The Ionospheric Effects of the 2022 Hunga Tonga Volcano Eruption and the Associated Impacts on GPS Precise Point Positioning Across the Australian Region by B. A. Carter, R. Pradipta, T. Dao, J. L. Currie, S. Choy, P. Wilkinson, P. Maher, R. Marshall, K. Harima, M. Le Huy, T. Nguyen Chien, T. Nguyen Ha, T. J. Harris

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Multiscale modeling of reservoir systems using geostatistical methods by Chihi, Hayet, Hammami, Mohamed Amin, Mezni, Imen, Belayouni, Habib, Ben Mammou, Abdallah

“…This provides a detailed input for the geostatistical modeling procedures that enabled to precisely capture the varying extent and shape of the hydrogeological units at regional scale.Geophysical data, available along the Jeffara plain, were added as a complement to the Jeffara geodatabase and used to establish the fault network and to build a local architectural model of the coastal aquifer system, based on time-to-depth conversion using kriging with external drift.The results have allowed (i) a major update of the geological configuration of the Jeffara basin, (ii) more precision on the geometries and extent of the stratigraphic sequences and (iii) an accurate prediction of the main characteristics of water reservoirs, i.e. their occurrence, thickness, facies and dynamic properties variation at the basin and reservoir scale. …”
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Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning [version 1; peer review: awaiting peer review] by David Garrett Brown, Darwin J. Operario, Lan Wang, Shanrui Wu, Daniel T. Leung, Eric R. Houpt, James A. Platts-Mills, Jie Liu, Ben J. Brintz

“…First, a classification model predicted whether amplification occurred or not, and if so, a second model predicted the cycle threshold (Ct) value. …”
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Detection of Dengue Virus-Specific IgM and IgG Antibodies through Peptide Sequences of Envelope and NS1 Proteins for Serological Identification by Pradeep Kumar Nagar, Deepali Savargaonkar, Anupkumar R. Anvikar

“…On the basis of algorithm prediction from DNASTAR, BCEPRED, and IEDB data resources, twelve peptides of E (EP1 to EP12) and eight peptides of NS1 (NS1-1 to NS1-8) were selected, which were common in all serotypes. …”
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Application of deep learning and feature selection technique on external root resorption identification on CBCT images by Nor Hidayah Reduwan, Azwatee Abdul Aziz, Roziana Mohd Razi, Erma Rahayu Mohd Faizal Abdullah, Seyed Matin Mazloom Nezhad, Meghna Gohain, Norliza Ibrahim

“…Kruskal Wallis test revealed a significant difference (p = 0.008) in the prediction accuracy among the eight DLMs. Conclusion In general, all DLMs have similar performance on ERR identification. …”
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High-resolution mapping of peatland CO2 fluxes using drone multispectral images by R. Walcker, C. Le Lay, L. Gandois, A. Elger, V.E.J. Jassey

“…Our predictions were in the range of those found in the satellite remote sensing literature with errors lesser than 0.5 gCO2.m−2.h−1. …”
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Social Acceptance of Smart Glasses in Health Care: Model Evaluation Study of Anticipated Adoption and Social Interaction by Niek Zuidhof, Oscar Peters, Peter-Paul Verbeek, Somaya Ben Allouch

“…In summary, constructs that focus on social interaction could contribute to better explanation and prediction of the expected adoption of smart glasses in health care. …”
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Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTMResearch in context by Xueting Jin, Fangwu Wei, Srinivasa Srivatsav Kandala, Tejas Umesh, Kayleigh Steele, John N. Galgiani, Manfred D. Laubichler

“…By predicting the CM prevalence, our results can inform researchers, epidemiologists, clinicians, and the public in order to assist public health. …”
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Salinity affects the lipid metabolism and intestinal microbial composition of swimming crab Portunus trituberculatus by Meimei Liu, Tong Li, Hao Zhang, Zi Wang, Xugan Wu, Jie He, Zhiguo Dong

“…Bacterial functional pathway prediction has also shown that the KEGG pathways involved in ovarian steroidogenesis, NF-kappa B signaling pathway and regulation of lipolysis in adipocytes increased in 28 ‰ group compared with 19 ‰ group. …”
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A comparative analysis of sphenoid and frontal sinuses using cone beam computed tomography for sex determination by Junaid Ahmed, Namrata, Nanditha Sujir, Nandita Shenoy, Srikant Natarajan, Archana Muralidharan, Ashwin C. Shetty

