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| 1 | Zinc Application Affects Tissue Zinc Concentration and Seed Yield of Pea(Pisum sativum L.)显示文摘A 2-year field experiment was conducted to assess the effect of applied zinc(Zn) on the seed yield of pea(Pisum sativum L.) and to determine the internal Zn requirement of pea with emphasis on the seed and leaves as index tissues.The experiment was carried out at two different locations(Talagang,Chakwal district and National Agricultural Research Centre(NARC),Islamabad) in the Potohar Plateau,Pakistan by growing three pea cultivars(Green feast,Climax,and Meteor).The soils were fertilized with 0,2,4,8,and 16 kg Zn ha^(-1) along with recommended basal fertilization of nitrogen(N),phosphorus(P),potassium(K),and boron(B).Zinc application increased seed yield significantly for all the three cultivars.Maximum increase in the pea seed yield(2-year mean) was21%and 15%for Green feast,28%and 21%for Climax,and 34%and 26%for Meteor at Talagang and NARC,respectively.In all cultivars,Zn concentrations in leaves and seed increased to varying extents as a result of Zn application.Fertiliser Zn requirement for near-maximum seed yield varied from 3.2 to 5.3 kg ha^(-1) for different cultivars.Zinc concentrations of leaves and seeds appeared to be a good indicator of soil Zn availability.The critical Zn concentration range sufficient for 95%maximum yield(internal Zn requirement)was 42-53 mg kg^(-1) in the pea leaves and 45-60 mg kg^(-1) in the seeds of the three pea cultivars studied. | Ejaz RAFIQUE Munazza YOUSRA Muhammad MAHMOOD-UL-HASSAN Sair SARWAR Tauseef TABASSAM Tayyaba K.CHOUDHARY | 2015 | Pedosphere2015，25，2： | 2 |
| 2 | Towards a virtual research environment for language and literature researchers显示文摘 | Muhammad S. Sarwar T. Doherty J. Watt Richard O. Sinnott | 2013 | Future Generation Computer Systems2013，，2： | 1 |
| 3 | Stable Huh-7 cell lines expressing non-structural proteins of genotype 1a of hepatitis C virus显示文摘 | Imran Shahid Sana Gull Bushra Ijaz Waqar Ahmad Muhammad Ansar Sultan Asad Humera Kausar Muhammad Tahir Sarwar Muhammad Kazim Khan Sajida Hassan | 2013 | Journal of Virological Methods2013，，1： | 1 |
| 4 | Education and economic growth in Pakistan: A cointegration and causality analysis显示文摘 | Muhammad Afzal Hafeez Ur Rehman Muhammad Shahid Farooq Kafeel Sarwar | 2011 | International Journal of Educational Research2011，，5： | 1 |
| 5 | Recognizing Breast Cancer Using Edge-Weighted Texture Features of Histopathology Images显示文摘Around one in eight women will be diagnosed with breast cancer at some time.Improved patient outcomes necessitate both early detection and an accurate diagnosis.Histological images are routinely utilized in the process of diagnosing breast cancer.Methods proposed in recent research only focus on classifying breast cancer on specific magnification levels.No study has focused on using a combined dataset with multiple magnification levels to classify breast cancer.A strategy for detecting breast cancer is provided in the context of this investigation.Histopathology image texture data is used with the wavelet transform in this technique.The proposed method comprises converting histopathological images from Red Green Blue(RGB)to Chrominance of Blue and Chrominance of Red(YCBCR),utilizing a wavelet transform to extract texture information,and classifying the images with Extreme Gradient Boosting(XGBOOST).Furthermore,SMOTE has been used for resampling as the dataset has imbalanced samples.The suggested method is evaluated using 10-fold cross-validation and achieves an accuracy of 99.27%on the BreakHis 1.040X dataset,98.95%on the BreakHis 1.0100X dataset,98.92%on the BreakHis 1.0200X dataset,98.78%on the BreakHis 1.0400X dataset,and 98.80%on the combined dataset.The findings of this study imply that improved breast cancer detection rates and patient outcomes can be achieved by combining wavelet transformation with textural signals to detect breast cancer in histopathology images. | Arslan Akram Javed Rashid Fahima Hajjej Sobia Yaqoob Muhammad Hamid Asma Arshad Nadeem Sarwar | 2023 | Computers, Materials & Continua2023，77，10： | 1 |
