Enhanced group-level dorsolateral prefrontal cortex subregion parcellation through functional connectivity-based distance-constrained spectral clustering with application to autism spectrum disorder.

The dorsolateral prefrontal cortex (DLPFC) assumes a central role in cognitive and behavioral control, emerging as a crucial target region for interventions in autism spectrum disorder neuroregulation. Consequently, we endeavor to unravel the functional subregions within the DLPFC to shed light on the intricate functions of the brain. We introduce a distance-constrained spectral clustering (SC-DW) methodology that leverages functional connection to identify distinctive functional subregions within the DLPFC. Furthermore, we verify the relationship between the functional characteristics of these subregions and their clinical implications. Our methodology begins with principal component analysis to extract the salient features. Subsequently, we construct an adjacency matrix, which is constrained by the spatial properties of the brain, by linearly combining the distance matrix and a similarity matrix. The quality of spectral clustering is further optimized through multiple cluster evaluation coefficient. The results from SC-DW revealed four uniform and contiguous subregions within the bilateral DLPFC. Notably, we observe a substantial positive correlation between the functional characteristics of the third and fourth subregions in the left DLPFC with clinical manifestations. These findings underscore the unique insights offered by our proposed methodology in the realms of brain subregion delineation and therapeutic targeting.

Quantifying solid waste and recycling employment in Florida, USA: Trends in public and private sectors.

Measuring and tracking the numbers of jobs in solid waste management and recycling industries over time provide basic data to inform decision makers about the important role played by this sector in a state or region's 'green economy'. This study estimates the number of people employed in the solid waste and recycling industry from 1989 through 2011 in the state of Florida (USA), applying a classification scheme based on the Standard Industrial Code (SIC) and utilizing the National Establishment Time Series (NETS) database. The results indicate that solid waste and recycling jobs in the private sector steadily increased from 1989 to 2011, whereas government employment for solid waste management fluctuated over the same period.

Sensory and motor cortices parcellations estimated via distance-weighted sparse representation with application to autism spectrum disorder.

BACKGROUND: Motor impairments and sensory processing abnormalities are prevalent in autism spectrum disorder (ASD), closely related to the core functions of the primary motor cortex (M1) and the primary somatosensory cortex (S1). Currently, there is limited knowledge about potential therapeutic targets in the subregions of M1 and S1 in ASD patients. This study aims to map clinically significant functional subregions of M1 and S1. METHODS: Resting-state functional magnetic resonance imaging data (NTD = 266) from Autism Brain Imaging Data Exchange (ABIDE) were used for subregion modeling. We proposed a distance-weighted sparse representation algorithm to construct brain functional networks. Functional subregions of M1 and S1 were identified through consensus clustering at the group level. Differences in the characteristics of functional subregions were analyzed, along with their correlation with clinical scores. RESULTS: We observed symmetrical and continuous subregion organization from dorsal to ventral aspects in M1 and S1, with M1 subregions conforming to the functional pattern of the motor homunculus. Significant intergroup differences and clinical correlations were found in the dorsal and ventral aspects of M1 (p < 0.05/3, Bonferroni correction) and the ventromedial BA3 of S1 (p < 0.05/5). These functional characteristics were positively correlated with autism severity. All subregions showed significant results in the ROI-to-ROI intergroup differential analysis (p < 0.05/80). LIMITATIONS: The generalizability of the segmentation model requires further evaluation. CONCLUSIONS: This study highlights the significance of M1 and S1 in ASD treatment and may provide new insights into brain parcellation and the identification of therapeutic targets for ASD.

The Impact of Collaboration Network on Water Resource Governance Performance: Evidence from China's Yangtze River Delta Region.

Existing studies rarely examine the relationship between network structure and network performance. To fill this research gap, this article collects inter-local collaboration network data from 41 cities in the Yangtze River Delta region of China from 2009 to 2015. Based on the institutional collective action framework and social capital theory, we propose bridging and bonding hypotheses regarding the impact of network structures on governance performance. We employ social network analysis and panel data regression models to test the hypotheses. The results show that the coefficients for closeness centrality and clustering coefficient are statistically significant in this analysis, Wuxi played a central role in the collaboration network and the region had formed a close partner network, confirming the positive effect of bridging and bonding network social capital structures on network performance.

What Drives the Performance of Collaboration Networks: A Qualitative Comparative Analysis of Local Water Governance in China.

Local water governance is challenging given the significance to public health and the difficulties to manage it in a fragmented administrative system. A collaboration network is a popular governance tool in local governance to cope with functional fragmentation problems and institutional collective action (ICA) dilemmas. Empirical works are needed to examine the outcomes of such governance networks, especially in the context of environmental governance. With fuzzy-set qualitative comparative analysis (fsQCA), this article seeks to evaluate the outcomes of collaboration networks by investigating the influence of network structures on local water governance performance in China. Based on empirical analyses on a dataset of twenty local water governance networks implementing the Water Ecological Civilization Pilot Project in China, the findings suggest that a high overall bridging and bonding of social capital and a low network density are important determinants of effective collaboration networks. This study has policy implications for the design of local collaboration networks in facilitating effective environmental governance.

What Affects the Diffusion of New Energy Vehicles Financial Subsidy Policy? Evidence from Chinese Cities.

Designing and implementing effective new energy vehicle (NEV) policy are policy priorities for policymakers and energy policy scholars. However, the formulation, adoption, and diffusion of the NEV policies have not been fully examined in the extant literature. This article explores the mechanisms driving the diffusion of local financial subsidy policy for NEVs in China. In this context, we aim at analyzing the factors affecting the diffusion of local financial subsidies for NEVs in cities, to explain why some cities have taken the lead in adopting local financial subsidy policies for NEVs, while other cities have lagged behind. Based on a data set of 286 cities in China from 2009 to 2016, and with event history analysis (EHA) to analyze the strategic behaviors of local governments, we found that the number of the city's neighbors that have adopted the NEV policy, the financial incentive policy of the provincial government, the administrative ranking of the city, the city's financial situation and innovation capacity have a direct impact on whether the city adopts a local financial subsidy policy for NEVs. This study has practical implications for policymakers in designing and promoting the spread of NEV policies.

Evaluating the employment impact of recycling performance in Florida.

Recycling solid waste not only produces environmental and health benefits, but also generates economic benefit. This paper empirically evaluates the employment impact of Florida county recycling programs from 2000 through 2011, applying a fixed effects regression model. The results indicate that a one percentage point increase of county recycling rate leads to a 0.4% job growth in overall solid waste and recycling industry. However, the impact of recycling programs on green jobs are not uniform across the recycling subsectors: the effect is concentrated in the recycling processing sector while the solid waste collection sector and scrap materials businesses are unlikely to be influenced by county's recycling performance.