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This paper constructs a novel stress measurement system of carbon market from the perspective of trading, emission reduction, and external shocks and simulates the stress indices of national and pilot carbon markets of China with the methods of functional data analysis and criteria importance through intercriteria correlation. It concludes that the overall carbon market stress is in the shape of "W" and still at a high level, with frequent fluctuations and an upward trend. In addition, the stress of Hubei, Beijing, and Shanghai carbon market fluctuates and rises, while the stress of Guangdong carbon market decreases. Moreover, carbon market stress mainly comes from trading and emission reduction. Furthermore, stress fluctuation of Guangdong and Beijing carbon market is more prone to "big waves," indicating that the two markets are sensitive to big events. Finally, the pilot carbon markets are divided into stress-driven and stress-release market and the type of which keeps change in different period. [ABSTRACT FROM AUTHOR]

As development progresses over time and changes in the environment take place, carbon finance development has become a very interesting research topic for many scholars worldwide. This paper proposes a hybrid MCDM method that combines the distance solutions of the TOPSIS and VIKOR methods. The contribution of this paper combines TOPSIS and VIKOR, incorporating AISM models to obtain the development ranking of Chinese carbon finance pilot cities as related to the Chinese carbon finance development pilot provinces and cities. The conclusion notes that Guangdong and Beijing are the most preferred investment locations for carbon investors. In addition, technological innovation, financial sector development, and an active ETS market can effectively drive the level of local carbon finance. Additionally, the MCDM methodology in this paper provides new ideas in environmental and economic development assessment. [ABSTRACT FROM AUTHOR]

This special issue sets out to revisit major bilingual and multilingual education policy and planning issues in key cities across the dynamic Greater Bay Area (GBA) of China (including Guangdong, Hong Kong, and Macau), as informed by the emerging insights from translanguaging theory (Li in Appl Linguist 39(1):9–30, 2018). Specifically, contributions are invited from the GBA and beyond to trace the milestone developments of relevant language policy and planning (LPP) initiatives featuring governmental policies on the language of instruction (e.g., English as Medium of Instruction, Chinese as Medium of Instruction) and the daily use of multiple linguistic resources or repertoires (e.g., language learner's L1 or mother tongue) in foreign/second language classrooms and/or in content-based classroom instruction. As such, major papers in the special issue not only set out to provide historical and analytical reviews of these related LPP issues across Hong Kong, Macau, and Guangdong Province but also reflect upon the language use and behaviors of the residents, showcasing their identity and attitudes and ideological stance toward the multiple languages that are being taught or used in daily life. Toward the end, we outline our research agendas for future endeavors in broader domains in the GBA and beyond through the translanguaging analytical tools. Overall, our position is that the GBA presents itself as an evolving, complex, and superdiverse zone of "Translanguaging Spaces" within which key LPP issues may need to be reconceptualized and implemented in such a way so as to fully reflect the dynamic and fluid multilingual, multicultural, and multisemiotic lived reality of the residents in this megapolis region. [ABSTRACT FROM AUTHOR]

Scientific analysis of regional agricultural carbon emission prediction models and empirical studies are of great practical significance to the realization of low-carbon agriculture, which can help revitalize and build up ecological and beautiful countryside in China. This paper takes agriculture in Guangdong Province, China, as the research object, and uses the extended STIPAT model to construct an indicator system for the factors influencing agricultural carbon emissions in Guangdong. Based on this system, a combined Isomap–ACO–ET prediction model combing the isometric mapping algorithm (Isomap), ant colony algorithm (ACO) and extreme random tree algorithm (ET) was used to predict agriculture carbon emissions in Guangdong Province under five scenarios. Effective predictions can be made for agricultural carbon emissions in Guangdong Province, which are expected to fluctuate between 11,142,200 tons and 11,386,000 tons in 2030. And compared with other machine learning and neural network models, the Isomap–ACO–ET model has a better prediction performance with an MSE of 0.00018 and an accuracy of 98.7%. To develop low-carbon agriculture in Guangdong Province, we should improve farming methods, reduce the intensity of agrochemical application, strengthen the development and promotion of agricultural energy-saving and emission reduction technologies and low-carbon energy sources, reduce the intensity of carbon emissions from agricultural energy consumption, optimize the agricultural planting structure, and develop green agricultural products and agro-ecological tourism according to local conditions. This will promote the development of agriculture in Guangdong Province in a green and sustainable direction. [ABSTRACT FROM AUTHOR]

