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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Analysis of the efficacy of antiepileptic drugs in the treatment of infantile spasms and focal epilepsy associated with tuberous sclerosis complex by A. V. Grigoryeva, M. Yu. Dorofeeva, V. S. Perminov, E. D. Belousova

“…Background. Adequate selection of the 1st antiepileptic drug (AED) is an obligatory condition for the successful treatment of epilepsy. …”
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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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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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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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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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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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A Low-Complexity Resource Allocation Algorithm for MIMO-OFDMA Multicast Systems with Spectrum-Guarantee Provisioning by Ioannis G. Fraimis, Stavros A. Kotsopoulos

“…We study the important problem of resource allocation for the downlink of Multiple-Input Multiple output (MIMO) Multicast Wireless Systems operating over frequency-selective channels and we propose a low-complexity but efficient resource allocation algorithm for MIMO-enabled OFDMA systems. …”
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A preference random walk algorithm for link prediction through mutual influence nodes in complex networks by Kamal Berahmand, Elahe Nasiri, Saman Forouzandeh, Yuefeng Li

“…Predicting links in complex networks has been one of the essential topics within the realm of data mining and science discovery over the past few years. …”
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Zwitterionic Poly(sulfobetaine methacrylate) Brushes Functionalized Threads for DNA Extraction from Complex Cell Lysates by Xianlong Shi, Liang Wu, Ke Ning, Xinmei Li, Lingke Feng, Yirong Chen, Ling Yu

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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

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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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تحليل خصائص وكفاءة شبكة الطرق بحي المنتزه - محافظة الإسكندرية (دراسة في جغرافية النقل الحضري باستخدام نظم المعلومات الجغرافية)... by أسامة محمد منصور علي, أحمد سمير السعيد الخراشي

“…Moreover, there is a variation in the network's efficiency depending on the terrain and population density. …”
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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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Refined Monitoring of Water Bodies in Built-Up Areas and Analysis and Evaluation of Water Color Characteristics in Complex Urban Backgrounds by Bin Li, Yong Xie, Zui Tao, Wen Shao, Gan Qin

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Performance validation of microchannel heat sinks based on single/multiobjective topology optimization and manufactured by selective laser melting by Guangzhao Yang, Mingxuan Cao, Pingnan Huang, Linlin Pan, Xin Zhong, Liang Yang, Weiwei Guo, Matthew M.F. Yuen, Huijun Li

“…This study confirms that the P3D-MOTO provides efficient and energy-saving thermal management solutions, while emphasizing that the integration of topology optimization with SLM can create complex geometries, thereby enhancing thermal performance.…”
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DeepAT: A Deep Learning Wheat Phenotype Prediction Model Based on Genotype Data by Jiale Li, Zikang He, Guomin Zhou, Shen Yan, Jianhua Zhang

“…This provides a data-driven selection criterion for genomic selection, making the selection process more efficient and targeted. …”
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Novel Europium-Grafted 3D Covalent Organic Framework for Selective and Sensitive Fluorescence-Enhanced Detection of Levofloxacin by Junyi Zhao, Chao Zhang, Zhijie Qiu, Zerong Zhang, Xiaorou Lin, Shibin Huang, Jianfeng Zhang, Jingpeng Wu, Li Liao, Rui Wang

“…Altogether, Eu@SUZ−103 extends the practical scope of 3D COFs in fluorescence-based sensing, offering a robust platform for accurate, efficient, and selective LVFX monitoring in clinical and environmental applications.…”
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HLSK-CASMamba: hybrid large selective kernel and convolutional additive self-attention mamba for hyperspectral image classification by Xiaoqing Wan, Yupeng He, Feng Chen, Ziqi Sun, Dongtao Mo

“…Conversely, transformers, despite their efficacy in modeling spectral-spatial dependencies, introduce significant computational overhead due to their complexity. Mamba, leveraging the state space model (SSM), presents a compelling alternative that efficiently captures long-range dependencies in HSIs while ensuring computational efficiency with linear complexity. …”
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