Intestinal inflammation in TNBS sensitized rats as a model of chronic inflammatory bowel disease by N. Selve, T. Wöhrmann

“…An enteritis, based on a delayed-type hypersensitivity reaction, was induced in TNBS (2,4,4-trinitrobenzenesulphonic acid) sensitized rats by multiple intrajejunal challenge with TNBS via an implanted catheter. This treatment induced chronic inflammation of the distal small intestine characterized by intense hyperaemia, oedema and gut wall thickening as assessed by macroscopic scoring and weighing a defined part of the dissected intestine. …”
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Acute Limb Ischemia in the Young: A Rare Case of Essential Thrombocytosis by Johanes Nugroho, Ruth Gunadi

“…After careful management with catheter-directed thrombolysis, surgical thrombectomy, and cytoreductive therapy using hydroxyurea, the symptoms subsided and eventually restored the patient to physical activity in less than one month.…”
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Penile Glans Amputation following Circumcision: A Case Report of a Rare Complication by Salman Soltani, Mahdi Mottaghi, Amir Jafarpisheh, Mahmoud Tavakkoli

“…We approximated the ends over a size 4 : 0 catheter. The urethral anastomosis was performed via 6 : 0 Vicryl sutures. …”
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An approach to fluoroless radiofrequency atrial fibrillation ablation by Thaïs Pittet, Etienne Delacrétaz, Stéphane Cook, Hari Vivekanantham

“…It has initially been performed with fluoroscopic catheter guiding. The advent of three-dimensional (3D) electro-anatomical mapping has significantly reduced the need for fluoroscopy. …”
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Peritoneal Dialysis Drop-out: Causes and Prevention Strategies by Kunal Chaudhary

“…These include episodes of peritonitis, catheter-related problems, ultrafiltration failure, patient fatigue, and provider comfort. …”
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Improved object detection method for autonomous driving based on DETR by Huaqi Zhao, Songnan Zhang, Xiang Peng, Zhengguang Lu, Guojing Li

“…Experimental results demonstrate that the proposed method surpasses others, with improvements of 3.3%, 4.5%, and 3% in average precision on the COCO, PASCAL VOC, and KITTI datasets, respectively, and an 84% increase in FPS.…”
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Spectral Quantitative Analysis Model with Combining Wavelength Selection and Topology Structure Optimization by Qian Wang, Boyan Cai, Yajie Yu, Hui Cao

“…The first part represents the topology structure of neural network, the second part represents the selection of wavelengths in the spectral data, and the third part represents the parameters of mutation of NAEP. Two real flue gas datasets are used in the experiments. In order to present the effectiveness of the methods, the partial least squares with full spectrum, the partial least squares combined with genetic algorithm, the uninformative variable elimination method, the backpropagation neural network with full spectrum, the backpropagation neural network combined with genetic algorithm, and the proposed method are performed for building the component prediction model. …”
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Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power by Guibin Wang, Xinlong Huang, Yiqun Li, Hong Wang, Xian Zhang, Jing Qiu

“…The numerical experiment is carried out based on two different real‐life datasets. The results demonstrate the effectiveness of the proposed method in forecasting short‐term wind power compared to five benchmarks.…”
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UAV Data Collection Co-Registration: LiDAR and Photogrammetric Surveys for Coastal Monitoring by Carmen Maria Giordano, Valentina Alena Girelli, Alessandro Lambertini, Maria Alessandra Tini, Antonio Zanutta

“…The combination of multiple drone datasets (LiDAR and photogrammetric clouds) is performed via indirect georeferencing, using different executions of the ICP procedure. …”
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A comprehensive survey of scoring functions for protein docking models by Azam Shirali, Vitalii Stebliankin, Ukesh Karki, Jimeng Shi, Prem Chapagain, Giri Narasimhan

“…Conclusions We evaluate the strengths and weaknesses of classical and deep learning-based approaches across seven public and popular datasets to aid researchers in understanding the progress made in this field.…”
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Deep cryptic diversity in the Craugastor podiciferus Species Group (Anura: Craugastoridae) of Isthmian Central America revealed by mitochondrial and nuclear data by Erick Arias, Andrew J. Crawford, Andreas Hertz, Gabriela Parra Olea

