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| 1 | Novel mutations in PDE6A and CDHR1 cause retinitis pigmentosa in Pakistani families显示文摘AIM:To investigate the genetic basis of autosomal recessive retinitis pigmentosa(arRP)in two consanguineous/endogamous Pakistani families.METHODS:Whole exome sequencing(WES)was performed on genomic DNA samples of patients with arRP to identify disease causing mutations.Sanger sequencing was performed to confirm familial segregation of identified mutations,and potential pathogenicity was determined by predictions of the mutations’functions.RESULTS:A novel homozygous frameshift mutation[NM_000440.2:c.1054delG,p.(Gln352Argfs*4);Chr5:g.149286886del(GRCh37)]in the PDE6A gene in an endogamous family and a novel homozygous splice site mutation[NM_033100.3:c.1168-1G>A,Chr10:g.85968484G>A(GRCh37)]in the CDHR1 gene in a consanguineous family were identified.The PDE6A variant p.(Gln352Argfs*4)was predicted to be deleterious or pathogenic,whilst the CDHR1 variant c.1168-1G>A was predicted to result in potential alteration of splicing.CONCLUSION:This study expands the spectrum of genetic variants for arRP in Pakistani families. | Muhammad Dawood Siying Lin Taj Ud Din Irfan Ullah Shah Niamat Khan Abid Jan Muhammad Marwan Komal Sultan Maha Nowshid Raheel Tahir Asif Naveed Ahmed Muhammad Yasin Emma LBaple Andrew HCrosby Shamim Saleha | 2021 | International Journal of Ophthalmology(English edition)2021，14，12： | 0 |
| 2 | Feasibility-Guided Constraint-Handling Techniques for Engineering Optimization Problems显示文摘The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm and requires constraint handling techniques(CHTs)to solve constrained optimization problems(COPs).For this purpose,we integrate two CHTs,the superiority of feasibility(SF)and the violation constraint-handling(VCH),with a PSO.These CHTs distinguish feasible solutions from infeasible ones.Moreover,in SF,the selection of infeasible solutions is based on their degree of constraint violations,whereas in VCH,the number of constraint violations by an infeasible solution is of more importance.Therefore,a PSO is adapted for constrained optimization,yielding two constrained variants,denoted SF-PSO and VCH-PSO.Both SF-PSO and VCH-PSO are evaluated with respect to ve engineering problems:the Himmelblau’s nonlinear optimization,the welded beam design,the spring design,the pressure vessel design,and the three-bar truss design.The simulation results show that both algorithms are consistent in terms of their solutions to these problems,including their different available versions.Comparison of the SF-PSO and the VCHPSO with other existing algorithms on the tested problems shows that the proposed algorithms have lower computational cost in terms of the number of function evaluations used.We also report our disagreement with some unjust comparisons made by other researchers regarding the tested problems and their different variants. | Muhammad Asif Jan Yasir Mahmood Hidayat Ullah Khan Wali Khan Mashwani Muhammad Irfan Uddin Marwan Mahmoud Rashida Adeeb Khanum Ikramullah Noor Mast | 2021 | Computers, Materials & Continua2021，，6： | 0 |
| 3 | Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network显示文摘Appearance-based dynamic Hand Gesture Recognition(HGR)remains a prominent area of research in Human-Computer Interaction(HCI).Numerous environmental and computational constraints limit its real-time deployment.In addition,the performance of a model decreases as the subject’s distance from the camera increases.This study proposes a 3D separable Convolutional Neural Network(CNN),considering the model’s computa-tional complexity and recognition accuracy.The 20BN-Jester dataset was used to train the model for six gesture classes.After achieving the best offline recognition accuracy of 94.39%,the model was deployed in real-time while considering the subject’s attention,the instant of performing a gesture,and the subject’s distance from the camera.Despite being discussed in numerous research articles,the distance factor remains unresolved in real-time deployment,which leads to degraded recognition results.In the proposed approach,the distance calculation substantially improves the classification performance by reducing the impact of the subject’s distance from the camera.Additionally,the capability of feature extraction,degree of relevance,and statistical significance of the proposed model against other state-of-the-art models were validated using t-distributed Stochastic Neighbor Embedding(t-SNE),Mathew’s Correlation Coefficient(MCC),and the McNemar test,respectively.We observed that the proposed model exhibits state-of-the-art outcomes and a comparatively high significance level. | Muhammad Rizwan Sana Ul Haq Noor Gul Muhammad Asif Syed Muslim Shah Tariqullah Jan Naveed Ahmad | 2023 | Computers, Materials & Continua2023，，7： | 0 |
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