| 6 | Genetic variability predicting breeding potential of upland cotton(Gossypium hirsutum L.)for high temperature tolerance显示文摘Background High temperature stress at peak flowering stage of cotton is a major hindrance for crop potential.This study aimed to increase genetic divergence regarding heat tolerance in newly developed cultivars and hybrids.Fifty cotton genotypes and 40 F1(hybrids)were tested under field conditions following the treatments,viz.,high temperature stress and control at peak flowering stage in August and October under April and June sowing,respectively.Results The mean squares revealed significant differences among genotypes,treatments,genotype×treatment for relative cell injury,chlorophyll contents,canopy temperature,boll retention and seed cotton yield per plant.The genetic diversity among 50 genotypes was analyzed through cluster analysis and heat susceptibility index(HSI).The heat tolerant genotypes including FH-Noor,NIAB-545,FH-466,FH-Lalazar,FH-458,NIAB-878,IR-NIBGE-8,Weal-AGShahkar,and heat sensitive,i.e.,CIM-602,Silky-3,FH-326,SLH-12 and FH-442 were hybridized in line×tester fashion to produce F1 populations.The breeding materials’populations(40 F1)revealed higher specific combining ability variances along with dominance variances,decided the non-additive type gene action for all the traits.The best general combining ability effects for most of the traits were displayed by the lines,i.e.,FH-Lalazar,NIAB-878 along with testers FH-326 and Silky-3.Specific combining ability effects and better-parent heterosis were showed by the crosses,viz.,FH-Lalazar×Silky-3,FH-Lalazar×FH-326,NIAB-878×Silky-3,and NIAB-878×FH-326 for seed cotton yield and yield contributing traits under high temperature stress.Conclusion Heterosis breeding should be carried out in the presence of non-additive type gene action for all the studied traits.The best combiner parents with better-parent heterosis may be used in crossing program to develop high yielding cultivars,and hybrids for high temperature stress tolerance. | FAROOQ Amjad SHAKEEL Amir SAEED Asif FAROOQ Jehanzeb RIZWAN Muhammad CHATTHA Waqas Shafqat SARWAR Ghulam RAMZAN Yasir | 2023 | Journal of Cotton Research2023，6，2： | 1 |
| 7 | SC Currents Minimization in Distributed Generation Embedded Distribution Networks with Optimal Application of FCLs显示文摘For meeting the increased demand of electrical power,distributed generation(DG)based on renewable energy resources(RERs),has become a potential alternative to large plants based on fossil fuels.The power from environmentally friendly RERs is available at a competitive price due to technological advancements in recent times.Moreover,optimal allocation of DG at the distribution network(DN)level may result in power loss reduction,improvement in voltage profile and the network’s overall reliability.However,integration of DG may increase the short circuit(SC)level beyond the capacity of the protection gear,conductors,transformers and other components of a DN.The high short circuit currents(SCCs)may be reduced by application of a fault current limiter(FCL).However,most of the existing literature proposes optimization of FCLs size by considering only normal configurations of a DN.This approach is inappropriate as it may fail to produce the desired reduction in SCCs in different N−1 contingency scenarios.In this paper,a new strategy is presented that considers both normal as well as various contingency situations for optimal allocation of FCLs in a DN with DG connection.The strategy is implemented in the IEEE 30-bus system in a MATLAB environment using a genetic algorithm(GA).The simulation results prove that the proposed strategy is effective in determining the optimal FCLs size that restricts the SCCs to a safe level in different operating conditions including N−1 contingencies and thus,improves network safety and reliability.The strategy described in the paper can play an important role in DN planning involving optimal application of DG and FCLs. | Irtaza Sohail Babar Hussain M.Abubakar Intisar Ali Sajjad M.Faisal Nadeem Muhammad Sarwar | 2022 | CSEE Journal of Power and Energy Systems2022，8，5： | 1 |