It is essential to predict carbon prices precisely in order to reduce CO2 emissions and mitigate global warming. As a solution to the limitations of a single machine learning model that has insufficient forecasting capability in the carbon price prediction problem, a carbon price prediction model (GWO–XGBOOST–CEEMDAN) based on the combination of grey wolf optimizer (GWO), extreme gradient boosting (XGBOOST), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is put forward in this paper. First, a random forest (RF) method is employed to screen the primary carbon price indicators and determine the main influencing factors. Second, the GWO–XGBOOST model is established, and the GWO algorithm is utilized to optimize the XGBOOST model parameters. Finally, the residual series of the GWO–XGBOOST model are decomposed and corrected using the CEEMDAN method to produce the GWO–XGBOOST–CEEMDAN model. Three carbon emission trading markets, Guangdong, Hubei, and Fujian, were experimentally predicted to verify the model's validity. Based on the experimental results, it has been demonstrated that the proposed hybrid model has enhanced prediction precision compared to the comparison model, providing an effective experimental method for the prediction of future carbon prices. [ABSTRACT FROM AUTHOR]

Carbon emission trading scheme (ETS) policy is a quota-based market-motivated environmental regulation policy that by transforming environmental responsibility of enterprises into self-consciousness behavior induces green innovation behavior in enterprises and influences the level of regional green innovation. Based on panel data on green patents in 30 Chinese provinces from 2010 to 2019, the paper uses six Chinese pilot provinces for ETS as the treatment group to investigate the induced effects of Chinese ETS policy on the quantity and quality of green technology innovation using difference in difference model and analyzes the effects of Chinese ETS policy on green technology innovation in different pilot regions using a synthetic control method. The findings indicate that (1) compared with non-pilot areas, the carbon emission trading policies in pilot areas can induce green technology innovation activities. (2) In all pilot regions, ETS policies significantly promoted the quantity and quality of green technology innovation, but the quantity promotion effect was significantly better than the quality promotion effect, and the low-quality promotion effect was better than the high-quality promotion effect. (3) In terms of individual pilot region, ETS policies in Guangdong, Hubei and Tianjin significantly promoted the quantity of green technology innovation and low-quality green technology innovation, but significantly inhibited or suppressed high-quality green technology innovation in a short term. This paper not only enriches the research on environmental equity trading policies and green technology innovation theoretically, but also provides empirical evidence for the effectiveness of carbon emission trading schemes pilots program in China. [ABSTRACT FROM AUTHOR]

In this paper, we focus on Guangdong province, which is a frontier area of Reform and Opening up, and analyze the variation of urban and rural temperature to detect the urbanization warming effect from 1951 to 2018, based on the daily temperature data of 85 weather stations. We classified the metrological stations into urban and rural stations according to the urbanization population size, population density and urban built-up area data. The combined methodology of mathematical statistics, trend analysis, urban/rural station comparison and spatial analysis was adopted to reveal the urbanization warming and its spatial–temporal heterogeneity. The results show that the warming process in Guangdong Province is very complex and has high temporal and spatial heterogeneity. From 1951 to 2018, the average temperature in the coldest month in Guangdong Province increased with the fastest (0.27 °C/10a) rate, and the annual average temperature increased slightly faster than the average temperature in the warmest month (0.15 °C/10a vs. 0.12 °C/10a). The comparative study on the temperature of urban and rural stations shows that the temperature increase rate of urban stations is faster than that of rural stations (0.30 °C/10a vs. 0.23 °C/10a), especially the average temperature in the coldest month, which is most significantly driven by urbanization, and the contribution rate of urbanization is about 24.09% in general. Affected by the background climate and the stages of urbanization, the warming effect of urbanization fluctuates obviously in different periods. Stronger urbanization effect can be witnessed during 1980–2000, when the urbanization developed into mid-level with highest rate. The spatial differentiation of urbanization warming effect is prominent. The temperature of urban stations in Eastern Guangdong increases most rapidly. The urbanization contribution rates to the coldest month average, annual average and the warmest month average temperature reach 33.86%, 25.70% and 17.64%, respectively, which are around 1.69, 1.50 and 1.19 times that of the Pearl River Delta. The average temperature of the warmest month in Western Guangdong shows a weak cooling effect. Multi-faceted, multi-level regulation of sustainable urbanization is the key to mitigating the warming caused by urbanization. [ABSTRACT FROM AUTHOR]

