Correlations and functional connections in a population of grid cells. by Benjamin Dunn, Maria Mørreaunet, Yasser Roudi

“…Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern.…”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…By leveraging Explainable AI’s interpretability to analyze the features, the model elucidates the reasoning behind its classifications leading to a comprehension of hidden patterns associated with suicidal ideations. Our system is compared to cutting-edge methods on several social media datasets using experimental evaluations, demonstrating that it is superior, since it detects suicidal content more accurately than others. …”
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Robust fault detection and classification in power transmission lines via ensemble machine learning models by Tahir Anwar, Chaoxu Mu, Muhammad Zain Yousaf, Wajid Khan, Saqib Khalid, Ahmad O. Hourani, Ievgen Zaitsev

“…This research introduces a novel approach for fault detection and classification by analyzing voltage and current patterns across transmission line phases. Leveraging a comprehensive dataset of diverse fault scenarios, various machine learning algorithms—including Random Forest (RF), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) networks—are evaluated. …”
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Development of wireless electronic nose and using of remote monitoring by HU Ying, WANG Jun

“…The software introduces the structure of Z-Stack plate on the transplant, CC2530 data acquisition, AD (Analog to digital) conversion process and the development of the applications for the eight channel data acquisition and transmission, to ensure the accuracy of data transmission.Secondly, the communication quality of the system was evaluated and applied to detect the plum fruits. Plum samples were tested in 5 days (twice per day) at a certain temperature and humidity, using principal component analysis which can probably show the plum change trend, and the use of BP neural network can accurately determine the growth stage of each sample. …”
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Quantification of Subsurface Hydrological Connectivity Using Wavelet Coherence Analysis by REN Ruijie, Fan Bihang, ZHANG Yaling, WANG Erqing, YANG Ruxin, HAN Xiaole, LIU Jintao, GUO Li

“…Soil moisture sensor networks were installed within three genetic soil horizons: Horizon A (topsoil), Horizon B (subsoil/accumulation layer), and Horizon C (parent material/saprolite). …”
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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

“…Our approach systematically evaluates and compares the predictive performance of Artificial Neural Networks (ANNs) and Random Forests (RFs) for energy demand forecasting, leveraging each algorithm’s unique characteristics to assess their suitability for this application. …”
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A Natural Language Processing Model for Predicting Five-Star Ratings of Video Games on Short-Text Reviews by Piyush Jaiswal, Hardik Setia, Pranshu Raghuwanshi, Princy Randhawa

“…The growing number of people who have access to the internet, the widespread use of smartphones, and the introduction of high-bandwidth networks such as 5G have all contributed to an increase in the demand for gaming around the world. …”
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Adaptive Energy Management for MATTER-Enabled Smart Homes by Navodit Bhardwaj, Pallavi Joshi

“…For anomaly detection, a hybrid multi-stage approach incorporating Long Short-Term Memory (LSTM) networks, One-Class SVMs (OCSVM), and autoencoders delivers a precision of 0.97 and recall of 0.95 in identifying abnormal consumption patterns and potential cybersecurity threats. …”
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Cardioepigenetics in action: aerobic exercise-induced modulation of miRNAs, lncRNAs, and chromatin remodeling in cardiovascular disease by Shoudu Yuan, Qi Ye, Ran Qin

“…Emerging evidence highlights the central role of epigenetic modifications and non-coding RNAs including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in the regulation of gene expression networks underlying cardiovascular homeostasis and disease. …”
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Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

“…The models’ performances were evaluated using accuracy, precision, recall and F1-score and NN presented the best performance overall achieving an F1-score of 85% for the correlated feature pairs (CF) and 75% for the direct feature pairs. …”
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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…The research utilizes a dataset consisting of 1,428 training samples and 573 testing samples, evaluated using a 10-fold cross-validation technique. …”
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Modeling the Impact of Climate Change on Soil Health Using Predictive Analytics by Alsalami Zaid, Mandapati A. H. A. Hussein, Sundari Venkata Rama

“…To answer the problem of soil degradation under climate stress, this research develops and evaluates predictive models capable of predicting soil health indicators. …”
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Pose estimation for health data analysis: advancing AI in neuroscience and psychology by Juan Yu, Daoyu Zhu

“…The framework integrates multi-modal data sources and applies temporal graph convolutional networks, ensuring both scalability and adaptability to diverse tasks. …”
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ADPO: Adaptive DRAM Controller for Performance Optimization by Zhuorui Liu, Yan Li, Xiaoyang Zeng

“…Emerging applications like deep neural networks require high off-chip memory bandwidth and low dynamic loaded Double Data Rate SDRAM (DDR) latency. …”
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Neuromodulation Interventions for Language Deficits in Alzheimer’s Disease: Update on Current Practice and Future Developments by Fei Chen, Yuyan Nie, Chen Kuang

“…Key indicators such as publication trends, citation patterns, collaboration networks, and research themes were examined to map the intellectual landscape of this field. …”
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Automated Deadlift Techniques Assessment and Classification Using Deep Learning by Wegar Lien Grymyr, Isah A. Lawal

“…We adapted the MoveNet model to track keypoints on the lifter’s joints, which effectively represented their motion patterns. These keypoints not only served as visualization aids in the training of Convolutional Neural Networks (CNNs) but also acted as the primary features for Long Short-Term Memory (LSTM) models, both of which we employed to classify the various deadlift techniques. …”
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A bibliometric analysis of six decades of camel research in North Africa: Trends, collaboration, and emerging themes by Razan Naji, Mahmoud Kandeel, Maryam Mahmoud

“…Bibliometrix and VOSviewer were used to visualize co-authorship networks, citation patterns, and keyword trends. Results: The research output has increased dramatically since the mid-2000s, with a peak in publications between 2018 and 2020. …”
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Metabolome Profiling and Predictive Modeling of Dark Green Leaf Trait in Bunching Onion Varieties by Tetsuya Nakajima, Mari Kobayashi, Masato Fuji, Kouei Fujii, Mostafa Abdelrahman, Yasumasa Matsuoka, Jun’ichi Mano, Muneo Sato, Masami Yokota Hirai, Naoki Yamauchi, Masayoshi Shigyo

“…This trait is regulated by a complex network of pigment interactions, which not only determine coloration but also serve as critical indicators of plant growth dynamics and stress responses. …”
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Mapping the Landscape of Digital Government Transformation: A Bibliometric Analysis by Younus Muhammad, Purnomo Eko Priyo, Nurmandi Achmad, Mutiarin Dyah, Manaf Halimah Abdul, Prianto Andi Luhur, Sohsan Imron, Irawan Bambang, Salahudin Salahudin, Akbar Idil, Khairunnisa Tiara

“…The literature review makes use of citation analysis to detect patterns in the relationship between scientific papers, whereas the bibliometric analysis employs quantitative tools to evaluate published physical units. …”
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Targeting immune microenvironment in cervical cancer: current research and advances by Zhen Zhang, Miao Liu, Yu An, Chongqing Gao, Tao Wang, Zhi Zhang, Guixiang Zhang, Shuo Li, Wei Li, Mengjia Li, Gangcheng Wang

“…This review comprehensively examines the cellular and molecular components of the tumor immune microenvironment (TIME) in cervical cancer, encompassing patterns of immune cell infiltration (T cells, B cells, NK cells, DCs, TAMs), immune checkpoint molecules, and cytokine/chemokine networks. …”
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