Characteristic Path Research Articles

Functional Connectivity Alterations in Patients with Post-stroke Epilepsy Based on Source-level EEG and Graph Theory.

We investigated the differences in functional connectivity based on the source-level electroencephalography (EEG) analysis between stroke patients with and without post-stroke epilepsy (PSE). Thirty stroke patients with PSE and 35 stroke patients without PSE were enrolled. EEG was conducted during a resting state period. We used a Brainstorm program for source estimation and the connectivity matrix. Data were processed according to EEG frequency bands. We used a BRAPH program to apply a graph theoretical analysis. In the beta band, radius and diameter were increased in patients with PSE than in those without PSE (2.699 vs. 2.579, adjusted p = 0.03; 2.261 vs. 2.171, adjusted p = 0.03). In the low gamma band, radius was increased in patients with PSE than in those without PSE (2.808 vs. 2.617, adjusted p = 0.03). In the high gamma band, the radius, diameter, average eccentricity, and characteristic path length were increased (1.828 vs. 1.559, adjusted p < 0.01; 2.653 vs. 2.306, adjusted p = 0.01; 2.212 vs. 1.913, adjusted p < 0.01; 1.425 vs. 1.286, adjusted p = 0.01), whereas average strength, mean clustering coefficient, and transitivity were decreased in patients with PSE than in those without PSE (49.955 vs. 55.055, adjusted p < 0.01; 0.727 vs. 0.810, adjusted p < 0.01; 1.091 vs. 1.215, adjusted p < 0.01). However, in the delta, theta, and alpha bands, none of the functional connectivity measures were different between groups. We demonstrated significant alterations of functional connectivity in patients with PSE, who have decreased segregation and integration in brain network, compared to those without PSE.

Graph-Based Interpretability for Fake News Detection through Topic- and Propagation-Aware Visualization

In the context of the increasing spread of misinformation via social network services, in this study, we addressed the critical challenge of detecting and explaining the spread of fake news. Early detection methods focused on content analysis, whereas recent approaches have exploited the distinctive propagation patterns of fake news to analyze network graphs of news sharing. However, these accurate methods lack accountability and provide little insight into the reasoning behind their classifications. We aimed to fill this gap by elucidating the structural differences in the spread of fake and real news, with a focus on opinion consensus within these structures. We present a novel method that improves the interpretability of graph-based propagation detectors by visualizing article topics and propagation structures using BERTopic for topic classification and analyzing the effect of topic agreement on propagation patterns. By applying this method to a real-world dataset and conducting a comprehensive case study, we not only demonstrated the effectiveness of the method in identifying characteristic propagation paths but also propose new metrics for evaluating the interpretability of the detection methods. Our results provide valuable insights into the structural behavior and patterns of news propagation, contributing to the development of more transparent and explainable fake news detection systems.

Housing-industry transformation development and rural revitalization path based on complex adaptive system in Three Gorges Reservoir Area of China

The core of dual circulation in the Three Gorges Reservoir Area (TGRA) and the greening Yangtze River is sustainable development. Reservoir housing-industry coordinate sustainable is extremely important to ensuring a more sustainable TGRA. Here, we investigate the overall characteristics of housing-industry transformation development and rural revitalization path in the TGRA at microscopic perspective. Taking Wutu village (WTV), a historical and cultural rural in the TGRA, as case study area, we also analyze the evolution, stage characteristics, and trends of housing-industry system (HIS) using theoretical analysis and empirical research from the perspective of spatio-temporal-development and complex adaptability system model. The findings reveal that: (1) In the traditional housing-industry separation stage(1978–1998), the development of villagers' self-organization and the positive and correct leadership of the village party branch are the dominant forces for the evolution of HIS in WTV. The adaptive behavior of the main body and the strength of the housing-industry effect are limited, and the evolution of the HIS is in the accumulation stage of quantitative change. (2) In the stage of cooperative transformation of housing-industry (1999–2018), the positive and correct leadership of the village party branch is the dominant force of the evolution of HIS in WTV, and the government's policy support is the main force of the evolution of HIS in WTV. (3) In the stage of modern housing-industry integration (2019 to present), the interaction of multiple subjects is the dominant force in the evolution of HIS in WTV. Multiple entities further adapt to various changes in the external environment, and the system structure and level have taken a qualitative leap. Overall, the evolution of HIS in WTV is a dynamic and continuous process. Based on the evolution stage and driving mechanism of HIS, it is necessary to improve the self-organization and adaptive response and ability of the complex adaptive system in WTV, adapt to the general law of system evolution, and effectively regulate the transformation and upgrading of HIS in WTV. Our research outcomes offer valuable insights for fostering rural transformation, enhancing the housing-industry environment, and ultimately propelling the TGRA towards a more sustainable and prosperous future.

