Resolving Non-Proportional Frequency Components in Rotating Machinery Signals Using Local Entropy Selection Scaling–Reassigning Chirplet Transform by Dapeng Quan, Yuli Niu, Zeming Zhao, Caiting He, Xiaoze Yang, Mingyang Li, Tianyang Wang, Lili Zhang, Limei Ma, Yong Zhao, Hongtao Wu

“…In response to these issues, an enhanced time–frequency analysis approach, termed Local Entropy Selection Scaling–Reassigning Chirplet Transform (LESSRCT), has been developed to improve the representation accuracy for complex non-stationary signals. …”
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A new scheme for boosting in situ Fenton-like reaction in plant pathogenic tissues for selective structural degradation of capsid proteins by Jun Ma, Ming Chen, Yujie Wang, Jiaying Li, Jian Tang, Shengjun Wu, Chi He, J. Paul Chen

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Micro-nano manufacturing of a pre-identified organic hydrogel surface for selective oil/water separation with ultra-high flux by Yun-yun Song, Jiang-shen Lu, Yang Zhang, Zhao-peng Yu, Yan Liu, Zhong-qiang Zhang

“…The oily wastewater system is complex and most membrane materials cannot separate various oil-water mixtures. …”
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A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

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Optimal Industrial Waste Management Strategy for Pakistan Steel Mill Corporation Using Complex Spherical Fuzzy Einstein Aggregation Information by Ijaz Ur Rahman, Shahzaib Ashraf, Bushra Batool, K. C. Gokul

“…Applying greater generality in the dimensions of the abovementioned applications could potentially enhance a lot of their efficiency. Einstein norms/application of Einstein operations have not been effectively applied within the complex spherical fuzzy sets (CSFSs) framework as such; this study now advances the application of Einstein operators in CSFS which would provide an adiaphorous approach to solving issues related to decision-making problems (DMPs). …”
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Multi-model MCDM framework for sustainable renewable energy selection in India: integrating CRITIC-EDAS-CODAS-CoCoSo by Shankha Shubhra Goswami, T. Tapankumar, N. Channa Keshava Naik, J. Gowrishankar, Nilesh Bhosle, Amrita Singh, G. Sanyasi Raju, D. Nagesh, A. Johnson Santhosh

“…Abstract The global boom in the importance of renewable energy (RE) resources has accelerated the transition from traditional energy sources to sustainable alternatives. Selecting an optimum RE power plant is a complex task influenced by geographical factors, climatic differences, and regional peculiarities. …”
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Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…Identifying LRRC through imaging is complex, due to the mismatch between fibrosis and inflammatory pelvic tissue. …”
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Selective disruption of aurora C kinase reveals distinct functions from aurora B kinase during meiosis in mouse oocytes. by Ahmed Z Balboula, Karen Schindler

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PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity by Nakul Mehta, Nitesh Bharot, John G. Breslin, Priyanka Verma

“…Coping strategies for such challenges frequently involve transferring data to a central location, which raises concerns about latency, efficiency, and privacy. To address these issues, Federated Learning (FL) was developed as a solution to mitigate both the privacy concerns of organizations and the complexities of networked systems. …”
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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling by Maqsood Ahmed, Xiang Zhang, Yonglin Shen, Tanveer Ahmed, Shahid Ali, Ayaz Ali, Aminjon Gulakhmadov, Won-Ho Nam, Nengcheng Chen

“…Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. …”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study developed a practical approach integrating radiative transfer (RT) modeling and machine learning to estimate 30-m FAPAR from Landsat surface reflectance. A coupled land–atmosphere RT model (RTM) and shuffled complex evolution optimization algorithm were first implemented at globally distributed VIIRS pixels for realistic simulation of land surface reflectance corresponding Landsat spectral bands and FAPAR under various conditions. …”
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Dynamic Reporting Nodes Selection Method for Network Awareness Based on Active–Passive Integrated Network Telemetry in LEO Satellite Networks by Hang Di, Tao Dong, Zhihui Liu, Shuotong Wei, Qiwei Zhang, Dingyun Zhang

“…Satellite network awareness is a key technology for obtaining the status of onboard resources and supporting efficient network management. However, the dynamic characteristics of the network topology results in dynamic transmission delays of awareness data, while the instability of satellite-ground links poses challenges in selecting awareness reporting nodes. …”
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An interpretable and adaptable data-driven model for performance prediction in thermal plants by G. Prokhorskii, M. Preißinger, S. Rudra, E. Eder

“…Data-driven models are a useful aid for monitoring and control of thermal power plants, but they require an effective feature selection to allow for an accurate, computationally efficient, and interpretable model. …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

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Enhanced Multiple Pulse Position Modulation Aided Reverse Polarity Optical OFDM System With Extended Dimming Control by Zixian Yang, Ming Jiang, Lin Zhang, Hong-Zhou Tan

“…It is shown that the proposed system with extended dimming control can achieve the highest effective spectral efficiency in most scenarios without substantially increasing the computational complexity, while still maintaining a power consumption level similar to those of the reference systems.…”
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A Multi-stage Scenario Tree Generation Method for Wind-Solar Load Based on Complex Feature Extraction and Sinkhorn Distance by Rui WANG, Zhixin FU, Jian WANG, Haoming LIU

“…Finally, a simulation example showed that the proposed method had high calculation efficiency, and the generated multi-stage scenario tree for wind-solar load can reflect the uncertainty of wind-solar output and load growth.…”
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Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography by Solomon Temidayo Owolabi, Johanes A. Belle

“…Results indicate a mean soil erodibility of 0.062 ton•yr•MJ−1•mm−1, with a high bifurcation ratio (12.72) reflecting significant drainage complexity. Average form factor (0.44), elongation ratio (0.74), and wandering ratio (3.60) suggest moderate runoff and efficient drainage. …”
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Integrate computation intelligence with Bayes theorem into complex construction installation: a heuristic two-stage resource scheduling optimisation approach by Jia Zhao, Wenhao Wang, Liyuan Zhang, Yan Ding

“…Experimental results demonstrate the effectiveness and efficiency of the MERD approach in reducing work time and cost in engineering projects.…”
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Leaching of heavy metals from post-neutralization sludge from zinc and lead metallurgy using complexing, alkaline and acidic agents by Milena Nocoń, Irena Korus, Gabriela Kamińska

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Copper(I) Complexes with Terphenyl-Substituted NPN Ligands Bearing Pyridyl Groups: Synthesis, Characterization, and Catalytic Studies in the S-Arylation of Thiols by M. Trinidad Martín, Ana Gálvez del Postigo, Práxedes Sánchez, Eleuterio Álvarez, Celia Maya, M. Carmen Nicasio, Riccardo Peloso

“…These findings highlight the potential of well-defined Cu(I)–NPN complexes as efficient and versatile precatalysts for C–S bond formation.…”
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