Hermeneutics and its New Tendencies: to the Question of Aesthetic Paradigm Change by N. F. Shcherbak

“…The work examines the main vector of development of contemporary literary and hermeneutics studies. …”
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Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors by Céline Patte, Roxane M. Pommier, Anthony Ferrari, Felicia Fei-Lei Chung, Maria Ouzounova, Pauline Moullé, Mathieu Richaud, Rita Khoueiry, Maëva Hervieu, Silvia Breusa, Marion Allio, Nicolas Rama, Laura Gérard, Valérie Hervieu, Gilles Poncet, Tanguy Fenouil, Vincent Cahais, Anne-Sophie Sertier, Anne Boland, Delphine Bacq-Daian, Benjamin Ducarouge, Julien C. Marie, Jean-François Deleuze, Alain Viari, Jean-Yves Scoazec, Colette Roche, Patrick Mehlen, Thomas Walter, Benjamin Gibert

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Research on hybrid strategy Particle Swarm Optimization algorithm and its applications by Jicheng Yao, Xiaonan Luo, Fang Li, Ji Li, Jundi Dou, Hongtai Luo

“…HSPSO is evaluated using CEC-2005 and CEC-2014 benchmark functions, demonstrating superior performance over standard PSO, Dynamic Adaptive Inertia Weight PSO (DAIW-PSO), Hummingbird Flight patterns PSO (HBF-PSO), Butterfly Optimization Algorithm (BOA), Ant Colony Optimization (ACO), and Firefly Algorithm (FA). …”
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Unraveling Cyberbullying Dynamis: A Computational Framework Empowered by Artificial Intelligence by Liliana Ibeth Barbosa-Santillán, Bertha Patricia Guzman-Velazquez, Ma. Teresa Orozco-Aguilera, Leticia Flores-Pulido

“…By integrating artificial intelligence techniques with image analysis, our model detects visual patterns associated with violent threats, creating safer digital environments. …”
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Mapping gender networks of smartphone addiction and academic procrastination: a network analysis study by Lu Song, Zhilin Liu, Yujia Yang, Shuangshuang Yuan

“…The findings reveal the complexity of gender differences in behavioral patterns and psychological mechanisms, moving beyond the limitations of previous research that primarily focused on mean-level differences. …”
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Spatiotemporal Decoupling Between Intensive Policy Interventions and Natural Gradual Recovery in Human–Land Systems During Transition Periods: A Remote Sensing Analysis by Xiao Xie, Chunxiao Zhang, Haojie Kang, Chao E, Jingzhong Li, Wanxia Ren

“…Addressing the ecological vulnerability and challenges of degradation-restoration dynamics in transitional human–earth systems represented by the Kubuqi Desert region, this study leverages the advantages of multisource remote sensing imagery in multifactor, annual cyclical, long-term, and spatially heterogeneous complex surface feature analysis. By integrating discrete pixel characteristics with continuous change processes in landscape pattern dynamics, we developed a remote sensing ecological index cube framework. …”
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Comparative Study of Rheological Properties of Gels and Creams on Different Carrier Bases by U. V. Nogaeva, A. A. Naumova, A. G. Novinkov, E. V. Flisyuk, M. A. Burakova, A. N. Shikov, O. N. Abrosimova

“…Study of the main rheological parameters of the developed gels and creams on various carrier bases.Materials and methods. …”
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Feasibility of Using Wavelet Analysis and Machine Learning Method in Technical Diagnosis of Car Seats by Cezary BARTMAŃSKI, Alicja BRAMORSKA

“…A method of feature extraction (diagnostic symptoms) using wavelet decomposition of acoustic signals was developed. …”
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Ангари як архітектурний елемент авіаційних музейних комплексів by Yuriy Doroshenko, Alexander Khlyupin, Bohdana Nikolchuk

“…This article explores the various uses of civil aircraft in museum hangars, ranging from flying for entertainment and exploring the world to distant communities. The patterns of design of this type of buildings are characterized, the specifics of their planning are analyzed. …”
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Hybrid Android Malware Detection and Classification Using Deep Neural Networks by Muhammad Umar Rashid, Shahnawaz Qureshi, Abdullah Abid, Saad Said Alqahtany, Ali Alqazzaz, Mahmood ul Hassan, Mana Saleh Al Reshan, Asadullah Shaikh

