Recent advances in the inverse design of silicon photonic devices and related platforms using deep generative models by Sun Jae Baek, Minhyeok Lee

“…Deep generative models offer additional capabilities by leveraging their ability to learn complex patterns and generate novel designs. This review examines various deep learning methodologies, including multi-layer perceptrons (MLP), convolutional neural networks (CNN), auto-encoders (AE), Generative Adversarial Networks (GAN), and reinforcement learning (RL) approaches. …”
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Potential multiple disease progression pathways in female patients with Alzheimer's disease inferred from transcriptome and epigenome data of the dorsolateral prefrontal cortex. by Kousei Honda, Akinori Awazu

“…An inference of adjacency networks among substages, evaluated via partition-based graph abstraction using the gene expression profiles of individuals, suggested the possibility of multiple typical disease progression pathways from NCI to different AD substages through various MCI substages. …”
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Dynamics of Acculturation and Enculturation of Languages to Socio-Economic Development in Nigeria: Implication for Poverty Reduction by Khadijah Ashiru Abdulrahman

“… Every group and society has cultures constituting frameworks for their lives and behavioral patterns. Cultural factors affect socio-economic behavior in at least four ways: its impact on organization and production, attitudes towards consumption and work, the ability to create and manage institutions, and the creation of social networks. …”
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Deep learning to promote health through sports and physical training by Xinyue Li

“…Recent advancements in deep learning and time-series analysis offer an opportunity to develop more personalized and accurate predictive models for assessing health improvement trends.MethodsThis study proposes a Health Improvement Score (HIS) prediction model based on a sequence-to-sequence deep learning architecture with Long Short-Term Memory (LSTM) networks and an attention mechanism. The model integrates heterogeneous time-series data, including physiological parameters (heart rate, blood oxygen levels, respiration rate), activity metrics (steps, distance, calories burned), sleep patterns, and body measurements. …”
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Multistage Training of Fuzzy Cognitive Maps to Predict Preeclampsia and Fetal Growth Restriction by William Hoyos, Rodrigo Garcia, Jose Aguilar

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Comparison of alternative approaches for analysing multi-level RNA-seq data. by Irina Mohorianu, Amanda Bretman, Damian T Smith, Emily K Fowler, Tamas Dalmay, Tracey Chapman

“…It enables the description of genome-wide patterns of expression and the identification of regulatory interactions and networks. …”
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Deep Hierarchical Representation from Classifying Logo-405 by Sujuan Hou, Jianwei Lin, Shangbo Zhou, Maoling Qin, Weikuan Jia, Yuanjie Zheng

“…We introduce a logo classification mechanism which combines a series of deep representations obtained by fine-tuning convolutional neural network (CNN) architectures and traditional pattern recognition algorithms. …”
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Mechanism of action of Xipayimaizibizi oral liquid on outlet obstruction-induced overactive bladder: An integrated study by Menglu Wang, Yang Yang, Yuhang Du, Jiamei Xie, Yige Zhao, Yongcheng An, Ziyi Shan, Shenyujun Wang, Meng Hao, Baosheng Zhao

“…The study observed the body weight, water intake, bladder and kidney indices (to evaluate their general status), urination behavior pattern (to observe frequency and urgency), and urodynamics (to measure bladder parameters). …”
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Study protocol for a multi-session randomized sham-controlled trial of PCC- and amygdala-targeted neurofeedback for the treatment of PTSD by Jonathan M. Lieberman, Ruth A. Lanius, Jean Théberge, Benicio N. Frey, Paul A. Frewen, Frank Scharnowski, David Steyrl, Tomas Ros, Maria Densmore, Emma Tassinari, Vangel Matic, Niki Hosseini-Kamkar, Sandhya Narikuzhy, Fardous Hosseiny, Rakesh Jetly, Andrew A. Nicholson

“…Neural outcomes will also be examined, focusing on brain activation and connectivity patterns. Additionally, qualitative interviews and actigraphy will assess participants’ subjective experiences and track sleep and physical activity patterns. …”
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Calibration of Low-cost Gas Sensors for Air Quality Monitoring by Dimitris Margaritis, Christos Keramydas, Ioannis Papachristos, Dimitra Lambropoulou

