The unresolved struggle of 16S rRNA amplicon sequencing: a benchmarking analysis of clustering and denoising methods by Mohamed Fares, Engy K. Tharwat, Ilse Cleenwerck, Pieter Monsieurs, Rob Van Houdt, Peter Vandamme, Mohamed El-Hadidi, Mohamed Mysara

“…Using unified preprocessing steps, we were able to compare DADA2, Deblur, MED, UNOISE3, UPARSE, DGC (Distance-based Greedy Clustering), AN (Average Neighborhood), and Opticlust objectively. Results ASV algorithms—led by DADA2— resulted in having a consistent output, yet suffered from over-splitting, while OTU algorithms—led by UPARSE—achieved clusters with lower errors, yet with more over-merging. …”
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Application of the LDA model to identify topics in telemedicine conversations on the X social network by Mario Sierra Martín, Fang-Wei Chen, Pilar Alarcón Urbistondo

“…In the present analysis, we focus on unstructured tweet texts written by Internet users and apply both machine learning and the Latent Dirichlet Allocation algorithm to model X databases and identify tweet topics. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…However, the system’s efficiency and accuracy are compromised by the significant delay incurred while obtaining real-time motion signals and driving the actuator for motion compensation. …”
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A Novel Prognostic Nomogram Based on TIGIT and NKG2A Can Predict Relapse‐Free Survival of Hepatocellular Carcinoma After Hepatectomy by Junqi Wang, Yuqing Cao, Yu Tian, Chaoliu Dai, Tianqiang Jin, Feng Xu

“…Results TIGIT and NKG2A expression were identified as independent risk factors for RFS, while TIGIT expression alone significantly impacted OS. …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

“…High-frequency noise-containing IMFs are selectively removed, while LSTM predicts retained components. SSA optimizes LSTM parameters (learning rate, hidden layers, epochs) to minimize prediction errors. …”
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Fractional-Order Swarming Intelligence Heuristics for Nonlinear Sliding-Mode Control System Design in Fuel Cell Hybrid Electric Vehicles by Nabeeha Qayyum, Laiq Khan, Mudasir Wahab, Sidra Mumtaz, Naghmash Ali, Babar Sattar Khan

“…The increasing demand for FCHEVs necessitates control systems capable of handling nonlinear dynamics, while ensuring robust, precise energy distribution among fuel cells, batteries, and super-capacitors. …”
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Computer Program for Primer Design for Loop-Mediated Isothermal Amplification (LAMP) by L. U. Akhmetzianov

“…More than 150 computer programs have been proposed for the design of PCR primers, while for LAMP-primers there are less than 10 of them, and each of them has a number of drawbacks, e.g., in terms of the length of the analyzed site. …”
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Towards a global spatial machine learning model for seasonal groundwater level predictions in Germany by S. Kunz, A. Schulz, M. Wetzel, M. Nölscher, T. Chiaburu, F. Biessmann, S. Broda

“…Performance varied widely: 25 % of wells achieved an NSE <span class="inline-formula">&gt;0.68</span>, while 15 % had an NSE <span class="inline-formula">&lt;0</span> with the best N-HiTS model. …”
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An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

“…This study aims to improve SICH outcome prediction by developing the Alpha Evolution Moss Growth Optimization (AEMGO) algorithm for feature selection in high-dimensional medical datasets. …”
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Use of RUSH protocol to diagnose the type of shock in children by K. Yu. Ermolenko, K. V. Pshenisnov, Yu. S. Aleksandrovich, A. I. Konev, T. M. Kalinichenko, D. D. Lopareva, D. R. Rybakova, I. E. Gorbunov, L. O. Kiseleva

“…In three patients, the RUSH protocol diagnosed a combined type of shock (sensitivity 100%), while the physical examination did not establish a diagnosis of shock depending on the leading link of pathogenesis.Conclusion. …”
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Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis by Erfan Shirmohamadi, Reza Hosseini Dolama, Narjes Mohammadzadeh, Navid Ebrahimi, Negar Ghasemloo

“…Studies were included if they utilized machine learning algorithms, including HPI, to predict or detect IOH in adult surgical patients. …”
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Enhanced Navigation Precision Through Interaction Multiple Filtering: Integrating Invariant and Extended Kalman Filters by Maher Tarek, Syed Tariq Shah, Shady Zahran, Eyad S. Oda, Mostafa M. Ahmed, Ahmad Almogren, Mahmoud A. Shawky, Sherif F. Nafea