Graph theory-based analysis reveals neural anatomical network alterations in chronic post-traumatic stress disorder

Abstract Multimodal imaging using network connectivity techniques shows promise for investigating neuropathology influencing Post-Traumatic Stress Disorder (PTSD) symptom maintenance and course. We recruited World Trade Center (WTC) responders who continued to suffer from chronic PTSD into a diffusion tensor neuroimaging protocol (n=100), along with nine unexposed controls without PTSD from other sources. Using a graph theory approach to probe network alterations in brain diffusion images, we calculated weighted characteristics path length as a surrogate marker for the effective neuroanatomical distance between anatomical nodes. The sample (N=109; 47 with chronic PTSD) was in their mid-fifties, and the majority were male. Responders were matched in terms of cognitive performance, occupation, and demographics. The anatomical connectivity graph was constructed for each participant using deterministic diffusion tractography. We identified a significant difference in weighted Characteristic Path Length (wCPL) between trauma-exposed WTC responders (Cohen’s d = 0.42, P&amp;lt;0.001) that was highest in people with PTSD, and not explained by WTC exposure severity or duration. We also found that wCPL was associated with PTSD symptom severity in responders with PTSD. In the largest study to date to examine the relationship between chronic PTSD and anatomy, we examined the anatomical topography of neural connections and found that wCPL differed between the PTSD+ and PTSD- diagnostic categories.

Mathematical model of an antenna-waveguide path with signal separation by polarization – frequency

Background. The need to create antenna-waveguide paths for multi-band reflector antennas of satellite communication systems requires the use of various methods for selecting the structure, determining and optimizing the parameters of antenna-waveguide paths.&#x0D; Aim. Development of a mathematical model of antenna-waveguide paths of multi-band reflector antennas, built on the basis of the «polarization separation – frequency separation» method with the implementation of the auto-tracking function.&#x0D; Methods. A mathematical model of antenna-waveguide paths of multi-band reflector antennas, built on the basis of the «polarization separation – frequency separation» method, allows us to determine the main characteristics of antenna-waveguide paths and incoming devices with an auto-tracking function.&#x0D; Results. The main elements of the mathematical model of multi-band antenna-waveguide paths built on the basis of the «polarization separation – frequency separation» method are determined.&#x0D; Conclusion. A mathematical model has been proposed that makes it possible to reduce the requirements for the computing tools used when developing antenna-waveguide paths in terms of RAM capacity and performance. The ability to analyze and determine the characteristics of antenna-waveguide paths using a mathematical model has been implemented. The stages of determining the parameters of antenna-waveguide paths are presented, based on the developed mathematical model of the corresponding design option, as well as theoretical and experimental data confirming the correctness of the model of antenna-waveguide paths.

Increased Thalamic Connectivity in Juvenile Myoclonic Epilepsy Based on Electroencephalography Source-Level Analysis.