“…Abstract Mobile monitoring devices equipped with low-cost gas sensors in fixed stations are an emerging solution to enhance the spatial coverage of air quality monitoring networks. We estimated the measurement accuracy of two AQMesh devices, evaluated their agreement, and examined the related calibration characteristics. …”
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Emerging research themes in ferroptosis research for non-small cell lung cancer: a bibliometric and visualized analysis by Wenbo Zhang, Wenbo Zhang, Wenbo Zhang, Wenbo Zhang, Jianwei Gu, Jianwei Gu, Jianwei Gu, Jianwei Gu, Yong Chen, Guolu Jiang, Diego Gonzalez-Rivas, Diego Gonzalez-Rivas, Minjie Ma, Chang Chen, Chang Chen, Chang Chen

“…Bibliometric tools including VOSviewer, CiteSpace, and GraphPad Prism were used to analyze publication trends, citation patterns, collaborative networks, and research hotspots. …”
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Rethinking Inequality: The Complex Dynamics Beyond the Kuznets Curve by Sarthak Pattnaik, Maryan Rizinski, Eugene Pinsky

“…Forecasts using ARIMA and neural networks indicate continued fluctuations in inequality through 2030, with the U.S. and Germany showing upward trends while France and the UK demonstrate relative stability. …”
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Sentiment Analysis of ChatGPT on Indonesian Text using Hybrid CNN and Bi-LSTM by Vincentius Riandaru Prasetyo, Mohammad Farid Naufal, Kevin Wijaya

“…This study explores sentiment analysis on Indonesian text using a hybrid deep learning approach that combines Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM). …”
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Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies by MD Shahriar Mahmud Bhuiyan, MD AL Rafi, Gourab Nicholas Rodrigues, MD Nazmul Hossain Mir, Adit Ishraq, M.F. Mridha, Jungpil Shin

“…We analyze and synthesize the key DL architectures, such as recurrent neural networks (RNN), long short-term memory (LSTM), convolutional neural networks (CNN), and hybrid models, to evaluate their performance in predicting stock prices, volatility, and market trends. …”
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Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor... by Alkinoos Athanasiou, Chrysa Lithari, Konstantina Kalogianni, Manousos A. Klados, Panagiotis D. Bamidis

“…The study of functional connectivity networks (FCNs) aims at successfully modeling the dynamics of information flow between cortical areas. …”
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The Effect of Different Altitude Conditions on the Quality Characteristics of Turnips (<i>Brassica rapa</i>) by Peng Jin, Min Liu, Meirong Chen, Weiwai Zhao, Xuemin Zhang, Tao Mou, Wang A., Zongsong Wang, Xingliang Xu, Lili Jiang

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Smart E-Tongue Based on Polypyrrole Sensor Array as Tool for Rapid Analysis of Coffees from Different Varieties by Alvaro Arrieta Almario, Oriana Palma Calabokis, Eisa Arrieta Barrera

“…Traditional sensory evaluations by expert tasters and chemical analysis methods, although effective, are time-consuming, costly, and require skilled personnel. …”
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Cognitive difference text classification in online knowledge collaboration based on SA-BiLSTM hybrid model by Fengjun Liu, Na Zhao, Guoqing Zhu

“…However, accurate extraction of semantic features and contextual patterns from such texts remains challenging in multi-dimensional discourse contexts. …”
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A GPT-Based Approach for Cyber Threat Assessment by Fahim Sufi

“…It utilizes a hybrid methodology combining spectral residual transformation and Convolutional Neural Networks (CNNs) to identify anomalies in time-series cyber event data, alongside regression models for evaluating the significant factors associated with cyber events. …”
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Association Mining for Operation and Maintenance Safety Risks of EMUs Based on Unstructured Event Data by Haixing Wang, Longtao Guo, Hong Yin, Yuefeng Huang, Shimeng Li

“…Constructing appropriate safety feature quantities by fully and effectively utilizing this data is a prerequisite for establishing a safety prevention and control network for EMUs. This paper proposes a model that matches risks in the operation and maintenance safety of EMUs with associated unsafe events, utilizing regular expression and pattern-matching technologies. …”
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