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| 1 | Solar-assisted post-combustion carbon capture feasibility 显示文摘 | MARWAN M MUHAMMAD T A RAJAB K | 2012 | Applied Energy2012，92，： | 1 |
| 2 | Advancing male age differentially alters levels and localization patterns of PLCzeta in sperm and testes from different mouse strains显示文摘Sperm-specific phospholipase C zeta(PLCζ)initiates intracellular calcium(Ca2+)transients which drive a series of concurrent events collectively termed oocyte activation.Numerous investigations have linked abrogation and absence/reduction of PLCζwith forms of male infertility in humans where oocyte activation fails.However,very few studies have examined potential relationships between PLCζand advancing male age,both of which are increasingly considered to be major effectors of male fertility.Initial efforts in humans may be hindered by inherent PLCζvariability within the human population,alongside a lack of sufficient controllable repeats.Herein,utilizing immunoblotting,immunofluorescence,and quantitative reverse transcription PCR(qRT-PCR)we examined for the first time PLCζprotein levels and localization patterns in sperm,and PLCζmRNA levels within testes,from mice at 8 weeks,12 weeks,24 weeks,and 36 weeks of age,from two separate strains of mice,C57BL/6(B6;inbred)and CD1(outbred).Collectively,advancing male age generally diminished levels and variability of PLCζprotein and mRNA in sperm and testes,respectively,when both strains were examined.Furthermore,advancing male age altered the predominant pattern of PLCζlocalization in mouse sperm,with younger mice exhibiting predominantly post-acrosomal,and older mice exhibiting both post-acrosomal and acrosomal populations of PLCζ.However,the specific pattern of such decline in levels of protein and mRNA was strain-specific.Collectively,our results demonstrate a negative relationship between advancing male age and PLCζlevels and localization patterns,indicating that aging male mice from different strains may serve as useful models to investigate PLCζin cases of male infertility and subfertility in humans. | Junaid Kashir Bhavesh V Mistry Maha Adel Gumssani Muhammad Rajab Reema Abu-Dawas Falah AlMohanna Michail Nomikos Celine Jones Raed Abu-Dawud Nadya Al-Yacoub Kevin Coward F Anthony Lai Abdullah M Assiri | 2021 | Asian Journal of Andrology2021，23，2： | 0 |
| 3 | Improved-Equalized Cluster Head Election Routing Protocol for Wireless Sensor Networks显示文摘Throughout the use of the small battery-operated sensor nodes encou-rage us to develop an energy-efficient routing protocol for wireless sensor networks(WSNs).The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of WSN.Many routing protocols are available,but the issue is still alive.Clustering is one of the most important techniques in the existing routing protocols.In the clustering-based model,the important thing is the selection of the cluster heads.In this paper,we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining energy and the distance of the nodes in each cluster.Initially,the bubble sort algorithm chose the two nodes with the maximum remaining energy in the cluster and chose a cluster head with a small distance.The proposed scheme performs hierarchal routing and direct routing with some energy thresholds.The simulation will be performed in MATLAB to justify its performance and results and compared with the ECHERP model to justify its performance.Moreover,the simulations will be performed in two scenarios,gate-way-based and without gateway to achieve more energy-efficient results. | Muhammad Shahzeb Ali Ali Alqahtani Ansar Munir Shah Adel Rajab Mahmood Ul Hassan Asadullah Shaikh Khairan Rajab Basit Shahzad | 2023 | Computer Systems Science & Engineering2023，44，1： | 0 |
| 4 | Optimizing Steering Angle Predictive Convolutional Neural Network for Autonomous Car显示文摘Deep learning techniques,particularly convolutional neural networks(CNNs),have exhibited remarkable performance in solving visionrelated problems,especially in unpredictable,dynamic,and challenging environments.In autonomous vehicles,imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of CNNs.In this regard,globally,researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best results.Literature has proven the superiority of metaheuristic algorithms over the manual-tuning of CNNs.However,to the best of our knowledge,these techniques are yet to be applied to address the problem of imitationlearning-based steering angle prediction.Thus,in this study,we examine the application of the bat algorithm and particle swarm optimization algorithm for the optimization of the CNN model and its hyperparameters,which are employed to solve the steering angle prediction problem.To validate the performance of each hyperparameters’set and architectural parameters’set,we utilized the Udacity steering angle dataset and obtained the best results at the following hyperparameter set:optimizer,Adagrad;learning rate,0.0052;and nonlinear activation function,exponential linear unit.As per our findings,we determined that the deep learning models show better results but require more training epochs and time as compared to shallower ones.Results show the superiority of our approach in optimizing CNNs through metaheuristic algorithms as compared with the manual-tuning approach.Infield testing was also performed using the model trained with the optimal architecture,which we developed using our approach. | Hajira Saleem Faisal Riaz Asadullah Shaikh Khairan Rajab Adel Rajab Muhammad Akram Mana Saleh Al Reshan | 2022 | Computers, Materials & Continua2022，，5： | 0 |
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