A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables. by Julian Hecker, Dmitry Prokopenko, Matthew Moll, Sanghun Lee, Wonji Kim, Dandi Qiao, Kirsten Voorhies, Woori Kim, Stijn Vansteelandt, Brian D Hobbs, Michael H Cho, Edwin K Silverman, Sharon M Lutz, Dawn L DeMeo, Scott T Weiss, Christoph Lange

“…Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios, and we show how the screening strategy influences statistical power. …”
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Deep learning based predictive models for real time accident prevention in autonomous vehicle networks by Ahmed Almutairi, Abdullah Faiz Al Asmari, Fayez Alanazi, Tariq Alqubaysi, Ammar Armghan

“…These studies evaluate key metrics such as the accuracy of predictions, the response time, the reduction in accident rate, the efficiency of decision-making, and the resilience to false data. …”
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Nonlinear variations and drivers of vegetation NPP on the Tibetan Plateau: Interaction of natural and human factors. by Jie Tang, Xinghong Peng, Wenfu Peng

“…Results revealed nonlinear fluctuations in NPP during the study period, ranging from 184.06 to 208.53 gC m-2.a-1, with an average annual growth rate of 1.16 gC m-2.a-1. Significant spatial differences were observed, with higher NPP in the grasslands and forests of the southeast, while lower productivity was found in the alpine deserts of the northwest. …”
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Optimization of CNN Activation Functions using Xception for South Sulawesi Batik Classification by Aswan Aswan, Eva Yulia Puspaningrum, Billy Eden William Asrul

“…With identical hyperparameters including a learning rate of 0.001, a batch size of 64 and training for 100 epochs using the Adam optimizer, ReLU, ELU, Leaky ReLU and Swish activation functions were compared. …”
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COVID-19 global risk evaluation: rankings, reducing surveillance bias, and infodemic by Michał P. Michalak, Elżbieta Węglińska, Agnieszka Kulawik, Jack Cordes, Michał Lupa, Andrzej Leśniak

“…Conversely, the case fatality rate exhibited only a weak positive correlation with probabilistic metrics, though these correlations were not consistently statistically significant. …”
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Residential Location Preferences in a Post-Conflict Context: An Agent-Based Modeling Approach to Assess High-Demand Areas in Kabul New City, Afghanistan by Vineet Chaturvedi, Walter Timo de Vries

“…The model simulates three alternative growth rate scenarios, i.e., ambitious, moderate, and steady. …”
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Anomaly Detection in Nuclear Power Production Based on Neural Normal Stochastic Process by Linyu Liu, Shiqiao Liu, Shuan He, Kui Xu, Yang Lan, Huajian Fang

“…On the Power Generation System (PGS) dataset with a 15% missing rate, our model achieves an F1 score of 83.72%, surpassing all baseline methods and maintaining strong performance across multiple industrial subsystems.…”
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Advancing sedimentation modeling in large reservoir systems: Insights from multi-scale process coupling and machine learning by Yuning Tan, Huaixiang Liu, Yongjun Lu, Zhili Wang, Wenjie Li

“…Our climate scenario simulations revealed uneven sedimentation patterns and projected declining sedimentation rates over the next 30 years. …”
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Initial Stages of Electrocrystallization of Coatings with Tin and Tin-Copper and Tin-Copper-Ultradisperse Diamond Alloys by I. I. Kuzmar, D. Y. Gulpa, L. K. Kushner

“…With an increase in electrocrystallization over-voltage, the rate of nucleation increases and their size decreases, while fine-grained and dense deposits are formed. …”
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Using Eye Tracking to Assess Reading Performance in Patients with Glaucoma: A Within-Person Study by Nicholas D. Smith, Fiona C. Glen, Vera M. Mönter, David P. Crabb

“…Reading duration and saccade rate were significantly different on average in the worse eye when compared to the better eye (P<0.001) in 14 patients with glaucoma that had median (interquartile range) between-eye difference in mean deviation (MD; a standard clinical measure for VF loss) of 9.8 (8.3 to 14.8) dB; differences were not related to the size of the difference in MD between eyes. …”
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User Perception and Acceptance of Central Bank Digital Currency in Developed and Developing Countries: An Empirical Study using Technology Acceptance Model.

