Inter-annual cascade effect on marine food web: A benthic pathway lagging nutrient supply to pelagic fish stock. by Lohengrin Dias de Almeida Fernandes, Eduardo Barros Fagundes Netto, Ricardo Coutinho, PELD-RECA

“…These sequential events can explain major changes in ecosystem food web that were not predicted in previous short-term models.…”
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Translational control by the DEAD Box RNA helicase belle regulates ecdysone-triggered transcriptional cascades. by Robert J Ihry, Anne L Sapiro, Arash Bashirullah

“…The accumulation of E74A mRNA in belle mutant salivary glands is a result of auto-regulation, fulfilling a prediction made by Ashburner nearly 40 years ago. In this model, Ashburner postulates that, in addition to regulating secondary response genes, protein products of primary response genes like E74A also inhibit their own ecdysone-induced transcription. …”
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Spatiotemporal Differences in Dominants of Dryness/Wetness Changes in Southwest China by Shujia Zhou, Shanlei Sun, Wanrong Shi, Jiazhi Wang, Jinjian Li, Guojie Wang, Weiping Lou

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Multi-Scale Self-Attention-Based Convolutional-Neural-Network Post-Filtering for AV1 Codec: Towards Enhanced Visual Quality and Overall Coding Performance by Woowoen Gwun, Kiho Choi, Gwang Hoon Park

“…The objective is to address two persistent artifact issues observed in our previous MTSA model: visible seams at patch boundaries and grid-like distortions from upsampling. …”
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Gene circuit analysis of the terminal gap gene huckebein. by Maksat Ashyraliyev, Ken Siggens, Hilde Janssens, Joke Blom, Michael Akam, Johannes Jaeger

“…We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. …”
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Coinfection of hepatitis B, tuberculosis, and HIV/AIDS in Beijing from 2016 to 2023: a surveillance data analysis by Chao Wang, Yunping Shi, Yang Liu, Ying Zhou, Jing Du, Xiao Hu, Wei Li, Jiaze Li, Yanlin Gao, Gang Li

“…The multivariate logistic model shown that males were more susceptible to be coinfected (ORs ranged from 1.50 to 27.81). …”
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Neuropsychological and clinical variables associated with cognitive trajectories in patients with Alzheimer's disease by Marianna Riello, Monica Moroni, Stefano Bovo, Flavio Ragni, Manuela Buganza, Raffaella Di Giacopo, Marco Chierici, Lorenzo Gios, Matteo Pardini, Matteo Pardini, Federico Massa, Federico Massa, Monica Dallabona, Elisa Vanzetta, Cristina Campi, Cristina Campi, Michele Piana, Michele Piana, Sara Garbarino, Manuela Marenco, Venet Osmani, Giuseppe Jurman, Antonio Uccelli, Antonio Uccelli, Bruno Giometto, Bruno Giometto, NeuroArtP3 Network, Filippo Gerli, Guido Pasquini, Claudia Niccolai, Matteo Betti, Emilio Portaccio, Maria Pia Amato, Rossi Andrea, Parodi Costanza, Ramaglia Antonia, Tortora Domenico, Severino Mariasavina, Andrea Falini, Antonella Castellano, Nicolò Pecco, Paola Scifo, Sonia Calloni

“…Model interpretability analysis revealed that the global cognitive state progression in AD patients is associated with: low spatial memory (Corsi block-tapping), verbal episodic long-term memory (Babcock's story recall) and working memory (Stroop Color) performances, the presence of hypertension, the absence of hypercholesterolemia, and functional skills inabilities at the IADL scores at baseline.ConclusionThis is the first AI study to predict cognitive trajectories of AD patients using routinely collected clinical data, while at the same time providing explainability of factors contributing to these trajectories. …”
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Enhancing flood susceptibility mapping in Sana’a, Yemen with random forest and eXtreme gradient boosting algorithms by Yahia Alwathaf, Ahmed M. Al-Areeq, Yousef A. Al-Masnay, Ali R. Al-Aizari, Nabil M. Al-Areeq

“…Both models demonstrated high accuracy in predicting flood-prone areas, with RF achieving an accuracy of 92% and XGBoost slightly outperforming it with an accuracy of 94%. …”
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Pathways to Turbulent Dissipation in a Submarine Canyon by Charlotte Bellerjeau, Matthew H. Alford, Arnaud Le Boyer, Giovanni Dematteis, Alberto Naveira Garabato, Gunnar Voet, Nicole Couto, Bethan L. Wynne‐Cattanach

