DEBEcoMod: A dynamic energy budget R tool to predict life-history traits of marine organisms across time and space by A. Giacoletti, M. Bosch-Belmar, G. Di Bona, M.C. Mangano, B. Stechele, G. Sarà

“…It utilises parameters from the AddMyPet database for various species and environmental time series to simulate the past, present, and future performance of organisms. …”
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A Hybrid LMD–ARIMA–Machine Learning Framework for Enhanced Forecasting of Financial Time Series: Evidence from the NASDAQ Composite Index by Jawaria Nasir, Hasnain Iftikhar, Muhammad Aamir, Hasnain Iftikhar, Paulo Canas Rodrigues, Mohd Ziaur Rehman

“…This study proposes a novel hybrid forecasting approach designed explicitly for long-horizon financial time series. It incorporates LMD (Local Mean Decomposition), SD (Signal Decomposition), and sophisticated machine learning methods. …”
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A Full-Life-Cycle Modeling Framework for Cropland Abandonment Detection Based on Dense Time Series of Landsat-Derived Vegetation and Soil Fractions by Qiangqiang Sun, Zhijun You, Ping Zhang, Hao Wu, Zhonghai Yu, Lu Wang

“…The parameters of the optimization model (fitting type, change magnitude, start timing, and change duration) are subsequently integrated to develop a rule-based hierarchical identification scheme for cropland abandonment based on these complex scenarios. …”
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Finite-Time Synchronization and Practical Synchronization for Caputo Fractional-Order Fuzzy Cellular Neural Networks with Transmission Delays and Uncertainties via Information Feed... by Hongguang Fan, Hui Wen, Kaibo Shi, Anran Zhou

“…Namely, changing one of the feedback terms from positive to negative can cause PFT synchronization to switch to FT synchronization via adjusted control parameters, making our control methods applicable to different scenarios. The settling time depends explicitly on feedback coefficients, initial conditions, and fractional order.…”
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Noise Pollution Prediction in a Densely Populated City Using a Spatio-Temporal Deep Learning Approach by Marc Semper, Manuel Curado, Jose Luis Oliver, Jose F. Vicent

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Artificial intelligence of things for sustainable smart city brain and digital twin systems: Pioneering Environmental synergies between real-time management and predictive planning by Simon Elias Bibri, Jeffrey Huang

“…To the best of our knowledge, research on the explicit fusion of UB's real-time analytics—enabled through stream processing—with UDT's predictive analytics—driven by simulation modeling—is scant, if not absent. …”
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Ball-Flight Viewing Duration and Estimates of Passing Height in Baseball by Emily Benson, Andrew J. Toole, Nick Fogt

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Robust super-twisting algorithm-based single-phase sliding mode frequency controller in power systems integrating wind turbines and energy storage systems by Van Van Huynh, Shahalam Naqvi, Bang Le-Huy Nguyen, Anh-Tuan Tran, Jae Woong Shim, Ton Duc Do

“…Abstract Frequency regulation in multi-area power systems (MPSs) faces increasing challenges due to the integration of renewable energy sources, such as wind power, and the dynamic behavior of energy storage systems (ESSs). …”
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Linearization (in)stabilities and crossed products by Julian De Vuyst, Stefan Eccles, Philipp A. Höhn, Josh Kirklin

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The socioeconomic dimension of forest therapy: A contribution to human well-being and sustainable forest management by Carsten Mann, Mónica Hernández-Morcillo, Harumi Ikei, Yoshifumi Miyazaki