“…Abstract This paper presents a deep learning-based framework for Android malware detection that addresses critical limitations in existing methods, particularly in handling obfuscation and scalability under rapid mobile app development cycles. Unlike prior approaches, the proposed system integrates a multi-dimensional analysis of Android permissions, intents, and API calls, enabling robust feature extraction even under reverse engineering constraints. …”
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Text-mining metadata: What can titles tell us of the history of modern and contemporary art? by Mike Bowman

“…The use of topic modelling, parts-of-speech tagging and word counting allows me to identify large-scale and long-run patterns in the language used in the titles of those artworks. …”
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Improving internet of vehicles research: A systematic preprocessing framework for the VeReMi datasetZenodo by Aparup Roy, Debotosh Bhattacharjee, Ondrej Krejcar

“…This preprocessing pipeline effectively maintains data integrity and preserves the representativeness of malicious patterns. The optimized dataset is well-suited for ITS and IoV applications, such as anomaly detection and network security, underscoring the crucial role of preprocessing in overcoming real-world constraints and enhancing model performance.…”
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The challenge of a late diagnosis of Autism Spectrum Disorder: co-occurring trajectories and camouflage tendencies. a case report of a young Autistic female with Avoidant Restricti... by Sara Passarini, Sara Passarini, Silvia Guerrera, Maria Picilli, Maria Picilli, Elisa Fucà, Laura Casula, Deny Menghini, Sabine Pirchio, Valeria Zanna, Giovanni Valeri, Stefano Vicari, Stefano Vicari

“…Additionally, it underscores the importance of improving tailored evaluation, combined treatment plans, with both cognitive-behavioral therapy and drugs, and monitoring the evolving patterns of Autistic manifestations and associated psychiatric co-occurrences.…”
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Spatiotemporal regulation of alginate sub-structures at multiple scales revealed by monoclonal antibodies by Catherine T. Jones, Cassie Bakshani, Ieva Lelenaite, Jozef Mravec, Stjepan Krešimir Kračun, Jeff Pearson, Mathew D. Wilcox, Kevin Hardouin, Sonia Kridi, Cécile Hervé, William G.T. Willats

“…Alginates are comprised of D-mannuronic acid (M) and L-guluronic acid (G) and the ratios and distribution patterns of M and G profoundly impact their physiological and rheological properties. …”
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Ornamental Plant Growth in Different Culture Conditions and Fluoride and Chloride Removals with Constructed Wetlands by José Luis Marín-Muñiz, María E. Hernández, Sergio Zamora Castro

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A Study on the Spatiotemporal Heterogeneity and Driving Forces of Ecological Resilience in the Economic Belt on the Northern Slope of the Tianshan Mountains by Keqi Li, Qingwu Yan, Zihao Wu, Guie Li, Minghao Yi, Xiaosong Ma

“…The overall distribution pattern exhibited a spatial feature of south higher, north lower, where the southern region displayed a clear high-high clustering characteristic, exerting a positive and radiating influence on surrounding areas. (2) The main driving factors of the spatial heterogeneity are DEM, precipitation, NPP, GDP, and PM2.5. …”
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Preparation of Porous F-WO3/TiO2 Films with Visible-Light Photocatalytic Activity by Microarc Oxidation by Chung-Wei Yeh, Kee-Rong Wu, Chung-Hsuang Hung, Hao-Cheng Chang, Chuan-Jen Hsu

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Advancement of a diagnostic prediction model for spatiotemporal calibration of earth observation data: a case study on projecting forest net primary production in the mid-latitude... by Eunbeen Park, Hyun-Woo Jo, Gregory Scott Biging, Jong Ahn Chun, Seong Woo Jeon, Yowhan Son, Florian Kraxner, Woo-Kyun Lee

“…Developing a precise and interpretable spatiotemporal model is need for establishing evidence-based adaptation strategies on climate change-driven disasters. …”
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Characteristics, Outcomes and Mortality Risk Factors of Pediatric In-Hospital Cardiac Arrest in Western China: A Retrospective Study Using Utstein Style by Jiaoyang Cao, Jing Song, Baoju Shan, Changxin Zhu, Liping Tan

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Unsupervised Binary Classifier-Based Object Detection Algorithm with Integrated Background Subtraction Suitable for Use with Aerial Imagery by Gabija Veličkaitė, Ignas Daugėla, Ivan Suzdalev

“…Unlike conventional supervised models, SARGAS is trained in a partially unsupervised manner, learning to recognize feature patterns without requiring labeled data. The algorithm achieved a recall of 93%, demonstrating strong detection capability even under challenging conditions. …”
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