“…Species delimitation was discordant between the mitochondrial and nuclear datasets and among analytical methods. Adopting a conservative approach, we propose that the C. podiciferus species group contains at least 12 unconfirmed candidate species. …”
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In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability by Azhar Ali Khaked, Nobuyuki Oishi, Daniel Roggen, Paula Lago

“…In this study, we isolated and analyzed the effects of the subject, device, position, and orientation variabilities on DL HAR models using the HARVAR and REALDISP datasets. The Maximum Mean Discrepancy (MMD) was used to quantify shifts in the data distribution caused by these variabilities, and the relationship between the distribution shifts and model performance was drawn. …”
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Effects of Pooling Samples on the Performance of Classification Algorithms: A Comparative Study by Kanthida Kusonmano, Michael Netzer, Christian Baumgartner, Matthias Dehmer, Klaus R. Liedl, Armin Graber

“…We evaluate a variety of experimental designs using mock omics datasets with varying levels of pool sizes and considering effects from feature selection. …”
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Inclined Aerial Image and Satellite Image Matching Based on Edge Curve Direction Angle Features by Hao Wang, Chongyang Liu, Yalin Ding, Chao Sun, Guoqin Yuan, Hongwen Zhang

“…Experiments run on a variety of remote sensing datasets including forests, hills, farmland, and lake scenes demonstrate that the effectiveness of the proposed algorithm shows a great improvement over existing state-of-the-art algorithms.…”
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Krait2: a versatile software for microsatellite investigation, visualization and marker development by Lianming Du, Jiahao Chen, Dalin Sun, Kelei Zhao, Qianglin Zeng, Nan Yang

“…Results We present Krait2, a user-friendly graphical tool for investigating perfect, imperfect and compound microsatellites from FASTA and FASTQ formatted genomic datasets. Krait2 not only provides features such as primer design, repeat filtering, repeat annotation and statistical analysis, but also offers various output formats to support customized downstream analysis. …”
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Genome-scale data resolve ancestral rock-inhabiting lifestyle in Dothideomycetes (Ascomycota) by Claudio G. Ametrano, Felix Grewe, Pedro W. Crous, Stephen B. Goodwin, Chen Liang, Laura Selbmann, H. Thorsten Lumbsch, Steven D. Leavitt, Lucia Muggia

“…We assembled phylogenomic datasets from newly sequenced (4) and previously available genomes (238) of 242 taxa. …”
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Comparisons between Arabidopsis thaliana and Drosophila melanogaster in relation to Coding and Noncoding Sequence Length and Gene Expression by Rachel Caldwell, Yan-Xia Lin, Ren Zhang

“…Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. …”
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Advancing Trans-Domain Classification With Knowledge Distillation: Bridging LIDAR and Image Data by Jesus Eduardo Ortiz, Werner Creixell

“…Experimental evaluations across various benchmark datasets demonstrate that our distilled models not only rival their original counterparts in accuracy but also surpass conventional point cloud classification methods in both efficiency and scalability. …”
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Prediction of viscosity of blast furnace slag based on NRBO-DNN model by Zhe Li, Meng Wang, Rui Xu, Juanjuan Jiang, Jie Li, Zunqian Zhang, Aimin Yang

“…Compared to the unoptimized DNN, MAE, MSE, and RMSE decreased by 53.86 %, 50.30 %, and 29.50 %, while R² improved by 8.11 %. Tests on 100 datasets confirmed the NRBO-DNN’s superior accuracy, with an average error of 4.30 %. …”
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Advancing Model Explainability: Visual Concept Knowledge Distillation for Concept Bottleneck Models by Ju-Hwan Lee, Dang Thanh Vu, Nam-Kyung Lee, Il-Hong Shin, Jin-Young Kim

“…VICO-KD demonstrates superior performance on benchmark datasets compared to Vanilla-KD, ensuring the student model learns visual concepts while maintaining the local interpretation capabilities of the teacher CBM. …”
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