“…For forest therapy to become part of the forestry portfolio and a medical alternative, we recommend: • Interdisciplinary research approaches and new actor alliances that link societal demands for forest therapy with insights from forest management and medical health research, • Transdisciplinary research and multi-actor approaches to link insights from forest and medical research with practitioners’ skills for forest management, service design, and communication, • To identify trade-offs and conflict potentials with forest therapy, for example in relation to timber production or questions of insurance in case of injuries by falling branches etc., that allow to develop integrated and sustainable solutions, • Policy backup and economic support for forest managers and owners to compensate for their efforts to manage their forests for therapeutic purposes • Recognition of forest therapy as an explicit part of the forestry portfolio and an alternative medical offer for clinical treatments.…”
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Cosmological correlators with double massive exchanges: bootstrap equation and phenomenology by Shuntaro Aoki, Lucas Pinol, Fumiya Sano, Masahide Yamaguchi, Yuhang Zhu

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Machine-Learning-Based Integrated Mining Big Data and Multi-Dimensional Ore-Forming Prediction: A Case Study of Yanshan Iron Mine, Hebei, China by Yuhao Chen, Gongwen Wang, Nini Mou, Leilei Huang, Rong Mei, Mingyuan Zhang

“…Combined with LiDAR image elevation data, a real-time three-dimensional surface mineral monitoring model for the mining area was built. (4) The Bagged Positive Label Unlabeled Learning (BPUL) method was adopted to integrate five evidence maps—carbonate alteration, chloritization, mixed rockization, fault zones, and magnetic anomalies—to conduct three-dimensional mineralization prediction analysis for the mining area. …”
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Survey on Image-Based Vehicle Detection Methods by Mortda A. A. Adam, Jules R. Tapamo

“…Vehicle detection is essential for real-world applications such as road surveillance, intelligent transportation systems, and autonomous driving, where high accuracy and real-time performance are critical. However, achieving robust detection remains challenging due to scene complexity, occlusion, scale variation, and varying lighting conditions. …”
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Observer-based finite-time event-triggered secure control for fuzzy implicit systems against deception attacks: A single-link flexible joint robotic application by M. Kchaou, L. Ladhar, M. Omri, R. Abbassi, H. Jerbi

“…This study significantly advances the security and resilience of cyber-physical systems by presenting a novel finite-time control strategy tailored for discrete-time fuzzy implicit systems in the context of sensor and actuator attacks. …”
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Multi-objective optimization of hybrid microgrid for energy trilemma goals using slime mould algorithm by Alok Kumar Shrivastav, Soham Dutta

“…The superior performance of SMA is attributed to its dynamic balance between exploration and exploitation, leading to faster convergence and enhanced computational efficiency. The novel integration of EV batteries as DERs, with explicit modeling of bidirectional V2G operations, distinguishes this work from previous studies that considered only unidirectional or static EV participation. …”
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Distributionally robust hybrid energy management in smart mining using process-coupled primal-dual mirror descent by Dawei Wang, Yifei Li, Cheng Gong, Tianle Li, Fang Wang, Shanna Luo, Jun Li

“…The framework addresses three major challenges: (i) multi-source uncertainty propagation, (ii) cross-process energy coupling, and (iii) time-varying, safety-critical operational constraints. …”
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Retrospective trend analysis of biocides in suspended particulate matter of major German rivers by Georg Dierkes, Susanne Schmidt, Christiane Meier, Korinna Ziegler, Jan Koschorreck, Arne Wick

“…Moreover, time trends could be affected by remobilization of legacy contamination from contaminated sites. …”
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Considering temporality for SES analysis with reflections from urban food forests and orchards by Anastasia Luise Gramatakos, Andrea Rawluk, Catherine Phillips

“…To consider how diverse temporal experiences might be better integrated in SES, we sketch how time and temporality have been addressed in SES research and in the social sciences and humanities. …”
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Thermo-rheologically complex polymers: multiaxial constitutive modeling, numerical implementation and experimental validation by Paolo Iaccarino, Ernesto Di Maio, Andrei Constantinescu, Ferdinando Auricchio

“…The frequency-temperature superposition principle is applied to the experimental data using horizontal and vertical shift functions, explicitly integrated into the constitutive model framework. …”
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Reductionist modeling of calcium-dependent dynamics in recurrent neural networks by Mustafa Zeki, Tamer Dag

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