Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer by Yang Cui, Weihang Zhang, Xin Zeng, Yitao Yang, Sung-Joon Park, Kenta Nakai, Kenta Nakai

“…Remarkably, we identified a prognostic signature comprising 40 significant genes in the MHC-II-expressing tumors in which machine leaning models with the signature successfully predicted patient survival outcomes and the degree of immune infiltration. …”
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Neutrophil to Lymphocyte Ratio and Spontaneous Bacterial Peritonitis among Cirrhotic Patients: A Systematic Review and Meta-analysis by Seyed Arsalan Seyedi, Seyed Ali Nabipoorashrafi, Jairo Hernandez, Andrew Nguyen, Brandon Lucke-Wold, Shima Nourigheimasi, Shokoufeh Khanzadeh

“…The goal of this systematic review and meta-analysis was analyzing published studies on the role of neutrophil to lymphocyte ratio (NLR) in infection and spatially spontaneous bacterial peritonitis (SBP) among cirrhotic patients. …”
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Application of deep learning for coherent pixel selection in time series InSAR for urban area and transport infrastructure monitoring by S. Azadnejad, A. Kandiri, A. Hrysiewicz, F. O’Loughlin, E.P. Holohan, S. Dev, S. Donohue

“…Predictions of temporal coherence from MLP and LSTM models are similar, but the MLP model training time is much faster. …”
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Monitoring sub-arctic wetland vegetation using nested scales of spectrometry to inform multiple endmember spectral unmixing of Sentinel-2A imagery by Heidi Cunnick, Joan M Ramage, Dawn Magness, Stephen C Peters

“…We develop a bottom–up reference library for unmixing based on nested scales of data beginning with the highest resolution of a ground collected handheld spectral measurements, progressing to 1 m ^2 resolution using fused hyperspectral-LiDAR data, and then subsequently map predictively at the spatial resolution of the 10 m ^2 multi-spectral imagery of the European Space Agency’s Sentinel-2A. …”
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Retrospective evaluation of Facial nerve monitoring to prevent nerve damage during robotic drilling in the largest series of patients undergoing the HEARO-procedure. by Jaouad Abari, Marco Matulic, Pablo Galeazzi, Masoud Zoka Assadi, Paul Van de Heyning, Vedat Topsakal

“…Linear regression was used to determine if the minimum stimulation thresholds (FNM) could significantly predict the intra-operative distance (CBCT) between the drilled trajectory and the facial nerve. …”
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Transcending the urban–rural dichotomy: inequality in urban green space availability among urban neighbourhoods, urban villages and rural villages in Guangzhou, China by Fubin Luo, Yunzheng Zhang, Luyang Zhang

“…This study unveils the spatial disparity of UGS inequality among different types of neighbourhoods, providing insights into equal green space planning and contributing to environmental justice.…”
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High-frequency Coronal Alfvénic Waves Observed with DKIST/Cryo-NIRSP by Richard J. Morton, Momchil Molnar, Steven R. Cranmer, Thomas A. Schad

“…This result appears to challenge some models of photospheric-driven Alfvénic waves that predict a lack of high-frequency wave power in the corona owing to strong chromospheric damping. …”
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Real-Time Human Group Detection and Clustering in Crowded Environments Using Enhanced Multi-Object Tracking by Hyunmin Lee, Donggoo Kang, Hasil Park, Sangwoo Park, Dasol Jeong, Joonki Paik

“…To address these limitations, we propose a novel algorithm that integrates an optimized YOLOv8 model with DeepSORT tracking, enhancing both detection accuracy and real time performance. …”
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Volcano activity classification from synergy of EO data and machine learning: an application to Mount Etna volcano (Italy) by C. Petrucci, G. Romoli, A. Pignatelli, E. Trasatti, F. Zuccarello, F. Greco, M. Dozzo, G. Bilotta, F. Spina, G. Ganci

