Low-level Regions Research Articles

Coupled Spatial–Temporal Evolution and Influencing Factors of Chemical Industry Development and Water Environment in Yangtze River Economic Belt

Revealing the coordinated correlation between chemical industry development and the water environment is essential for promoting high-quality development in the Yangtze River Economic Belt. Based on the data in the Yangtze River Economic Belt from 2011 to 2021, this study explores the spatial–temporal evolution and influencing factors of the coupled coordination between chemical industry development and the water environment by using the global entropy method, a coupling coordination model, and the Tobit model. The results indicate a general upward trend in the comprehensive indices of chemical industry development and water environment systems, albeit with distinct spatial patterns. A mismatch between the two systems is observed in terms of spatial distribution. Regarding the coupling coordination degree, the relationship shows an upward trend, primarily at a mild-to-moderate coupling stage, exhibiting a spatial pattern of “downstream > midstream > upstream”. Moreover, a trend of increasing coordination and narrowing disparities between high- and low-level regions can be observed. The model results suggest that environmental regulation, economic development, government capacity, and urbanization play a crucial role in promoting the coupled development of the chemical industry and the water environment. However, openness to external markets may not enhance coupled coordination. These findings may provide policy guidance for the development status of two subsystems in other locations.

Spontaneous cortical activity is altered in persons with HIV and related to domain-specific cognitive function.

Whilst the average lifespan of persons with HIV now approximates that of the general population, these individuals are at a much higher risk of developing cognitive impairment with ∼35-70% experiencing at least subtle cognitive deficits. Previous works suggest that HIV impacts both low-level primary sensory regions and higher-level association cortices. Notably, multiple neuroHIV studies have reported elevated levels of spontaneous cortical activity during the pre-stimulus baseline period of task-based experiments, but only a few have examined such activity during resting-state conditions. In the current study, we examined such spontaneous cortical activity using magnetoencephalography in 79 persons with HIV and 83 demographically matched seronegative controls and related this neural activity to performance on neuropsychological assessments of cognitive function. Consistent with previous works, persons with HIV exhibited stronger spontaneous gamma activity, particularly in inferior parietal, prefrontal and superior temporal cortices. In addition, serostatus moderated the relationship between spontaneous beta activity and attention, motor and processing speed scores, with controls but not persons with HIV showing stronger beta activity with better performance. The current results suggest that HIV predominantly impacts spontaneous activity in association cortices, consistent with alterations in higher-order brain function, and may be attributable to deficient GABAergic signalling, given its known role in the generation of gamma and beta oscillations. Overall, these effects align with previous studies showing aberrant spontaneous activity in persons with HIV and provide a critical new linkage to domain-specific cognitive dysfunction.

Hierarchical Gradients of Encoded Spatial and Sensory Information in the Neocortex Are Attenuated by Dorsal Hippocampal Lesions.

During navigation, the neocortex actively integrates learned spatial context with current sensory experience to guide behaviors. However, the relative encoding of spatial and sensorimotor information among cortical cells, and whether hippocampal feedback continues to modify these properties after learning, remains poorly understood. Thus, two-photon microscopy of male and female Thy1-GCaMP6s mice was used to longitudinally image neurons spanning superficial retrosplenial cortex and layers II-Va of primary and secondary motor cortices before and after bilateral dorsal hippocampal lesions. During behavior on a familiar cued treadmill, the locations of two obstacles were interchanged to decouple place-tuning from cue-tuning among position-correlated cells with fields at those locations. Subpopulations of place and cue cells each formed interareal gradients such that higher-level cortical regions exhibited higher fractions of place cells, whereas lower-level regions exhibited higher fractions of cue cells. Position-correlated cells in the motor cortex also formed translaminar gradients; more superficial cells were more likely to exhibit fields and were more sparsely and precisely tuned than deeper cells. After dorsal hippocampal lesions, a neural representation of the learned environment persisted, but retrosplenial cortex exhibited significantly increased cue-tuning, and, in motor cortices, both position-correlated cell recruitment and population activity at the unstable obstacle locations became more homogeneously elevated across laminae. Altogether, these results support that the hippocampus continues to modulate cortical responses in familiar environments, and the relative impact of descending feedback obeys hierarchical interareal and interlaminar gradients opposite to the flow of ascending sensory inputs.