“…It also identifies new factors influencing human behavior patterns in the digital economy, such as perceived usefulness, perceived ease of use, perceived security, perceived trust, perceived privacy, perceived social influence, and perceived compatibility. …”
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A data driven framework for optimizing droplet microfluidics with residual block and Fourier enhanced networks by Alireza Samari, Kamal Jannati, Azadeh Jafari

“…We developed two innovative machine learning models: the Fourier-Enhanced Network (FEN), which utilizes Fourier series to decompose input features into harmonic components; and the Residual Block Network (ResBNet), which incorporates skip connections within residual layers to capture complex nonlinear patterns. ResBNet demonstrated high accuracy in predicting relative droplet radius, Strouhal number, and optimized geometric ratios, while FEN offered computational efficiency and robust performance across a broad range of flow rates. …”
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Global spatio-temporal ERA5 precipitation downscaling to km and sub-hourly scale using generative AI by Luca Glawion, Julius Polz, Harald Kunstmann, Benjamin Fersch, Christian Chwala

“…SpateGAN-ERA5 enhances ERA5 precipitation data from 24 km and 1 h to 2 km and 10 min, delivering high-resolution rainfall fields with realistic spatio-temporal patterns and accurate rain rate distribution, including extremes. …”
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Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing by Severin Josef Schink, Dimitris Christodoulou, Avik Mukherjee, Edward Athaide, Viktoria Brunner, Tobias Fuhrer, Gary Andrew Bradshaw, Uwe Sauer, Markus Basan

“…Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. …”
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ENHANCING 〖PM〗_(2.5) PREDICTION IN KEMAYORAN DISTRICT, DKI JAKARTA USING DEEP BILSTM METHOD by Nabila Karin, Gumgum Darmawan, Triyani Hendrawati

“…Traditional forecasting methods like ARIMA have limitations in handling non-linear and complex patterns. Therefore, an accurate machine learning method is needed to improve forecasting performance. …”
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The impact of COVID-19 on clinical research for Neglected Tropical Diseases (NTDs): A case study of bubonic plague. by Tsinjo Fehizoro Rasoanaivo, Josephine Bourner, Ravaka Niaina Randriamparany, Théodora Mayouya Gamana, Voahangy Andrianaivoarimanana, Mily Harijaona Raherivelo, Harivelo Randriamampionona, Minoarisoa Rajerison, Mihaja Raberahona, Alex Paddy Salam, Tansy Edwards, Piero L Olliaro, Rindra Vatosoa Randremanana

“…<h4>Methods</h4>To understand the impact of the COVID-19 pandemic on the trial accrual rate, we documented changes in patterns of all-cause consultations that took place before and during the pandemic at health centres in two districts of the Amoron'I Mania region of Madagascar where the trial is underway. …”
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Preparation of Porous F-WO3/TiO2 Films with Visible-Light Photocatalytic Activity by Microarc Oxidation by Chung-Wei Yeh, Kee-Rong Wu, Chung-Hsuang Hung, Hao-Cheng Chang, Chuan-Jen Hsu

“…Owing to the high specific surface area from the porous microstructure, the mTiO2 film shows a 61% and 50% rate increase in the photocatalytic dye degradation, as compared with the N,C-codoped TiO2 films under UV and Vis irradiation, respectively.…”
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Melanoma Skin Lesion Classification Using Neural Networks: A systematic review by ahmed hammo, Mohammed Younis

“…Therefore, detection of this disease must be early and sound due to the high mortality rate. It is driven by researchers' desire to use computers to obtain accurate diagnostic systems to help diagnose and detect this disease early. …”
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MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…These datasets serve two functions: improving illness prediction and examining large data reservoirs to identify previously unknown disease patterns. Leveraging deep learning models, it becomes feasible to detect and forecast the early stages of numerous diseases based on individual health conditions. …”
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Finding the Context of High‐Risk Behavioral Factors and the Effectiveness of Addiction Treatment Centers in Preventing the Transmission of Hepatitis C Virus Among Injecting Drug Ad... by Neda Asadi, Sirous Pourkhajoei

“…The studied IDUs reported minor rate of risky injecting and sexual behavior after participation in MMT program. …”
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