Simulation results reveal the accuracy of the proposed model as 98.72%during the validation phase in contrast to the highest accuracies achieved by state-of-the-art techniques in the literature such as 90.6%,95.84%,97.56%and 98.03%,respectively.As far as the training phase analysis is concerned,the proposed scheme exhibits 99.214% accuracy. The proposed prediction modelis a potential contribution towards smart cities environment. | Mohammed Gollapalli Atta-ur-Rahman Dhiaa Musleh Nehad Ibrahim Muhammad Adnan Khan Sagheer Abbas Ayesha Atta Muhammad Aftab Khan Mehwash Farooqui Tahir Iqbal Mohammed Salih Ahmed Mohammed Imran BAhmed Dakheel Almoqbil Majd Nabeel Abdullah Omer | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 8 | Topological Evaluation of Certain Computer Networks by Contraharmonic-Quadratic Indices显示文摘In various fields,different networks are used,most of the time not of a single kind;but rather a mix of at least two networks.These kinds of networks are called bridge networks which are utilized in interconnection networks of PC,portable networks,spine of internet,networks engaged with advanced mechanics,power generation interconnection,bio-informatics and substance intensify structures.Any number that can be entirely calculated by a graph is called graph invariants.Countless mathematical graph invariants have been portrayed and utilized for connection investigation during the latest twenty years.Nevertheless,no trustworthy evaluation has been embraced to pick,how much these invariants are associated with a network graph or subatomic graph.In this paper,it will discuss three unmistakable varieties of bridge networks with an incredible capacity of assumption in the field of computer science,chemistry,physics,drug industry,informatics and arithmetic in setting with physical and manufactured developments and networks,since Contraharmonic-quadratic invariants(CQIs)are recently presented and have different figure qualities for different varieties of bridge graphs or networks.The study settled the geography of bridge graphs/networks of three novel sorts with two kinds of CQI and Quadratic-Contraharmonic Indices(QCIs).The deduced results can be used for the modeling of the above-mentioned networks. | Ahmed M.Alghamdi Khalid Hamid Muhammad Waseem Iqbal M.Usman Ashraf Abdullah Alshahrani Adel Alshamrani | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 9 | Detecting and Mitigating DDOS Attacks in SDNs Using Deep Neural Network显示文摘Distributed denial of service(DDoS)attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user.We proposed a deep neural network(DNN)model for the detection of DDoS attacks in the Software-Defined Networking(SDN)paradigm.SDN centralizes the control plane and separates it from the data plane.It simplifies a network and eliminates vendor specification of a device.Because of this open nature and centralized control,SDN can easily become a victim of DDoS attacks.We proposed a supervised Developed Deep Neural Network(DDNN)model that can classify the DDoS attack traffic and legitimate traffic.Our Developed Deep Neural Network(DDNN)model takes a large number of feature values as compared to previously proposed Machine Learning(ML)models.The proposed DNN model scans the data to find the correlated features and delivers high-quality results.The model enhances the security of SDN and has better accuracy as compared to previously proposed models.We choose the latest state-of-the-art dataset which consists of many novel attacks and overcomes all the shortcomings and limitations of the existing datasets.Our model results in a high accuracy rate of 99.76%with a low false-positive rate and 0.065%low loss rate.The accuracy increases to 99.80%as we increase the number of epochs to 100 rounds.Our proposed model classifies anomalous and normal traffic more accurately as compared to the previously proposed models.It can handle a huge amount of structured and unstructured data and can easily solve complex problems. | Gul Nawaz Muhammad Junaid Adnan Akhunzada Abdullah Gani Shamyla Nawazish Asim Yaqub Adeel Ahmed Huma Ajab | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 10 | A Nonstandard Computational Investigation of SEIR Model with Fuzzy Transmission, Recovery and Death Rates显示文摘In this article,a Susceptible-Exposed-Infectious-Recovered(SEIR)epidemic model is considered.The equilibrium analysis and reproduction number are studied.The conventional models have made assumptions of homogeneity in disease transmission that contradict the actual reality.However,it is crucial to consider the heterogeneity of the transmission rate when modeling