IF 8.2 1区环境科学与生态学

Bioresource Technology Pub Date : 2026-12-01 Epub Date: 2026-08-16 DOI: 10.1016/j.biortech.2026.135614

Jiawen Du, Long Liu, Jiawen Gao, Xiaofeng Zhu, Lingkai Kong, Ting Cui, Menghao Cai, Xuemei Li, Yunxia Zhao, Xinyu Lu, Nengfei Wang, Shusheng Zhang

{"title":"The spatiotemporal-specific regulation of cell wall-related proteins promotes the secretion of pigments in Antarctic fungi Geomyces sp. wnf-18c.","authors":"Jiawen Du, Long Liu, Jiawen Gao, Xiaofeng Zhu, Lingkai Kong, Ting Cui, Menghao Cai, Xuemei Li, Yunxia Zhao, Xinyu Lu, Nengfei Wang, Shusheng Zhang","doi":"10.1016/j.biortech.2026.135614","DOIUrl":"10.1016/j.biortech.2026.135614","url":null,"abstract":"The polar environment harbors extremely rich and valuable natural product resources. In this study, a strain of Antarctic fungus, Geomyces sp. wnf-18c, in Antarctic soil was isolated in a laboratory. This fungus produces a purplish-red pigment whose hue closely resembles that of the high-end pigment carminic acid. However, approximately 50 % of the pigment remains within the fungal hyphae, restricting subsequent separation and extraction. In this study, the deletion of the key cell wall protein-encoding genes CHS3 and AGS1 enhanced pigment secretion. It also considerably inhibited the strain's growth, making it difficult to substantially increase the total pigment yield. To overcome these hurdles, the xylose-inducible system from Trichoderma reesei was heterologously expressed in Antarctic fungi, and the CRISPR-Cas9 system was placed under the control of this induction system. The exogenous addition of xylose as a signal to initiate genetic editing achieved the spatiotemporal regulation of the target gene-activating gene editing that restricts growth only after the completion of the strain's growth phase. The spatiotemporal regulation of key cell wall proteins significantly mitigated growth inhibition, greatly enhanced pigment secretion, and raised the total pigment yield. This discovery advances our understanding of the spatiotemporal specificity and dynamic regulation of microorganisms, offering novel strategies for exploiting polar microbial resources and reducing industrial production costs.","PeriodicalId":258,"journal":{"name":"Bioresource Technology","volume":" ","pages":"135614"},"PeriodicalIF":8.2,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148760457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electroacupuncture modulates cortical functional connectivity and network topology in healthy adults: an fNIRS study. 电针调节健康成人皮质功能连通性和网络拓扑：一项fNIRS研究。

IF 4.5 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-09-30 DOI: 10.1007/s11571-026-10560-x

Xiang Chen, Banghua Yang, Dongyang Shen, Junhua Chen, Dongsheng Xu, Wenxi Li

{"title":"Electroacupuncture modulates cortical functional connectivity and network topology in healthy adults: an fNIRS study.","authors":"Xiang Chen, Banghua Yang, Dongyang Shen, Junhua Chen, Dongsheng Xu, Wenxi Li","doi":"10.1007/s11571-026-10560-x","DOIUrl":"https://doi.org/10.1007/s11571-026-10560-x","url":null,"abstract":"Acupuncture has shown clinical benefits in post-stroke rehabilitation, yet its central neural mechanisms remain incompletely understood. In particular, how cortical activation, inter-regional functional connectivity, and brain network topology are modulated during electroacupuncture stimulation has not been systematically characterised. This study aimed to investigate the central effects of verum electroacupuncture (VE) applied to the non-dominant hand in healthy adults. In a randomized, crossover design, functional near-infrared spectroscopy (fNIRS) data were collected from 24 participants during VE and sham electroacupuncture (SE) sessions. Cortical activation was assessed using a general linear model (GLM), functional connectivity (FC) was analysed using lagged cross-correlation, and brain network topology was examined using graph-theoretical metrics. No significant differences in cortical activation were observed between VE and SE. During the needles retention phase, VE significantly reduced functional connectivity between R-MPFC and right primary somatosensory cortex (R-PSC), and between middle MPFC and R-PSC. Graph-theoretical analysis revealed decreased clustering coefficient and increased small-worldness under VE. These findings suggest that VE may optimise brain networks through an connectivity-topology mechanism. Brain networks shifted from excessive localisation toward higher integration. This study establishes a baseline central response profile in healthy individuals and provides theoretical support for the application of electroacupuncture in post-stroke upper-limb rehabilitation. Trial registration: ITMCTR, TRN: ITMCTR2025000595, Registration date: 19 March 2025.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"193"},"PeriodicalIF":4.5,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149105142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Domain generalized feature embedded learning for calibration-free event-related potentials recognition. 面向无标定事件相关电位识别的领域广义特征嵌入学习。

