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"theoretical analysis"
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EEG-based functional and effective connectivity patterns during emotional episodes using graph theoretical analysis
Understanding the neural mechanisms underlying emotional processing is critical for advancing neuroscience and mental health interventions. This study examined these mechanisms by analyzing EEG connectivity patterns across different brain regions while participants evoked various emotions. After applying independent component analysis (ICA) to eliminate non-cortical activity, we assessed frequency-specific connectivity patterns using coherence, Granger causality, and graph theoretical measures to evaluate both functional and effective connectivity. Graph theoretical analysis revealed significant differences in connectivity between emotions across multiple frequency bands, particularly in the delta and beta bands. These results indicated modulations in key brain regions, such as the precentral, superior frontal, and temporal areas, suggesting that these regions play a crucial role in emotional processing. Coherence analysis demonstrated predominant alpha band activity across all emotions, with specific emotional states, such as fear, grief, and jealousy, exhibiting enhanced beta band activity. In terms of coherence strength, we observed that the gamma band was largely inactive, except for the emotion of sadness, which displayed significant activity in the right lobe, particularly in regions such as the supplementary motor area and the lingual gyrus. Additionally, Granger causality analysis highlighted that the beta and gamma bands were dominant across all emotional states, with minimal modulation observed in the theta band. Clustering coefficients from the graph analysis further revealed distinct patterns of connectivity in the delta and beta bands, with significant variations across different emotions, particularly in the temporal and frontal regions. These findings enhance our understanding of emotional processing and have practical applications in mental health, biomarker identification, and human-computer interaction.
Journal Article
A proposal for the theoretical analysis of the interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations
Mega-urban agglomerations are strategic core areas for national economic development and the main regions of new urbanization. They also have important roles in shifting the global economic center of gravity to China. However, the development of mega-urban agglomerations has triggered the interactive coercion between resources and the eco-envi- ronment. The interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations represent frontier and high-priority research topics in the field of Earth system science over the next decade. In this paper, we carried out systematic theo- retical analysis of the interactive coupling mechanisms and coercing effects between ur- banization and the eco-environment in mega-urban agglomerations. In detail, we analyzed the nonlinear-coupled relationships and the coupling characteristics between natural and human elements in mega-urban agglomerations. We also investigated the interactive coercion intensities between internal and external elements, and the mechanisms and patterns of local couplings and telecouplings in mega-urban agglomeration systems, which are affected by key internal and external control elements. In addition, we proposed the interactive coupling theory on urbanization and the eco-environment in mega-urban agglomerations. Furthermore we established a spatiotemporal dynamic coupling model with multi-element, multi-scale, multi-scenario, multi-module and multi-agent integrations, which can be used to develop an intelligent decision support system for sustainable development of mega-urban agglomera- tions. In general, our research may provide theoretical guidance and method support to solve problems related to mega-urban agglomerations and maintain their sustainable development.
Journal Article
Disrupted topological organization of functional brain networks is associated with cognitive impairment in hypertension patients: a resting-state fMRI study
Purpose
To investigate the alterations of topological organization of the whole brain functional networks in hypertension patients with cognitive impairment (HTN-CI) and characterize its relationship with cognitive scores.
Methods
Fifty-seven hypertension patients with cognitive impairment and 59 hypertension patients with normal cognition (HTN-NC), and 49 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Graph theoretical analysis was used to investigate the altered topological organization of the functional brain networks. The global topological properties and nodal metrics were compared among the three groups. Network-based statistic (NBS) analysis was used to determine the connected subnetwork. The relationships between network metrics and cognitive scores were also characterized.
Results
HTN-CI patients exhibited significantly decreased global efficiency, lambda, and increased shortest path length when compared with HCs. In addition, both HTN-CI and HTN-NC groups exhibited altered nodal degree centrality and nodal efficiency in the right precentral gyrus. The disruptions of global network metrics (lambda, Lp) and the nodal metrics (degree centrality and nodal efficiency) in the right precentral gyrus were positively correlated with the MoCA scores in HTN-CI. NBS analysis demonstrated that decreased subnetwork connectivity was present both in the HTN-CI and HTN-NC groups, which were mainly involved in the default mode network, frontoparietal network, and cingulo-opercular network.
Conclusion
This study demonstrated the alterations of topographical organization and subnetwork connectivity of functional brain networks in HTN-CI. In addition, the global and nodal network properties were correlated with cognitive scores, which may provide useful insights for the understanding of neuropsychological mechanisms underlying HTN-CI.
Journal Article
An Improved Backoff Scheme and Its Performance Analysis for Full Duplex MAC Protocols in VLC Networks
IEEE 802.15.7 Visible Light Communication (VLC) networks suffer from performance degradation caused by the hidden device collisions due to the directional transmission with narrow beamwidth. One of the solutions for mitigating the hidden device collisions is to employ a full-duplex transmission technique. As a side effect of the full-duplex transmission in the VLC networks, however, the data-packet discard due to the retransmission limitation occurs frequently in the networks. This paper proposes an improved backoff scheme and its performance analysis to suppress the packet discard. The proposed backoff scheme increases the Backoff Exponent (BE) and the Number of Backoff stage (NB) in IEEE 802.15.7 only when the data packet transmission fails. To evaluate the system performance theoretically, this paper also provides the Markov-chain model for channel access with the proposed scheme. The performance evaluations through simulation and theoretical analysis show the effectiveness of the proposed scheme.