The ICT service industry has become a burgeoning industry at a high and stable speed. Their equitable distribution can improve national and global positive peace. This paper aimed to verify the characteristics of spatio-temporal evolution and its influencing factors in the ICT service industry. Based on the data from 31 Provinces in China from 2015 to 2019, this paper uses location quotient, spatial autocorrelation methods and spatial econometric analysis to explore the development characteristics, evolution and influencing factors of the ICT service industry, respectively. The main results are shown as follows: (1) China's ICT service industry is mainly concentrated in Beijing, Shanghai, Zhejiang, Tibet, and Guangdong, with a trend of specialisation development. They are not only distributed in cities with relatively superior overall development but also those with superior industrial and development carrier elements. Technological relevance, aggregation, and political difference might have an impact on promoting the emergence and development of these industries. (2) ICT service industry is characterised by stable and highly concentrated development. Numbers between three to five significant provinces and types with high-high (HH) and high-low (HL) clusters of local spatio-temporal association kept stable in the period. The HH was in eastern coastal areas, including Zhejiang, Shanghai, Jiangsu, and Shandong, and the HL was in Guangdong in 2015. There is a definite spatial correlation in spatial distribution with constant strengthening. (3) TUR, NDN, MIAT and the area were shown to have a significant role in promoting the ICT service industry, while NW, GDP and ICT Employment were shown to have a significant negative impact on this industry. Correspondingly, two strategies were put forward here: (1) accelerating the inter-provincial networking development of the ICT service industry, and (2) strengthening government policy guidance for the ICT service industry. These outcomes can not only provide a scientific basis and theoretical support for the distribution of strategies and resources for these industries at the theoretical level but also improve resource integration from the national perspective and the efficiency of resource use at the practical level. [ABSTRACT FROM AUTHOR]

In the field of world heritage conservation, there has been broad consensus on carrying out heritage conservation research on the basis of spatial integration and interregional and international cooperation. However, there are still many deficiencies in the integration of culture with the environment, regional economic and social development, and the regional, holistic and multimodal conservation and utilization of cultural heritage sites. In China, the Dongjiang-Hanjiang River Basin is a representative area of substantial cultural and ecological value for both Guangdong Province and the whole country. This paper uses the morphological spatial pattern analysis and the minimum cumulative resistance model to integrate cultural ecology sources and establish a cross-regional and large-scale cultural ecology network system that includes 1 main corridor, 22 important corridors and 17 secondary corridors. In addition, based on identified cultural landscape nodes and cultural ecology services, the economy of the cultural ecology corridor could be developed with large-scale co-construction, co-governance and shared working mechanisms to overcome administrative limits and realize the conservation and utilization of multimodal and large-scale heritage sites. This approach has strong theoretical and practical significance for innovative methods in cultural ecology research, as well as for new content in the research of Lingnan culture, ecosystem restoration, and the economic and social development of towns and villages. This article supplements unilateral studies of regional culture and ecology and demonstrates an in-depth application of cultural ecology theory. [ABSTRACT FROM AUTHOR]