IF 4.5 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-04-09 DOI: 10.1007/s11571-026-10450-2

Tian-Jian Luo

{"title":"Domain generalized feature embedded learning for calibration-free event-related potentials recognition.","authors":"Tian-Jian Luo","doi":"10.1007/s11571-026-10450-2","DOIUrl":"10.1007/s11571-026-10450-2","url":null,"abstract":"Event-related potentials (ERPs) play an important role for building EEG-based brain computer interfaces (BCIs). However, due to the complex and varied spatio-temporal characteristics of ERPs across subjects, data distribution across subjects a very important issue to be solved for constructing calibration-free BCIs. To achieve calibration-free ERPs recognition, we propose a Domain Generalized Feature Embedded Learning (DGFEL) method. First, we align the ERPs of each existed subject based on covariance centroids. Then, we enhanced the aligned samples based on xDAWN filter and extract spatio-temporal features. Finally, the spatio-temporal features are further generalized by the decomposed adversarial loss, and we construct a neural network embedding backbone to implement features generalization across subjects. The proposed method has been systematically validated on two benchmark EEG-based ERP datasets, and its classification performance surpasses several state-of-the-art methods as well as deep learning models. Moreover, it effectively captures robust features from existed source subjects, and can be generalized to new subjects without accessing target ERP samples. Our method therefore provides a novel selection to construct calibration-free ERP-BCIs.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"77"},"PeriodicalIF":4.5,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13065971/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147671004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From nonlinear neuronal dynamics to AI-optimized VLSI hardware: multiplier-free FPGA implementation of memristive FN-HR coupled neural networks for intelligent systems. 从非线性神经元动力学到人工智能优化的VLSI硬件：智能系统记忆性FN-HR耦合神经网络的无乘法器FPGA实现。

IF 3.9 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-06-08 DOI: 10.1007/s11571-026-10476-6

Wei Wu, Wensen Yu, Chaochao Wang, Mohammad Sh Daoud, Abdulilah Mohammad Mayet, Yisu Ge, Xiaotian Pan, Guodao Zhang

{"title":"From nonlinear neuronal dynamics to AI-optimized VLSI hardware: multiplier-free FPGA implementation of memristive FN-HR coupled neural networks for intelligent systems.","authors":"Wei Wu, Wensen Yu, Chaochao Wang, Mohammad Sh Daoud, Abdulilah Mohammad Mayet, Yisu Ge, Xiaotian Pan, Guodao Zhang","doi":"10.1007/s11571-026-10476-6","DOIUrl":"https://doi.org/10.1007/s11571-026-10476-6","url":null,"abstract":"This paper proposes an innovative approach to translating the nonlinear dynamics of a memristive FitzHugh-Nagumo-Hindmarsh-Rose (FN-HR) coupled neuron model into an AI-optimized, resource-efficient VLSI implementation on FPGA platforms, advancing intelligent computing paradigms. The bidirectional memristive synapse coupling FN and HR neurons enables rich dynamic behaviors such as mixed-mode oscillations and chaos, which are harnessed to enhance adaptive machine learning and neural network training. A detailed dynamical analysis, including Lyapunov exponent spectra and synchronization properties, identifies parameter regimes suitable for AI applications. Nonlinear operators are approximated using quantized lookup tables and three-term sinusoidal expansions, achieving RMSE values of 0.0105 (FN) and 0.0114 (HR) while eliminating DSP usage. Synthesized on an AMD Zynq UltraScale+ ZCU104 FPGA, a 50-neuron network utilizes 5.3% LUTs and 7% BRAM, delivering 42 million neuron-updates per second at 210 mW. This work establishes a scalable, low-power platform for real-time AI-driven neuromorphic computing and intelligent adaptive control systems.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"113"},"PeriodicalIF":3.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13243168/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148210407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Memristor-based neuromorphic circuit for visual emotional non-associative learning. 基于记忆器的视觉情感非联想学习神经形态回路。

IF 3.9 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-06-08 DOI: 10.1007/s11571-026-10479-3

