Deterministic weather forecasting models based on intelligent predictors: A survey by K.U. Jaseena, Binsu C. Kovoor

“…Weather forecasting has now entered the era of Big Data due to the advancement of climate observing systems like satellite meteorological observation and also because of the fast boom in the volume of weather data. …”
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Gamma-Ray Effects of Dark Forces in Dark Matter Clumps by K. Belotsky, M. Khlopov, A. Kirillov

“…For possible cross sections, mass of annihilating particles, masses of clumps, and the contribution of annihilating particles in the total DM density we constrain the strength of new dark long range forces from comparison of predicted gamma-ray signal with Fermi/LAT data on unidentified point-like gamma-ray sources (PGS) as well as on diffuse γ-radiation. …”
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Optimizing Selection of Brown Bear Hair for Noninvasive Genetic Analysis by Aaron J. Wirsing, Thomas P. Quinn, Jennifer R. Adams, Lisette P. Waits

“…If laboratory costs preclude processing all samples, it may be important to know a priori which samples are most likely to yield useful DNA. …”
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Insights into microphysical and optical properties of typical mineral dust within urban snowpack via wet and dry deposition in Changchun, northeastern China by T. Shi, T. Shi, T. Shi, J. Wang, J. Wang, D. Zhang, J. Cui, Z. Wang, Y. Zhou, W. Pu, Y. Bai, Y. Bai, Z. Han, Z. Han, M. Liu, Y. Liu, H. Xie, M. Yang, Y. Li, M. Gao, X. Wang, X. Wang

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Multimodal Artificial Intelligence in Medicine by Conor S. Judge, Finn Krewer, Martin J. O'Donnell, Lisa Kiely, Donal Sexton, Graham W. Taylor, Joshua August Skorburg, Bryan Tripp

“…Multimodal transformer models in health care can effectively process and interpret diverse data forms, such as text, images, and structured data. …”
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Perceptual and attentional impairments of conscious access involve distinct neural mechanisms despite equal task performance by Samuel Noorman, Timo Stein, Johannes Jacobus Fahrenfort, Simon van Gaal

“…We trained and tested classifiers on electroencephalogram (EEG) data to reflect the processing of specific stimulus features, with increasing levels of complexity. …”
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A comprehensive study of ALPs from B-decays by Deepanshu Bisht, Sabyasachi Chakraborty, Atanu Samanta

“…Abstract We present a comprehensive study of axion-like particles (ALPs) through flavor changing neutral current processes, such as B → Ka followed by a → hadronic, γγ, μ + μ − channels. …”
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ENHANCING EXPLAINABILITY IN DEEPFAKE DETECTION WITH GRAPH ATTENTION NETWORKS by Aleksandr S. Pikul, Ilya Yu. Popov

“…Many current methods, like Shapley additive explanations (SHAP) and Gradient-weighted Class Activation Mapping (Grad-CAM), help explain these decisions, but they often aren't detailed enough for tasks involving complex data like human faces. …”
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Machine learning and deep learning in medicine and neuroimaging by Iván Sánchez Fernández, Jurriaan M. Peters

“…Deep learning algorithms learn by processing the data with increasing levels of abstraction in each layer. …”
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3D-Printed microneedle assays for point-of-care applications by Haoyang Yan, Huibin Ma, Xin Jiang, Jintao Zheng, Mingxi Chen, Kayan Awawdeh, Xiaohong Jiang, Runzhi Zhou, Jiacheng Yu, Haotian Luo, Yue Jia, Zheng Liang, Weini Xin, Ester Segal, Keying Guo

“…High-resolution techniques like two-photon polymerization (2PP) produce intricate designs but are slow, while faster methods like stereolithography (SLA) and digital light processing (DLP) may compromise sharpness. …”
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Prognostic value of tumor-infiltrating T-lymphocytes density in the therapeutic response to initial platinum-based chemotherapy in patients with non-small cell lung cancer by Novaković-Lacković Lora, Latinović-Tadić Ljilja, Stanetić Mirko, Lacković Marko