| 8 | Probing the potential of polyester for CO_2 capture显示文摘Global warming, the major environmental issue confronted by humanity today, is caused by rising level of green house gases. Carbon capture and storage technologies offer potential for tapering CO2 emission in the atmosphere. Adsorption is believed to be a promising technology for CO2 capture. For this purpose, a polyester was synthesized by polycondensation of1,3,5-benzenetricarbonyl trichloride and cyanuric acid in pyridine and dichloromethane mixture. The polymer was then characterized using FT-IR, TGA, BET surface area and pore size analysis, FESEM and CO2 adsorption measurements. The CO2 adsorption capacities of the polyester were evaluated at a pressure of 1 bar and two different temperatures(273 and 298 K).The performance of these materials to adsorb CO2 at atmospheric pressure was measured by optimum CO2 uptake of 0.244 mmol/g at 273 K. The synthesized polyester, therefore, has the potential to be exploited as CO2 adsorbent in pre-combustion capture process. | Sonia Zulfiqar Muhammad Ilyas Sarwar | 2014 | Journal of Environmental Sciences2014，26，7： | 1 |
| 9 | Education and economic growth in Pakistan: A cointegration and causality analysis显示文摘 | Mnhammad Afza/ Hafeez Ur Rehman Muhammad Shahid Farooq Kafeel Sarwar | 2011 | International Journal of Educational Research2011，，50： | 1 |
| 10 | 3D Head Pose Estimation through Facial Features and Deep Convolutional Neural Networks显示文摘Face image analysis is one among several important cues in computer vision.Over the last five decades,methods for face analysis have received immense attention due to large scale applications in various face analysis tasks.Face parsing strongly benefits various human face image analysis tasks inducing face pose estimation.In this paper we propose a 3D head pose estimation framework developed through a prior end to end deep face parsing model.We have developed an end to end face parts segmentation framework through deep convolutional neural networks(DCNNs).For training a deep face parts parsing model,we label face images for seven different classes,including eyes,brows,nose,hair,mouth,skin,and back.We extract features from gray scale images by using DCNNs.We train a classifier using the extracted features.We use the probabilistic classification method to produce gray scale images in the form of probability maps for each dense semantic class.We use a next stage of DCNNs and extract features from grayscale images created as probability maps during the segmentation phase.We assess the performance of our newly proposed model on four standard head pose datasets,including Pointing’04,Annotated Facial Landmarks in the Wild(AFLW),Boston University(BU),and ICT-3DHP,obtaining superior results as compared to previous results. | Khalil Khan Jehad Ali Kashif Ahmad Asma Gul Ghulam Sarwar Sahib Khan Qui Thanh Hoai Ta Tae-Sun Chung Muhammad Attique | 2021 | Computers, Materials & Continua2021，，2： | 1 |
| 11 | A new route for the synthesis of CuIn 0.5 Ga 0.5 Se 2 powder for solar cell applications显示文摘 | Emre Yassitepe Zaki Khalifa G. Hassnain Jaffari Chuen-Shii Chou Sonia Zulfiqar Muhammad Ilyas Sarwar Syed Ismat Shah | 2010 | Powder Technology2010，，1： | 1 |
| 12 | Soluble aromatic polyamide bearing ether linkages: synthesis and characterization显示文摘 | Sonia Zulfiqar Zahoor Ahmad Muhammad Ilyas Sarwar | 2007 | Colloid and Polymer Science2007，，15： | 1 |
| 13 | Enhanced Accuracy for Motor Imagery Detection Using Deep Learning for BCI显示文摘Brain-Computer Interface(BCI)is a system that provides a link between the brain of humans and the hardware directly.The recorded brain data is converted directly to the machine that can be used to control external devices.There are four major components of the BCI system:acquiring signals,preprocessing of acquired signals,features extraction,and classification.In traditional machine learning algorithms,the accuracy is insignificant and not up to the mark for the classification of multi-class motor imagery data.The major reason for this is,features are selected manually,and we are not able to get those features that give higher accuracy results.In this study,motor