“…Inertial navigation systems (INS) are the prime source of navigation information for these applications, while global navigation satellite system (GNSS) measurements act as an aided source to bound INS drift and provide global positioning. …”
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Optimizing wireless dynamic charging infrastructure for electric vehicles: A predictive and adaptive framework leveraging decision-dependent uncertainties and renewable energy util... by Yanjia Wang, Xianlong Li, Mohannad Alhazmi, Da Xie, Xitian Wang

“…The rapid adoption of electric vehicles (EVs) is transforming modern transportation systems while presenting challenges related to charging infrastructure, grid integration, and renewable energy utilization. …”
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Development of a Serum Metabolome‐Based Test for Early‐Stage Detection of Multiple Cancers by Rajnish Nagarkar, Mamillapalli Gopichand, Suparna Kanti Pal, Ankur Gupta, Najmuddin Md Saquib, Ahmad Ahmad, Ganga Sagar, Kanury V. S. Rao, Zaved Siddiqui, Imliwati Longkumer

“…Our goal here was to maximize the number of cancers that could be detected, while also covering cancers in both females and males. …”
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Map-Guided Coarse-to-Fine Lunar Rover Localization via Multiview Crater Matching by Chenming Ye, Zhizhong Kang, Xue Wan, Shuai Shao, Juntao Yang, Zhen Cao

“…In the past decades, manual-assisted station visual positioning has been extensively employed, while recent studies on track reckoning and visual odometry have provided a foundation for the advancement of automated localization of rovers. …”
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A Novel Smart Molecular Fuzzy Decision Support System for Solid-State Battery Investments in Grid-Level Renewable Energy Storage by Gang Kou, Hasan Dincer, Serhat Yuksel, Edanur Ergun, Serkan Eti

“…For this purpose, a new decision-making model is developed that includes expert weighting with the entropy game, evaluation balancing with the Q-learning algorithm, calculation of criterion weights with the least squares optimization (LSO) and alternative ranking with the molecular ranking (MORAN) method. …”
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Learning Gaussian graphical models from correlated data by Zeyuan Song, Zeyuan Song, Sophia Gunn, Stefano Monti, Stefano Monti, Gina M. Peloso, Ching-Ti Liu, Kathryn Lunetta, Paola Sebastiani, Paola Sebastiani, Paola Sebastiani

“…In this paper, we propose a cluster-based bootstrap algorithm to infer GGMs from correlated data. We use extensive simulations of correlated data from family-based studies to show that the proposed bootstrap method does not inflate the Type I error while retaining statistical power compared to alternative solutions when there are sufficient number of clusters. …”
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Evaluating the spatiotemporal patterns of GPP and tree growth for their response to CO2 fertilization effects in mid-latitude forests of China by Bin Wang, Xiangqi Kong, Shaojie Bian, Ying Quan, Zechuan Wu, Jianyang Liu, Mingze Li

“…In particular, the EC-LUE GPP exhibited a decrease rate of −0.46%.100 ppm−1yr−1, while the NIRv GPP showed a decrease rate of −0.04%.100ppm−1yr−1. …”
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Enhancing environmental models with a new downscaling method for global radiation in complex terrain by A. Druel, J. Ruffault, H. Davi, A. Chanzy, O. Marloie, M. De Cáceres, A. Olioso, F. Mouillot, C. François, K. Soudani, N. K. Martin-StPaul

“…<p>Global radiation is a key climate input in process-based models (PBMs) for forests, as it determines photosynthesis, transpiration and the canopy energy balance. While radiation is highly variable at a fine spatial resolution in complex terrain due to shadowing effects, the data required for PBMs that are currently available over large extents are generally at a spatial resolution coarser than <span class="inline-formula">∼9</span> km. …”
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Spatiotemporal Mapping of Soil Profile Moisture in Oases in Arid Areas by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Li Li, Liya Shi, Yue Liu

“…Traditional monitoring methods are limited in achieving large-scale, real-time observations, while deep learning offers new avenues to model the complex nonlinear relationships between spectral features and soil moisture content. …”
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