A parallel CNN architecture for sport activity recognition based on minimal movement data by Huipeng Zhao

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Incidence of Congenital Limb Reduction Defects: A Systematic Review by Gabrielle Levesque, Renitha Reddi, Harpreet Chhina, Alison M. Elliott, Colleen Pawliuk, Jeffrey Bone, Anthony Cooper

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A hybrid attention multi-scale fusion network for real-time semantic segmentation by Baofeng Ye, Renzheng Xue, Qianlong Wu

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Research Progress on Effects and Treatment of Microplastic Pollution in Freshwater Ecosystems by TANG Hongliang, MA Jinlong, XU Chenchen, PENG Songyao, FENG Lijuan

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L’impact des pesticides utilisés en lutte contre le criquet pèlerin (schistocerca gregaria Forskål, 1775) (orthoptera, acrididae) sur deux espèces de pimelia (coleoptera, tenebrion... by Abdou Mamadou, Ahmed Mazih, Alzouma Inezdane

“…According to the classification of FAO, these risks are regarded as high (>75%). …”
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The Effects of Exercise on Inhibitory Function Interventions for Patients With Major Depressive Disorder (MDD): A Systematic Review and Meta‐Analysis by Zhihui Xu, Cong Liu, Peng Wang, Xing Wang, Yuzhang Li

“…Conclusion Based on the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual of Mental Disorders (DSM) classification systems, a research framework for exercise interventions on executive function in MDD patients was constructed, demonstrating that exercise can improve inhibitory function in MDD with high evidence quality. …”
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TRANSPORT OF GOODS ON THE EXAMPLE OF A SELECTED SECTION OF TRANSPORT IN POLAND by Elżbieta MACIOSZEK, Irena JURDANA

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PHYSIOLOGICAL EFFICACY OF MELANIN AS A FOOD INGREDIENT by N. Cherno, A. Kapustian, K. Naumenko, L. Gural, S. Osolina

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Treatment of Pelvic Organ Prolapse in a Patient with a Thermal Burn Wound Caused by Hot Stone Therapy, a Traditional Thai Treatment by Sasivimol Srisukho, Orawee Chinthakanan

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Measuring and utilizing temporal network dissimilarity by Xiu-Xiu Zhan, Chuang Liu, Zhipeng Wang, Huijuan Wang, Petter Holme, Zi-Ke Zhang

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IDENTIFICATION OF STUDENTS’ DIFFICULTIES IN MASTERING PASSIVE VOICE by Nurlaila Kadariyah, Ida Liani

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Learning-Based Dark and Blurred Underwater Image Restoration by Yifeng Xu, Huigang Wang, Garth Douglas Cooper, Shaowei Rong, Weitao Sun

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« This » comme marqueur privilégié du genre : le cas des résumés de thèses by Geneviève Bordet

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Craniomandibular Disorders and Mandibular Reference Position in Orthodontic Treatment by Farid Bourzgui, Hakima Aghoutan, Samir Diouny

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Moral passion and legal positivism: reply to Anton Didikin by A. V. Nekhaev

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Atypical Bilateral Posterior Semicircular Canalolithiasis – A Case Series by Ajay K Vats, Shreya Vats, Sudhir Kothari, Nishant Aswani

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A membrane permeability database for nonpeptidic macrocycles by Qiushi Feng, Danjo De Chavez, Jan Kihlberg, Vasanthanathan Poongavanam

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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process by Akshansh Mishra, Vijaykumar S Jatti, Nitin K Khedkar, Rahul B. Dhabale, Ashwini V Jatti

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A network intrusion detection method designed for few-shot scenarios by Weichen HU, Congyuan XU, Yong ZHAN, Guanghui CHEN, Siqing LIU, Zhiqiang WANG, Xiaolin WANG

“…Existing intrusion detection techniques often require numerous malicious samples for model training.However, in real-world scenarios, only a small number of intrusion traffic samples can be obtained, which belong to few-shot scenarios.To address this challenge, a network intrusion detection method designed for few-shot scenarios was proposed.The method comprised two main parts: a packet sampling module and a meta-learning module.The packet sampling module was used for filtering, segmenting, and recombining raw network data, while the meta-learning module was used for feature extraction and result classification.Experimental results based on three few-shot datasets constructed from real network traffic data sources show that the method exhibits good applicability and fast convergence and effectively reduces the occurrence of outliers.In the case of 10 training samples, the maximum achievable detection rate is 99.29%, while the accuracy rate can reach a maximum of 97.93%.These findings demonstrate a noticeable improvement of 0.12% and 0.37% respectively, in comparison to existing algorithms.…”
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