Work Systems Analysis of Emergency Nurse Patient Flow Management Using the Systems Engineering Initiative for Patient Safety Model: Applying Findings From a Grounded Theory Study by Ellen Benjamin, Karen K Giuliano

“…Other noteworthy findings include obscurity and variability across departments’ staff roles titles, functions, and norms; the degree of provider involvement in patient flow management decisions; and management’s enforcement of timing metrics. …”
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fNIRS neurofeedback facilitates emotion regulation: Exploring individual differences over the ventrolateral prefrontal cortex by Yiwei Li, Sijin Li, Hua Li, Yuyao Tang, Dandan Zhang

“…Participants in the experimental group underwent VLPFCNF training over eight sessions across two consecutive days, while those in the sham group received random signals from functional near-infrared spectroscopy (fNIRS). To investigate individual variability, participants in the experimental group were further categorized as high or low-efficacy groups based on their training efficiency, determined by the regression slope of VLPFC activity over the sessions. …”
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Energy management of microgrid coalitions considering renewable energy prediction based on machine learning algorithms by Negar Dehghani Mahmoudabadi, Mehran Khalaj, Davood Jafari, Ali Taghizadeh Herat, Parisa Mousavi Ahranjani

“…Due to the inherent variability of renewable resources, an extreme learning machine (ELM) model is applied in order to forecast solar irradiation and wind power. …”
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Eco-engineered remediation: Microbial and rhizosphere-based strategies for heavy metal detoxification by Arun Karnwal, Gaurav Kumar, Alaa El Din Mahmoud, Joydeep Dutta, Rattandeep Singh, Abdel Rahman Mohammad Said Al-Tawaha, Tabarak Malik

“…Moreover, a detailed understanding of plant–microbe interactions and the role of secondary metabolite signalling in the rhizosphere is essential to improve remediation efficiency. Future strategies should prioritize the application of functional genomics, developing bioinoculants tailored to specific environmental conditions, and implementing robust ecological risk assessments for GEMs. …”
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Optimal Design of Interior Permanent Magnet Synchronous Motor Considering Various Sources of Uncertainty by Giacomo Guidotti, Dario Barri, Federico Soresini, Massimiliano Gobbi

“…The method incorporates an innovative use of the neural network-based variance estimation (NNVE) technique to efficiently calculate the standard deviation of the objective functions. …”
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Statistical and reliability analysis of communication disability severity in Saudi Arabia using novel probability distribution by Laila A. AL-Essa, Mohammed M. Ali Al-Shamiri, Mohammed M. A. Almazah, Fathi M. Hamdoon

“…The dataset, sourced from Disability Statistics 2023, exhibits significant variability, requiring a flexible probabilistic framework. …”
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A Comparative Study of Deep Reinforcement Learning Algorithms for Urban Autonomous Driving: Addressing the Geographic and Regulatory Challenges in CARLA by Yechan Park, Woomin Jun, Sungjin Lee

“…To evaluate the adaptability of each algorithm to geographical variability and complex traffic laws, scenario-specific reward and penalty functions were carefully designed and incorporated. …”
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Advancing geohazard risk assessment – A digital tool for steep slope management by Cherry Rose Godes, One-Bin Lim, Shanelle Aira Rodrigazo, Yongseong Kim, Yongjin Kim, Seungjoo Lee, Jaeheum Yeon

“…Growing climatic variability and rapid urbanization have increased landslide occurrences, posing significant challenges for risk assessment. …”
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La biodiversidad y los servicios ecosistémicos en sistemas agroecológicos. Una revisión by Wendy Mercedes Ramírez-Suárez, Jorge Carlos López-Chouza, María de los Ángeles Flores-Acosta, Saray Sánchez-Cárdenas, Pedro Lázaro Rodríguez-Morejón

“…There is a strong interrelationship between the functioning of biodiversity and the development of ecosystem processes that will subsequently form the basis of production, based on the richness and spatial and temporal variability of species, their performance in the complexity of ecosystems and the maintenance of ecosystem services at different scales.…”
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A systematic literature review on the role of artificial intelligence in citizen science by Germain Abdul-Rahman, Andrej Zwitter, Noman Haleem

“…However, challenges such as data quality variability, algorithmic opacity, and scalability constraints persist. …”
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SALM: A Unified Model for 2D and 3D Region of Interest Segmentation in Lung CT Scans Using Vision Transformers by Hadrien T. Gayap, Moulay A. Akhloufi

“…Accurate segmentation of Regions of Interest (ROI) in lung Computed Tomography (CT) is crucial for early lung cancer diagnosis and treatment planning. However, the variability in size, shape, and location of lung lesions, along with the complexity of 3D spatial relationships, poses significant challenges. …”
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FMRI insights into the neural alterations and clinical correlates in multiple sclerosis: A comprehensive overview of systematic reviews and meta-analyses by Sama Rahnemayan, Arezoo Fathalizadeh, Mehdi Behroozi, Mahnaz Talebi, Amirreza Naseri, Elham Mehdizadehfar

“…Graph theory metrics identified disrupted global efficiency and clustering in functional networks, linked to gray matter atrophy. …”
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RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…The model demonstrated superior accuracy and interpretability compared to existing methods, addressing variability and complexities inherent in cytological images. …”
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A Robust Multi-Objective Evolutionary Framework for Artificial Island Construction Scheduling Under Dynamic Constraints by Tianju Zheng, Liping Sun, Mingwei Li, Guangyao Yuan, Shuqi Li

“…MACEMGA combines cooperative coevolution, adaptive dynamic weighting, dynamic penalty functions, and advanced genetic operators to navigate the solution space efficiently and identify Pareto optimal schedules. …”
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Nitrogen deposition favors later leaf senescence in woody species by Jian Wang, Xiaoyue Wang, Josep Peñuelas, Hao Hua, Chaoyang Wu

“…Changes in climate conditions and nitrogen deposition levels jointly controlled the direction of date of foliar senescence trends (advance or delay). The spatial variability of nitrogen deposition effects can be related to plant traits (e.g., nitrogen resorption and use efficiencies), climatic conditions, and soil properties. …”
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Geospatial Multi-User Channel Condition Interpolation for Instantaneous Sporadic Transmission and CSI Feedback Overhead Reduction in 5G and Beyond by Jasna Jankovic, Zeljko Ilic, Gordan Sisul

“…Next-generation networks look for innovative solutions to enable new service functionalities while increasing the system efficiency. …”
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MODELING THE IMPACT OF THE TRANSPORT PROVISION OPTION ON PROJECT RISKS by Svitlana Rusanova

“…At the same time, the alternatives and variability of transport provision form a corresponding impact on the project risks. …”
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Sustainable extraction of bioproducts from cactus pear waste: Economic viability and market opportunities in a green economy by Giuseppe Timpanaro, Vera Teresa Foti

“…These findings suggest that while the project is economically feasible, managing supply chain variability and optimising energy consumption are critical for long-term sustainability. …”
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Ectopic expression of vaccinia virus E3 and K3 cannot rescue ectromelia virus replication in rabbit RK13 cells. by Erin S Hand, Sherry L Haller, Chen Peng, Stefan Rothenburg, Adam R Hersperger

“…However, there is individual variability in the range of species able to be productively infected. …”
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On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…</p> <p>The generated patterns of global ET variability were relatively consistent across the ML models overall, but in regions with low data support via eddy covariance (EC) stations, we observed substantial biases across models and covariate setups and large ensemble uncertainties. …”
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