Using network analysis to personalize treatment for individuals with co-occurring restrictive eating disorders and suicidality: a proof-of-concept study by Lauren M. Harris, Irina A. Vanzhula, Elizabeth D. Cash, Cheri A. Levinson, April R. Smith

Get full text

Deriving Early Citrus Fruit Yield Estimation by Combining Multiple Growing Period Data and Improved YOLOv8 Modeling by Menglin Zhai, Juanli Jing, Shiqing Dou, Jiancheng Du, Rongbin Wang, Jichi Yan, Yaqin Song, Zhengmin Mei

“…In this study, a new network model, YOLOv8-RL, was proposed using citrus multigrowth period characteristics as a data source. …”
Get full text

Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
Get full text

Deep learning-based identification of precipitation clouds from all-sky camera data for observatory safety by Mohammad H. Zhoolideh Haghighi, Alireza Ghasrimanesh, Habib Khosroshahi

“…We train our model on a set of roughly 2445 images taken by the INO all-sky camera through the deep learning method based on the EfficientNet network. Our model reaches an average accuracy of 99% in determining the cloud rainfall’s potential and an accuracy of 96% for cloud coverage. …”
Get full text

Data-driven design of topologically optimized auxetic metamaterials for tailored stress–strain and Poisson’s ratio-strain behaviors by Yueyou Tang, Anfu Zhang, Qi Zhou, Mu He, Liang Xia

“…To overcome these limitations, present work proposes a physics–data collaborative design framework that integrates nonlinear topology optimization with neural networks. …”
Get full text

Transcriptomic and metabolomic profiling reveals genotype-dependent alkali tolerance in triticale roots: amino acid, flavonoid, and betalain metabolism linked to gene networks by Mingke Yan, Guodong Yang, Zhuoqi Liu, Dongming Yang, Xin Zhang, Chugang Mei

Get full text

A Machine Learning Approach for User Behavior Analysis in Developing Websites by Aeesha Shaheen

“…After training, the accuracy of network assesses using test data, and evaluate the effectiveness of forecasting. …”
Get full text

Non-Invasive Localization of Epileptogenic Zone in Drug-Resistant Epilepsy Based on Time–Frequency Analysis and VGG Convolutional Neural Network by Yaqing Liu, Yalin Wang, Tiancheng Wang

“…Previous researchers have proposed a range of methods for this purpose, but these suffer from limits such as unclear post-operative outcomes, invasiveness, limited data volume, and single DRE type. This study constructed a non-invasive epilepsy localization method, integrating sLORETA source imaging, time–frequency analysis, and Visual Geometry Group (VGG-16) deep learning. …”
Get full text

Bridging the gap: A comparative analysis of traditional and neural network regression methods for predicting university entrant performance in SUAST examination by Nikka A. Singh, Diether C. Montejo

Get full text

The comparative effectiveness of 55 interventions in obese patients with polycystic ovary syndrome: A network meta-analysis of 101 randomized trials. by Mohamed Abdel-Maboud, Amr Menshawy, Elfatih A Hasabo, Mohamed Ibrahim Abdelraoof, Mohamed Alshandidy, Muhammad Eid, Esraa Menshawy, Oumaima Outani, Ahmed Menshawy

“…We performed both a pairwise meta-analysis and a network meta-analysis to evaluate the effect sizes with 95% CI, and we calculated the surface under the cumulative ranking curve (SUCRA) for each intervention.…”
Get full text

Comparative Analysis of AI Models for Atypical Pigmented Facial Lesion Diagnosis by Alessandra Cartocci, Alessio Luschi, Linda Tognetti, Elisa Cinotti, Francesca Farnetani, Aimilios Lallas, John Paoli, Caterina Longo, Elvira Moscarella, Danica Tiodorovic, Ignazio Stanganelli, Mariano Suppa, Emi Dika, Iris Zalaudek, Maria Antonietta Pizzichetta, Jean Luc Perrot, Gabriele Cevenini, Ernesto Iadanza, Giovanni Rubegni, Harald Kittler, Philipp Tschandl, Pietro Rubegni

Get full text

Prediction and analysis of power consumption and power loss at industrial facilities by E. Y. Abdullazyanov, E. I. Gracheva, A. Alzakkar, M. F. Nizamiev, O. A. Shumikhina, S. Valtchev