Research on Territorial Spatial Development Non-Equilibrium and Temporal–Spatial Patterns from a Conjugate Perspective: Evidence from Chinese Provincial Panel Data

Clarifying the intrinsic nature and formation mechanisms of the territorial spatial development non-equilibrium, optimizing the allocation of territorial resources, promoting regional balanced development, and alleviating regional development disparities have become common endeavors of all countries seeking to enhance development quality. This study, based on the land use and socio-economic data of 31 provinces and cities in China from 2006 to 2020, utilized the kernel density estimation method and ArcGIS spatial analysis to explore the spatiotemporal evolution characteristics of China’s territorial spatial development non-equilibrium. The research findings are as follows: (1) From 2006 to 2020, both the land development intensity and land supply capacity showed an increasing trend, with increases of 21.4% and 8.03%, respectively. However, their spatiotemporal evolutions significantly differed. (2) The state of the territorial spatial development non-equilibrium in China significantly improved, with a rising trend in the territorial spatial equilibrium degree. Regional disparities in the territorial spatial equilibrium degree decreased. The number of provinces and cities in a state of underdevelopment decreased from 23 to 8, while the number in an equilibrium state increased from 7 to 21. The central and western regions showed more significant improvements in the territorial spatial equilibrium degree and a greater reduction in regional disparity when compared to the eastern and northeastern regions. (3) China exhibited distinct regional disparities in the territorial spatial equilibrium degree. The overdeveloped areas were Beijing and Shanghai. The underdeveloped regions were primarily concentrated in western areas, including Sichuan, Yunnan, and Xinjiang. The high-level equilibrium regions were predominantly located in the southeastern coastal provinces and the central plains region, while the low-level equilibrium regions included Inner Mongolia, Ningxia, Qinghai, and the three northeastern provinces. (4) From the perspective of the number of agglomeration types, the order is HH (high–high) > LH (low–high) > LL (low–low) > HL (high–low), and China’s TSED exhibits a spatial proximity peer effect. The innovation of this study consists of the following aspects: (1) The clarification of the fact that the essence of equilibrium does not require an exact 1:1 match, as with “two horses”; rather, it entails the maintenance of a slight surplus of land supply capacity over land development intensity. This approach allows the possibility of future sustainable development by leaving room for expansion. (2) The differentiation between high-intensity conjugation (in terms of both quantity and quality) and low-intensity conjugation (quantity only) from a conjugate perspective. This categorization aids in a more comprehensive and in-depth understanding of the territorial spatial development non-equilibrium and its spatiotemporal patterns. It provides crucial information for the formulation of sustainable national territorial development plans and the promotion of a regional development equilibrium.

Local and global effects of sedation in resting-state fMRI: a randomized, placebo-controlled comparison between etifoxine and alprazolam

TSPO ligands are promising alternatives to benzodiazepines in the treatment of anxiety, as they display less pronounced side effects such as sedation, cognitive impairment, tolerance development and abuse potential. In a randomized double-blind repeated-measures study we compare a benzodiazepine (alprazolam) to a TSPO ligand (etifoxine) by assessing side effects and acquiring resting-state fMRI data from 34 healthy participants after 5 days of taking alprazolam, etifoxine or a placebo. To study the effects of the pharmacological interventions in fMRI in detail and across different scales, we combine in our study complementary analysis strategies related to whole-brain functional network connectivity, local connectivity analysis expressed in regional homogeneity, fluctuations in low-frequency BOLD amplitudes and coherency of independent resting-state networks. Participants reported considerable adverse effects such as fatigue, sleepiness and concentration impairments, related to the administration of alprazolam compared to placebo. In resting-state fMRI we found a significant decrease in functional connection density, network efficiency and a decrease in the networks rich-club coefficient related to alprazolam. While observing a general decrease in regional homogeneity in high-level brain networks in the alprazolam condition, we simultaneously could detect an increase in regional homogeneity and resting-state network coherence in low-level sensory regions. Further we found a general increase in the low-frequency compartment of the BOLD signal. In the etifoxine condition, participants did not report any significant side effects compared to the placebo, and we did not observe any corresponding modulations in our fMRI metrics. Our results are consistent with the idea that sedation globally disconnects low-level functional networks, but simultaneously increases their within-connectivity. Further, our results point towards the potential of TSPO ligands in the treatment of anxiety and depression.