Background: This study investigated alterations in the intrinsic thalamic network of patients with juvenile myoclonic epilepsy (JME) based on an electroencephalography (EEG) source-level analysis. Materials and Methods: We enrolled patients newly diagnosed with JME as well as healthy controls. The assessments were conducted in the resting state. We computed sources based on the scalp electrical potentials using a minimum-norm imaging method and a standardized, low-resolution, brain electromagnetic tomography approach. To create a functional connectivity matrix, we used the Talairach atlas to define thalamic nodes and applied the coherence method to measure brain synchronization as edges. We then calculated the intrinsic thalamic network using graph theory. We compared the intrinsic thalamic network of patients with JME with those of healthy controls. Results: This study included 67 patients with JME and 66 healthy controls. EEG source-level analysis revealed significant differences in the intrinsic thalamic networks between patients with JME and healthy controls. The measures of functional connectivity (radius, diameter, and characteristic path length) were significantly lower in patients with JME than in healthy controls (radius: 2.769 vs. 3.544, p = 0.015; diameter: 4.464 vs. 5.443, p = 0.024; and characteristic path length: 2.248 vs. 2.616, p = 0.046). Conclusions: We demonstrated alterations in the intrinsic thalamic network in patients with JME compared with those in healthy controls based on the EEG source-level analysis. These findings indicated increased thalamic connectivity in the JME group. These intrinsic thalamic network changes may be related to the pathophysiology of JME.

Study on the Characteristic Path of Transformation and Development of Resource-Based Cities in China

Study on the Characteristic Path of Transformation and Development of Resource-Based Cities in China

Temperature difference and systemic risk: Evidence from LASSO-VAR-DY based on China's pan-financial market.

Climate change-induced pan-financial market and the contagion of systemic financial risks are becoming important issues in the financial sector. The paper measures the temperature difference in terms of the degree and direction of deviation of the actual temperature relative to the average temperature of the same historical period. Based on the high-dimensional time-series variable LASSO-VAR-DY framework, we construct a pan-financial market volatility correlation network consisting of 112 Chinese listed companies in banking, insurance, securities, real estate, traditional energy, and new energy, use eigenvector centrality to measure the systematic risk of each firm, and then empirically test the effect of temperature difference on systematic risk under pan-financial market scenario. The results of the study show that (ⅰ) There is a significant difference among the systemic risk of financial sectors such as banking, insurance, and securities in the financial market pan-financial market scenario and the systemic risk when the financial market pan-financial market is not taken into account;(ⅱ) Higher temperature significantly exacerbates systemic financial risk, while colder temperature significantly mitigates systemic risk, but both have an asymmetric effect on systemic risk, and there is sectoral heterogeneity.(ⅲ) From the dynamic evolutionary characteristics, there are significant differences in the response of systemic financial risk to positive and negative temperature shocks;(iv) The results of the systemic risk variance decomposition indicate that the temperature change contributes more to the variance of systemic risk in the banking and securities sectors in pan-financial market;(ⅴ) The contagion source of financial systemic risk shows an obvious path of leaping and changing characteristics, and the contagion source of systemic risk (source of impact) shows the evolution law of "bank → real estate → new energy → temperature difference," which means that the temperature difference has become the contagion source of systemic financial risk. This study provides a reference for preventing and resolving systemic risks under pan-financial market scenario and provides a basis for improving the current macroprudential regulatory framework.

Numerical Study on the Self-Pulsation Characteristics of LOX/GH2 Swirl Coaxial Injector

