Specificity, propagation, and memory of pericentric heterochromatin by Katharina Müller‐Ott, Fabian Erdel, Anna Matveeva, Jan‐Philipp Mallm, Anne Rademacher, Matthias Hahn, Caroline Bauer, Qin Zhang, Sabine Kaltofen, Gunnar Schotta, Thomas Höfer, Karsten Rippe

“…Abstract The cell establishes heritable patterns of active and silenced chromatin via interacting factors that set, remove, and read epigenetic marks. …”
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A Novel Hypoxia-Immune Signature for Gastric Cancer Prognosis and Immunotherapy: Insights from Bulk and Single-Cell RNA-Seq by Mai Hanh Nguyen, Hoang Dang Khoa Ta, Doan Phuong Quy Nguyen, Viet Huan Le, Nguyen Quoc Khanh Le

“…Single-cell RNA-seq data from the TISCH database were used to explore gene expression patterns across cell types. <b>Results</b>: Five genes (<i>TGFB3</i>, <i>INHA</i>, <i>SERPINE1</i>, <i>GPC3</i>, <i>SRPX</i>) were identified. …”
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Efficient and Accurate Zero-Day Electricity Theft Detection from Smart Meter Sensor Data Using Prototype and Ensemble Learning by Alyaman H. Massarani, Mahmoud M. Badr, Mohamed Baza, Hani Alshahrani, Ali Alshehri

“…Smart meter data is compressed using Principal Component Analysis (PCA) and K-means clustering to extract representative consumption patterns, i.e., prototypes, achieving a 92% reduction in dataset size while preserving critical anomaly-relevant features. …”
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Identity negotiation on the LIHKG platform: a grounded theory study of Mainland Chinese immigrants’ adaptation to Hong Kong society by Lingxiao Zhang, Tao Shen

“…Results reveal a dynamic identity negotiation process characterized by four patterns (integrative, confrontational, collaborative, and avoidance) that immigrants strategically employ across different contexts. …”
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Impact of Situation Awareness Variations on Multimodal Physiological Responses in High-Speed Train Driving by Wenli Dong, Weining Fang, Hanzhao Qiu, Haifeng Bao

“…Results: The results of statistical analysis confirmed the effectiveness of this paradigm in inducing SA level changes, revealing significant relationships between SA levels and key physiological metrics, including eye movement patterns, ECG features (e.g., heart rate variability), and EEG power spectral density across theta, alpha, and beta bands. …”
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System Approach to the Combined Use of Large Language Models and Classical Models in Foresight Tasks by Володимир Савастьянов, Михайло Столяр

“…The main result of the proceeding is that the patterns that reveal LLMs under certain settings can also be identified by classical models. …”
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USING THE ANYLOGIC ENVIRONMENT FOR MODELING AND ANALYSIS OF THE INFORMATION SECURITY AUDIT PROCESS by Kamilla M. Khuranova, Igor D. Kologorov, Sergey A. Reznichenko, Leonid N. Kessarinskiy

“…AnyLogic's visualization tools helped pinpoint process bottlenecks. The developed model features adaptability, allowing parameter adjustments to align with organizational specifics. …”
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A step forward in enhancing the health-promoting properties of whole tomato as a functional food to lower the impact of non-communicable diseases by Pier Giorgio Natali, Pier Giorgio Natali, Mauro Piantelli, Alessandra Sottini, Margherita Eufemi, Cristina Banfi, Luisa Imberti

“…Although WTFS may be susceptible to further improvements and clinical scrutiny, its composition embodies the features of advanced functional foods to ease adherence to dietary patterns, that is, the Mediterranean diet, aimed at contrasting and mitigating the low-grade inflammation, thus being interceptive or preventive of non-communicable diseases.…”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…By examining the timing between packets and other statistical features, we detected patterns of malicious activity, allowing early and effective DoS threat mitigation. …”
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Analysis and Optimization of Customer Lifetime Value Prediction using Machine Learning and Deep Learning Models by RFM Techniques by Leila Taherkhani, Amir Daneshvar, Hossein Amoozad Khalili, MohammadReza Sanaei