“…Fluxes from both methods agree within a factor of 3 with dissipation estimates from a finescale parameterization which is often used in climate‐scale ocean models. Coarse graining predicts 68% of energy fluxing to dissipation from frequencies lower than 8cpd, while the weakly nonlinear method predicts 34%. …”
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Vision transformer-based diagnosis of lumbar disc herniation with grad-CAM interpretability in CT imaging by Qingsong Chu, Xingyu Wang, Hao Lv, Yao Zhou, Ting Jiang

“…The performance of the model was further validated via gradient-weighted class activation mapping (Grad-CAM), providing interpretable insights into the regions of the CT scans that contributed to the model predictions. …”
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Vortex Avalanches and Collective Motion in Neutron Stars by I-Kang Liu, Andrew W. Baggaley, Carlo F. Barenghi, Toby S. Wood

“…We simulate the dynamics of about 600 quantum vortices in a spinning-down cylindrical container using a Gross–Pitaevskii model. For the first time, we find convincing spatial-temporal evidence of avalanching behavior resulting from vortex depinning and collective motion. …”
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AI-driven fusion of multimodal data for Alzheimer’s disease biomarker assessment by Varuna H. Jasodanand, Sahana S. Kowshik, Shreyas Puducheri, Michael F. Romano, Lingyi Xu, Rhoda Au, Vijaya B. Kolachalama

“…Our approach achieved an AUROC of 0.79 and 0.84 in classifying Aβ and τ status, respectively. Predicted PET status was consistent with various biomarker profiles and postmortem pathology, and model-identified regional brain volumes aligned with known spatial patterns of tau deposition. …”
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TourismNeuro xLSTM: neuro-inspired xLSTM for rural tourism planning and innovation by Jing Jiang, You Li, You Li

“…Our model integrates an extended Long Short-Term Memory (xLSTM) framework with spatial and temporal attention mechanisms and a memory module, enabling it to capture both short-term fluctuations and long-term trends in tourism data. …”
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Evaluating the impact of watershed management on surface soil moisture in the Kulfo watershed, Ethiopia by Aklilu Assefa Tilahun, Wondafrash Atnafu Zewde, Bizuayehu Abera Ersuncho

“…The results revealed strong agreement between the SSM predicted by the model and the SSM observed on the ground. …”
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Geochemical Influences on Carbon Nanotubes Transport in Subsurface Environments: Integrating Millifluidics, Spectral Induced Polarization, and Machine Learning by Yixin Yang, Pengfei Liu, Kexin Chen, Sheng Zhou, Longlong Meng, Chi Zhang, Junnan Cao, Bate Bate

“…SIP detected real‐time retention by chargeability (R2 = 0.82–0.96), while a DNN decoded SIP signals to predict spatially resolved CNT deposition (R2 = 0.926), outperforming phenomenological Cole‐Cole modeling. …”
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A Difference-In-Differences Study of the Effects of a New Abandoned Building Remediation Strategy on Safety. by Michelle C Kondo, Danya Keene, Bernadette C Hohl, John M MacDonald, Charles C Branas

“…Building remediations were also significantly associated with reductions in violent gun crimes in one city section (p < 0.01). …”
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A Multidimensional Analysis Approach Toward Sea Cliff Erosion Forecasting by Maria Krivova, Michael J. Olsen, Ben A. Leshchinsky

“…Erosion is episodic and varies both spatially and temporarily; hence, forecasting erosion patterns to identify vulnerable infrastructure is immensely challenging. …”
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Quantitative Rockfall Hazard Assessment of the Norwegian Road Network and Residences at an Indicative Level from Simulated Trajectories by François Noël, Synnøve Flugekvam Nordang

“…It details how the temporal hazard component, related to the likelihood of failure, can be distributed spatially using simulated trajectories. The method can be applied with results from any process-based software and combined with various prediction methods of the temporal aspect, although this aspect is not the primary focus. …”
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BathyFormer: A Transformer-Based Deep Learning Method to Map Nearshore Bathymetry with High-Resolution Multispectral Satellite Imagery by Zhonghui Lv, Julie Herman, Ethan Brewer, Karinna Nunez, Dan Runfola

“…The model learns to predict water depths by analyzing the spectral signatures and spatial patterns present in the multispectral imagery. …”
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AI Painting Effect Evaluation of Artistic Improvement with Cross-Entropy and Attention by Yihuan Tian, Shiwen Lai, Zuling Cheng, Tao Yu

“…DBAM enhances the feature fusion capability of the model by explicitly focusing on the important channel and spatial features, and it enables the model to more accurately recognize and differentiate between changes in the creative abilities of different users before and after using AI painting tools. …”
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