Mapping the neural mechanism that distinguishes between holistic thinking and analytic thinking

Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

Spatio-temporal patterns and population exposure risks of urban heat island in megacity Shanghai, China

Accompanied by global warming and rapid urbanization, the urban heat island (UHI) effect has been intensifying, which leads to an increased risk of population heat exposure, especially in mega-cities. However, there are fewer studies on the identification of UHI ranges and the associated population heat exposure risks, particularly on the fine scale. Therefore, this study took Shanghai as a case study and explored the spatio-temporal evolution characteristics of the UHI ranges and population heat exposure risks, based on five-period MODIS land surface temperature (LST) product, population density distribution data, and land use and cover change data from 2000 to 2020, combined with the temperature attenuation mutation (TAM) method, breakpoint regression model, population heat exposure relative risk assessment method, and spatial autocorrelation analysis. The results showed that: (1) From 2000 to 2020, the UHI range in Shanghai was continuously expanding, and the intensity of the surface UHI was gradually increasing. The overall pattern was characterized by a stable large heat island in the central urban area and new small heat islands that continued to emerge in the peripheral suburbs. (2) The population heat exposure risks in Shanghai intensified from 2000 to 2020, with an increasing number of people exposed to high-intensity UHI ranges, doubling the population coverage in these areas. By the end of 2020, the population exposed to UHI ranges accounted for approximately 81 % of the total population of Shanghai. (3) The spatial pattern of population heat exposure risks from 2000 to 2020 was generally similar. Population heat exposure regions of high risk level were primarily concentrated in the central urban areas, showing typical spatial clustering characteristics, while population heat exposure regions of low risk level were mainly dispersed in the peripheral suburbs, and showed a gradual transformation trend into population heat exposure regions of high risk level. Our findings can provide scientific basis and decision support for precise and refined urban heat risk control and planning management.

Bioinspired multilayer braided structure with controllable nonlinear mechanical properties for artificial ligaments

Inspired by “crimped” collagen fiber, which induce a low-level load region within the hierarchical structures of ligaments and tendons, this study introduces a braiding technology aiming at characterizing nonlinear mechanical behavior. Samples of the developed artificial ligament with a multilayer braided structure were fabricated and tested. Alterations in the number of braiding layers, wales, and courses significantly affect the mechanical properties of the artificial ligaments. Specifically, the toe length exhibited an increase of up to 104.58 %, while the linear stiffness exhibited variations concomitant with changes in these parameters. Additionally, a mathematical model to describe the relationship between the toe length and linear stiffness was developed based on the braiding parameters and material properties of the fibers. Alternative fibers were employed and tested to demonstrate a consistency with the mathematical model. The correlation coefficients were calculated as 0.9644 for the toe length and 0.9203 for the linear stiffness. Lastly, this study mimics the mechanical behavior of the human medial collateral ligament (MCL) by integrating the artificial ligament into a bio-fidelity knee model with a joint stiffness of 1.77 Nm/deg, resulting in a high degree of similarity with human knee in valgus-varus, further affirming the utility and applicability of this study.

Neurofeedback training of executive function in autism spectrum disorder: distinct effects on brain activity levels and compensatory connectivity changes