disease dynamics.Describing the heterogeneity of disease transmission mathematically can be achieved by incorporating fuzzy theory.A numerical scheme nonstandard,finite difference(NSFD)approach is developed for the studied model and the results of numerical simulations are presented.Simulations of the constructed scheme are presented.The positivity,convergence and consistency of the developed technique are investigated using mathematical induction,Jacobean matrix and Taylor series expansions respectively.The suggested scheme preserves all these essential characteristics of the disease dynamical models.The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease.Moreover,the obtained method generates plausible predictions that can be used by regulators to support the decision-making process to design and develop control strategies.Effects of the natural immunity on the infected class are studied which reveals that an increase in natural immunity can decrease the infection and vice versa. | Ahmed H.Msmali Fazal Dayan Muhammad Rafiq Nauman Ahmed Abdullah Ali H.Ahmadini Hassan A.Hamali | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 11 | Tuning-up Learning Parameters for Deep Convolutional Neural Network:A Case Study for Hand-Drawn Sketch Images显示文摘Several recent successes in deep learning(DL),such as state-of-the-art performance on several image classification benchmarks,have been achieved through the improved configuration.Hyperparameters(HPs)tuning is a key factor affecting the performance of machine learning(ML)algorithms.Various state-of-the-art DL models use different HPs in different ways for classification tasks on different datasets.This manuscript provides a brief overview of learning parameters and configuration techniques to show the benefits of using a large-scale handdrawn sketch dataset for classification problems.We analyzed the impact of different learning parameters and toplayer configurations with batch normalization(BN)and dropouts on the performance of the pre-trained visual geometry group 19(VGG-19).The analyzed learning parameters include different learning rates and momentum values of two different optimizers,such as stochastic gradient descent(SGD)and Adam.Our analysis demonstrates that using the SGD optimizer and learning parameters,such as small learning rates with high values of momentum,along with both BN and dropouts in top layers,has a good impact on the sketch image classification accuracy. | Shaukat Hayat Kun She Muhammad Mateen Parinya Suwansrikham Muhammad Abdullah Ahmed Alghaili | 2022 | Journal of Electronic Science and Technology2022，20，3： | 0 |
| 12 | 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 |
| 13 | Hybrid Color Texture Features Classification Through ANN for Melanoma显示文摘Melanoma is of the lethal and rare types of skin cancer.It is curable at an initial stage and the patient can survive easily.It is very difficult to screen all skin lesion patients due to costly treatment.Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders,pigment networks,and the color of melanoma.These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease.The trained clinicians can overcome the issues such as low contrast,lesions varying in size,color,and the existence of several objects like hair,reflections,air bubbles,and oils on almost all images.Active contour is one of the suitable methods with some drawbacks for the segmentation of irre-gular shapes.An entropy and morphology-based automated mask selection is pro-posed for the active contour method.The proposed method can improve the overall segmentation along with the boundary of melanoma images.In this study,features have been extracted to perform the classification on different texture scales like Gray level co-occurrence matrix(GLCM)and Local binary pattern(LBP).When four different moments pull out in six different color spaces like HSV,Lin RGB,YIQ,YCbCr,XYZ,and CIE L*a*b then global information from different colors channels have been combined.Therefore,hybrid fused texture features;such as local,color feature as global,shape features,and Artificial neural network(ANN)as classifiers have been proposed for the categorization of the malignant and non-malignant.Experimentations had been carried out on datasets Dermis,DermQuest,and PH2.The results of our advanced method showed super-iority and contrast with the existing state-of-the-art techniques. | Saleem Mustafa Arfan Jaffar Muhammad Waseem Iqbal Asma Abubakar Abdullah S.Alshahrani Ahmed Alghamdi | 2023 | Intelligent Automation & Soft Computing2023，，2： | 0 |
