Research on Underwater Sensor Network Adaptive Clustering Algorithm for Marine Environment Monitoring by Libin Xue, Chunjie Cao, Rongxin Zhu

“…This demonstrates that the algorithm can achieve efficient energy utilization and notably enhance network performance.…”
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Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings by Stelios Prekas, Panagiotis A. Karkazis, Panagiotis Trakadas

“…The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. …”
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Urgent surgical patient classification: Development and validation of a novel instrument using the Delphi approach by Priscila Buck de Oliveira Ruiz, Jaqueline Lopes Gouveia, Paula Buck de Oliveira Ruiz, João Daniel de Souza Menezes, Matheus Querino da Silva, Emerson Roberto dos Santos, Alba Regina de Abreu Lima, Vânia Maria Sabadoto Brienze, Júlio César André, Rita de Cássia Helu Mendonça Ribeiro

“…Developing an instrument to objectively identify the complexity of care required for each case is challenging. …”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…Despite its potential to revolutionize the field, researchers are often encumbered by obstacles, such as the complexity of selecting optimal algorithms, the automation of data pre-processing steps, the necessity for adaptive feature engineering, and the assurance of model performance consistency across different datasets. …”
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Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

“…But, it is realized that adaptation of the intensification and diversification for solving complex optimization problems are challenging tasks. …”
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Advances in the management of posttraumatic stress disorder after critical illness: a narrative review by Evanthia Asimakopoulou, Panagiotis Theodosis-Nobelos, Charalampos Triantis

“…Antidepressants, particularly selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs), have demonstrated efficiency in alleviating symptoms. 3,4-Methylenedioxymethamphetamine–assisted therapy is the most promising approach, and the results of the clinical trials are encouraging. …”
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The Association between Rainfall and Taxi Travel Activities: A Case Study from Wuhan, China by Rong Chen, Lingjia Liu, Yongping Gao

“…Rainfall altered residents’ travel preferences to some extent, with more residents choosing taxis during rainy weather, which led to decreased transportation efficiency and increased traffic congestion. These findings contribute to a deeper understanding of the complex relationship between population mobility patterns and the urban ecological environment, providing valuable insights for planning resident travel and taxi dispatching under adverse weather conditions.…”
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Data-driven cultural background fusion for environmental art image classification: Technical support of the dual Kernel squeeze and excitation network. by Chenchen Liu, Haoyue Guo

“…A novel Dual Kernel Squeeze and Excitation Network (DKSE-Net) model is proposed for the complex cultural background and diverse visual representation in environmental art images. …”
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Exploring infill pattern and density effects on the tensile properties of 3D printed ABS by Bruno Leonardelli, Cesar Pandolfi, Gustavo Alberto Ludwig, Cristian Padilha Fontoura

“…Fused Deposition Modeling (FDM) is recognized as an efficient method for creating durable, complex parts quickly and affordably. …”
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Using BWRO for removal of Arsenic III from anaerobic groundwater by A.H. Haidari, T. van Dijk, W.G. Siegers, T. Rijnaarts, E.R. Cornelissen

“…The study explores membrane performance under conditions not extensively addressed before, such as using natural anaerobic groundwater with arsenic concentrations of 70–80 µg/L and examining the effect of sulfide complexation on arsenic rejection. The impact of sodium sulfide and antiscalant on arsenic rejection was investigated, with Na₂S tested as a complexing agent. …”
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Evaluating the Effectiveness of Dimensionality Reduction on Machine Learning Algorithms in Time Series Forecasting by Rida Zaheer, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Ramzan Talib

“…High dimensionality of time series data can lead to computational inefficiencies and increased complexity. Dimensionality reduction techniques play a crucial role in handling the high-dimensional nature of time series data essential information while reducing computational complexity. …”
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Temporal Pyramid Alignment and Adaptive Fusion of Event Stream and Image Frame for Keypoint Detection and Tracking in Autonomous Driving by Peijun Shi, Chee-Onn Chow, Wei Ru Wong

