AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…The output of AngleCam is compatible with a range of applications, including functional‐structural plant modelling, Earth system modelling or radiative transfer modelling of plant canopies. …”
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High-intensity zones in dogs with lumbosacral intervertebral disc degeneration: insights from MRI and histopathological findings by S. Amir Kamali, Michelle Teunissen, Dirk Hendrik Nicolaas van den Broek, Elisabeth M. Burgers, Guy C. M. Grinwis, Keita Ito, Marianna A. Tryfonidou, Björn P. Meij

“…Histopathological analysis of 11 dorsal AF samples collected during standard-of-care decompressive surgery revealed two patterns: reactive cystic structures (3/11) and granulation tissue (8/11), with differential MRI presentation. …”
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Enhancing outlying growth simulation in urban cellular automata via intelligent extraction-fusion of land suitability and neighborhood effects: a case study of Wuhan, China by Qingyang Xu, Xuefeng Guan, Changlan Yang, Weiran Xing, Xiaoyu Chen, Huayi Wu

“…In this model, a dual-path convolution structure is employed to extract spatial features from driving factors and cell states; geographical coordinates of each cell then input into a multilayer perceptron to derive spatially varying weights for feature fusion. …”
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FetalMovNet: A Novel Deep Learning Model Based on Attention Mechanism for Fetal Movement Classification in US by Musa Turkan, Emre Dandil, Furkan Erturk Urfali, Mehmet Korkmaz

“…To evaluate FetalMovNet, we construct a new dataset containing fetal movements in US across seven different anatomical structures-head, body, arm, hand, heart, leg, and foot. …”
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Digital Forest Inventory Using Fused UAV and PLS Point Cloud Data by R. Bülbül, S. Reder, F. Berendt, K. Beiler, T. Cremer, J.-P. Mund

“…Accurate digital forest inventory (DFI) is essential for sustainable forest management, yet single-sensor LiDAR approaches often fall short in capturing the full vertical structure of forest stands. This study evaluates the performance of a fused dataset combining UAV-based LiDAR (ULS) and personal laser scanner (PLS) data to overcome platform-specific limitations. …”
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Role of wave coupling in the simulation of tropical storm Choi-wan (2021) using a coupled ocean-atmosphere model by Haofeng Xia, Haofeng Xia, Haofeng Xia, Shuai Tang, Shuai Tang, Jie Chen, Shengtao Du, Wuhong Guo, Wuhong Guo

“…A wave dependent surface roughness scheme is evaluated to understand the wave influence on tropical cyclone induced changes in sea surface temperature (SST), ocean currents, and wave fields. …”
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Novel polycyclic meroterpenoids with protein tyrosine phosphatase 1B inhibitory activity isolated from desert-derived fungi Talaromyces sp. HMT-8 by Xin-yi Zhai, Jin-jie Liu, Cui-duan Wang, Yi-fan Dou, Jian-hua Lv, Li-an Wang, Jin-xiu Zhang, Zhuang Li

“…Compounds 1–12 were evaluated for their inhibitory activity against protein tyrosine phosphatase 1B (PTP1B). …”
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The Trans-Olecranon Approach for a Concomitant Radial Head Arthroplasty and Internal Fixation of the Ulna in Monteggia-Equivalent Fractures by David Shaked Zari, Itay Ron, Doron Norman, Jihad Dabbah, Bezalel Peskin, Nabil Ghrayeb, Jacob Shapira

“…Background: Monteggia-equivalent fractures are similar to Monteggia fractures but involve different patterns and locations. When these fractures include a severe radial head fracture, radial head arthroplasty (RHA) should be considered. …”
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Analysis of deformation rule of deep foundation pit excavation of railway station in soft soil with silt by Weijian Liu, Zhonghe Wang, Zhizeng Zhang, Zhengyu Zhang, Yongfu Jia, Zhun Li

“…By analyzing actual monitoring data collected from the site, the study identifies patterns in the settlement and deformation of both the retaining structure and the surface. …”
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Delivering data: A real-world dataset for last-mile delivery optimizationZenodo by Anna Vrani, Savvas D. Apostolidis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos

“…Data retrieval was performed through automated API queries, ensuring consistency in structure and format. The collected matrices were processed and structured for direct use in VRP algorithms.The dataset offers substantial reuse potential by serving as a benchmark for evaluating VRP algorithms, enabling the comparison of optimization methods based on real-world logistics problems. …”
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A Hybrid Method Combining Variational Mode Decomposition and Deep Neural Networks for Predicting PM2.5 Concentration in China by Senlin Li, Bo Tang, Xiaowu Deng

“…The results confirm that the proposed hybrid structure outperforms single deep neural prediction structures in terms of performance metrics. …”
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Hypothesis‐Driven Research on Multiple Stressors: An Analytical Framework for Stressor Interactions by Iris Madge Pimentel, Dania Albini, Arne J. Beermann, Florian Leese, Samuel J. Macaulay, Christoph D. Matthaei, James A. Orr, Jeremy J. Piggott, Ralf B. Schäfer

“…Statistical models are commonly used to evaluate the statistical significance of interaction terms. …”
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THE NORTHERN TERRITORIES OF WESTERN SIBERIA: DEMOGRAPHIC TRENDS AND GROWTH PARADOXES by Andrei G. Shelomentsev, Vladimir M. Kurikov, Kseniya S. Goncharova, Alina V. Istratii

“…Meanwhile, both regions exhibit similar changes in the age and gender structure of their populations and a shift in settlement patterns between urban and rural areas. …”

Masked pre-training of transformers for histology image analysis by Shuai Jiang, Liesbeth Hondelink, Arief A. Suriawinata, Saeed Hassanpour

“…We pre-trained MaskHIT model using over 7000 WSIs from TCGA and extensively evaluated its performance in multiple experiments, covering survival prediction, cancer subtype classification, and grade prediction tasks. …”
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A Bibliometric Assessment of AI, IoT, Blockchain, and Big Data in Renewable Energy-Oriented Power Systems by Manuel Jaramillo, Diego Carrión, Jorge Muñoz, Luis Tipán

“…The objective is to evaluate the research landscape, trends, and integration potential of these technologies within sustainable energy infrastructures. …”
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Geospatial Clustering in Smart City Resource Management: An Initial Step in the Optimisation of Complex Technical Supply Systems by Aliaksey A. Kapanski, Roman V. Klyuev, Aleksandr E. Boltrushevich, Svetlana N. Sorokova, Egor A. Efremenkov, Anton Y. Demin, Nikita V. Martyushev

“…However, without a clear understanding of the network structure and water consumption patterns, addressing these challenges becomes significantly more complex. …”
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A Review of Multiscale Interaction Mechanisms of Wind–Leaf–Droplet Systems in Orchard Spraying by Yunfei Wang, Zhenlei Zhang, Ruohan Shi, Shiqun Dai, Weidong Jia, Mingxiong Ou, Xiang Dong, Mingde Yan

“…Its coupling mechanisms fundamentally influence pesticide transport pathways, deposition patterns, and drift behavior within crop canopies, forming the foundational basis for achieving intelligent and site-specific spraying operations. …”
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Numerical investigation on damage characteristics of surrounding rocks in the deep underground tunnel subjected to full-face smooth blasting by Hongbo Du, Xiao Huang, Haoran Wang, Yu Wan, Shiyuan Huang, Wenjie Li

“…In light of this, this study employs the LS-DYNA software coupled with a fluid–structure interaction algorithm to simulate full-face smooth blasting excavation in tunnels, accounting for scenarios both with and without in-situ stress. …”
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Noise Pollution Prediction in a Densely Populated City Using a Spatio-Temporal Deep Learning Approach by Marc Semper, Manuel Curado, Jose Luis Oliver, Jose F. Vicent

“…This study explores and evaluates the application of deep learning techniques to predict urban noise levels, using the city of Madrid, Spain, as a case study. …”
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AnoViT: Unsupervised Anomaly Detection and Localization With Vision Transformer-Based Encoder-Decoder by Yunseung Lee, Pilsung Kang

“…These methods are actively used in various fields such as manufacturing, medical care, and intelligent information. Encoder-decoder structures have been widely used in the field of anomaly detection because they can easily learn normal patterns in an unsupervised learning environment and calculate a score to identify abnormalities through a reconstruction error indicating the difference between input and reconstructed images. …”
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