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PCR-HRM for Genomic Surveillance of SARS-CoV-2: A Variant Detection Tool in Côte d’Ivoire, West Africa

American Journal of Molecular Biology 2024年第3期14卷 166-185页

作者： Aboubacar Sylla Solange Kakou-Ngazoa Tata Gniré Safiatou Coulibaly Yakoura Karidja ouattara Mireille Sylvie Kouamé-Sina zeinab ouattara David Ngolo Coulibaly Brice Kouakou Bla Mireille Dosso Molecular Biology Platform Pasteur Institute Cte dIvoire Abidjan Cte dIvoire Laboratory of Biology and Health UFR Biosciences University Flix Houphout Boigny Abidjan Cte dIvoire Genetic and Cancer Laboratory Molecular Genetics Platform Pasteur Institute Cte dIvoire Abidjan Cte dIvoire Epidemic Virus Department Pasteur Institute Cte dIvoire Abidjan Cte dIvoire

The rise of new viruses, like SARS-CoV-2 causing the COVID-19 outbreak, along with the return of antibiotic resistance in harmful bacteria, demands a swift and efficient reaction to safeguard the health and welfare of the global population. It is crucial to have effective measures for prevention, intervention, and monitoring in place to address these evolving and recurring risks, ensuring public health and international security. In countries with limited resources, utilizing recombinant mutation plasmid technology in conjunction with PCR-HRM could help differentiate the existence of novel variants. cDNA synthesis was carried out on 8 nasopharyngeal samples following viral RNA extraction. The P1 segment of the SARS-CoV-2 Spike S protein was amplified via conventional PCR. Subsequently, PCR products were ligated with the pGEM-T Easy vector to generate eight recombinant SARS-CoV-2 plasmids. Clones containing mutations were sequenced using Sanger sequencing and analyzed through PCR-HRM. The P1 segment of the S gene from SARS-CoV-2 was successfully amplified, resulting in 8 recombinant plasmids generated from the 231 bp fragment. PCR-HRM analysis of these recombinant plasmids differentiated three variations within the SARS-CoV-2 plasmid population, each displaying distinct melting temperatures. Sanger sequencing identified mutations A112C, G113T, A114G, G214T, and G216C on the P1 segment, validating the PCR-HRM findings of the variations. These mutations led to the detection of L452R or L452M and F486V protein mutations within the protein sequence of the Omicron variant of SARS-CoV-2. In summary, PCR-HRM is a vital and affordable tool for distinguishing SARS-CoV-2 variants utilizing recombinant plasmids as controls.

关键词： Genomic Surveillance SARS-CoV-2 PCR-HRM Variants Côte d’Ivoire

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Construction of the rat brain spatial cell firing model on a quadruped robot

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CAAI Transactions on Intelligence Technology 2022年第4期7卷 732-743页

作者： Naigong Yu Yishen Liao Hejie Yu ouattara Sie Faculty of Information Technology Beijing University of TechnologyBeijingChina Beijing Key Laboratory of Computational Intelligence and Intelligent System BeijingChina Engineering Research Center of Digital Community Ministry of EducationBeijingChina College of Robotic UniversitéFélix Houphouet-BoignyAbidjanCote d'Ivoire

Physiological studies have shown that rats in a dark environment rely on the limbs and vestibule for their self-motion information,which can maintain the specific firing patterns of grid cells and hippocampal CA3 place *** the development stage of rats,grid cells are considered to come from place cells,and place cells can be encoded by hippocampal theta *** on these,the quadruped robot is used as a platform in this ***,the sensing information of the robot's limbs and inertial measurement unit is obtained to solve its position in the *** the position information is encoded by theta cells and mapped to place cells through a neural *** obtaining the place cells with singlepeak firing fields,Hebb learning is used to adjust the connection weight of the neural network between place cells and grid *** order to verify the model,3-D simulation experiments are designed in this *** experiment results show that with the robot exploring in space,the spatial cells firing effects obtained by the model are consistent with the physiological research facts,which lay the foundation for the bionic environmental cognition model.