Journal Article
Impact of policy incentives on electric vehicles development: a system dynamics-based evolutionary game theoretical analysis
A system dynamics-based evolutionary game theoretical analysis is proposed to examine the impact of policy incentives, i.e., price subsidy and taxation preference on electric vehicles (EVs) industry development. Two case scenarios were used to distinguish policy performance by dividing it into a static and dynamic incentive. The result reflected that the game in implementation of the static incentive policy did not achieve stable equilibrium, indicating that such a policy is not effective for driving the development of the EVs industry. However, the game had stable equilibrium when dynamic incentive policy was implemented. The taxation preference had better performance in incentivizing EVs production than the direct subsidy. The study is expected to provide insight into policy making in the industrial transition toward low-carbon consumption. Limitations are given to indicate opportunities for further research.Graphical abstract
Journal Article
Alterations of gray matter volume and structural covariance network in unilateral frontal lobe low-grade gliomas
Purpose
To explore the alterations of gray matter volume (GMV) and structural covariant network (SCN) in unilateral frontal lobe low-grade gliomas (FLGGs).
Materials and methods
The three dimensional (3D) T1 structural images of 117 patients with unilateral FLGGs and 68 age- and sex-matched healthy controls (HCs) were enrolled. The voxel-based morphometry (VBM) analysis and graph theoretical analysis of SCN were conducted to investigate the impact of unilateral FLGGs on the brain structure. This represents the first structural MRI study integrating both voxel-level morphometric changes and network-level reorganization patterns in unilateral FLGGs.
Results
Through VBM analysis, we found that unilateral FLGGs can cause increased GMV in contralesional amygdala, calcarine, and angular gyrus, ipsilesional amygdala as well as vermis_6. The SCN of contralesional cerebrum, ipsilesional unaffected regions and cerebellum in both patients and HCs have typical small-world properties (Sigma > 1, Lambda ≈ 1 and Gamma > 1). Compared to HCs, global and nodal network metrics changed significantly in patients.
Conclusion
The combination of VBM and SCN analysis revealed both focal GMV enlargement and topological alterations in patients with unilateral FLGGs, and provide a novel perspective of cross regional morphological collaborative changes for understanding the glioma-related neuroadaptation. These findings may suggest potential neuroimaging correlates of adaptive changes, which could inform future investigations into personalized treatment approaches.
Clinical trial number
Not applicable.
Journal Article
Finite Element Analysis of Hysteretic Behavior of Superposed Shear Walls Based on OpenSEES
The superimposed slab shear wall has been found to be more and more applicable in the building construction industry due to its building industrialization superiority. The hysteretic behavior of superimposed slab shear walls accounts for an important part of seismic performance analysis. This paper presents the results of a numerical study to investigate the hysteretic behavior of superimposed slab shear walls. Different calculation methods of the shear capacity of the combined interface and horizontal connection are introduced. The calculated results show that the shear capacity of the combined interface and horizontal connection is much larger than the ultimate shear capacity of a superimposed slab shear wall. Therefore, the bond slip effect of a combined interface and horizontal connection can be ignored in finite element analysis on the premise of it not affecting calculation precision. Three different theoretical analysis models, namely the vertical multi-line element model, bend–shear coupled fiber model and layered shell element model, were established in OpenSEES based on a macro-model and a micro-model. The results show that the calculated results of the vertical multi-line element model and the bend–shear coupled fiber model agree reasonably with the experiment results, whereas the calculated results of the layered shell model gave a relatively larger initial stiffness.
Journal Article
Modeling, analysis and experimental verification of two non-electrolytic capacitor Z-source converters
This paper gives a detailed theoretical analysis of two popular non-electrolytic capacitor NEC–Z-source converters (NEC–ZSCs) including analyses of their operation, the voltage stresses of the capacitors and diodes, the current stresses of the inductors, the voltage and current stresses of the switches, and the voltage gain with and without considering parasitic parameters. Parameter design and small signal modeling of NEC–ZSCs are conducted, and a proportional–integral (PI) controller is designed to form the closed-loop control circuit. Simulations and experiments are conducted and their results are collected and analyzed. These results corroborate the feasibility and effectiveness of the theoretical analysis for the two NEC–ZSCs and the closed-loop control design.
Journal Article
Brain structural networks and connectomes: the brain-obesity interface and its impact on mental health
Obesity is a complex and multifactorial disease identified as a global epidemic. Convergent evidence indicates that obesity differentially influences patients with neuropsychiatric disorders providing a basis for hypothesizing that obesity alters brain structure and function associated with the brain's propensity toward disturbances in mood and cognition. Herein, we characterize alterations in brain structures and networks among obese subjects (ie, body mass index [BMI] ≥30 kg/m
) when compared with non-obese controls.
We obtained noninvasive diffusion tensor imaging and generalized q-sampling imaging scans of 20 obese subjects (BMI=37.9±5.2 SD) and 30 non-obese controls (BMI=22.6±3.4 SD). Graph theoretical analysis and network-based statistical analysis were performed to assess structural and functional differences between groups. We additionally assessed for correlations between diffusion indices, BMI, and anxiety and depressive symptom severity (ie, Hospital Anxiety and Depression Scale total score).
The diffusion indices of the posterior limb of the internal capsule, corona radiata, and superior longitudinal fasciculus were significantly lower among obese subjects when compared with controls. Moreover, obese subjects were more likely to report anxiety and depressive symptoms. There were fewer structural network connections observed in obese subjects compared with non-obese controls. Topological measures of clustering coefficient (C), local efficiency (E
), global efficiency (E
), and transitivity were significantly lower among obese subjects. Similarly, three sub-networks were identified to have decreased structural connectivity among frontal-temporal regions in obese subjects compared with non-obese controls.
We extend knowledge further by delineating structural interconnectivity alterations within and across brain regions that are adversely affected in individuals who are obese.
Journal Article