| 14 | Injections Attacks Efficient and Secure Techniques Based on Bidirectional Long Short Time Memory Model显示文摘E-commerce,online ticketing,online banking,and other web-based applications that handle sensitive data,such as passwords,payment information,and financial information,are widely used.Various web developers may have varying levels of understanding when it comes to securing an online application.Structured Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the OpenWeb Application Security Project(OWASP)for its 2017 Top Ten List Cross Site Scripting(XSS).An attacker can exploit these two flaws and launch malicious web-based actions as a result of these flaws.Many published articles focused on these attacks’binary classification.This article described a novel deep-learning approach for detecting SQL injection and XSS attacks.The datasets for SQL injection and XSS payloads are combined into a single dataset.The dataset is labeledmanually into three labels,each representing a kind of attack.This work implements some pre-processing algorithms,including Porter stemming,one-hot encoding,and the word-embedding method to convert a word’s text into a vector.Our model used bidirectional long short-term memory(BiLSTM)to extract features automatically,train,and test the payload dataset.The payloads were classified into three types by BiLSTM:XSS,SQL injection attacks,and normal.The outcomes demonstrated excellent performance in classifying payloads into XSS attacks,injection attacks,and non-malicious payloads.BiLSTM’s high performance was demonstrated by its accuracy of 99.26%. | Abdulgbar A.R.Farea Gehad Abdullah Amran Ebraheem Farea Amerah Alabrah Ahmed A.Abdulraheem Muhammad Mursil Mohammed A.A.Al-qaness | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 15 | National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma显示文摘A consensus meeting of national experts from all major national hepatobiliary centres in the country was held on May 26,2023,at the Pakistan Kidney and Liver Institute&Research Centre(PKLI&RC)after initial consultations with the experts.The Pakistan Society for the Study of Liver Diseases(PSSLD)and PKLI&RC jointly organised this meeting.This effort was based on a comprehensive literature review to establish national practice guidelines for hilar cholangiocarcinoma(hCCA).The consensus was that hCCA is a complex disease and requires a multidisciplinary team approach to best manage these patients.This coordinated effort can minimise delays and give patients a chance for curative treatment and effective palliation.The diagnostic and staging workup includes high-quality computed tomography,magnetic resonance imaging,and magnetic resonance cholangiopancreato-graphy.Brush cytology or biopsy utilizing endoscopic retrograde cholangiopancreatography is a mainstay for diagnosis.However,histopathologic confirmation is not always required before resection.Endoscopic ultrasound with fine needle aspiration of regional lymph nodes and positron emission tomography scan are valuable adjuncts for staging.The only curative treatment is the surgical resection of the biliary tree based on the Bismuth-Corlette classification.Selected patients with unresectable hCCA can be considered for liver transplantation.Adjuvant chemotherapy should be offered to patients with a high risk of recurrence.The use of preoperative biliary drainage and the need for portal vein embolisation should be based on local multidisciplinary discussions.Patients with acute cholangitis can be drained with endoscopic or percutaneous biliary drainage.Palliative chemotherapy with cisplatin and gemcitabine has shown improved survival in patients with irresectable and recurrent hCCA. | Faisal Saud Dar Zaigham Abbas Irfan Ahmed Muhammad Atique Usman Iqbal Aujla Muhammad Azeemuddin Zeba Aziz Abu Bakar Hafeez Bhatti Tariq Ali Bangash Amna Subhan Butt Osama Tariq Butt Abdul Wahab Dogar Javed Iqbal Farooqi Faisal Hanif Jahanzaib Haider Siraj Haider Syed Mujahid Hassan Adnan Abdul Jabbar Aman Nawaz Khan Muhammad Shoaib Khan Muhammad Yasir Khan Amer Latif Nasir Hassan Luck Ahmad Karim Malik Kamran Rashid Sohail Rashid Mohammad Salih Abdullah Saeed Amjad Salamat Ghias-un-Nabi Tayyab Aasim Yusuf Haseeb Haider Zia Ammara Naveed | 2024 | World Journal of Gastroenterology2024，30，9： | 0 |
