Optimal Stopping Theory-Based Online Node Selection in IoT Networks for Multi-Parameter Federated Learning by Seda Dogan-Tusha, Faissal El Bouanani, Marwa Qaraqe

“…This study introduces a novel optimal stopping theory (OST) based online node selection scheme for low complex and multi-parameter FL procedure in IoT networks. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…Results on microarray datasets for leukemia prediction show that the hybrid approach outperforms other methods in terms of both effectiveness and efficiency. This work demonstrates the potential of hybrid optimization techniques in bioinformatics for better gene selection and cancer diagnosis. • Hybrid ACO-ALO approach combines strengths of both algorithms for better feature selection. • Enhances classifier performance while reducing computational complexity. • Outperforms traditional methods on leukemia prediction datasets.…”
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A Novel Improvement of Feature Selection for Dynamic Hand Gesture Identification Based on Double Machine Learning by Keyue Yan, Chi-Fai Lam, Simon Fong, João Alexandre Lobo Marques, Richard Charles Millham, Sabah Mohammed

“…This selection allows us to classify and analyze gestures more efficiently, thereby improving models’ performance and interpretability. …”
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Simple Cobalt Nanoparticle-Catalyzed Reductive Amination for Selective Synthesis of a Broad Range of Primary Amines by Bingxiao Zheng, Liqin Yang, Yashuang Hei, Ling Yu, Sisi Wen, Lisi Ba, Long Ao, Zhiju Zhao

“…This work presents a facile, aqueous-phase synthesis of highly active cobalt catalysts (Co-Ph@SiO₂(x)) via pyrolysis of silica-supported cobalt–phenanthroline complexes. The optimized Co-Ph@SiO₂(900) catalyst achieved exceptional performance (>99% conversion, >98% selectivity) in the reductive amination of acetophenone to 1-phenylethanamine using NH₃/H₂. …”
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Microscopic Origin of Polarity‐Dependent VTH Shift in Amorphous Chalcogenides for 3D Self‐Selecting Memory by Ha‐Jun Sung, Minwoo Choi, Zhe Wu, Hwasung Chae, Sung Heo, Youngjae Kang, Bonwon Koo, Jong‐Bong Park, Wooyoung Yang, Yongyoung Park, Yongnam Ham, Kiyeon Yang, Chang Seung Lee

“…Abstract Ovonic threshold switching (OTS) selectors based on amorphous chalcogenides can revolutionize 3D memory technology owing to their self‐selecting memory (SSM) behavior. However, the complex mechanism governing the memory writing operation limits compositional and device optimization. …”
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Unsupervised Learning for Distributed Downlink Power Allocation in Cell-Free mMIMO Networks by Mattia Fabiani, Asmaa Abdallah, Abdulkadir Celik, Omer Haliloglu, Ahmed M. Eltawil

“…Furthermore, an LSF-based radio unit (RU) selection algorithm is employed to activate only the contributing RUs, allowing efficient utilization of network resources. …”
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Complexation reaction with Sm(III): a facile spectrophotometric quantification of daunorubicin in pharmaceutical preparation and biological fluids by Basima A. A. Saleem

“…Optimal conditions for the formation of the pink complex were established by studying various factors, including pH, time, samarium concentration, and temperature. …”
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MSCPUnet: A multi-task neural network for plot-level crop classification in complex agricultural areas by Kedi Fang, Shengwei Zhang, Yongting Han, Lin Yang, Meng Luo, Lu Liu, Qian Zhang, Bo Wang

“…High-precision mapping of agricultural crops in complex planting areas is a prerequisite for precision agricultural management. …”
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A novel Complex q-rung orthopair fuzzy Yager aggregation operators and their applications in environmental engineering by Jabbar Ahmmad, Tahir Mahmood, Dragan Pamucar, Hafiz Muhammad Waqas

“…We have introduced aggregation theory named complex q-rung orthopair fuzzy Yager weighted average and complex q-rung orthopair fuzzy Yager weighted geometric aggregation operators in Cartesian form. …”
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Effect of age on complexity and causality of the cardiovascular control: comparison between model-based and model-free approaches. by Alberto Porta, Luca Faes, Vlasta Bari, Andrea Marchi, Tito Bassani, Giandomenico Nollo, Natália Maria Perseguini, Juliana Milan, Vinícius Minatel, Audrey Borghi-Silva, Anielle C M Takahashi, Aparecida M Catai