Get full text

Adverse fetal and perinatal outcomes associated with Zika virus infection during pregnancy: an individual participant data meta-analysisResearch in context by Edna Acosta Pérez, Juan Aguilar Ticona, Jackeline Alger, Celia Alpuche Aranda, Angélica Amado Niño, Emily Ansusinha, Thalia Araújo, Juan Arias, Lumumba Arriaga Nieto, Marcos Ávila, Azucena Bardají, Carlos Becerra Mojica, Andrea Benedetti, Ana Bertozzi, Sarah Bethencourt, Karen Blackmon, Victor Borja Aburto, Patrícia Brasil, Elizabeth Brickley, William Britt, Nathalie Broutet, Pierre Buekens, André Cabié, David Alejandro Cabrera-Gaytán, Rodrigo Cachay, Maria Luisa Cafferata, Isaac Caicedo-Castro, Juan Calle, Guilherme Calvet, Harlan Campbell, Maribel Campos, Mabel Carabali, Helen Cerigo, Celia Cordon, Juliana Silva Corrêa, Federico Costa, Conrado Coutinho, Antonio Cunha, Carlos Cure Cure, Johanna Damen, Marcela Daza, Ilich De la Hoz Siegler, Roberta DeBiasi, Thomas Debray, Valentijn de Jong, Camille Delgado-López, Geraldo Duarte, Gabriella Duarte Miranda, Valorie Eckert, Sophie Eickmann, Esther Ellis, Cassia Estofolete, Lester Figueroa Bolaños, Olivier Fléchelles, Kirsten Fong, Maria Barbara Franco Gomes, Trevon Fuller, Victoria Fumadó, Anna Funk, Luis Galvão, Gabriela Lopes Gama, Patrick Gérardin, Luz Gibbons, Anna Goncé, Amy Gonzalez, Eduardo Gotuzzo, Concepción Grajales-Muñiz, Paul Gustafson, Tahani Hamdan, Eva Harris, Cosme Harrison, Najeh Hcini, Cristina Hofer, Natanaël Holband, Claudia Hormiga Sánchez, Ivonne Huerta, Isabel Hurtado, Irene Inwani, David Cruvinel Isaac, Thomas Jaenisch, Esaú João, Amadu Juliana, Jose Paulo Pereira Junior, Edna Kara, Caron Kim, Albert Ko, Nancy Krebs, Angelle Desiree LaBeaud, Heather Lake-Burger, Jill Lebov, Yee-Sin Leo, Brooke Levis, Talita Lima, Simon Ling, Eduardo Lopez-Medina, Cynthia Lorenzo, Calum Macpherson, Olivia Manders, Elena Marbán-Castro, Ernesto Torres de Azevedo Marques, Celina Turchi Martelli, Flor Martinez-Espinosa, Gloria Martinó González, Gustavo Matta, Salim Máttar, Lauren Maxwell, John McCracken, Adriana Melo, Clara Menéndez, Marcela Mercado Reyes, María Consuelo Miranda Montoya, Demócrito de Barros Miranda-Filho, Ulisses Montarroyos, Karel Moons, Maria Elisabeth Moreira, Jack Moye, Sarah Mulkey, José Muñoz-Medina, Johanna Munoz, Marisa Mussi-Pinhata, Silvia Negrini, Nivison Nery, Jurg Niederbacher Velásquez, Karin Nielsen, M. Kariuki Njenga, Trevor Noël, Mauricio Nogueira, Theresa Ochoa, Consuelo Oliveira, Eric Osoro, Ester Paiva Souto, Miguel Parra-Saavedra, Saulo Passos, Luiza Pela Rosado, Bernadete Perez Coêlho, Priscila Cardia Petra, Léo Pomar, Arnaldo Prata-Barbosa, Ingrid Rabe, Mitermayer G. Reis, Ana Maria Rivera Casas, Diana Rojas, Kerstin Daniela Rosenberger, Paola Mariela Saba Villarroel, Nuria Sanchez Clemente, Magda Sanz Cortes, Janet Sayers, Deolinda Scalabrin, Lavinia Schuler-Faccini, Stacey Schultz-Cherry, Aluisio Segurado, Kirstin Short, Priya Shreedhar, Antônio Silva, Ronaldo Silva, Vivian Avelino Silva, Isadora Cristina de Siqueira, Karen Sohan, Antoni Soriano-Arandes, Carmen Soria-Segarra, Paulo Sucasas da Costa, Adriana Tami, Jousilene Tavares, Maria Benamor Teixeira, Robert F. Terry, Tun-Linn Thein, Soe Soe Thwin, Frank Tobian, Vivian Torres Rodríguez, Isabel Trejos, Marilia Dalva Turchi, César Ugarte-Gil, Miguel Valencia-Prado, Alfonso Vallejos-Parás, Zilton Vasconselos, Ana Beatriz Gorini da Veiga, Carmen Viñuela-Benéitez, Manon Vouga, Yinghui Wei, Jamie Westcott, Marc-Alain Widdowson, Ricardo Ximenes, Carmen Zorrilla