| 16 | Automatic Detection of Weapons in Surveillance Cameras Using Efficient-Net显示文摘The conventional Close circuit television(CCTV)cameras-based surveillance and control systems require human resource supervision.Almost all the criminal activities take place using weapons mostly a handheld gun,revolver,pistol,swords etc.Therefore,automatic weapons detection is a vital requirement now a day.The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–Net.Real time datasets,from local surveillance department’s test sessions are used for model training and testing.Datasets consist of local environment images and videos from different type and resolution cameras that minimize the idealism.This research also contributes in the making of Efficient-Net that is experimented and results in a positive dimension.The results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research contribution.Efficient-Net algorithm gives better results than existing algorithms.By using Efficient-Net algorithms the accuracy achieved 98.12%when epochs increase as compared to other algorithms. | Erssa Arif Syed Khuram Shahzad Muhammad Waseem Iqbal Muhammad Arfan Jaffar Abdullah S.Alshahrani Ahmed Alghamdi | 2022 | Computers, Materials & Continua2022，，9： | 0 |
| 17 | Resource Based Automatic Calibration System (RBACS) Using Kubernetes Framework显示文摘Kubernetes,a container orchestrator for cloud-deployed applications,allows the application provider to scale automatically to match thefluctuating intensity of processing demand.Container cluster technology is used to encapsulate,isolate,and deploy applications,addressing the issue of low system reliability due to interlocking failures.Cloud-based platforms usually entail users define application resource supplies for eco container virtualization.There is a constant problem of over-service in data centers for cloud service providers.Higher operating costs and incompetent resource utilization can occur in a waste of resources.Kubernetes revolutionized the orchestration of the container in the cloud-native age.It can adaptively manage resources and schedule containers,which provide real-time status of the cluster at runtime without the user’s contribution.Kubernetes clusters face unpredictable traffic,and the cluster performs manual expansion configuration by the controller.Due to operational delays,the system will become unstable,and the service will be unavailable.This work proposed an RBACS that vigorously amended the distribution of containers operating in the entire Kubernetes cluster.RBACS allocation pattern is analyzed with the Kubernetes VPA.To estimate the overall cost of RBACS,we use several scientific benchmarks comparing the accomplishment of container to remote node migration and on-site relocation.The experiments ran on the simulations to show the method’s effectiveness yielded high precision in the real-time deployment of resources in eco containers.Compared to the default baseline,Kubernetes results in much fewer dropped requests with only slightly more supplied resources. | Tahir Alyas Nadia Tabassum Muhammad Waseem Iqbal Abdullah S.Alshahrani Ahmed Alghamdi Syed Khuram Shahzad | 2023 | Intelligent Automation & Soft Computing2023，，1： | 0 |
| 18 | A qualitative exploration of Pakistan’s street children, as a consequence of the poverty-disease cycle显示文摘Background:Street children are a global phenomenon,with an estimated population of around 150 million across the world.These children include those who work on the streets but retain their family contacts,and also those who practically live on the streets and have no or limited family contacts.In Pakistan,many children are forced to work on the streets due to health-related events occurring at home which require children to play a financially productive role from an early stage.An explanatory framework adapted from the poverty-disease cycle has been used to elaborate these findings.Methods:This study is a qualitative study,and involved 19 in-depth interviews and two key informant interviews,conducted in Rawalpindi,Pakistan,from February to May 2013.The data was audio taped and transcribed.Key themes were identified and built upon.The respondents were contacted through a gatekeeper ex-street child who was a member of the street children community.Results:We asked the children to describe their life stories.These stories led us to the finding that street children are always forced to attain altered social roles because health-related problems,poverty,and large family sizes leave them no choice but to enter the workforce and earn their way.We also gathered information regarding high-risk practices and increased risks of sexual and substance abuse,based on the street children’s increased exposure.These children face the issue of social exclusion because diseases and poverty push them into a life full of risks and hazards;a life which also confines their social role in the future.Conclusion:The street child community in Pakistan is on the rise.These children are excluded from mainstream society,and the absence of access to education and vocational skills reduces their future opportunities.Keeping in mind the implications of health-related events on these children,robust inter-sectoral interventions are required. | Muhammad Ahmed Abdullah Zeeshan Basharat Omairulhaq Lodhi Muhammad Hisham Khan Wazir Hameeda Tayyab Khan Nargis Yousaf Sattar Adnan Zahid | 2014 | Infectious Diseases of Poverty2014，3，1： | 0 |