BackgroundDeficits in executive function (EF) are consistently reported in autism spectrum disorders (ASD). Tailored cognitive training tools, such as neurofeedback, focused on executive function enhancement might have a significant impact on the daily life functioning of individuals with ASD. We report the first real-time fMRI neurofeedback (rt-fMRI NF) study targeting the left dorsolateral prefrontal cortex (DLPFC) in ASD.MethodsThirteen individuals with autism without intellectual disability and seventeen neurotypical individuals completed a rt-fMRI working memory NF paradigm, consisting of subvocal backward recitation of self-generated numeric sequences. We performed a region-of-interest analysis of the DLPFC, whole-brain comparisons between groups and, DLPFC-based functional connectivity.ResultsThe ASD and control groups were able to modulate DLPFC activity in 84% and 98% of the runs. Activity in the target region was persistently lower in the ASD group, particularly in runs without neurofeedback. Moreover, the ASD group showed lower activity in premotor/motor areas during pre-neurofeedback run than controls, but not in transfer runs, where it was seemingly balanced by higher connectivity between the DLPFC and the motor cortex. Group comparison in the transfer run also showed significant differences in DLPFC-based connectivity between groups, including higher connectivity with areas integrated into the multidemand network (MDN) and the visual cortex.ConclusionsNeurofeedback seems to induce a higher between-group similarity of the whole-brain activity levels (including the target ROI) which might be promoted by changes in connectivity between the DLPFC and both high and low-level areas, including motor, visual and MDN regions.

County Town Comprehensive Service Functions in China: Measurement, Spatio-Temporal Divergence Evolution, and Heterogeneity of Influencing Factors

Strengthening the service function of small towns, using its fundamental role in the urban system to drive rural development, is the main issue that needs to be addressed urgently in numerous developing countries. County towns are unique types of small towns in China. Analyzing the spatial-temporal patterns and differentiation mechanisms of comprehensive service functions of county towns in China from a geographic point of view can not only provide a basis for the macro-control of county towns but also provide typical regional research results for the study of urban systems and urban–rural coordination in developing countries. Based on Point of Interest (POI) data of 1788 county towns in China, this study analyzes the evolution of spatial and temporal differentiation of comprehensive service functions and influencing factors by using modeling methods such as Getis-Ord Gi* analysis, the random forest model, and Multiscale Geographically Weighted Regression (MGWR). The obtained results show that (1) from 2012 to 2021, the average value of the comprehensive service function index (CSFI) of county towns in China shows a significant increase, and the proportion of county towns with medium–high service levels and above increases from 3.41% to 54.50%; (2) spatially, the comprehensive service function of county towns is characterized by the basic pattern of “high east, low west; high south, low north”, which keeps getting stronger. During the study period, eastern China has always been a high-level region, northwestern and southwestern China have always been low-level regions, and northeastern China has been a stagnant region, while central, northern, and southern China have been fast-growing regions; (3) county general public budget revenues, value added of secondary industry, GDP per capita, county town resident population, altitude, and GDP per capita of affiliated prefecture-level cities to which it belongs are the key factors influencing the comprehensive service function of county towns in China. The county general public budget revenue indicator, which represents the governmental capacity, has the strongest influence; and (4) the results of the MGWR analysis indicate that there is spatial and temporal heterogeneity in the intensity of the above-mentioned key influencing factors on the development of comprehensive service functions of county towns in China. Based on this finding, differentiated strategies should be proposed to policy makers and urban planners in different regions in order to effectively enhance the level of comprehensive service functions of county towns in China.

Dynamic evolution and obstacle factor analysis of green development in China's agriculture and rural areas based on entropy-based TOPSIS model

Green development of agriculture and rural areas (GDARA) is an essential part of rural revitalization and high-quality development. Based on 2011 to 2020 provincial panel data from China, the entropy-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model is constructed to measure the level of GDARA, finding that the overall level during the sample period was positive. Then the regional differences mainly from intra-regional were revealed by the methods of Dagum Gini coefficient and Kernel density estimation and were shrinking overall. Besides, the results of Markov chain transfer matrix show the dynamic characteristics clearly, which the low-level regions shift to the middle and high levels with a greater probability. The results of the spatial autocorrelation test display that GDARA has a spatial clustering effect. Finally, the industrial upgrading and the business income of leisure agriculture are respectively proven to hinder GDARA at most by the Obstacle degree model empirically. Based on a series of empirical tests, a few relevant policy recommendations are proposed to promote the road to strong agriculture and rural areas in China.

How does the digital economy affect the provincial "zero-waste city" construction? Evidence from China.