关键词： robot neural firing

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Effect of SAP on Properties of High Performance Concrete under Marine Wetting and Drying Cycles

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Journal of Wuhan University of Technology(Materials Science) 2019年第5期34卷 1136-1142页

作者： ouattara Coumoin Cherel WANG Fazhou YANG Jin LIU Zhichao[[ State Key Laboratory of Silicate Materials for Architecture Wuhan University of TechnologyWuhan 430070China School of Materials Science and Engineering Wuhan University of TechnologyWuhan 430070China School of Civil Engineering and Architecture Hubei University of TechnologyWuhan 430070China State Key Laboratory of Green Building Materials China Building Materials AcademyBeijing 100024China

The internal curing effect of superabsorbent polymer(SAP) on the properties of high performance concrete(HPC) under marine wetting and drying cycles(WD cycles) was investigated. Compressive strength, hydration and chloride migration were experimentally investigated and the results were evaluated by compasison with those under fresh water curing(FW). Water absorption and porosity were also evaluated only under WD cycles. The results showed the important influence of wetting and drying cycles on the properties of SAP modified HPC properties. Carefully designed, SAP minimized the long-term compressive strength of HPC under marine WD cycles. The hydration rate was faster in the initial curing, but became lower as compared with that cured in FW. In addition, SAP improved the long-term water absorption resistance and chloride migration resistance of HPC under marine WD cycles. The examination of the porosity showed a lower increase of the volume of capillary pores in SAP modified HPC under long term WD cycles compared with that without SAP. Therefore, internal curing by SAP could improve the durability properties of HPC under marine WD cycles.

关键词： superabsorbent polymer(SAP) high performance concrete wetting and drying cycles internal curing

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3D reconstruction and defect pattern recognition of bonding wire based on stereo vision

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 348-364页

作者： Naigong Yu Hongzheng Li Qiao Xu ouattara Sie Essaf Firdaous Faculty of Information Technology Beijing University of TechnologyBeijingChina Beijing Key Laboratory of Computing Intelligence and Intelligent System Beijing University of TechnologyBeijingChina Engineering Research Center of Digital Community Ministry of EducationBeijingChina College of Robotic UniversitéFélix Houphouët‐BoignyAbidjanCôte d’Ivoire

Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after ***-processing-based methods do not provide a detailed evaluation of the three-dimensional defects of the bonding ***,a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision,which can achieve non-destructive detection of bonding wire defects is *** contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding *** to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface,a point cloud segmentation method based on spatial surface feature detection(SFD)was *** can extract more distinct features from the bonding wire surface during the point cloud segmentation ***,in the defect detection process,a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding *** descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of *** experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires,and the average accuracy of defect recognition is 96.47%,which meets the production requirements of bonding wire defect detection.

关键词： bonding wire defect detection point cloud point cloud segmentation

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Wafer map defect patterns classification based on a lightweight network and data augmentation

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1029-1042页

作者： Naigong Yu Huaisheng Chen Qiao Xu Mohammad Mehedi Hasan ouattara Sie Faculty of Information Technology Beijing University of TechnologyBeijingChina Beijing Key Laboratory of Computational Intelligence and Intelligent System BeijingChina Engineering Research Center of Digital Community Ministry of EducationBeijingChina College of Robotic UniversitéFélix Houphouët‐BoignyAbidjanCôte d'Ivoire

Accurately identifying defect patterns in wafer maps can help engineers find abnormal failure factors in production *** the wafer testing stage,deep learning methods are widely used in wafer defect detection due to their powerful feature extraction ***,most of the current wafer defect patterns classification models have high complexity and slow detection speed,which are difficult to apply in the actual wafer production *** addition,there is a data imbalance in the wafer dataset that seriously affects the training results of the *** reduce the complexity of the deep model without affecting the wafer feature expression,this paper adjusts the structure of the dense block in the PeleeNet network and proposes a lightweight network WM‐PeleeNet based on the PeleeNet *** addition,to reduce the impact of data imbalance on model training,this paper proposes a wafer data augmentation method based on a convolutional autoencoder by adding random Gaussian noise to the hidden *** method proposed in this paper has an average accuracy of 95.4%on the WM‐811K wafer dataset with only 173.643 KB of the parameters and 316.194 M of FLOPs,and takes only 22.99 s to detect 1000 wafer *** with the original PeleeNet network without optimization,the number of parameters and FLOPs are reduced by 92.68%and 58.85%,*** augmentation on the minority class wafer map improves the average classification accuracy by 1.8%on the WM‐811K *** the same time,the recognition accuracy of minority classes such as Scratch pattern and Donut pattern are significantly improved.

