Neonatal encephalopathy in Aotearoa New Zealand: a review utilising two existing population datasets by Malcolm R. Battin, Lynn Sadler, Jutta van den Boom

“…As these datasets have different entry criteria, there is potential to combine and gain greater insight into treatment provided nationally for NE.MethodsThe specific objectives were (1) to compare the NE dataset collected by the PMMRC and the ANZNN cooling dataset from all level 2 and 3 neonatal intensive care units (NICUs) in NZ to understand differences, including the ability to estimate rates of NE over time; (2) to review temporal trends in the provision of TH nationally in NZ over the 9-year period (2010–2018), including documenting the number/year in both datasets and between centre variations; and (3) to assess receipt of TH for NZ infants with moderate to severe NE to ensure it was appropriate and equitable across all groups. …”
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Estimation of the air conditioning energy consumption of a classroom using machine learning in a tropical climate by Liliana Ortega-Diaz, Julian Jaramillo-Ibarra, German Osma-Pinto

“…Training the models with a larger amount of data allows for capturing more representative patterns, which improves their generalization ability and performance on new data.…”
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Variability of gross and fine motor control in different tasks in fibromyalgia patients by Nancy Brígida, David Catela, Cristiana Mercê, Marco Branco

“…Measuring the spatial and temporal gait parameters or gait variability has been used to assess motor pathologies and identify gait disorders. …”
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Macrophages on the run: Exercise balances macrophage polarization for improved health by Yotam Voskoboynik, Andrew D. McCulloch, Debashis Sahoo

“…Conclusions: These consistent patterns across all 75 examined studies suggest that the long term health benefits of exercise stem from its ability to orchestrate a balanced and temporally-regulated interplay between pro-immune response (M1) and reparative macrophage activity (M2). …”
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Simulating Land Use and Evaluating Spatial Patterns in Wuhan Under Multiple Climate Scenarios: An Integrated SD-PLUS-FD Modeling Approach by Hao Yuan, Xinyu Li, Meichen Ding, Guoqiang Shen, Mengyuan Xu

“…This three-dimensional framework reveals how land systems respond to socioclimatic drivers across temporal, spatial, and structural scales, offering strategic insights for climate-resilient planning and optimized land resource management in rapidly urbanizing regions.…”
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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

“…Complementing these data-driven insights, we develop a Caputo fractional-order model that captures the temporal dynamics of glucose-insulin regulation, BMI, and blood pressure. …”
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Neurovascular coupling of inhibitory control in late-onset depression: a simultaneous EEG-fMRI study by Elena Bondi, Alessandro Pigoni, Adele Ferro, Maria Pia Marra, Guido Nosari, Giandomenico Schiena, Fabio M. Triulzi, Anna M. Bianchi, Paolo Brambilla, Eleonora Maggioni

“…Moreover, EEG-driven fMRI analysis showed alterations in the MDD group in the superior temporal gyrus and cerebellar areas for N2 correlates, whereas in the supramarginal, left rolandic, and Heschl’s areas for P3 correlates.The study showed the potentiality of the EEG-fMRI integration for investigating complex cognitive processes. …”
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Evaluating the performance of herd-specific long short-term memory models to identify automated health alerts associated with a ketosis diagnosis in early-lactation cows by N. Taechachokevivat, B. Kou, T. Zhang, M.E. Montes, J.P. Boerman, J.S. Doucette, R.C. Neves

“…To our knowledge, no work has been done to compare the use of models accounting for herd-level variability on their predictive ability against automated systems. Long short-term memory (LSTM) models are machine learning models capable of learning temporal patterns and making predictions based on time series data. …”
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Near-infrared fluorescent nanoprobe enables noninvasive, longitudinal monitoring of graft outcome in RPE transplantation by Guanzhou Di, Chen Lu, Mengting Xue, Limin Zheng, Limin Zheng, Weiqi Li, Runmin Xie, Xinpei Yuan, Xu Zhen, Min Wu, Xiying Mao, Songtao Yuan

“…Conversely, in mice administered the immunosuppressive drug cyclosporine A, the decrease in signal intensity was slower and the expansion of the signal distribution was less pronounced. Immunofluorescence analysis revealed a significant temporal increase in the proportion of macrophages with nanoprobe-labeled cells following transplantation. …”
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Facilitating convergence research on water resource management with a collaborative, adaptive, and multi-scale systems thinking framework by Alex J. Webster, Yolanda C Lin, Caroline E Scruggs, Rebecca J Bixby, Laura J Crossey, Kun Huang, Atlin Johnson, Patria de Lancer Julnes, Constanza A Kremer, Melinda Morgan, Anjali Mulchandani, Lindsey Rotche, Asa B Stone, Lani M. Tsinnajinnie, Mark C Stone