The economic and social structures of Chinese cities are constantly transforming in recent years. The coordinated development of economic, social, and ecological environment is an important path to achieving the construction of high-quality development. Taking Guangdong Province, the largest economic province in China, as an example, the evaluation index systems of economic development system (ED), social development system (SD), and ecological environment system (EE) are constructed, respectively. The entropy weight method and comprehensive evaluation method are applied to measure the evaluation indexes of economic, social, and ecological environment levels of each city in Guangdong Province from 2010 to 2020. The coupled coordination model is used to measure the spatial and temporal evolution of the coupled ED-SD-EE coordination of Guangdong cities and explore the impact of the epidemic on the coupling coordination degree. The results concluded that (i) the economic, social, and ecological environment of each city in Guangdong Province will be more harmonious from 2010 to 2020. ED-SD-EE coupling coordination of Guangdong cities shows a "rising and then declining" trend, but it is still in a "high coupling-low coordination" development state. (ii) The lagging development of the coupled ED-SD-EE system in Guangdong cities is mainly the ecological environment system. (iii) Epidemic harms the coupling and coordination of Guangdong cities, with the most negative effect on the coordination development of the EE. The paper findings clarify the current state of ED-SD-EE coupling and coordination in Guangdong cities, with a view to providing a reference basis for policy formulation and research on quality urban development. [ABSTRACT FROM AUTHOR]

Rural sewage collection networks play extremely important roles in rural sewage treatment, and the lack of a suitable collection model makes this task difficult. Hence, there is an urgent need to develop a new method to collect and deal with rural sewage. This paper establishes a rural sewage optimal collection model (RSOCM) with critical distance (d) and sewage quota per unit area (qs) as the constraint factors. The implementation of critical distance for rural sewage collection pipeline networks was demonstrated for 38 rural areas in the Huicheng District, Huizhou City, Guangdong Province of China. The average critical distances of 22 m, 38 m, 29 m, 29 m, 41 m, and 55 m were demonstrated for Sandong Town, Ma'an Town, Luzhou Town, Ruhu Town, Hengli Town, and Shuikou Subdistrict, respectively. The qs is used to create the best possible pipe network layout, determine the appropriate treatment method, and reduce construction costs. This model can be widely applied to sewage collection in rural areas of China, where the overall sewage collection system can implement different regional strategies to maximize rural pollution control and protect the environment. [ABSTRACT FROM AUTHOR]

Carbon sequestration in farmland ecosystems is an important link in the world carbon cycle and plays an important role in regional carbon reduction. Guangdong, a major industrial and economic province in China, was used as the study area, and the period 2001–2020 was taken as the study period. The carbon emissions, sequestration, and footprint of farmland ecosystems in Guangdong were estimated using carbon emission factors for agricultural inputs that are closer to the actual situation in China. The study showed that: (1) Carbon average emissions from farmland in Guangdong during the study period was 3.7624 million t a−1, with a balanced overall trend of change, and that nitrogen fertilize applications was the main factor contributing to carbon emissions. (2) The carbon sink capacity of Guangdong farmland ecosystems showed an overall decreasing trend of 10.32%, with an average annual carbon sink of 19.0363 million t a−1. Paddy and sugar cane cultivations were the main factor of carbon sink in farmland. (3) The average annual carbon footprint of Guangdong's farmland ecosystems was 531,100 ha a−1, which was in a carbon surplus. Carbon surplus and footprint showed a decreasing trend year by year. The paper results provide a theoretical basis for the formulation of carbon emission reduction policies and industrial restructuring in Guangdong and provinces with the same industrial structure. [ABSTRACT FROM AUTHOR]

From June 10 to 13, 2019, continuous heavy rainfall occurred in Longchuan County, Guangdong Province, yielding a cumulative rainfall of nearly 270 mm. The heavy rainfall triggered a large number of landslide disasters and formed three hardest-hit areas. In this paper, Mibei village, Beiling town, Longchuan County, is chosen as the research object; detailed field investigation data, satellite remote sensing images, rainfall monitoring data, and artificial rainfall physical model test results are integrated; the temporal and spatial distribution characteristics of rainfall-induced group-occurring landslides in the study area are obtained; and the rainfall instability mechanism of granite residual soil slopes is explained. Under the influence of continuous heavy rainfall from June 10 to 13, 2019, 327 landslides developed in Mibei village, Beiling town, and these landslides were mainly distributed in low mountainous areas, of which the sections at elevations from 300 ~ 400 m and slopes ranging from 35 ~ 45° were the most susceptible to landslide disasters. Continuous rainfall on June 10 and 11 was the controlling factor leading to these large number of landslides, with numerous landslides occurring from 20:00 on June 11 to 04:00 on June 13. These group-occurring landslides exhibited the characteristics of a considerable rainfall lag. The deformation and failure characteristics of the numerous observed landslides within the study area were highly similar, mainly involving traction sliding failure, and the sliding mass thickness ranged mostly from 1.5 ~ 3 m. The flow pattern characteristics of unconsolidated deposits after landslide instability were significant. According to the deformation and failure characteristics of landslides and the rainfall infiltration pattern, the development of landslides was divided into stages in this paper. Due to the difference between the rainfall intensity and permeability of granite residual soil, the main influence depth of heavy rainfall was limited to the superficial zone of slopes, which is the main reason why the shallow surface zone was damaged by landslides. Under the action of continuous heavy rainfall, a saturated seepage field was established in the shallow surface zone of slopes. Driven by gravitational potential energy, this led to an uneven distribution of the slope saturation zone. Attenuation of the mechanical strength of saturated soil reduced the slope stability, and sliding failure consequently occurred in the shallow surface saturation zone. In regard to excavated slopes, anti-sliding force reduction and free face formation enhanced the slope's susceptibility to sliding failure under the influence of heavy rainfall, which is also the reason for the large-scale distribution of landslides along the X158 county road. [ABSTRACT FROM AUTHOR]