“…Based on the mean value, the samples were classified into the following groups: score 0, score 1, score 2, and score 3. During statistical data processing, low infiltration density combined score 0 and score 1 groups, and high infiltration density combined score 2 and score 3 groups. …”
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Pulscan: Binary Pulsar Detection Using Unmatched Filters on NVIDIA GPUs by Jack White, Karel Adámek, Jayanta Roy, Scott M. Ransom, Wesley Armour

“…The Fourier domain acceleration search (FDAS) and Fourier domain jerk search (FDJS) are proven matched-filtering techniques for detecting binary pulsar signatures in time-domain radio astronomy data sets. Next-generation radio telescopes such as the SPOTLIGHT project at the Giant Metrewave Radio Telescope (GMRT) produce data at rates that mandate real-time processing, as storage of the entire captured data set for subsequent offline processing is infeasible. …”
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Mind the gap: DNA barcoding on Pachygrapsus crabs by Cátia Alves, Lara Baptista, Patrícia Madeira, Nuno Vaz Álvaro, António Santos, Harald Meimberg, Sérgio P. Ávila, Manuel Curto

“…This highlights the importance of the availability of robust genetic data to resolve taxonomic uncertainties and improve species identification, which in many groups of invertebrates, like crustaceans, is lacking. …”
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Diversities of chromite mineralization induced by chemo–thermal evolution of the mantle during subduction initiation by Peng-Fei Zhang, Mei-Fu Zhou, Paul T. Robinson, John Malpas, Graciano P. Yumul, Christina Yan Wang, Jie Li

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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…New tools, including optical sensors, now allow for real-time monitoring. Still, issues like limited data and complex models remain. This study contributes by reviewing how machine learning is applied to transformer fault detection, exploring hybrid methods that combine traditional techniques like DGA with advanced models for better accuracy. …”
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A bird song detector for improving bird identification through deep learning: A case study from Doñana by Alba Márquez-Rodríguez, Miguel Ángel Mohedano-Munoz, Manuel J. Marín-Jiménez, Eduardo Santamaría-García, Giulia Bastianelli, Pedro Jordano, Irene Mendoza

“…Our working pipeline included, first, the development of a Bird Song Detector to isolate bird vocalizations, using spectrograms as graphical representations of bird audio data and applying image processing methods. Second, we classified bird species training custom classifiers at the local scale with BirdNET’s embeddings. …”
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Correlation between crystal orientation and morphology of electrolytically produced powder particles: Analysis of the limiting cases by Miomir G. Pavlović, Vesna M. Maksimović, Goran Branković, Predrag M. Živković

“…Lead and nickel powder particles were produced by the processes of electrolysis and characterized by scanning electron microscope (SEM). …”
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Agent-based multimodal information extraction for nanomaterials by R. Odobesku, K. Romanova, S. Mirzaeva, O. Zagorulko, R. Sim, R. Khakimullin, J. Razlivina, A. Dmitrenko, V. Vinogradov

“…Our approach is extensible to other domains of materials science and fields like biomedicine, advancing data-driven research methodologies and automated knowledge extraction.…”
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Application of Deep Learning Algorithm for Web Shell Detection in Web Application Security System by Rezky Yuranda, Edi Surya Negara

“…Training deep learning models like CNN and RNN with LSTM on processed data leads to accuracy evaluation using classification metrics. …”
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Construction and application of a TCN-LSTM-SVM-based time series prediction model for water inflow in coal seam roofs by Xuan LIU, Yadong JI, Kaipeng ZHU, Chunhu ZHAO, Kai LI, Chaofeng LI, Chenhan YUAN, Panpan LI, Pengzhen YAN

“…Accordingly,this study proposed a prediction model for water inflow along the mining face in the studied mine based on the temporal convolutional network (TCN), long short-term memory (LSTM), and support vector machine (SVM)—the TCN-LSTM-SVM model. First, by raw data processing using the TCN framework, this model extracted the dependency between mining footage and water inflow and its dynamic characteristics. …”
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