Remote Sensing Time Series Analysis: A Review of Data and Applications by Yingchun Fu, Zhe Zhu, Liangyun Liu, Wenfeng Zhan, Tao He, Huanfeng Shen, Jun Zhao, Yongxue Liu, Hongsheng Zhang, Zihan Liu, Yufei Xue, Zurui Ao

“…., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. …”
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Land Surface Temperature Super-Resolution With a Scale-Invariance-Free Neural Approach: Application to MODIS by Romuald Ait-Bachir, Carlos Granero-Belinchon, Aurelie Michel, Julien Michel, Xavier Briottet, Lucas Drumetz

“…Most of them are trained at low resolution but applied at fine resolution, and so they require a scale-invariance hypothesis that is not always adapted. The main contribution of this work is the introduction of a Scale-Invariance-Free approach for training neural network (NN) models, and the implementation of two NN models, called Scale-Invariance-Free Convolutional Neural Network for Super-Resolution (SIF-CNN-SR) for the super-resolution of MODIS LST products. …”
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A Multivariate Phenotypical Approach of Sepsis and Septic Shock—A Comprehensive Narrative Literature Review by Alina Tita, Sebastian Isac, Teodora Isac, Cristina Martac, Geani-Danut Teodorescu, Lavinia Jipa, Cristian Cobilinschi, Bogdan Pavel, Maria Daniela Tanasescu, Liliana Elena Mirea, Gabriela Droc

“…This review aims to identify the main sources of variability in clustering septic patients in various clinical phenotypes as a useful clinical tool for a precision-based approach in sepsis and septic shock.…”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). …”
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A Convolutional Neural Network–Based Approach for Detecting Solar System Objects in Wide-field Imaging by Aram Lee, J. J. Kavelaars, Hossen Teimoorinia, Wesley Fraser, Edward Ashton

“…A separate regression model predicted the source locations with a mean absolute error of ±1.5 pixels for sources with a signal-to-noise ratio (SNR) of 16.5 or higher. …”
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Continuous Speech-Based Fatigue Detection and Transition State Prediction for Air Traffic Controllers by Susmitha Vekkot, Surya Teja Chavali, Charan Tej Kandavalli, Rama Sai Abhishek Podila, Deepa Gupta, Mohammed Zakariah, Yousef Ajami Alotaibi

“…The ensemble algorithms demonstrated the best performance, achieving a maximum accuracy of 100% on the XGBoost test set. …”
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Efficacy of drugs most commonly prescribed at functional gastrointestinal diseases (functional dyspepsia syndrome and irritable bowel syndrome) observational study results by V. T. Ivashkin, Ye. A. Poluektova, D. V. Reykhart, O. S. Shifrin, A. G. Beniashvili, O. S. Lyashenko, A. V. Belostotsky

“…It is established that presence of probiotic in the treatment mode leads to significant reduction in main symptoms severity typical both for FD and IBS according to the «7×7» questionnaire.…”
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Aided Greenway Design Approach Based on Internet Big Data and AIGC Fine-Tuning Model by Yifan WU, Lu MENG, Liang LI

“…Image features are extracted using the pre-trained convolutional neural network model Inception ResNetV2 and image data is clustered by K-means clustering algorithm. Through the process of image recognition and clustering, a total of 11 categories of images are obtained, including signage systems, pathways (cycling lanes, pedestrian walkways, and waterside promenades), recreational facilities (children’s playgrounds, elderly activity areas, fitness areas, and rest benches), flora (flowers), forested hills, trees, water bodies (hard and soft waterside spaces), sculptures, plazas, and pavilions/towers/halls. …”
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Phasic and periodic change of drought under greenhouse effect by Yang Li, Zhicheng Zheng, Yaochen Qin, Haifeng Tian, Zhixiang Xie, Peijun Rong

“…Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. …”
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Synergizing remote sensing, support vector machine, and aeromagnetic data for precise lithological and mineral potential mapping: a case study from Egypt by Hatem M. El-Desoky, Ahmed M. Abdel-Rahman, Hamada El-Awny, Wael Fahmy, Reda Abdu Yousef El-Qassas, Kamal Abdelrahman, Hassan Alzahrani, Peter Andráš, Yahia Z. Amer, Ahmed M. Eldosouky

“…Additionally, the airborne magnetic data were processed and interpreted to detect the main lineament structures controlling the favorable locations with high potential for gold mineralization and associated minerals. …”
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Research on Model Reconstruction Methods for Partial Point Cloud Information Loss by Zhengping CHANG, Guoshuai YUAN, Jiuhua LI, Yang ZHAO, Zhongqi WANG