“…There was an improvement in the accuracy of sex prediction when the linear measurements of FS and SS were considered in combination rather than in isolation. …”
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Knowledge‐Informed Deep Neural Networks for Solar Flare Forecasting by Ming Li, Yanmei Cui, Bingxian Luo, Xianzhi Ao, Siqing Liu, Jingjing Wang, Shuxin Li, Chenxi Du, Xiaojing Sun, Xin Wang

“…Abstract Recently, although various deep learning techniques have been applied to building space weather prediction models, a large amount of relevant prior knowledge of solar eruptions and magnetic properties is ignored during the model development. …”
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Glymphatic system clearance and Alzheimer’s disease risk: a CSF proteome-wide study by Natalia Cullell, Giovanni Caruana, Andrea Elias-Mas, Ariane Delgado-Sanchez, Cristina Artero, Maria Teresa Buongiorno, Marta Almería, Nicola J. Ray, Sonia A. L. Correa, Jerzy Krupinski

“…In Stage 2, we validated these proteomic results in a new cohort of aMCI participants (with and without evidence of AD pathology in CSF (aMCI(-) and aMCI/AD( +); n = 22 and 7, respectively) and healthy controls (n = 10). Proteomic prediction models were generated in each ROI. These were compared with demographic-only models for identifying participants with aMCI(-) and aMCI/AD( +) vs controls. …”
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Physical activity and the outcome of cognitive trajectory: a machine learning approach by Bettina Barisch-Fritz, Jay Shah, Jelena Krafft, Yonas E. Geda, Teresa Wu, Alexander Woll, Janina Krell-Roesch

“…Less is known about the value of ML for predicting cognitive decline in people with dementia (PwD). …”
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Associations of the Need for Surgery in Emergency Department Patients with Small Bowel Obstructions by Daniel J. Berman, Alexander W. Mahler, Ryan C. Burke, Andrew E. Bennett, Nathan I. Shapiro, Leslie A. Bilello

“…These associations are a step toward building better prediction models and improving decision-making in the ED, allowing for a more adequate treatment plan.…”
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Risk Factors Influencing Cognitive Function in Elderly Patients With Late‐Life Depression: A Scoping Review by Ping Jiang, Yunfeng Gao, Lin Wang, Xiaojun Shao, Lei Zhang, Gang Zhu, Li Duan

“…However, there remains an incomplete understanding of the relevant influencing factors for cognitive impairment in elderly depressed patients, which seriously impedes the development of risk prediction models and the subsequent research on precision intervention programs. …”
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Seasonal dynamics of dissolved organic matter in a small tropical estuary-coastal bay continuum: distribution, transformation, flux, and global perspectives by Pengfei Liu, Kuan Jiang, Qi Tan, Fajin Chen, Renming Jia, Chao Wang, Chao Wang, Chao Wang, Chao Wang

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The ANFIS-RSM based multi-objective optimization and modelling of ultrasound-assisted extraction of polyphenols from jamun fruit (Syzygium cumini) by Mohammad Ganje, Somayyeh Gharibi, Fatemeh Nejatpour, Maryam Deilamipour, Kimia Goshadehrou, Sahra Saberyan, Gholamreza Abdi

“…Error indices demonstrated that ANFIS (R2 = 0.8490–0.9989) outperformed RSM (R2 = 0.9265) in predictive capability, underscoring the relative superiority of ANFIS.…”
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Spectral and coupling characteristics of somatosensory cortex and centromedian thalamus differentiate between pre- and inter-ictal 5–9 Hz oscillations in a genetic rat model of abs... by Eleni Nikalexi, Vladimir Maksimenko, Thomas Seidenbecher, Thomas Budde, Hans-Christian Pape, Annika Lüttjohann

“…In general, pre-ictal oscillations display a unique electrophysiological profile in GAERS that might pave the way for qualification as biomarker for SWD generation and seizure prediction.…”
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Trust Management in Social Internet of Things (SIoT): A Survey by Sana Alam, Shehnila Zardari, Shaheena Noor, Shakil Ahmed, Haralambos Mouratidis

“…Our work classifies studies (policy-based, prediction-based, weighted sum-based/weighted linear combination-based) by trust computation/aggregation approach. …”
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Numerical Study of the Effect of Out-of-Plane Distance in the Lateral Direction at the Mid-Span of a Steel Beam on the Sectional Moment Capacity by Ahmed Mohamed Sayed, Nageh M. Ali, Mishal H. Aljarbou, Abdullah Alzlfawi, Salman Aldhobaib, Hani Alanazi, Abdulmalik H. Altuwayjiri

“…For all the beams with out-of-plane distances, all the design codes were unable to predict this ultimate capacity.…”
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