imagery(MI)signals have been classified using different deep learning algorithms.We have explored two different methods:Artificial Neural Network(ANN)and Long Short-Term Memory(LSTM).We test the classification accuracy on two datasets:BCI competition III-dataset IIIa and BCI competition IV-dataset IIa.The outcome proved that deep learning algorithms provide greater accuracy results than traditional machine learning algorithms.Amongst the deep learning classifiers,LSTM outperforms the ANN and gives higher classification accuracy of 96.2%. | Ayesha Sarwar Kashif Javed Muhammad Jawad Khan Saddaf Rubab Oh-Young Song Usman Tariq | 2021 | Computers, Materials & Continua2021，，9： | 1 |
| 14 | Improved Hybrid Deep Collaborative Filtering Approach for True Recommendations显示文摘Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep learning approaches for capturing user and product information from a short text.However,such previously used approaches do not fairly and efficiently incorporate users’preferences and product characteristics.The proposed novel Hybrid Deep Collaborative Filtering(HDCF)model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations.To overcome the cold start problem,the new overall rating is generated by aggregating the Deep Multivariate Rating DMR(Votes,Likes,Stars,and Sentiment scores of reviews)from different external data sources because different sites have different rating scores about the same product that make confusion for the user to make a decision,either product is truly popular or not.The proposed novel HDCF model consists of four major modules such as User Product Attention,Deep Collaborative Filtering,Neural Sentiment Classifier,and Deep Multivariate Rating(UPA-DCF+NSC+DMR)to solve the addressed problems.Experimental results demonstrate that our novel model is outperforming state-of-the-art IMDb,Yelp2013,and Yelp2014 datasets for the true top-n recommendation of products using HDCF to increase the accuracy,confidence,and trust of recommendation services. | Muhammad Ibrahim Imran Sarwar Bajwa Nadeem Sarwar Haroon Abdul Waheed Muhammad Zulkifl Hasan Muhammad Zunnurain Hussain | 2023 | Computers, Materials & Continua2023，，3： | 1 |
| 15 | Liver-Tumor Detection Using CNN ResUNet显示文摘Liver tumor is the fifth most occurring type of tumor in men and the ninth most occurring type of tumor in women according to recent reports of Global cancer statistics 2018.There are several imaging tests like Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and ultrasound that can diagnose the liver tumor after taking the sample from the tissue of the liver.These tests are costly and time-consuming.This paper proposed that image processing through deep learning Convolutional Neural Network(CNNs)ResUNet model that can be helpful for the early diagnose of tumor instead of conventional methods.The existing studies have mainly used the two Cascaded CNNs for liver segmentation and evaluation of Region Of Interest(ROI).This study uses ResUNet,an updated version of U-Net and ResNet Models that utilize the service of Residential blocks.We apply over method on the 3D-IRCADb01 dataset that is based on CT slices of liver tumor affected patients.The results showed the True Value Accuracy around 99%and F1 score performance around 95%.This method will be helpful for early and accurate diagnose of the Liver tumor to save the lives of many patients in the field of Biotechnology. | Muhammad Sohaib Aslam Muhammad Younas Muhammad Umar Sarwar Muhammad Arif Shah Atif Khan MIrfan Uddin Shafiq Ahmad Muhammad Firdausi Mazen Zaindin | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 16 | Estimation of Genetic Divergence and Character Association Studies in Local and Exotic Diversity Panels of Soybean(Glycine max L.)Genotypes显示文摘The availability of favorable genetic diversity is a thriving vitality for the success of a breeding program.It provides a firm basis of selecting superior breeding lines for the development of high yielding crop genotypes.In this context,present investigation aimed to generate information on genetic divergence and character association in a diversity panel of 123 local and exotic soybean