“…We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of respiratory sinus arrhythmia.…”
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Development and Application of Efficient Oil Displacement System for Middle-Low Permeability and High Pour-Point Heavy Oil Reservoirs by Zhenfu Ma, Kai Zhang, Mengjie Zhao, Lu Liu, Chao Zhong, Jian Wang

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Enhanced Grounding DINO: Efficient Cross-Modality Block for Open-Set Object Detection in Remote Sensing by Zibo Hu, Kun Gao, Jingyi Wang, Zhijia Yang, Zefeng Zhang, Haobo Cheng, Wei Li

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Implications of reduced-complexity aerosol thermodynamics on organic aerosol mass concentration and composition over North America by C. Serrano Damha, K. Gorkowski, A. Zuend

“…We have implemented the Binary Activity Thermodynamics model coupled to a volatility basis set partitioning scheme in the GEOS-Chem CTM, providing an efficient reduced-complexity OA model that predicts relative-humidity-dependent mixing and partitioning thermodynamics, while limiting the impact on computational efficiency. …”
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Selection of the optimal medical waste incineration facility location: A challenge of medical waste risk management by Stanojević Kristina, Radovanović Goran, Makajić-Nikolić Dragana, Savić Gordana, Simeunović Barbara, Petrović Nataša

“…In the proposed methodology on the chosen scenario and analysing the criteria relevant for selecting the most suitable location, using the DEA method, seven efficient locations for MW incineration facility were obtained. …”
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Preparation and Characterization of Ternary Complexes to Improve the Solubility and Dissolution Performance of a Proteolysis-Targeting Chimera Drug by Heng Zhang, Hengqian Wu, Lili Wang, Laura Machín Galarza, Chuanyu Wu, Mingzhong Li, Zhengping Wang, Erpeng Zhou, Jun Han

“…<b>Methods:</b> Initially, sulfobutyl ether-β-cyclodextrin (SBE-β-CD) was selected to improve the solubility of LC001. The polymer TPGS was screened based on the phase solubility method to enhance the efficiency of complexation and solubilization capacity, and its ratio with SBE-β-CD was optimized. …”
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Enhancing PV power forecasting through feature selection and artificial neural networks: a case study by Mokhtar Ali, Abdelhalim Rabehi, Abdelkerim Souahlia, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem, Takele Ferede Agajie

“…For instance, integrating ReliefF with MLP reduced the normalized mean absolute error (nMAE) to 9.21% with an R2 of 0.9608, while the best LSTM configuration achieved an nMAE of 9.29% and an R2 of 0.946 when using Chi-square selected features. These findings confirm that careful feature selection enhances model performance, reduces complexity, and ensures better generalization, offering valuable insights for more efficient solar energy management and grid stability.…”
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Molecularly Woven Cationic Covalent Organic Frameworks for Highly Selective Electrocatalytic Conversion of CO2 to CO by Fentahun Wondu Dagnaw, Karim Harrath, Tao Zheng, Xu‐Dong Wu, Yu‐Ze Liu, Rui‐Qi Li, Luo‐Han Xie, Zhen Li, Xuezhong He, Qing‐Xiao Tong, Jing‐Xin Jian

“…After loading Pd nanoparticles, CuCOF‐Pd and CuCOF+‐Pd performed increased CO selectivity up to 84.97% and 95.45%, respectively. Combining the DFT theoretical calculations and experimental measurements, it is assumed that the molecularly woven cationic COF provides a catalytic microenvironment for CO2R and ensures efficient charge transfer from the electrode to the catalytic center, thereby achieving high electrocatalytic activity and selectivity. …”
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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…Quantum mechanical (ONIOM) optimizations and molecular dynamics simulations confirmed the stability and favorable interaction profiles of the selected protein–ligand complexes, resembling that of navtemadlin, a known MDM2 inhibitor. …”
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Background of Data Envelopment Analysis Implementation in Moscow Healthcare System: International and Russian Experience by Yu. V. Budarina

“…The publications were selected using the PRISMA guidelines. A complex of modern general scientific methods of cognition was also used: system and structural approach, analytical method, comparison, and generalization.Results. …”
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Dynamics-based predictions of infinite-dimensional complex systems using dynamical system deep learning method by Hao Li, Jianping Li, Zixiang Wu, Mingyu Wang, Guangcan Liu, Ruipeng Sun, Ruize Li, Ning Wang, Houbin Song, Shixin Zhen

“…Predicting complex nonlinear chaotic dynamical systems constitutes a critical and formidable challenge across various disciplines. …”
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