“…Additionally, the framework incorporates a Dynamic Inference Path Selection mechanism, guided by input complexity, to optimize computational resource allocation, along with a dynamic noise suppression mechanism to improve the robustness of feature extraction. …”
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A practical workflow to facilitate analysis of the emission dynamics of non-target BVOCs in terrestrial ecosystems by PTR-TOF-MS by Mathias Fontez, Joris Huguenin, Frédéric Jullien, Sandrine Moja, Magali Proffit, Florence Nicole

“…Proton Transfer Reaction Time-of-Flight Mass Spectrometry (PTR-TOF-MS) provides high-resolution, real-time tracking of volatile organic compounds (VOCs), yet its analytical workflows for complex mixtures are often underexplored. This study presents a flexible data analysis workflow tailored for PTR-TOF-MS, designed to manage datasets with multiple replicates and experimental factors efficiently. …”
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Online Identification of Aircraft Model Parameters Based on Recursive Least Squares Method by JIANG Yongming, WANG Changqing, XU Cheng

“…However, this method is only suitable for simple linear models and cannot be directly adopted for nonlinear complex motion models.…”
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Developing stock sentiment rank metric for forecasting stock sentiments: a statistical perspective by Rachna Sable, Aman Singh, Sudhanshu Gupta, Shivani Goel, Pallavi Parlewar

“…This statistic will help readers find the best successful models for high-scalability situations by one metric for both performance and efficiency-oriented factors.…”
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OSBF: One-Sided Box Filter for Edge-Preserving Image Processing by Yuanhao Gong

“…Box filter is well-known for the image smoothing task, thanks to its effectiveness and computation efficiency. However, it can NOT preserve edges. In contrast, edge-preserving methods can NOT achieve the high computation performance as the box filter. …”
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New Insights into the Function of the Immunoproteasome in Immune and Nonimmune Cells by Hiroaki Kimura, Patrizio Caturegli, Masafumi Takahashi, Koichi Suzuki

“…The immunoproteasome is a highly efficient proteolytic machinery derived from the constitutive proteasome and is abundantly expressed in immune cells. …”
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Runoff Forecasting Research Coupling Quadratic Factor Screening and Deep Learning by CHENG Liwen, HUANG Shengzhi, LI Pei, LI Ziyan, JIA Songtao, HUANG Qiang

“…The effective screening of factors influencing runoff is a key aspect of runoff forecasting research.However,there are many factors affecting runoff,and these factors have complex interactions.Most of the existing studies use numerically driven models with primary factor screening,and the results show that the input factors are spatially redundant,leading to poor forecasting results.In view of this,the support vector regression (SVR) and the long-short memory network model (LSTM) are compared with Weihe River Basin as an example,and the LSTM model is selected as the optimal forecasting model.Principal component analysis and gray correlation analysis are used for secondary screening of the input terms to form a model coupling principal component analysis,gray correlation analysis,and LSTM.The results show that:①the fitting accuracy of LSTM is higher than that of SVR;②the secondary screening of the input terms improves the forecast accuracy,and the forecast accuracy of the coupled model is better than that of the single model,specifically,the model accuracy evaluation indexes of the coupled model are substantially improved compared with those of the single model;③the Nash efficiency coefficient and deterministic coefficient of the coupled model of gray system correlation analysis are improved by 0.13% and 0.03%,respectively,compared with those of the coupled model of principal component analysis,and the standard deviation ratio of observed values is improved by 42.9%.The study shows that the secondary factor screening by using gray correlation can effectively improve forecast accuracy.…”
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Rope-Riding Mobile Anchor for Robots Operating on Convex Facades by Chaewon Kim, KangYup Lee, Jeongmo Yang, TaeWon Seo

“…This structural principle was selected for its simplicity, stability under heavy loads, and efficient actuation. …”
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Two New Approaches (RAMS-RATMI) in Multi-Criteria Decision-Making Tactics by Reda M. S. Abdulaal, Omer A. Bafail

“…When a decision must be made, a tool called multi-criteria decision-making (MCDM) is used to assess and select alternatives among numerous criteria. For a wide variety of complex problems, MCDM methods have demonstrated usefulness in finding the optimal solutions. …”
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