To investigate the self-pulsation characteristics of a liquid-centered swirl coaxial injector with liquid oxygen (LOX) and gas hydrogen (GH2) as the working mediums under supercritical condition, a numerical simulation was employed. The transient simulation of the flow and injection process of cryogenic propellant was carried out using the RNG k−ε turbulence model, VOF model, and Peng-Robinson equation of state. The frequency spectrum of calculated pressure oscillation agreed with the experimental data. The amplitude-frequency characteristics of recess region, LOX, and GH2 paths when self-pulsation occurs were analyzed. The effects of operating parameters, such as the flow rate of LOX or GH2 and the initial GH2 temperature, on the self-pulsation, were evaluated specifically. Results reveal that the self-pulsation results from the periodic variation of pressure and velocity caused by the periodic blocking of annular gas by the liquid sheet. The dominant frequencies of pressure oscillation in the recess region, upstream of LOX, or GH2 path are diverse. But for the points in each region, the dominant frequency is about the same. When the LOX/GH2 mixing ratio increases, the liquid sheet thickness and the number of liquid filaments increase. The position where filaments are massively broken into droplets moves further downstream. For the same mixing ratio, the flow rate of LOX has a greater impact on the atomization features. The pressures corresponding to low or high frequency increase when the initial GH2 temperature raises. The higher temperature would shift the dominant oscillation between the low and high regimes.

Effect of blood oxygen-level-dependent signal data trimming on functional connectivity metrics

In the big data era, with a lack of comparable functional neuroimaging data, researchers try to combine heterogeneous data of different lengths, trimming those to the same number of timepoints (NTPs). However, the effects of trimming blood-oxygen-level dependent (BOLD) signal data on functional connectivity (FC) are still poorly understood.Resting-state functional magnetic resonance imaging data from thirty healthy subjects were pre-processed for five different NTPs, from which FC matrices were computed. These BOLD signal correlation matrices were binarized for several thresholds, excluding weak correlations. Graph metrics were computed to study FC differences between different NTPs. The study included node degree analysis for each brain region and assessment of small-worldness coefficients (σ and ω), whereas in small-world networks, characteristic values are σ > 1 and ω≈ 0, indicating a balance between high clustering coefficients and short characteristic path lengths.A tendency of decreasing global network degrees for higher NTPs was observed, translating the loss of stronger correlations with longer BOLD signals. Trimming such data affects brain regions differently, probably due to brain network dynamics. Regarding small-worldness, we observed that σ was greater than 1 for all the different NTPs, showing an increasing trend for higher NTPs (median value: σBRAIN= 3.05). In addition, ω consistently remained greater than 0 for all NTPs, gradually approaching 0 as the NTPs increased (median value ωBRAIN= 0.20). As such, the results suggest a tendency for an increase of small-world properties for increasing NTPs. Nonetheless, the overall properties of brain networks almost remain constant. In conclusion, trimming BOLD signal data leads to small differences in FC.

What network roles affect the decline of the embodied carbon emission reduction pressure in China's manufacturing sector foreign trade?

China's manufacturing sector faces pressure to reduce its carbon emissions embodied in foreign trade, yet the influence of the sector's structural and path characteristics on reducing embodied carbon emission (ECE) remains unclear. We developed a research framework to analyze the trade-embodied carbon transfer networks of China's 11 manufacturing industries with 48 economies from 2000 to 2019, identifying the key carbon transfer-in industries and paths. By integrating network characteristics, we assessed the ECE reduction pressure on key manufacturing industries and identified factors hindering its decline. ECE in China's manufacturing foreign trade increased by 273.1% from 2000 to 2019, with the ECE in exports to developing countries since 2012 (255.58 Mt) surpassing exports to developed countries (228.31 Mt). China's medium-low and medium-high technology manufacturing are key carbon transfer-in industries, observed large decreases in the importance of the carbon transfer-in paths from Europe, the United States, Japan, and South Korea, versus notable increases from the Row Asia and Pacific region. Metal manufacturing, non-metallic mineral manufacturing, and chemical manufacturing were the top three industries facing ECE reduction pressure. The network structure indicators obstruct the ECE reduction pressure in metal manufacturing, whereas the network path indicators obstruct the pressure in the other key manufacturing industries. To alleviate the ECE reduction pressure within China's manufacturing foreign trade, China's manufacturing sector should enhance trade cooperation with Asia–Pacific countries. The study's insights offer valuable references for China's formulation of domestic manufacturing emission reduction policies and its participation in international climate negotiations.

