Blockchain and smart contracts for secure and transparent salary grade structure management by Ebenezer Essel Mensah, Richard Kwasi Ahiable, Jonah Nud-Worgbah, Kofi Sarpong Adu-Manu

“…Unlike existing blockchain payroll applications, this work explicitly targets the salary grade adjustment processes within state institutions, providing a real-world prototype validated with actual agency data. …”
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Forgetting phenomena in the Iowa Gambling Task: a new computational model among diverse participants by Tiancheng Yang, Chenghan Xie, Xuehe Wang

“…IntroductionThe Iowa Gambling Task (IGT) is a widely used paradigm for evaluating decision-making and executive functioning, yet existing computational models seldom account for the phenomenon of forgetting, which is critical to understanding dynamic decision processes.MethodsWe developed the Exploitation and Exploration with Forgetting (EEF) model, which integrates a dynamic forgetting parameter (λ) and participants' first-choice priors into a unified reinforcement-learning framework. …”
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More sustainable choices in the workplace: a systematic review of nudge theory applications by Giulia De Paolis, Lorenza Tiberio, Federica Caffaro

“…It emphasizes the importance of integrating behavioral insights into organizational structures and processes to foster environmentally responsible behaviors at work and beyond.…”
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A psychometric evaluation of an item bank for an English reading comprehension tool using Rasch analysis by Louis Wai Keung Yim, Che Yee Lye, Poh Wee Koh

“…Four main comprehension processes outlined in PIRLS were assessed: focusing on and retrieving explicitly stated information, making straightforward inferences, interpreting and integrating ideas and information, and evaluating and critiquing content and textual elements. …”
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From communication to action: using ordered network analysis to model team performance in clinical simulation by Vitaliy Popov, Lauryn R. Rochlen

“…High-performers demonstrated stronger associations between invited input, explicitly assessing the situation, stating plans, and implementation. …”
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Messy Data in Education: Enhancing Data Science Literacy Through Real-World Datasets in a Master’s Program by Iraklis Varlamis

“…They also learn the importance of finding and integrating supplementary open data sources to enhance the value and depth of their analyses. …”
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Climatological Seasonal Cycle of River Discharge into the Oceans: Contributions from Major Rivers and Implications for Ocean Modeling by Moncef Boukthir, Jihene Abdennadher

“…Compared to previous datasets, this updated compilation includes a broader set of rivers, explicitly integrates tributary inflows, and quantifies both the absolute and relative seasonal amplitudes of discharge variability. …”
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Advanced Temporal Convolutional Network Framework for Intrusion Detection in Electric Vehicle Charging Stations by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, It Ee Lee, Muhammad Sheraz, Eng Eng Ngu, Teong Chee Chuah

“…The proposed Temporal Convolutional Network (TCN)-based Intrusion Detection System (IDS) architecture integrates four key innovations: multi-receptive fields, a gating mechanism, iterative dilation, and a self-attention mechanism combined with a Squeeze-and-Excitation (SE) block to recalibrate feature responses by explicitly modeling interactions between different channels. …”
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Modeling plankton diversity in a coupled optical-biogeochemical ocean framework by Eva Álvarez, Guido Occhipinti, Gianpiero Cossarini, Cosimo Solidoro, Cosimo Solidoro, Paolo Lazzari, Paolo Lazzari

“…Plankton community modelling is a critical tool for understanding the processes that shape marine ecosystems and their impacts on global biogeochemical cycles. …”
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GLIHamba: global–local context image harmonization based on Mamba by Jinsheng SUN, Jiao PAN, Yu GUO, Chao YAO

“…The LFSE preserves the locality of adjacent features in high-dimensional arrays to explicitly ensure consistency among spatially neighboring features along the channels and thereby guarantee the local content integrity and consistency of the harmonization results. …”
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Interference of endogenous benzoic acid with the signatures of sulfonic acid derivatives and carbohydrates in fermented dairy products by Wei Jia, Xin Wang, Lin Shi