| 19 | Multi Layered Rule-Based Technique for Explicit Aspect Extraction from Online Reviews显示文摘In the field of sentiment analysis,extracting aspects or opinion targets fromuser reviews about a product is a key task.Extracting the polarity of an opinion is much more useful if we also know the targeted Aspect or Feature.Rule based approaches,like dependency-based rules,are quite popular and effective for this purpose.However,they are heavily dependent on the authenticity of the employed parts-of-speech(POS)tagger and dependency parser.Another popular rule based approach is to use sequential rules,wherein the rules formulated by learning from the user’s behavior.However,in general,the sequential rule-based approaches have poor generalization capability.Moreover,existing approaches mostly consider an aspect as a noun or noun phrase,so these approaches are unable to extract verb aspects.In this article,we have proposed a multi-layered rule-based(ML-RB)technique using the syntactic dependency parser based rules along with some selective sequential rules in separate layers to extract noun aspects.Additionally,after rigorous analysis,we have also constructed rules for the extraction of verb aspects.These verb rules primarily based on the association between verb and opinion words.The proposed multi-layer technique compensates for the weaknesses of individual layers and yields improved results on two publicly available customer review datasets.The F1 score for both the datasets are 0.90 and 0.88,respectively,which are better than existing approaches.These improved results can be attributed to the application of sequential/syntactic rules in a layered manner as well as the capability to extract both noun and verb aspects. | Mubashar Hussain Toqir A.Rana Aksam Iftikhar M.Usman Ashraf Muhammad Waseem Iqbal Ahmed Alshaflut Abdullah Alourani | 2022 | Computers, Materials & Continua2022，，12： | 0 |
| 20 | Molecular detection of Leishmania species in human and animals from cutaneous leishmaniasis endemic areas of Waziristan, Khyber Pakhtunkhwa, Pakistan显示文摘Objectives: To detect Leishmania species in human patients, animal reservoirs and Phlebotomus sandflies in Waziristan, Pakistan. Methods: Tissue smears and aspirates from 448 cutaneous leishmaniasis(CL) suspected patients were analyzed. To sort out role of the reservoir hosts, skin scrapings, spleen and liver samples from 104 rodents were collected. Furthermore, buffy coat samples were obtained from 60 domestic animals. Sandflies were also trapped. All human, animals and sandfly samples were tested by microscopy, kinetoplastic PCR and internal transcribed spacer 1(ITS1) PCR followed by restriction fragment length polymorphism for detection of Leishmania species. Results: An overall prevalence of 3.83% and 5.21% through microscopy and ITS1 PCR respectively was found. However, the statistically non-significant correlation was found between area, gender, and number of lesions. The presence of rodents, sandflies, domestic animals and internally displaced people increased the risk of CL. Using ITS1-PCR-RFLP, Leishmania tropica(L. tropica) was confirmed in 106 samples while 25 of the isolates were diagnosed as Leishmania major(L. major). Similarly, 3/104 rodents were positive for L. major and 14 pools of DNA samples containing Phlebotomus sergenti sandflies were positive for L. tropica. None of samples from domestic animals were positive for leishmaniasis. Conclusions: In the present study, L. tropica and L. major are found to be the main causative agents of CL in study area. Movement of internally displaced people from CL endemic areas presents a risk for nearby CL free areas. To the best of our knowledge, we report for the first time L. major infection in rodents(Rattus rattus) and L. tropica in Phlebotomus sergenti sandflies trapped in Waziristan, Pakistan. | Mubashir Hussain Shahzad Munir Abdullah Jalal Taj Ali Khan Niaz Muhammad Bahar Ullah Khattak Abdullah Khan Irfan Ahmed Zulqarnain Baloch Nawaz Haider Bashir Muhammad Ameen Jamal Kashif Rahim Humaira Mazhar Maira Riaz Noha Watany | 2018 | Asian Pacific Journal of Tropical Medicine2018，11，8： | 0 |
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