“…Water resource systems display complex behavior that challenges our ability to identify paths toward improved management. …”
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Smart wearable sensor-based model for monitoring medication adherence using sheep flock optimization algorithm-attention-based bidirectional long short-term memory (SFOA-Bi-LSTM) by Yasser Alatawi, Palanisamy Amirthalingam, Narmatha Chellamani, Manimurugan Shanmuganathan, Mostafa A. Sayed Ali, Saleh Fahad Alqifari, Vasudevan Mani, Muralikrishnan Dhanasekaran, Abdulelah Saeed Alqahtani, Ahmed Aljabri

“…The SFOA-Bi-LSTM model offers several unique advantages, including efficient hyperparameter tuning via the SFOA, enhanced feature representation through an attention mechanism, and comprehensive temporal analysis using Bi-LSTM. It demonstrates superior performance compared to conventional models while being robust to noisy data due to effective preprocessing.…”
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PL1GD-T: a high-resolution gridded daily air temperature dataset for Poland by A. Jaczewski, M. Marosz, M. Miętus, M. Miętus

“…The availability of high-resolution datasets in both spatial and temporal contexts is essential for climate change impact analysis on a smaller scale. …”
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Persistence of Reptile DNA in a Terrestrial Substrate: A Case Study Using the Eastern Indigo Snake by Leah R. N. Samuels, Houston C. Chandler, Michelle Hoffman, John A. Kronenberger, Michele Elmore, Robert Aldredge, Benjamin S. Stegenga, James E. Bogan Jr., Mark A. Davis, Stephanie Hertz, Michael K. Schwartz, Taylor Wilcox

“…ABSTRACT Environmental DNA (eDNA) analysis of terrestrial substrates, such as soil and sand, is a rapid and potentially cost‐effective way to monitor rare wildlife species. …”
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Financial and Non-Financial Information Seeking: The Role of Managing Anger and Fear in Investment Strategies and Decision-making by Vahid Oskou, Sahar Yousefizadeh, Fatemeh Asnad

“…This study aims to examine the relationship between investors' excitement and their information search behaviors, with the ability to manage emotions serving as a moderating variable. …”
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Two new positive psychosocial measures for persons living with dementia by Sheila L. Molony, Sam Fazio, Kimberly Van Haitsma, Richard Feinn, Joseph Montminy, Maureen Rulison, Ricci Sanchez, Sheryl Zimmerman

“…RESULTS Data from both pilot studies are reported including item analysis and quantitative and qualitative results. …”
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STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG by Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens

“…Still, the rise of deep learning (DL)—with its ability to reproduce human-like abilities—could revolutionize clinical MEG practice. …”
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Predictive significance of the hemoglobin, albumin, lymphocyte, and platelet score for radiation pneumonitis in lung cancer patients: a respective comparative study with dosimetric... by Xiaoxuan Xie, Ming Pei, Ming Pei, Meng Chen, Yun Zhou, Dunqiang Ren, Yongzhong Guo

“…The predictive performance of the nomogram was comprehensively evaluated using the area under the receiver operating characteristic (AUROC) analyses, calibration curve, and decision curve analysis.ResultsA total of 396 patients’ data were analyzed (development cohort: 301; temporal validation cohort: 95). …”
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Alterations of interhemispheric functional connectivity in patients with hypertensive retinopathy using voxel-mirrored homotopic connectivity: a resting state fMRI study by Xue-Lin Wang, Yu Chen, Jin-Yu Hu, Hong Wei, Qian Ling, Liang-Qi He, Cheng Chen, Yi-Xin Wang, Yan-Mei Zeng, Xiao-Yu Wang, Qian-Min Ge, Xu Chen, Yi Shao

“…The functional connectivity between the hemispheres of the cerebrum was assessed by measuring VMHC, with the ability of VMHC to distinguish between the HR and HC groups assessed using receiver operating characteristic (ROC) curve analysis. …”
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The innovation capability equation: A systematic review of global determinants of SME’s success by Mariza Tsakalerou, Akmaral Abil, Vincent Ribiere, Yevgeniy Lukhmanov, Narkes Tynybayeva

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Water and heat resource utilization influence cotton yield through sowing date optimization under varied climate by Hamad Khan, Nangial Khan, Zeeshan Khan, Han Yingchun, Yang Beifang, Lei Yaping, Zhi Xiaoyu, Xiong Shiwu, Shang Shilong, Ma Yunzhen, Jiao Yahui, Lin Tao, Yabing Li

“…This study introduces a novel integration of temporal sowing optimization, multi-sensor environmental monitoring, and resource coupling analysis. …”
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