Yingcong Wang, Shuai Shao, Yanfeng Wang, Junwei Sun

{"title":"Memristor-based neuromorphic circuit for visual emotional non-associative learning.","authors":"Yingcong Wang, Shuai Shao, Yanfeng Wang, Junwei Sun","doi":"10.1007/s11571-026-10479-3","DOIUrl":"https://doi.org/10.1007/s11571-026-10479-3","url":null,"abstract":"Most of the nonassociative learning neural networks based on memristor only consider habituation or sensitization and ignore the combination with emotions. According to biological characteristics, a nonassociative learning memristive neural network circuit of emotions induced by vision is designed in this paper. The circuit comprises the voltage control module, the synapse module, the potentiation of habituation module and the spontaneous recovery module. The functions such as habituation and spontaneous recovery, habituation of dishabituation, potentiation of habituation and sensitization are implemented by the circuit. Emotions through visual stimuli of different intensities are induced in designed circuit. The designed circuit is able to implement emotional habituation and sensitization like humans after processing the sensory signals from vision. At the same time, based on picture stimuli as inputs, PSpice simulations confirm the feasibility and accuracy of the proposed circuit at the circuit-simulation level. The proposed circuit may serve as a potential neuromorphic module for robotic affective perception and emotional learning, providing a reference for future research on brain-inspired emotional intelligence.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"114"},"PeriodicalIF":3.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13243158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148210450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correction: Olfactory Perception and Neural Rhythms: A Simulation-Based EEG Analysis Using Power Spectral Density Features. 修正：嗅觉感知和神经节律：基于功率谱密度特征的模拟脑电图分析。

IF 4.5 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-07-21 DOI: 10.1007/s11571-026-10511-6

Aadhitya S V

引用次数: 0

Speech-based depression detection using higher-order spectral features and a multi-level transformer. 基于高阶频谱特征和多级变压器的语音抑制检测。

IF 4.5 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-07-08 DOI: 10.1007/s11571-026-10500-9

Uma Jaishankar, Jagannath H Nirmal

{"title":"Speech-based depression detection using higher-order spectral features and a multi-level transformer.","authors":"Uma Jaishankar, Jagannath H Nirmal","doi":"10.1007/s11571-026-10500-9","DOIUrl":"10.1007/s11571-026-10500-9","url":null,"abstract":"A precise and prompt automated depression detection system utilizing auditory signals is essential, considering the scarcity of psychiatrists and the exorbitant expense of clinical diagnosis, resulting in approximately 60% of psychiatric patients globally lacking access to mental health care. This study proposes a Depression Detection model utilizing voice, which integrates hierarchical higher-order spectral distribution with deep learning models to overcome these issues. The utilized dataset is the Distress Analysis Interview Corpus, Wizard of Oz (DAIC-WOZ), comprising audio recordings of clinical interviews designed to facilitate the detection of psychological distress disorders such as depression, anxiety, and post-traumatic stress disorder. Two categories of features are extracted: statistical, handmade and bispectral features, as well as deep features utilizing the Multi-level Convolutional Transformer with attention learning (ML-CoT-AL) model. The ML-CoT-AL integrates the Convolutional Transformer (CoT), Channel and Element-wise Attention Module (CEAM), and Negotiator Modules (NM). The study presents the RIME optimization technique utilizing ML-CoT-AL for hyperparameter tuning, leading to improved accuracy in multi-level depression identification.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"130"},"PeriodicalIF":4.5,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13346385/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synergistic entrainment: a multiscale neurodynamic framework for closed-loop cross-modal neuromodulation. 协同夹带：闭环跨模态神经调节的多尺度神经动力学框架。

IF 4.5 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-07-11 DOI: 10.1007/s11571-026-10503-6

Chenfei Yan, Shuo Zhang, Yingwei Li, Qianxiang Zhou, Zhongqi Liu

{"title":"Synergistic entrainment: a multiscale neurodynamic framework for closed-loop cross-modal neuromodulation.","authors":"Chenfei Yan, Shuo Zhang, Yingwei Li, Qianxiang Zhou, Zhongqi Liu","doi":"10.1007/s11571-026-10503-6","DOIUrl":"10.1007/s11571-026-10503-6","url":null,"abstract":"The brain's higher cognitive functions rely on the dynamic integration of multimodal information, supported by coordinated neural oscillations. However, current neuromodulation approaches often fail to reliably control these dynamics due to high inter-individual variability and limited mechanistic grounding. To address this challenge, we introduce the Synergistic Entrainment Framework, which conceptualizes the brain as a dynamical system in which neural oscillations create periodic windows of excitability that regulate when information can be effectively processed. Within this framework, rhythmic inputs from different physical modalities (e.g., sensory streams and electromagnetic stimulation) can interact nonlinearly, leading to amplification or stabilization of neural responses, when their timing is aligned with ongoing cortical phase dynamics. We propose that this interaction operates across three coupled scales: (i) microscopic constructive interference that amplifies local neural responses, (ii) mesoscopic phase resetting that aligns regional excitability, and (iii) macroscopic network synchronization constrained by the brain's structural connectome. By explicitly linking these multiscale mechanisms, we propose the framework as a theoretical perspective and operational scaffold for formulating testable hypotheses about state-dependent, closed-loop neuromodulation. Rather than claiming empirical validation, it aims to organize operational criteria for future studies of how stimulation timing may be aligned with intrinsic brain dynamics.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"134"},"PeriodicalIF":4.5,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13356205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148430078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A geometric rs-fMRI connectome descriptor reveals individual stability without robust autism group differences. 几何rs-fMRI连接体描述符揭示了个体的稳定性，没有明显的自闭症组差异。