“…This study analyse the prediction of Customer Lifetime Value (CLV) using machine learning models—Linear Regression, Random Forest, and LightGBM—trained on features derived from hotel website interactions and booking records. …”
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High-intensity zones in dogs with lumbosacral intervertebral disc degeneration: insights from MRI and histopathological findings by S. Amir Kamali, Michelle Teunissen, Dirk Hendrik Nicolaas van den Broek, Elisabeth M. Burgers, Guy C. M. Grinwis, Keita Ito, Marianna A. Tryfonidou, Björn P. Meij

“…T2-weighted (T2W) and T1-weighted (T1W) sagittal MRI scans were evaluated using a classification system developed in human medicine to analyze HIZ characteristics. …”
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Perforated imprinting on high moisture meat analogue confers long range mechanical anisotropy resembling meat cuts by Xuanming Lou, Jiahao Wang, Leng Gek Kwang, Hanzhang Zhou, Francesca Yi Teng Ong, Shengyong Ng, Hanry Yu

“…By imprinting 1 mm thick HMMA sheets with perforated patterns (optimized by AI), we observed up to 5 × more anisotropic separation of fibrous structures in a one-dimensional pulling LMA analysis, to match the fibrousness of the cooked chicken breast, duck breast, pork loin and beef loin. …”
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RotJoint-Based Action Analyzer: A Robust Pose Comparison Pipeline by Guo Gan, Guang Yang, Zhengrong Liu, Ruiyan Xia, Zhenqing Zhu, Yuke Qiu, Hong Zhou, Yangwei Ying

“…Human pose comparison involves measuring the similarities in body postures between individuals to understand movement patterns and interactions, yet existing methods are often insufficiently robust and flexible. …”
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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

“…Abstract Model optimization is a problem of great concern and challenge for developing an image classification model. In image classification, selecting the appropriate hyperparameters can substantially boost the model’s ability to learn intricate patterns and features from complex image data. …”
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Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait by Brendan West, Devin O’Connor, Matthew Parno, Max Krackow, Christopher Polashenski

“…The results indicate that the bonded DEM model is capable of qualitatively capturing the dynamic sea ice patterns through constrictions such as ice bridges, arch kinematic features, and lead formation. …”
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Extreme high temperatures and heatwave events across Europe in 2023 by Yuqing Sun, Gensuo Jia, Xiyan Xu

“…However, there is a lack of quantitative analysis of spatial and temporal features of such record high heatwaves. Here, we investigated the spatial patterns and seasonal evolution of heatwaves over Europe in 2023. …”
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Rainfall-induced Landslide Susceptibility Prediction Considering Spatial Heterogeneity by ZHANG Xingfu, JIANG Yuanjun, ABI Erdi

“…Inputs such as terrain features, soil characteristics, vegetation indices, and rainfall patterns were utilized to train and evaluate the models. …”
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Machine Learning Model Coupled with Graphical User Interface for Predicting Mechanical Properties of Flax Fiber by T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale, L. K. Nayak, D. B. Shakyawar, Indran Suyambulingam, P. Senthamaraikannan, R. Kumar

“…In this study, a total of 432 patterns of input and output parameters obtained from laboratory experiments were used to develop machine learning algorithms (Random forest, support vector, and XGBoost). …”
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Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning by Mohammed Assiri, Mahmoud M. Selim

“…To accomplish that, the GRHIP-EDLIBWO method initially performs image preprocessing using a Sobel filter (SF) to enhance edge detection and extract critical gesture features. For the feature extraction process, the squeeze-and-excitation capsule network (SE-CapsNet) effectively captures spatial hierarchies and complex relationships within gesture patterns. …”
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ID3RSNet: cross-subject driver drowsiness detection from raw single-channel EEG with an interpretable residual shrinkage network by Xiao Feng, Xiao Feng, Zhongyuan Guo, Zhongyuan Guo, Sam Kwong

“…To address these issues, we propose a novel interpretable residual shrinkage network, namely, ID3RSNet, for cross-subject driver drowsiness detection using single-channel EEG signals. First, a base feature extractor is employed to extract the essential features of EEG frequencies; to enhance the discriminative feature learning ability, the residual shrinkage building unit with attention mechanism is adopted to perform adaptive feature recalibration and soft threshold denoising inside the residual network is further applied to achieve automatic feature extraction. …”
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