The digital economy is playing a crucial effect in the field of environmental governance. Digital and intelligent management is an essential means to fully realize the "zero-waste city" construction. The present paper investigates the impact of digital economy on China's provincial "zero-waste city" construction. The results indicate that digital economy can contribute to "zero-waste city" construction. The digital economy has a positive nonlinear effect on the construction of "zero-waste city," but the marginal effect is diminishing. The digital economy can facilitate "zero-waste city" construction by improving industrial structure upgrading and green technology innovation. Heterogeneity analysis reveals that digital economy contributes to the construction of "zero-waste city" in the eastern and western regions and high-level environmental regulation regions, while this impact is insignificant in the central region and low-level environmental regulation regions. The digital economy exerts the most significant positive influence on waste resource recycling followed by waste final disposal and then waste reduction at the source. These findings underscore the effect of digital economy in fostering "zero-waste city" construction and promoting sustainable waste management. The present study provides new ideas for the "zero-waste city" construction in emerging developing countries such as China.

Learning Structured Relation Embeddings for Fine-Grained Fashion Attribute Recognition

Fashion attribute recognition is a not-new topic, but rather a core task in understanding fashion from the perspective of computer vision. This paper proposes a structured relation-aware network (sRA-Net), which exploits multiple hidden relations in fashion images to enrich and achieve accurate attribute representations to boost the performance of fashion attribute recognition. Specifically, it deconstructs the features of a clothing fashion item into three levels, including low-level attribute-related image region information, mid-level attribute dependency information, and high-level clothing look information. To learn these multi-relational embeddings, we present three relation-aware attention mechanisms. The attribute attention mechanism describes the relationship among different attribute vectors through self-attention and uses the attention map to update the attribute embedding. Then, the spatial attention mechanism associates the attribute with the image features and enhances the attribute embedding by leveraging the attribute-related image region. Finally, the channel attention mechanism selects attribute-related image feature channels to obtain a more fine-grained attribute embedding. Furthermore, we introduce structure-aware embedding to constrain attribute recognition in images from a global perspective by identifying the inner structure of the clothing. Without bells and whistles, sRA-Net outperforms all state-of-the-art attribute recognition methods on two mainstream fashion attribute datasets, namely the DeepFashion-C dataset and iFashion-Attribute dataset, with over 1%-3% improvement.

Challenges and Way Forward to Maintain Air Quality Standard in Urban Areas

This thesis explores the intricate relationship between urban air pollution, economic growth, population dynamics, and energy consumption. Addressing impacts on climate change, biodiversity, agriculture, and human health, it emphasizes compromised urban air quality due to pollution sources such as power generation, vehicle traffic, and construction. Key pollutants like particulate matter, carbon dioxide, sulfur dioxide, and nitrogen dioxide pose significant health risks. The study identifies road transportation as a primary contributor, underlining alarming statistics from WHO on global air quality, particularly impacting low-level socio-economic regions. Legislations and policies dating back over a century form the foundation for global air pollution control efforts. The research highlights innovative solutions like urban green spaces, smart traffic management, and renewable energy investments. It stresses the importance of public transportation, electric vehicles, clean construction practices, and initiatives to reduce industrial emissions. In response to challenges, the thesis proposes a comprehensive mitigation plan covering strategy such as promoting public transport, energy conservation, recycling, and afforestation. It outlines a way forward, emphasizing integrated urban planning, public awareness campaigns, government policies, and international collaboration. In conclusion, the thesis calls for collective responsibility to address urban air pollution's adverse effects on public health and the environment. The proposed roadmap aims to create sustainable, resilient, and healthier urban environments through a holistic and collaborative approach.

Does digital technology innovation promote low-carbon development in agriculture?: A spatial econometric analysis based on 31 provinces in China.