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Spike-Driven Channel-Temporal Attention Network with Multi-Scale Convolution for Energy-Efficient Bearing Fault Detection by JinGyo Lim, Seong-Eun Kim

“…To address these demanding requirements, we propose the Spike Convolutional Attention Network (SpikeCAN), a novel spike-driven neural architecture tailored explicitly for real-time industrial diagnostics. SpikeCAN utilizes the inherent sparsity and event-driven processing capabilities of spiking neural networks (SNNs), significantly minimizing both computational load and power consumption. …”
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Genome‐Enabled Parameterization Enhances Model Simulation of CH4 Cycling in Four Natural Wetlands by Yunjiang Zuo, Liyuan He, Yihui Wang, Jianzhao Liu, Nannan Wang, Kexin Li, Ziyu Guo, Lihua Zhang, Ning Chen, Changchun Song, Fenghui Yuan, Li Sun, Xiaofeng Xu

“…Abstract Microbial processes are crucial in producing and oxidizing biological methane (CH4) in natural wetlands. …”
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Land Surface Modeling in the Himalayas: On the Importance of Evaporative Fluxes for the Water Balance of a High‐Elevation Catchment by Pascal Buri, Simone Fatichi, Thomas E. Shaw, Evan S. Miles, Michael J. McCarthy, Catriona L. Fyffe, Stefan Fugger, Shaoting Ren, Marin Kneib, Achille Jouberton, Jakob Steiner, Koji Fujita, Francesca Pellicciotti

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Planning Amidst Uncertainty: Identifying Core CCS Infrastructure Robust to Storage Uncertainty by Daniel Olson, Sean Yaw

“…To address this challenge, we propose a novel optimization workflow that is based on mixed-integer linear programming and explicitly integrates probabilistic modeling of storage uncertainty into CCS infrastructure design. …”
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Catchments Amplify Reservoir Thermal Response to Climate Warming by Bo Gai, Rohini Kumar, Frank Hüesker, Chenxi Mi, Xiangzhen Kong, Bertram Boehrer, Karsten Rinke, Tom Shatwell

“…Abstract Lentic waters integrate atmosphere and catchment processes, and thus ultimately capture climate signals. …”
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TMTS: A Physics-Based Turbulence Mitigation Network Guided by Turbulence Signatures for Satellite Video by Jie Yin, Tao Sun, Xiao Zhang, Guorong Zhang, Xue Wan, Jianjun He

“…By bridging turbulence physics with deep learning, our approach provides both performance enhancements and interpretable restoration mechanisms, offering a viable solution for operational satellite video processing under atmospheric disturbances.…”
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Joint Intensity and Spatio-Temporal Representation Learning for Extreme Precipitation Nowcasting by Zefeng Pan, Renlong Hang, Qingshan Liu, Chunxiang Shi, Zhiqiang Xu, Xiao-Tong Yuan

“…Hence, we also design a Spatio-Temporal Coherence Module (STCM), which exploits voxel flow to capture spatio-temporal coherence features. Subsequently, by processing multitemporal state features and integrating coherence features, STCM can preserve the spatio-temporal structure of extreme precipitation events. …”
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A calibration framework toward model generalization for bacteria concentration estimation in water resource recovery facilities by Fahad Aljehani, Ibrahima N’Doye, Pei-Ying Hong, Mohammad Khalil Monjed, Taous-Meriem Laleg-Kirati

“…Our findings highlight the importance of integrating the calibration framework with neural network approaches to achieve model generalization.…”
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The complexity of addressing equity in COVID-19-related global health governance and population health research priorities in Canada: a multilevel qualitative study by Muriel Mac-Seing, Erica Di Ruggiero

“…Abstract Background Since COVID-19 emerged in 2020, the promotion of health equity, including in research, has further been challenged worldwide by both global health governance (GHG) processes and decisions, and national public health control measures. …”
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