关键词： convolutional autoencoder lightweight network wafer defect detection

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Position-aware pushing and grasping synergy with deep reinforcement learning in clutter

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 738-755页

作者： Min Zhao Guoyu Zuo Shuangyue Yu Daoxiong Gong Zihao Wang ouattara Sie Intelligent Robotics Laboratory Faculty of Information TechnologyBeijing University of TechnologyBeijingChina Beijing Key Laboratory of Computational Intelligence and Intelligent Systems BeijingChina Laboratory of Biomechatronics and Intelligent Robotics(BIRO) Department of Mechanical and Aerospace EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA

The positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in *** effectively perform grasping and pushing manipu-lations,robots need to perceive the position information of objects,including the co-ordinates and spatial relationship between objects(e.g.,proximity,adjacency).The authors propose an end-to-end position-aware deep Q-learning framework to achieve efficient collaborative pushing and grasping in ***,a pair of conjugate pushing and grasping attention modules are proposed to capture the position information of objects and generate high-quality affordance maps of operating positions with features of pushing and grasping *** addition,the authors propose an object isolation metric and clutter metric based on instance segmentation to measure the spatial re-lationships between objects in cluttered *** further enhance the perception capacity of position information of the objects,the authors associate the change in the object isolation metric and clutter metric in cluttered environment before and after performing the action with reward function.A series of experiments are carried out in simulation and real-world which indicate that the method improves sample efficiency,task completion rate,grasping success rate and action efficiency compared to state-of-the-art end-to-end *** that the authors’system can be robustly applied to real-world use and extended to novel *** material is available at https://***/NhG\_k5v3NnM}{https://***/NhG\_k5v3NnM.

关键词： deep learning deep neural networks intelligent robots

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Sudden unexpected infant death rates and risk factors for unsafe sleep practices

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World Journal of Pediatrics 2022年第3期18卷 225-229页

作者： Balkissa S.ouattara Melissa K.Tibbits Drissa M.Toure Lorena Baccaglini Department of Environmental Agricultural and Occupational HealthCollege of Public HealthUniversity of Nebraska Medical Center984388 Nebraska Medical CenterOmahaNE 68198-4388USA Department of Health Promotion College of Public HealthUniversity of Nebraska Medical Center986075 Nebraska Medical CenterOmahaNE 68198-6075USA Department of Health Promotion Center for Reducing Health DisparitiesCollege of Public HealthUniversity of Nebraska Medical Center984340 Nebraska Medical CenterOmahaNE 68198-4340USA Department of Epidemiology College of Public HealthUniversity of Nebraska Medical Center984395 Nebraska Medical CenterOmahaNE 68198-4395USA

Sudden unexpected infant death(SUID),the leading cause of death in the post-neonatal period in developed countries,represents the death of an infant less than 1 year of age that is sudden and unexpected[1-3].SUID is a general term that encompasses the following:sudden infant death syndrome(SIDS),accidental suffocation and strangulation in bed,and unknown causes of death in infants less than 1 year of age[4,5].

关键词： death infant SIDS

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Sports Stars as a Means of Brand Communication in Cote d’Ivoire

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Journalism and Mass Communication 2019年第4期9卷 176-189页

作者： ouattara Katia Department of Information and Communication Sciences Université Peleforo Gon Coulibaly(UPGC)KorhogoCote d’Ivoire

The growing interest of Ivorian companies in sports celebrities has led us to conduct research on sports stars as a means of brand communication in C?te d’*** work,based on a semiological reading,reveals several persuasive strategies used by advertisers to seduce consumers:The use of sports celebrities as spokespersons for brands and above all as promoters of products because of their youth,elegance,and *** promotions are most often made from the competition areas where they *** to the low literacy level of the population,we are witnessing the use of simple language,etc.