genotypes.Analysis of variance revealed significant response of the evaluated genotypes based on studied attributes.It depicted the probability of selecting desirable soybean genotypes by focusing on character association studies and genetic diversity analysis.Correlation analysis revealed that seed yield per plant showed high positive correlation with 100-seed weight followed by pods per plant and plant height.Furthermore,path coefficient analysis exposed that pods per plant had maximum direct contribution in seed yield per plant followed by 100-seed weight,days to flowering and SPAD measurement.Genotype named“G-10”showed maximum yield per plant followed by 24607,G-52,24593,Arisoy,24566,17426,A-3127,24570 and 24567.Genetic diversity analysis grouped the evaluated germplasm into 17 clusters.All clusters showed zero intra-cluster variability;while inter-cluster divergence ranged from 9.00 to 91.11.Cluster V showed maximum inter-cluster distance with cluster XII followed by that of between V and VIII.Moreover,cluster IV with superior genotypes(G-10,24607,24593 and 24566),VI(17426 and 24567),XIII(24570)and X(Arisoy and G-52)showed above mean values for most of the studied characters.Overall,the results of hybridization between the superior genotypes of these cluster pairs might be useful for soybean breeding with improving agronomic traits and adaptability. | Syed Ali Zafar Muhammad Aslam Haroon Zaman Khan Sehrish Sarwar Rao Saad Rehman Mariam Hassan Ramala Masood Ahmad Rafaqat AGill Basharat Ali Ibrahim Al-Ashkar Abdullah Ibrahim Md Atikur Rahman Ayman El Sabagh | 2023 | Phyton-International Journal of Experimental Botany2023，92，6： | 0 |
| 17 | Exploring aramid as emerging contender for CO_2 capture显示文摘To prevent CO_2 accumulation in the atmosphere generated from scorching of fossil fuels, carbon capture and sequestration(CCS) technology is considered as a potential route to mitigate the emissions of CO_2 from reaching the atmosphere. Power generation from sources such as gas, coal and biomass can fulfill the energy demand more readily than many other sources of electricity production. Thus these sources may be retained as important alternative option in the global energy cycle. In order to curtail CO_2, porous aramid network was fabricated by the condensation of 1,3,5-benzenetricarbonyl trichloride and 1,3-phenylenediamine in 1,4-dioxane solvent. Aramid was characterized for various analyses including FTIR, XRD, TGA, BET surface area and pore size analysis, FESEM and CO_2 adsorption measurements. Excellent thermal stability was provided by strong amide linkages in the polymer backbone. Optimum CO_2 uptake of aramid was achieved to be 23.14 mg·g^(-1) at 273 K at 0.1 MPa. The basic amide groups of network structure showed greater affinity for CO_2.Excellent thermal stability of aramid makes it a promising sorbent for CO_2 capture in adverse conditions. | Sonia Zulfiqar Muhammad Ilyas Sarwar | 2016 | Chinese Journal of Chemical Engineering2016，24，7： | 0 |
| 18 | 2D seismic interpretation of Sawan gas field integrated with petrophysical analysis:A case study from Lower Indus Basin,Pakistan显示文摘The Lower Indus Basin is the leading hydrocarbon-bearing sedimentary basin in Pakistan.This study has been conducted on the Sawan gas field located in the Lower Indus Basin,adjacent to a few other wellknown gas fields of Pakistan like Kadanwari,Qadirpur,and Miano gas fields.This research aims to present the spatial distribution and reservoir potential of the productive zones of the Lower Goru Formation.The present study utilized various two-dimensional(2D)seismic lines and well-log data(Sawan-01 and Sawan-02)to investigate the structural and stratigraphic features of the area.The stratigraphic layers are mildly deepening in the southeast direction.The 2D seismic interpretation of the research area identifies the existence of extensional remanents,i.e.,normal faults.These extensional structures are associated with horst and graben geometry that acts as a trapping mechanism for hydrocarbons.Wireline logs are used to identify the reservoir's diverse lithology and petrophysical properties.Petrophysical results indicate fair to good effective porosities,low shale volume,and high hydrocarbon saturation(>55%),signifying good reservoir potential in C interval of the Lower Goru Formation. | Abd Ur Rehman Khan Muhammad Amar Gul Rizwan Sarwar Awan Ashar Khan Khawaja Hasnain Iltaf Sibt.E Hassan Butt | 2023 | Energy Geoscience2023，4，2： | 0 |