Residual phase noise measurements of elements of the radio frequency path of radiometric receivers

In this work, the measurement of the residual phase noise of amplifiers and frequency multipliers using frequency doublers and step recovery diodes, were performed utilizing the interferometric method. The results obtained showed the possibility of using the interferometric method in measuring the phase noise of radio frequency paths of radiometric receivers. The measured values of residual phase noise can be used to evaluate the characteristics of the radio frequency paths of receivers.

Spatial Fluctuations of Optical Turbulence Strength in a Laboratory Turbulence Simulator

Controlled turbulence simulators in the laboratory have been extensively employed to investigate turbulence effects on light propagation in the atmosphere, driven by some advanced optical engineering such as remote sensing, energy-delivery systems, and free-space optical communication systems. Many studies have achieved rich results on the optical turbulence intensity, scintillation index, and power spectral density characteristics of the light propagation path in the center of a turbulence simulator, but a comprehensive analysis of the optical turbulence characteristics for different spatial locations is still lacking. We simulate turbulence with air as the medium in a classical convective Rayleigh–Bénard turbulence simulator through high-resolution computational fluid dynamics methods, the three-dimensional refractive index distribution is obtained, and the optical properties are analyzed comprehensively. It is found that the hot and cold plumes and the large-scale circulation strongly influence the inhomogeneity of Cn2 in the turbulence tank, making it weak in the middle and strong near the boundary. The refractive index power spectral density at different heights is centrally symmetric, with the slope gradually deviating from the −5/3 scaling power with increasing distance from the central region. Under the log-log plot, the variation of the refractive index variance with height exhibits a three-segmented feature, showing in order: a stable region, a logarithmic profile, and a power-law profile, in the region close to the boundary. These results will contribute to the construction of a suitable turbulence simulator for optical engineering applications.

Personality and Learning Behavioral Characteristics as Predictors of Academic Achievement of Medical Students

This study investigates whether personality characteristics and learning behaviors can predict medical students’ academic achievement in Korea, specifically in terms of successfully completing medical school without delays or achieving a high grade point average (GPA) in their final year. In May 2018, 316 medical students took the Multi-Dimensional Learning Strategy Test, 2nd edition, which provided data on their personality and learning behavioral characteristics. Their final year’s GPA and any delays in completing medical school were ascertained by reviewing all electronic academic records of each semester they had been enrolled. The combination of personality and learning behavioral characteristics was significantly associated with completing medical school without delays, even after adjusting for sex and admission path. A multiple logistic regression analysis showed that the adjusted odds ratios and 95% confidence intervals for completing medical school without delays were 1.52 (95% confidence interval [CI], 0.83–2.78) and 3.64 (95% CI, 1.70–7.82) for “others” and “both high” categories, respectively, when compared with the “both low” category. For 235 students who completed medical school without delays, their learning behavioral characteristics (scores) were significantly associated with their final year’s GPA even after adjusting for sex, admission path, and personality characteristics (scores) as determined by the multiple linear regression analysis. This study suggests that individual personality and learning behavior characteristics are predictors of medical students’ academic achievement. Therefore, interventions such as personalized counseling programs should be provided in consideration of such student characteristics.

Disrupted small-world white matter networks in patients with major depression and recent suicide plans or attempts.