关键词： communication sports star advertising media semiology

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Biscuits: a systematic review and meta-analysis of improving the nutritional quality and health benefits

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Food Production, Processing and Nutrition 2021年第1期3卷 335-352页

作者： MahamadéGoubgou Laurencia TSongré-ouattara Fabrice Bationo Hagrétou Lingani-Sawadogo Yves Traoré Aly Savadogo Doctoral School of Sciences and Technology Laboratory of Applied Biochemistry and Immunology(LABIA)University Joseph KI-ZERBOOuagadougouBurkina Faso Department of Food Technology(DTA) Research Institute of Applied Sciences and Technology(IRSAT)OuagadougouBurkina Faso

Biscuits are ready-to-eat foods that are traditionally prepared mainly with wheat flour,fat,and ***,biscuits’technologies have been rapidly developed to improve their nutritional *** study aimed to determine the strategies of improving the nutritional quality of biscuits and the potential health benefits associated with them.A systematic review and meta-analysis were conducted,including articles on biscuits improved by technological processes and raw materials *** were searched from Google Scholar,PubMed,Scopus,and Web of Science published between 1997 and 2020,in English and *** meta-analysis was performed using RStudio software,version 4.0.4 to classify the *** hundred and seven eligible articles were ***,pea,potato,sorghum,buckwheat,and flaxseed flours were respectively the most found substitutes to wheat *** the meta-analysis shown that the copra and foxtail millet biscuit fortified with amaranth,the wheat biscuits fortified with okra,and rice biscuits fortified with soybeans had a high protein *** biscuits therefore have a potential to be used as complementary *** substitution of sugar and fat by several substitutes lead to a decrease in carbohydrates,fat,and energy *** has also brought about an increase in other nutrients such as dietary fiber,proteins/amino acids,fatty acids,and phenolic *** the sugar and fat substitutes,stevia and inulin were respectively the most *** the use of biscuits in clinical trials,they were mainly used for addressing micronutrient deficiency and for weight loss.

关键词： Biscuit Technology Nutrition Health benefits

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Optimal Classification of Minerals by Microscopic Image Analysis Based on Seven-State “Deep Learning” Combined with Optimizers

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Open Journal of Applied Sciences 2024年第6期14卷 1550-1572页

作者： Kouadio Krah Sie ouattara Gbele ouattara Alain Clement Joseph Vangah Laboratoire de Gnie Civil Gosciences et Sciences Gographiques Institut National Polytechnique Houphout Boigny (INPHB) Yamoussoukro Cte dIvoire Institut National Polytechnique Houphout Boigny (INPHB) Ecole Doctorale Polytechnique (EDP) Yamoussoukro Cte dIvoire Laboratoire des Sciences et Technologies de la Communication et de lInformation (LSTCI) Institut National Polytechnique Houphout Boigny (INP-HB) Yamoussoukro Cte dIvoire Ecole de Gomatique et du Territoire (EGT) Abidjan Cte dIvoire LARIS SFR MATHSTIC Universit dAngers Angers France Universit Virtuelle de Cte dIvoire Abidjan Cte dIvoire

The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, medicine, surveillance or security, agriculture, etc.). Most related works use open source consistent image databases. This is the case for ImageNet reference data such as coco data, IP102, CIFAR-10, STL-10 and many others with variability representatives. The consistency of its images contributes to the spectacular results observed in its fields with deep learning. The application of deep learning which is making its debut in geology does not, to our knowledge, include a database of microscopic images of thin sections of open source rock minerals. In this paper, we evaluate three optimizers under the AlexNet architecture to check whether our acquired mineral images have object features or patterns that are clear and distinct to be extracted by a neural network. These are thin sections of magmatic rocks (biotite and 2-mica granite, granodiorite, simple granite, dolerite, charnokite and gabbros, etc.) which served as support. We use two hyper-parameters: the number of epochs to perform complete rounds on the entire data set and the “learning rate” to indicate how quickly the weights in the network will be modified during optimization. Using Transfer Learning, the three (3) optimizers all based on the gradient descent methods of Stochastic Momentum Gradient Descent (sgdm), Root Mean Square Propagation (RMSprop) algorithm and Adaptive Estimation of moment (Adam) achieved better performance. The recorded results indicate that the Momentum optimizer achieved the best scores respectively of 96.2% with a learning step set to 10−3 for a fixed choice of 350 epochs during this variation and 96, 7% over 300 epochs for the same value of the learning step. This performance is expected to provide excellent insight into image quality for future studies. Then they participate in the development of

关键词： Classification Convolutional Neural Network Deep Learning Optimizers Transfer Learning Rock Mineral Images

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