China's traditional agriculture has grown quickly but at the cost of excessive pollution and energy consumption. Therefore, low-carbon development in agriculture is crucial to achieving "carbon neutrality" and "carbon peaking." With the development of China's digital economy and the construction of digital villages in recent years, digital technology innovation (DTI) is probably going to a significant role in lowering agricultural carbon emissions (ACEs). Based on Chinese provincial panel data from 2006 to 2021, we analyze the spatial and temporal evolution characteristics of DTI and ACE, explore the impact and the pathways of DTI on ACE using a spatial econometric model, and reveal this impact's heterogeneity and nonlinear character. The findings show that DTI and ACE increased significantly throughout all Chinese provinces. DTI agglomeration is becoming stronger, whereas ACE displays a tendency for discontinuous distribution. DTI is essential in promoting low-carbon development in agriculture, and there are significant spatial spillover effects due to technology spillovers. Heterogeneity analysis indicates that DTI has positive impacts on local agriculture in different regions. However, there is variation in the impact's degree. The mechanism test's findings show how DTI reduces ACE by improving technology and enhancing resource endowment. The relationship between DTI and ACE exhibits an inverted "U" curve, and the level of economic development is the threshold variable that constrains the relationship between the two variables. To achieve a regional balanced low-carbon development in agriculture through DTI, it is important to emphasize the impact of DTI on reducing carbon emissions and to encourage the transfer of mature technology from high-level regions to low-level regions.

An objective procedure for rainy season onset and withdrawal dates over the Mexico Valley Basin

This work aims to define a procedure to declare rainy season onset and withdrawal dates for the Mexico Valley Basin, located in central Mexico. The onset/withdrawal is obtained using only precipitation for the study period 1981–2020. The onset is defined as the first day, between May 1st and July 15th, of the first 20 consecutive days having a 20-day average precipitation over the Basin of at least 2.5 mm/day. The withdrawal is defined as the last day, between September 1st and November 15th, of the last 20 consecutive days having a 20-day average precipitation of at least 1.7 mm/day. The mean onset is June 6th, with a standard deviation of 14.3 days; the mean withdrawal date is October 15th, with a standard deviation of 16.1 days; and the average length of the rainy season is 131 days, with a standard deviation of 22.7 days. These criteria maximize the precipitation change slope during onset/withdrawal. We categorized pre- and post-onset/withdrawal periods to investigate mean circulation characteristic changes. Besides a stark increase (decrease) in rainfall over the Basin during onset (withdrawal), we found that vertically integrated moisture transport over the Caribbean Low-Level Jet core region increases (decreases). The onset/withdrawal dates derived show interannual trends, while a late (early) withdrawal is associated with a positive (negative) ENSO Index, and a strong (weak) Caribbean Low Level Jet (CLLJ) is associated with a late (early) onset.

Regional startup ecosystems of Ukraine

The startup ecosystem of each country contains separate elements and reflects the effectiveness of their interaction, which is also reflected in regional ecosystems. The aim of the research is to identify and rank the start-up ecosystems of the regions of Ukraine according to various indicators, distinguish the differences between the ecosystems and determine the main directions of their development, expansion within a separate region. In the research multifactorial comparative analysis in four stages has been used, such as: justification of the indicator system, normalization of the matrix of standardized coefficients, squaring of all elements of the matrix of standardized coefficients and placement of the obtained rating values by rank. The highest level is charac­terized by a sufficient number of supporting elements that help startups find financing options and accelerate market entry processes; the high level has a dynamic ecosystem that helps early-stage startups find support and funding programs; the medium level has a developing ecosystem, and the existing business structure contributes to the development of the startup movement in the region; the low level has the potential for further development and additional initiatives by local authorities and business structures. According to the rating, the highest level was determined in Kyiv region, the high level is found in Dnipropetrovsk, Lviv, Odesa and Kharkiv regions, the average level is found in Donetsk and Zaporizhia regions. Other regions belong to the lower and the lowest levels, which emphasize the promising development of startup ecosystems in the regions. Regions with the highest level can focus on maintaining and expanding their existing ecosystem by providing additional support and funding for startups; with high indicators they can focus on the further development of its dynamic ecosystem, creating more clusters and events to attract startups and investors; medium level regions can consentrate on increasing the number of supporting elements to make it easier for startups to find funding and scale; with a low level regions can focus on conducting competitions, hackathons, involving the IT community for the development of the startup community.

Theoretical Insights into Aggregation-Induced Emission with the Ionic π Fluorophore: The Importance of Choosing the Dimer QM Model in the ONIOM Study.