“…Finally, the scanned point cloud carried on region partition, and the Interactive Closest Point (ICP) algorithm was utilized to match the scanned area with the theoretical model. …”
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Framework Heurístico para la Implementación de Sistemas Activos de Reconocimiento de Objetos by E. González, A. Adán, V. Feliú

“…The proposed framework addresses the problem of uncertainty in object recognition based on monocular vision using a heuristic model that allow the implementation of the shape recognition stage by means of feature vectors without stochactic properties (PCA). …”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…PD outcomes were analysed in four categories (endurance, exit from PD, cause of PD end, technical failure) by using MMT biomarkers in effluents and clinical databases.Results MMT biomarkers and clinical data can predict PD with a mean absolute error of 16.99 months by using an Extra Tree (ET) regressor. …”
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Hyperspectral imaging for precision nitrogen management: A comparative exploration of two methodological approaches to estimate optimal nitrogen rate in processing tomato by Vito Aurelio Cerasola, Francesco Orsini, Giuseppina Pennisi, Gaia Moretti, Stefano Bona, Francesco Mirone, Jochem Verrelst, Katja Berger, Giorgio Gianquinto

“…PLSR outperformed the other algorithms in estimating N uptake (Relative Root Mean Square Error, RRMSE=21.8 %), while SVR better estimated NNI (RRMSE=10.2 %) and direct biomass (RRMSE=19.4 %). …”
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Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment by Chuanyu Ma, Chuanyu Ma, Guandu Li, Xiaohan Song, Xiaochen Qi, Tao Jiang

“…Currently, research progress in immunotherapy for prostate treatment is slower compared to other tumours, which is mainly considered to be caused by the low rate of immune response in prostate cancer as a cold tumour. …”
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A novel smart surveillance approach to strengthen health facility-based disease surveillance in Tanzania by Ms Happy Mkali, MD Alix Miauton, Dr. Alexandra Kulinkina, Ms. Magreth Joram, MD Caroline Enos, Mr. Lazar Pavicevic, Mr. Vincent Faivre, Dr. MD Rainer Tan, Dr. Sabine Renggli, Ms. Theopista Lotto, Mr. Sinamgoda Ngailla, MD Godfrey Kavishe, Mr. Ibrahim Mtebene, Mr. Peter Agrea, MD Lameck Luwanda, Mr Geofrey Ashery, MD Chacha Mangu, Dr. MD Nyanda Ntinginya, Prof. Dr. Honorati Masanja, Prof. Dr. MD Isabella Eckerle, Prof. Dr. MD Valerie D'Acremont

“…Introduction: The Integrated Disease Surveillance and Response system relies mainly on aggregated, paper-based, error-prone routine data from health facilities. …”
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A pharmacovigilance study on probiotic preparations based on the FDA Adverse Event Reporting System from 2005 to 2023 by Yitong Wang, Weifu Tan, Xuyang Li, Xuyang Li, Guangli Yang, Guangli Yang, Yunxiao Wang, Yunxiao Wang, Jing Liao, Aner Lu, Guoqing Zhang, Kuidai Chen, Liling Yang, Wei Li

“…R language was applied to analyze the standardized AE data and three algorithms including the reporting odds ratio (ROR), the proportional reporting ratio (PRR) and the empirical Bayes geometric mean (EBGM) were used to identify AE signals.ResultsIn this study, 10,698,312 reports were collected from the FAERS database, of which 74 probiotic-related adverse events were reported. …”
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Digital Humanities & Large Language Models: Practice and Research in Semantic Retrieval of Ancient Documents by Haoxian WANG, Ziming ZHOU, Feifei DING, Chengfu WEI

“…Utilizing the previously constructed vector engine, the model can efficiently retrieve relevant documents and intelligently sort the search results based on specific algorithms, ensuring that users can quickly obtain the most relevant and valuable information. …”
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Development and validation of interpretable machine learning models for postoperative pneumonia prediction by Bingbing Xiang, Yiran Liu, Shulan Jiao, Wensheng Zhang, Shun Wang, Mingliang Yi

“…Through correlation screening, chi-square tests, and feature importance ranking, 47 variables were narrowed down to 5 potential predictive factors based on the main cohort of 528 patients. Nine machine learning models, including k-nearest neighbors, support vector machine, random forest, decision tree, gradient boosting machine, adaptive boosting, naive bayes, general linear model, and linear discriminant analysis, were developed and validated to predict postoperative pneumonia. …”
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Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review by Rongrong Zhong, XiaoHui Wu, Jun Chen, Yiru Fang

“…For each included study, the following information was extracted: demographic characteristics, diagnostic criteria or psychiatric assessments, details of the technological tools and data types, duration of data collection, data preprocessing methods, selected variables or features, machine learning algorithms or statistical tests, validation, and main findings. …”
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