Validation of the version 4.5 MAESTRO ozone and NO₂ measurements by P. S. Jeffery, J. R. Drummond, C. T. McElroy, K. A. Walker, J. Zou

“…The version 4.5 retrieval algorithm represents an improvement from previous versions, with changes including updated pressure and temperature input information, an improved algorithm for high-Sun reference spectrum calculation, improved Rayleigh scattering modelling, and the change to a Twomey–Tikhonov inversion algorithm from a Chahine relaxation technique. …”
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Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). Relationships between water-cement (w/c) ratio, desert sand (DS) content, fly ash (FA) content, bentonite (BT) content, and superplasticizer (SP) dosage were established in relation to compressive strength. …”
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A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching by Jose Moises Araya-Martinez, Jose Moises Araya-Martinez, Vinicius Soares Matthiesen, Vinicius Soares Matthiesen, Simon Bøgh, Jens Lambrecht, Rui Pimentel de Figueiredo

“…In this study, we propose a template-based matching algorithm that utilizes a novel perceptual hashing method for binary images, enabling fast and robust pose estimation. …”
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Automated chest CT three-dimensional quantification of body composition: adipose tissue and paravertebral muscle by Akinori Hata, Yohei Muraguchi, Minoru Nakatsugawa, Xinan Wang, Jiyeon Song, Noriaki Wada, Takuya Hino, Kota Aoyagi, Masami Kawagishi, Takuo Negishi, Vladimir I. Valtchinov, Mizuki Nishino, Akihiro Koga, Naoki Sugihara, Masahiro Ozaki, Gary M. Hunninghake, Noriyuki Tomiyama, Mark L. Schiebler, Yi Li, David C. Christiani, Hiroto Hatabu

“…Abstract This retrospective study developed an automated algorithm for 3D segmentation of adipose tissue and paravertebral muscle on chest CT using artificial intelligence (AI) and assessed its feasibility. …”
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Prediction of implant failure risk due to periprosthetic femoral fracture after primary elective total hip arthroplasty: a simplified and validated model based on 154,519 total hip... by M. A. Alagha, Justin Cobb, Alexander D. Liddle, Henrik Malchau, Ola Rolfson, Maziar Mohaddes

“…Model performance was tested using the area under the curve (AUC), and feature importance was identified in the best-performing algorithm. Results: The Lasso regression excelled in predicting 30-day revisions (area under the receiver operating characteristic curve (AUC) = 0.85), while the Gradient Boosting Machine (GBM) model outperformed other models by a slight margin for all remaining endpoints (AUC range: 0.79 to 0.86). …”
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New approaches for capturing and estimating variation in complex animal color patterns from digital photographs: application to the Eastern Box Turtle (Terrapene carolina) by Erik Maki, Tilmann Glimm, Paramahansa Pramanik, Ylenia Chiari, Maria Kiskowski

“…In this study, we developed algorithms to capture and obtain data on 19 different pattern measurements from digital images of 55 individuals of the Eastern box turtle Terrapene carolina sampled in the field and in a museum. …”
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Scalable <i>O</i>(<i>log</i>₂<i>n</i>) Dynamics Control for Soft Exoskeletons by Julian D. Colorado, Diego Mendez, Andres Gomez-Bautista, John E. Bermeo, Catalina Alvarado-Rojas, Fredy Cuellar

“…The proposed parallel algorithm achieves an exponential speedup for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><mo>=</mo><mi>p</mi><mo>=</mo><mn>64</mn></mrow></semantics></math></inline-formula> DoF while achieving a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.96</mn></mrow></semantics></math></inline-formula> degree of parallelism for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><mo>=</mo><mi>p</mi><mo>=</mo><mn>256</mn></mrow></semantics></math></inline-formula>, which demonstrates the required scalability for controlling highly articulated soft exoskeletons in real time. …”
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Association between international normalized ratio-to-albumin ratio and mortality in critically ill patients with gastrointestinal bleeding: a retrospective MIMIC-IV database study by Xingyi Yang, Shasha Ying, Lihong Lv, Yishu Ji, Jiaqian Ying, Huyan Ke

“…Abstract Background While the international normalized ratio-to-albumin ratio (PTAR) is an established independent prognostic indicator for various diseases, its predictive value for clinical outcomes in critically ill patients with acute gastrointestinal bleeding (GIB) has not been systematically evaluated. …”
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Global trends in machine learning applications for single-cell transcriptomics research by Xinyu Liu, Zhen Zhang, Chao Tan, Yinquan Ai, Hao Liu, Yuan Li, Jin Yang, Yongyan Song