| 19 | Mineralogy and element geochemistry of the Sohnari rocks of Early Eocene Laki Formation in the Southern Indus Basin,Pakistan:Implications for paleoclimate,paleoweathering and paleoredox conditions显示文摘The Sohnari Member of the Early Eocene Laki Formation is massively deposited in the Southern Indus Basin of Pakistan and is considered a potential source rock to generate hydrocarbons.However,the detailed paleoclimatic,paleoweathering,and depositional conditions of the Sohnari Member have not been studied earlier.This research mainly discusses the detailed mineralogical(bulk and clay)and elemental geochemistry of the Laki Formation from two outcrop sections(Jhimpir and Lakhra)in the Southern Indus Basin,Pakistan.The bulk minerals,including quartz(low),hematite,calcite,halite,gypsum,and clay minerals such as kaolinite,chlorite,smectite and illite have been discussed here.These results demonstrate the paleo-environment of studied area was arid with enhanced saline and weak to strong oxidizing depositional conditions.The chemical index of alteration(CIA)values in Jhimpir and Lakhra sections are in the ranges of 41.30-97.93 and 22.30-96.19,respectively,indicating that the Sohnari sediments experienced weak to intense chemical weathering in the source area.The interpretation of the A-CN-K ternary diagram is consistent with the clay mineral contents in the studied sediments,which is characterized by the predominance of kaolinite,gibbsite and chlorite,demonstrating the weak to strong weathering state under warm and humid climatic conditions.The chemical indices such as Sr/Ba,δU,V/Cr,Ni/Co,and Cu/Zn,U/Th and Ba/Ga show that Sohnari rocks of Early Eocene Laki Formation underwent strong evaporation,oxic water column with warm to humid and minor contact of cold climatic conditions.Based on our present data,it can be concluded that the sediments of Sohnari Member of Laki Formation from Jhimpir and Lakhra areas of Southern Indus Basin in Pakistan are related to Indio-Eurasian collision and came from the Indian shield rocks that were deposited in a brackish water body with a minor contact of the freshwater oxidizing paleo-environment depositional conditions. | Asghar A.A.D.Hakro Sajjad Ali Abdul Shakoor Mastoi Riaz Hussain Rajper Rizwan Sarwar Awan Muhammad Soomar Samtio Hong Xiao Xiaolin Lu | 2023 | Energy Geoscience2023，4，1： | 0 |
| 20 | Analysis of Pneumonia Model via Efficient Computing Techniques显示文摘Pneumonia is a highly transmissible disease in children.According to the World Health Organization(WHO),the most affected regions include south Asia and sub-Saharan Africa.Worldwide,15%of pediatric deaths can be attributed to pneumonia.Computing techniques have a significant role in science,engineering,and many other fields.In this study,we focused on the efficiency of numerical techniques via computer programs.We studied the dynamics of the pneumonia-like infections of epidemic models using numerical techniques.We discuss two types of analysis:dynamical and numerical.The dynamical analysis included positivity,boundedness,local stability,reproduction number,and equilibria of the model.We also discusswell-known computing techniques including Euler,Runge Kutta,and non-standard finite difference(NSFD)for the model.The non-standard finite difference(NSFD)technique shows convergence to the true equilibrium points of the model for any time step size.However,Euler and Runge Kutta do not work well over large time intervals.Computing techniques are the suitable tool for crosschecking the theoretical analysis of the model. | Kamaledin Abodayeh Ali Raza Muhammad Rafiq Muhammad Shoaib Arif Muhammad Naveed Zunir Zeb Syed Zaheer Abbas Kiran Shahzadi Sana Sarwar Qasim Naveed Badar Ul Zaman Muhammad Mohsin | 2022 | Computers, Materials & Continua2022，，3： | 0 |
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