In understanding the mechanism of aggregation-induced emission (AIE), the multilevel ONIOM framework has been demonstrated as one of the efficient tools that can capture the essential mechanistic information by choosing a single fluorophore as the quantum mechanics (QM) model and putting all surrounding molecules in the low-level region. Recently, the ionic styryl-pyridine salt (namely, SPH) has been reported as a new class of AIEgen with a high fluorescence yield. In the SPH crystal, a pair of ionic SPH molecules are closely stacked with each other in an antiparallel, head-to-tail pattern, thus the choice of QM models (an individual or dimeric structure) becomes critical in the ONIOM study. Herein we report the AIE mechanism of the ionic SPH at the QM ((TD)-CAM-B3LYP) and ONIOM(QM:MM) levels. As usual, the fluorescence quenching of SPH in tetrahydrofuran (THF) solution is attributed to a nonradiative relaxation via the central C═C bond rotation, with a rather low barrier of 2.7 kcal/mol. In crystals, either with a monomer or dimer model, the fluorescence quenching channel is found to be restricted due to the obvious C═C rotation barriers. Compared with the monomer model, the dimer model, by treating the orbital interaction of the two SPH molecules at the QM level, provides significantly increased barriers and a red-shifted emission wavelength that better matches the experimental value. In addition, the calculated exciton coupling in the fluorescence emission state can be discovered only by a dimer model. The findings here emphasize not only the importance of choosing a proper model in the ONIOM study of AIE but also expanding our understanding of novel AIE systems.

Research on the Level of Agricultural Green Development, Regional Disparities, and Dynamic Distribution Evolution in China from the Perspective of Sustainable Development

Green development is a concept of sustainable development, aiming to protect the environment and ecosystems while meeting economic development needs. In the field of agriculture, green development has emerged as a crucial pathway for reconciling the conflicts between agricultural development and ecological conservation. To investigate the level of green development in Chinese agriculture, regional variations, and the evolutionary patterns, this paper is based on the framework of sustainable development theory. This study establishes a comprehensive evaluation system for agricultural green development and applies methods such as entropy-weighted TOPSIS, Dagum’s Gini coefficient, kernel density estimation, Moran’s I index, and Markov chains to analyze the level of agricultural green development, regional disparities, and dynamic evolution in China. The findings of this study reveal that: (1) The overall level of agricultural green development in China is steadily improving, with notable differences in the level of agricultural green development among different regions and provinces. There are significant disparities in agricultural green development between regions, and the overall disparities exhibit a fluctuating downward trend characterized by periods of increase followed by decrease. The regional disparities are identified as the primary cause of the overall disparities in agricultural green development in China. (2) The eight major economic regions in China are experiencing steady development in agricultural green practices, but there are varying degrees of polarization due to different development speeds. (3) This study also highlights a clear spatial positive correlation in the level of agricultural green development in China, with most provinces showing clustering in the first and third quadrants, indicating a “high–high” (H-H) and “low–low” (L-L) agglomeration pattern. (4) The study reveals that the level of agricultural green development in China exhibits a certain degree of stability. Over time, the probability of transitioning from lower-level regions to neighboring higher-level regions increases, and the agricultural green development level in neighboring regions can influence the spatial transfer probability within a given region. Therefore, agricultural green development demonstrates significant spatial dependence.

Impact of Digital Economy Development on Industrial Structure Upgrading--Based on Two-way Fixed Effects Model Analysis

Digital economy is an important engine for building a modernized economic system. Through new generation information technology, it improves the operation efficiency of industrial chain and expands the innovation space of industrial chain, thus helping to upgrade the industrial structure. Based on the balanced panel data of 30 provincial administrative regions in China from 2012 to 2020, a two-way fixed effects regression model is constructed to empirically test and explore the impact of digital economy development on industrial structure upgrading. It is found that: Digital economy development can significantly promote industrial structure upgrading, and the conclusion still holds after a series of robustness tests. The promotion effect of digital economy development on industrial structure upgrading is regionally heterogeneous and social consumption level heterogeneous, which can significantly promote industrial structure upgrading in western and low social consumption level regions, but not in eastern, central and high social consumption level regions. Accordingly, policy suggestions are made in three aspects: vigorously developing digital economy, formulating regional differentiated digital economy development policies, and coordinating the relationship between consumption upgrading and supply side