Suicide is a major concern for health, and depression is an established proximal risk factor for suicide. This study aimed to investigate white matter features associated with suicide. We constructed white matter structural networks by deterministic tractography via diffusion tensor imaging in 51 healthy controls, 47 depressed patients without suicide plans or attempts and 56 depressed patients with suicide plans or attempts. Then, graph theory analysis was used to measure global and nodal network properties. We found that local efficiency was decreased and path length was increased in suicidal depressed patients compared to healthy controls and non-suicidal depressed patients; moreover, the clustering coefficient was decreased in depressed patients compared to healthy controls; and the global efficiency and normalized characteristic path length was increased in suicidal depressed patients compared to healthy controls. Similarly, compared with those in non-suicidal depressed patients, nodal efficiency in the thalamus, caudate, medial orbitofrontal cortex, hippocampus, olfactory cortex, supplementary motor area and Rolandic operculum was decreased. In summary, compared with those of non-suicidal depressed patients, the structural connectome of suicidal depressed patients exhibited weakened integration and segregation and decreased nodal efficiency in the fronto-limbic-basal ganglia-thalamic circuitry. These alterations in the structural networks of depressed suicidal brains provide insights into the underlying neurobiology of brain features associated with suicide.

Electroencephalography oscillations can predict the cortical response following theta burst stimulation

BackgroundContinuous theta burst stimulation and intermittent theta burst stimulation are clinically popular models of repetitive transcranial magnetic stimulation. However, they are limited by high variability between individuals in cortical excitability changes following stimulation. Although electroencephalography oscillations have been reported to modulate the cortical response to transcranial magnetic stimulation, their association remains unclear. This study aims to explore whether machine learning models based on EEG oscillation features can predict the cortical response to transcranial magnetic stimulation. MethodTwenty-three young, healthy adults attended two randomly assigned sessions for continuous and intermittent theta burst stimulation. In each session, ten minutes of resting-state electroencephalography were recorded before delivering brain stimulation. Participants were classified as responders or non-responders based on changes in resting motor thresholds. Support vector machines and multi-layer perceptrons were used to establish predictive models of individual responses to transcranial magnetic stimulation. ResultAmong the evaluated algorithms, support vector machines achieved the best performance in discriminating responders from non-responders for intermittent theta burst stimulation (accuracy: 91.30%) and continuous theta burst stimulation (accuracy: 95.66%). The global clustering coefficient and global characteristic path length in the beta band had the greatest impact on model output. ConclusionThese findings suggest that EEG features can serve as markers of cortical response to transcranial magnetic stimulation. They offer insights into the association between neural oscillations and variability in individuals' responses to transcranial magnetic stimulation, aiding in the optimization of individualized protocols.

Variability of large timescale functional networks in patients with disorders of consciousness.

Most brain function assessments for disorders of consciousness (DOC) utilized quantified characteristics, measured only once, ignoring the variation of patients' brain states. The study aims to investigate the brain activities of patients with DOC from a new perspective: variability of a large timescale functional network. Forty-nine patients were enrolled in this study and performed a 1-week behavioral assessment. Subsequently, each patient received electroencephalography (EEG) recordings five times daily at 2-h intervals. Functional connectivity and networks were measured by weighted phase lag index and complex network parameters (characteristic path length, cluster coefficient, and betweenness centrality). The relative coefficient of variation (CV) of network parameters was measured to evaluate functional network variability. Functional networks of patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS) showed significantly higher segregation (characteristic path length) and lower centrality (betweenness centrality) than emerging from the minimal conscious state (EMCS) and minimal conscious state (MCS), as well as lower integration (cluster coefficient) than MCS. The functional networks of VS/UWS patients consistently presented the highest variability in segregation and integration (i.e., highest CV values of characteristic path length and cluster coefficient) on a larger time scale than MCS and EMCS. Moreover, the CV values of characteristic path length and cluster coefficient showed a significant inverse correlation with the Coma Recovery Scale-Revised scores (CRS-R). The CV values of network betweenness centrality, particularly of the cento-parietal region, showed a positive correlation with the CRS-R. The functional networks of VS/UWS patients present the most invariant segregation and integration but divergent centrality on the large time scale networks than MCS and EMCS. The variations observed within large timescale functional networks significantly correlate with the degree of consciousness impairment. This finding augments our understanding of the neurophysiological mechanisms underpinning disorders of consciousness.

Disrupted properties of functional brain networks in major depressive disorder during emotional face recognition: an EEG study via graph theory analysis.