“…Research hotspots concentrated on random forest (RF) and deep learning models, showing transition from algorithm development to clinical applications (e.g., tumor immune microenvironment analysis). …”
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Energy consumption reduction for an ultra-low-cost artificial pancreas using an event-trigger MPC strategy by Jhon E. Goez-Mora, Pablo S. Rivadeneira

“…This work aims to evaluate the performance of an impulsive Model Predictive Control (MPC) strategy with an event-triggered (ET) approach implemented in an artificial pancreas (AP) system to determine if insulin injection is necessary, avoiding the execution of the control algorithm and the use of hardware associated to that in each sampling period. …”
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Deep deterministic policy gradient-based automatic negotiation framework for shared decision-making by Xin Chen, Ping Lu, Yong Liu, Fei-Ping Hong

“…The key challenge lies in capturing the fuzzy preferences of doctors and patients while ensuring efficient and fair multi-issue negotiations. …”
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Traffic congestion forecasting using machine learning methods by Ramil R. Zagidullin, Almaz N. Khaybullin

“…The predictive model was implemented using a two-stage approach: the classical ARIMA algorithm was used for baseline forecasting, while an LSTM architecture with two recurrent layers and regularization was trained on 24-hour sequences. …”
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Aspects of aluminum alloy utilization in vertical cylindrical tank construction by Shuvalov Alexander, Mitrofanov Dmitry, Doroshin Ivan, Kazaryan Ruben

“…When working at low temperatures, the performance of steel deteriorates, ductility and toughness decrease, which leads to various emergency situations, while aluminum alloys are free of these disadvantages and their performance improves as the temperature decreases. …”
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Enhanced State-of-Charge Balancing Control for MMC-SCES Using Centralized Controllers and Adaptive Optimization by Qiluan Yang, Huangqing Xiao, Qionghai Zhu

“…The implementation of the reduced switching frequency voltage balancing algorithm reduced the average switching frequency by 94.54% while maintaining the maximum SOC difference below 0.50%. …”
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Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization by Piotr Okoniewski, Jacek Piskorowski

“…By employing a numerical optimization approach, we selectively adjust the coefficients of a single SOS within a higher-order filter to minimize the transient period while maintaining overall stability. Using a sequential quadratic programming (SQP) algorithm, we determine a time-varying coefficient trajectory over a finite horizon, ensuring a rapid convergence to steady-state behavior. …”
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Minimum Error Integration Method for Quadrilateral Flat Plate Fitting in Steel Construction by Zhuoju Huang, Jiemin Ding

“…While traditional approaches that rely on empirical craftsmanship or least-squares fitting lack precision, this study proposes a minimum error integration method that integrates Lagrange interpolation-based error estimation with an adaptive step-size steepest descent algorithm to reduce fitting error. …”
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Crystal structure prediction based on diffusion model and graph network optimization by Tao Hong, Jiong Yang, Guixin Cao

“…In this work, we propose a crystal structure prediction method called DiffOA, which combines a diffusion model with an optimization algorithm based on GNNs. By generating atomic coordinates through a diffusion process and minimizing the formation energy through an optimization process, DiffOA effectively reduces the searching space required for crystal structure prediction while respecting both the minimum energy principle and the symmetry of crystal structures. …”
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An Optimization Framework for Allocating and Scheduling Multiple Tasks of Multiple Logistics Robots by Byoungho Choi, Minkyu Kim, Heungseob Kim

“…To address this, we propose a five-step optimization framework that reduces computation time while maintaining practical applicability. The first step calculates and stores distances and paths between product locations using the A* algorithm, enabling reuse in subsequent computations. …”
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Gradient-Informed Pareto-Based Multi-Objective Binary Topology Optimization by Francesco Lucchini, Riccardo Torchio, Piergiorgio Alotto

“…While WS remains a dominant method in TO, GPBTO represents a promising alternative for cases where Pareto-based solutions are desirable. …”
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Towards a Standard Benchmarking Framework for Domain Adaptation in Intelligent Fault Diagnosis by Mohammed M. Farag

“…Domain shift is a major problem facing contemporary data-based intelligent fault diagnosis (IFD) solutions. While domain adaptation (DA) methods have been proposed to address this issue, standardizing DA benchmarks has not received much attention. …”
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