“…The study addresses challenges like temporal and spatial disparities and class imbalances through data preprocessing, ensuring a reliable dataset for training and validation. …”
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The hydrological impact of greening and climate change on the Mu Us Sandy land of China under the background of declining ecological efficiency by Jiazheng Li, Rong Wu, Mengjing Li, Zijun Wang, Chenfeng Cui, Junrong Liu

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Lower ambulatory care availability and greater hospital capacity are associated with higher hospital case volumes by Doreen Müller, Manas K. Akmatov, Dominik Graf von Stillfried

“…Global Moran’s I confirmed spatial clustering, and GWR revealed heterogeneous effects of primary-care access on hospital admissions, whereas bed capacity uniformly increased hospital cases and shorter GP distances consistently predicted more office visits across Germany. …”
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Evidence for a Fast Soft X-Ray Wind in M82 from XMM-RGS by Erin Boettcher, Edmund Hodges-Kluck

“…Starburst wind models predict that metals and energy are primarily carried out of the disk by hot gas ( T > 10 ^6 K), but the low energy resolution of X-ray CCD observations results in large uncertainties on the mass and energy loading. …”
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Differentiating Cheatgrass and Medusahead Phenological Characteristics in Western United States Rangelands by Trenton D. Benedict, Stephen P. Boyte, Devendra Dahal

“…Harmonized Landsat and Sentinel-2 (HLS)-derived predicted weekly cloud-free 30 m normalized difference vegetation index (NDVI) images were used to develop these metric maps. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…Furthermore, we propose a Position–Morphology Matching IoU loss function, P-MIoU, which integrates center distance constraints and morphological penalty mechanisms to more precisely capture the spatial and structural differences between predicted and ground truth bounding boxes. …”
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Physics‐Informed Neural Networks Trained With Time‐Lapse Geo‐Electrical Tomograms to Estimate Water Saturation, Permeability and Petrophysical Relations at Heterogeneous Soils... by C. Sakar, N. Schwartz, Z. Moreno

“…Water dynamics at the subsurface was accurately predicted with an average error of ∼3%. Adding water content measurements to PINNs training improved the system outcomes, mainly at the ERT low sensitivity zones. …”
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Review of Recent Advances in Remote Sensing and Machine Learning Methods for Lake Water Quality Management by Ying Deng, Yue Zhang, Daiwei Pan, Simon X. Yang, Bahram Gharabaghi

“…This review also discusses the effectiveness of these models in predicting various water quality parameters, offering insights into the most appropriate model–satellite combinations for different monitoring scenarios. …”
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Shafranov-shift destabilization of ballooning-type micro-instabilities by X. Jian, V. Chan, Z. Qiu, S. Ding, C. Holland, E. Bass, A. Garofalo, X. Liu

“…The reduced transport model TGLF can capture the physics reasonably well.…”
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Delimitation of Landslide Areas in Optical Remote Sensing Images Across Regions via Deep Transfer Learning by Zan Wang, Shengwen Qi, Yu Han, Bowen Zheng, Yu Zou, Yue Yang

“…A post-processing module is integrated into the Mask R-CNN architecture to address the challenge of overlapping mask predictions for individual landslide objects. The results indicate that the Mask R-CNN model exhibits superior overall performance in comparison with the U-Net model and is more suitable for tasks requiring detailed delineation of the object outlines in images. …”
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Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space by Shuai Li, Shufang He, Yuanrui Dong, Caihong Dai, Jinyuan Liu, Yanfei Wang, Hiroaki Shigemasu

“…In the future, it is necessary to explore methods for easier manipulating of depth cue signals in stereoscopic images and adopting deep learning-related methods to construct models and predict depths, to meet the increasing demand of human–computer interaction in complex 3D scenarios.…”
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Analysing cold-climate urban heat islands using personal weather station data by Jonathon Taylor, Charles H. Simpson, Jaana Vanhatalo, Hasan Sohail, Oscar Brousse, Clare Heaviside

“…Urban intensification of extreme heat was greater than extreme cold reduction. Practice relevance Urban climate research typically relies on sparse networks of official or researcher-deployed weather stations, interpolations thereof, land-surface temperature observations or urban climate models. …”
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