Previous neuroimaging studies have revealed abnormal brain networks in patients with major depressive disorder (MDD) in emotional processing. While any cognitive task consists of a series of stages, little is yet known about the topology of functional brain networks in MDD for these stages during emotional face recognition. To address this problem, electroencephalography (EEG)-based functional brain networks of MDD patients at different stages of facial information processing were investigated in this study. First, EEG signals were collected from 16 patients with MDD and 18 age-, gender-, and education-matched normal subjects when performing an emotional face recognition task. Second, the global field power (GFP) method was employed to divide group-averaged event-related potentials into different stages. Third, using the phase transfer entropy (PTE) approach, the brain networks of MDD patients and normal individuals were constructed for each stage in negative and positive face processing, respectively. Finally, we compared the topological properties of brain networks of each stage between the two groups using graph theory approaches. The results showed that the analyzed three stages of emotional face processing corresponded to specific neurophysiological phases, namely, visual perception, face recognition, and emotional decision-making. It was also demonstrated that depressed patients showed abnormally decreased characteristic path length at the visual perception stage of negative face recognition and normalized characteristic path length in the stage of emotional decision-making during positive face processing compared to healthy subjects. Furthermore, while both the MDD and normal groups' brain networks were found to exhibit small-world network characteristics, the brain network of patients with depression tended to be randomized. Moreover, for patients with MDD, the centro-parietal region may lose its status as a hub in the process of facial expression identification. Together, our findings suggested that altered emotional function in MDD patients might be associated with disruptions in the topological organization of functional brain networks during emotional face recognition, which further deepened our understanding of the emotion processing dysfunction underlying MDD.

Path length and sediment transport estimation from DEMs of difference: a signal processing approach

Abstract. The difficulties of measuring bedload transport in gravel-bed rivers have given rise to the morphological method wherein sediment transport can be inferred from changes in riverbed elevation and estimates of the distance traveled by sediment: its path length. Because current methods for estimating path length are time- and labor-intensive, we present a method to estimate a characteristic path length from repeat digital elevation models (DEMs of difference, i.e., DoDs). We propose an automated method to extract the spacing between erosional and depositional sites on the DoD by the application of variational mode decomposition (VMD), a signal processing method, to quantify the spacing as a proxy for path length. We developed this method using flume experiments where bed topography and sediment flux were measured and then applied it to published field data with physical path length measured from tracer measurements. Our sediment transport estimates were not significantly different than the measured sediment flux at lower discharges in the lab. However, we observed an underestimation of sediment flux at the higher discharges in the flume study. We interpret this as a limit of the method in confined settings, where sediment transport becomes decoupled from morphological changes. We also explore how the time between survey acquisitions, the morphological active width relative to the channel width, and DoD thresholding techniques affect the proposed method and the potential issues they pose for the morphological method in general.

How to Perceive National Governance Networks in the Global Commons of the Earth’s Surface: A Case Study of the Antarctic

The destiny of mankind is closely intertwined, and exploring new paths for the governance of the global commons of the earth’s surface (GCES) has become a worldwide topic. Thus, this paper attempts to carry out the following work by taking the Antarctic as an example: (1) Identify the characteristics of the governance subjects by using a literature review and the inductive analysis method. (2) Construct a network of responsive relationships among the governance subjects based on the evolutionary game approach. This study found the following: (1) A multi-subject participation in governance, i.e., with the Antarctic Treaty parties as the core, the seven major organizations as the main force, the United Nations as the support, enterprises as the emerging force, and other countries as the potential subjects. (2) Response-relational networks have high clustering coefficients and characteristic path lengths close to those of random networks, with significant small-world features of relational networks. (3) As important components of the benefit function, long-term benefits and benefit intensities together influence cooperative strategies for governance in the Antarctic. In the future, we should actively focus on long-term interests based on the concept of a community with a shared future for mankind, improve the governance structure at the right time, and strive to build a robust globalization.