“…Individual Participant Data Meta-Analysis (IPD-MA) offers an alternative approach to provide more precise and generalisable estimates through data harmonisation across studies, allowing for standardised definitions and exploration of heterogeneity. …”
Get full text

Extraction of Periodic Characteristics and Long-Term Stock Price Forecasting Using Non-Harmonic Analysis With Over 14 Years of NASDAQ Data Before and After COVID-19 by Yuki Kojima, Li Ma, Keisuke Nomoto, Masaya Hasegawa, Shigeki Hirobayashi

Get full text

Univariate Time Series Analysis of Short-Term Forecasting Horizons Using Artificial Neural Networks: The Case of Public Ambulance Emergency Preparedness by Tichaona W. Mapuwei, Oliver Bodhlyera, Henry Mwambi

Get full text

Integrating Fractional-Order Hopfield Neural Network with Differentiated Encryption: Achieving High-Performance Privacy Protection for Medical Images by Wei Feng, Keyuan Zhang, Jing Zhang, Xiangyu Zhao, Yao Chen, Bo Cai, Zhengguo Zhu, Heping Wen, Conghuan Ye

“…It features a large key space (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mn>383</mn></msup></semantics></math></inline-formula>), exceptional key sensitivity, extremely low ciphertext pixel correlations (<0.002), excellent ciphertext entropy values (>7.999 bits), uniform ciphertext pixel distributions, outstanding resistance to differential attacks (with average NPCR and UACI values of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>99.6096</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>33.4638</mn><mo>%</mo></mrow></semantics></math></inline-formula>, respectively), and remarkable robustness against data loss. …”
Get full text

Design of a dynamic trust management and defense decision system for shared vehicle data based on blockchain and deep reinforcement learning by Jinxiang Chen, Yan Li, Jiaxing Deng, Beicheng Qin, Chengcai He, Qiangsheng Huang, Jingchun Wu

“…A data analysis system integrating blockchain-based distributed trust management with deep reinforcement learning (DRL) is introduced to address these issues. …”
Get full text

Integrated Analysis Reveals Genetic Basis of Growth Curve Parameters in an F₂ Designed Pig Population Based on Genome and Transcriptome Data by Zhaoxuan Che, Jiakun Qiao, Fangjun Xu, Xinyun Li, Yunxia Zhao, Mengjin Zhu

“…Five growth parameters were estimated, including initial body weight <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mo>(</mo><mi>W</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>)</mo></mrow></semantics></math></inline-formula>, instantaneous growth rate per day (<i>L</i>), coefficient of relative growth or maturing index (<i>k</i>), body weight at inflection point <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mo>(</mo><mi>W</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></semantics></math></inline-formula>, and average growth rate (<i>GR</i>). These five parameters were subjected to a genome-wide association study, differential gene expression analysis, and weighted gene co-expression network analysis (WGCNA). …”
Get full text

Prediction of Landslide Displacement Based on GreyRelational Analysis and VMD-SES-BP Model by AN Bei, JIANG Yanan, ZENG Qifei

“…Aiming at the “stepped” landslide displacement in the Three Gorges area,this paper proposes a new landslide displacement time series prediction model,namely VMD-SES-BP prediction model by combining variational mode decomposition (VMD),second exponential smoothing (SES),and BP neural network (BPNN);conducts the VMD of the GPS monitoring displacement data of landslide at Baishuihe River of the Three Gorges through this model to obtain the trend component and other sub-sequence components;makes rolling predictions of trend components by the SES,determines the influencing factors of other displacement components of the landslide through gray relational analysis (GRA),and learns and predicts by considering it as the training sample of BPNN.Comparing the prediction results of each component with the true value,the average relative error of prediction is 0.78%,the mean square error is 3.14 cm,and the correlation coefficient is 0.986.The experimental results show that the model is well applicable to the prediction of “stepped” landslide displacement,with high prediction accuracy,which provides a certain reference value for landslide displacement prediction.…”
Get full text

Burden of Exacerbations in Patients Newly Initiating an Inhaled Regimen for COPD: A Claims Analysis by Sethi S, Wan ES, Tejwani V, Lamprey C, Aggarwal K, Dixon A, Pan Y, Siddharthan T

Get full text