IF 4.5 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2026-10-08 DOI: 10.1007/s11571-026-10563-8

Sai Prasanna M S, Senthil Thilak A

{"title":"A geometric rs-fMRI connectome descriptor reveals individual stability without robust autism group differences.","authors":"Sai Prasanna M S, Senthil Thilak A","doi":"10.1007/s11571-026-10563-8","DOIUrl":"https://doi.org/10.1007/s11571-026-10563-8","url":null,"abstract":"Autism spectrum disorder (ASD) has resisted reproducible case-control characterization in resting-state functional connectivity, leaving open whether reported group differences reflect genuine biology or methodological variability. We introduce a geometric framework that represents functional connectomes on the symmetric positive-definite Riemannian manifold and quantifies individual deviation as tangent-space dispersion, complemented by normative modeling of graph topology. Using the multi-site Autism Brain Imaging Data Exchange (ABIDE I) cohort (N=1035 subjects), we evaluate this descriptor under stringent robustness conditions and report three findings. First, individual connectome geometry is a stable, individually unique descriptor. The magnitude of a subject's deviation is highly reliable across split halves (intraclass correlation ICC[Formula: see text]) but is dominated by an acquisition-site scale, whereas its high-dimensional shape identifies subjects within-session with 98.9% accuracy once that scale is removed. Second, the case-control difference in dispersion is null and, by two one-sided equivalence tests against Cohen's d = 0.2, statistically equivalent to zero in all ABIDE I analysis cohorts (full cohort d = -0.007, N = 1035; strict cohort d = +0.038, N = 635); a nominal single-atlas effect (dispersion ratio 1.05, p = 0.046) does not survive multi-atlas reanalysis. Third, acquisition site explains 69% of dispersion variance while diagnosis explains 0.0001%; deviations form no discrete subtypes and do not predict symptom severity (minimum p=0.15 across tested graph-deviation predictors). Geometric dispersion is therefore a reproducible, individually unique connectome descriptor but not a case-control biomarker of ASD, which helps to explain the inconsistency of connectomic findings in autism.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"199"},"PeriodicalIF":4.5,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13650096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149164300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multimodal biometric authentication systems: exploring EEG and signature. 多模态生物识别认证系统：探索脑电图和签名。

IF 3.9 3区工程技术

Cognitive Neurodynamics Pub Date : 2026-12-01 Epub Date: 2025-12-06 DOI: 10.1007/s11571-025-10389-w

Banee Bandana Das, Chinthala Varnitha Reddy, Ujwala Matha, Chinni Yandapalli, Saswat Kumar Ram

{"title":"Multimodal biometric authentication systems: exploring EEG and signature.","authors":"Banee Bandana Das, Chinthala Varnitha Reddy, Ujwala Matha, Chinni Yandapalli, Saswat Kumar Ram","doi":"10.1007/s11571-025-10389-w","DOIUrl":"https://doi.org/10.1007/s11571-025-10389-w","url":null,"abstract":"Biometric traits are unique characteristics of an individual's body or behavior that can be used for identification and authentication. Biometric authentication uses unique physiological and behavioral traits for secure identity verification. Traditional unimodal biometric authentication systems often suffer from spoofing attacks, sensor noise, forgery, and environmental dependencies. To overcome these limitations, our work presents multimodal biometric authentication integrated with the characteristics of electroencephalograph (EEG) signals and handwritten signatures to enhance security, efficiency, and robustness. EEG-based authentication uses the brainwave patterns' intrinsic and unforgeable nature, while signature recognition demonstrates an additional behavioral trait for effectiveness. Our system processes EEG data of an individual with 14-channel readings, and the signature with the images ensures a seamless fusion of both modalities.Combining physiological and behavioral biometrics, our approach will significantly decrease the risk of unimodal authentication, including forgery, spoofing, and sensor failures. Our system, evaluated on a dataset of 30 subjects with genuine and forged data, demonstrates a 97% accuracy. Designed for small organizations, the modular structure, low computation algorithms, and simplicity of the hardware promote deployment scalability.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"20 1","pages":"17"},"PeriodicalIF":3.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12681505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145707485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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