Collaborative innovation can promote scientific productivity and the development of clean technology and thus has a great potential in constraining the ecological footprint. However, current studies on the impact of collaborative innovation on ecological footprint are insufficient, and results remain controversial. To better understand these impacts, this paper took Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, estimated the ecological footprint at the municipal level from 2008 to 2018, measured collaborative innovation both from four dimensions and from a composite approach, then applied threshold regression models to compare the impact of collaborative innovation on the ecological footprint across different economic intervals. The findings showed that: the ecological footprint of the Greater Bay Area displayed an overall upward trend with prominent spatial heterogeneity. The impact of collaborative innovation on the ecological footprint presented a double-threshold effect when examined with different indicators. Among which, the flow of scientific personnel and capital boosted the ecological footprint, which intensified with economic development, while collaboration in technology exerted significant inhibitory effects on ecological footprint, and the influence of inter-city knowledge collaboration was limited. Overall, collaborative innovation inhibited ecological footprint when measured by a composite index. This might inspire policymakers to adopt sustainable strategies depending on the type of collaborative innovation and the economic status of the city to constrain growth of the ecological footprint, thus minimizing the pressures of human activities on the environment and moving towards a more carbon neutral society. [ABSTRACT FROM AUTHOR]

The study of happiness and subjective wellbeing (SWB) has received increased interest among scholars in the People’s Republic of China (PRC), who published their findings nationally in Chinese language journals. This paper introduces their work to the international audience. The first study appeared in the journals in 1999, and about 800 research papers have been published to date. The field is anchored in ten areas: the most salient are the general surveying of SWB; areas within health psychology; and personality research. There was a paucity of research in most areas, and a disproportional amount of research in relation to geographical area. Most research was conducted in Shandong (North East China) and Guangdong (South China), whereas no studies reported in the Chinese journals have been conducted in regions such as Inner Mongolia and Tibet. The majority of studies used augmented versions of Western scales as their measurement instrument, although Chinese scholars have developed their own scales. The research field is developing rapidly, but is limited currently by its infancy, overuse of student samples, inadequate descriptions of research methodology, and isolation from studies published outside the country. Recommendations are provided to overcome these issues and to advance the field further. [ABSTRACT FROM AUTHOR]

This paper evaluates the carrying capacity of cultivated land in Guangdong Province, China, using the entropy weight method. Ecological and environmental pressure significantly impacts capacity, while economic and social factors are stable. Production pressure fluctuates and rises. To improve capacity, we must reduce ecological and environmental pressure, protect cultivated land resources, develop and promote green technology, and maintain water conservation facilities. The results indicate that reducing ecological and environmental pressure is essential to improve the carrying capacity of cultivated land in Guangdong Province. In conclusion, this study highlights the importance of balancing economic growth with environmental sustainability in developing regions like Guangdong Province. It suggests that a holistic approach that considers ecological, economic, and social factors is necessary to ensure long-term food security and sustainable land use practices. [ABSTRACT FROM AUTHOR]

Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable basis for carbon pricing and ensuring the healthy development of carbon markets. Therefore, this paper proposes a two-stage interval-valued carbon price combination forecasting model based on bivariate empirical mode decomposition (BEMD) and error correction. In Stage I, the raw carbon price and multiple influencing factors are decomposed into several interval sub-modes by BEMD. Then, we select artificial intelligence-based multiple neural network methods such as IMLP, LSTM, GRU, and CNN to conduct combination forecasting for interval sub-modes. In Stage II, the error generated in Stage I is calculated, and LSTM is used to predict the error; then, the error forecasting result is added to the first stage result to obtain the error-corrected forecasting result. Taking the carbon trading prices of Hubei, Guangdong, and the national carbon market, China, as the research object, the empirical analysis proves that the combination forecasting of interval sub-modes of Stage I outperforms the single forecasting method. In addition, the error correction technique in Stage II can further improve the forecasting accuracy and stability, which is an effective model for interval-valued carbon price forecasting. This study can help policymakers formulate regulatory policies to reduce carbon emissions and help investors avoid risks. [ABSTRACT FROM AUTHOR]

The Lianhuashan metallogenic belt in Eastern Guangdong Province (South China) is the most important Sn polymetallic district in the region, hosting many medium-sized deposits such as the Tashan, Xianshuili, and Jiangxikeng. However, the metallogenic mechanism of these deposits remains hotly debated. In this paper, two types of cassiterites (Cst1 and Cst2) have been identified in the Xianshuili and Jiangxikeng Sn deposits, which are hosted in the biotite-mylonite and garnet-cordierite-muscovite blastomylonite, respectively. The euhedral Cst1 (0.50–1.8 mm) coexists with biotite, feldspar, and quartz. It is platy and zoned with a mosaic structure. The subhedral to anhedral Cst2 (0.02–0.35 mm) coexists with metamorphic minerals such as garnet and cordierite, and it is characterized by well-developed porosity and has no zonation. In-situ U-Pb dating of the Cst1 and Cst2 yielded ages of 149.5±1.0 Ma (MSWD=1.6, n=45) and 125.1±2.3 Ma (MSWD=4.5, n=43), respectively. Cst1 is most likely to be related to the intermediate-felsic magmatism that formed Gaojiping Group, whereas Cst2 has relatively high Ta, Nb, Fe, and W contents with obvious rare earth tetragroup effect, and may have formed by the late Early Cretaceous dynamic metamorphism. Results presented here, when combined with regional geology and geochemistry, led us to suggest that the Mesozoic intermediate-felsic volcanic rocks in the LMB are significantly enriched in Sn and F, with high Sn-polymetallic mineralization potential which likely have contributed to the volcanic-related Cst1. In the late Early Cretaceous period, due to the NW-dipping subduction of the paleo-Pacific plate, the intermediate-felsic volcanic rocks underwent dynamic metamorphism that led to Sn mobilization, migration, and precipitation in the regional ductile shear zones, and eventually generating Sn mineralization. We propose that areas beneath Xianshuili and Jiangxikeng have great potential for discovery of new Sn resources. Our findings likely offer practical importance to regional geological ore prospecting. [ABSTRACT FROM AUTHOR]

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As China has become the largest user of industrial robots, the need to understand how workers perceive robot-human substitution and how their perceptions influence their job behaviors is becoming increasingly crucial. This paper examined whether workers' fear of being replaced by robots (FRR) is correlated with one aspect of job behavior: turnover intention, which refers to the extent to which an individual intends to change their job within a specific time period. Using a dataset covering 1512 manufacturing workers in Guangdong province of China, we found that workers who fear losing their jobs to robots report significantly higher turnover intention. We also found that the positive effect of FRR on turnover intention increased when robots were already utilised in the workplace. This effect was also found to be increase when workers perceived that their wages did not increase with the rise in productivity due to robotisation. Based on these findings, we provide practical recommendations to organizations on effectively addressing the turnover intention arising from the FRR. [ABSTRACT FROM AUTHOR]

Aim: Personality is a critical predictor of the depression levels of adolescents, and neurotic individuals have more severe depressive symptoms than their counterparts. Thus, it is necessary to increase our knowledge about the influencing mechanism of neuroticism on depression. The mediating variables of negative cognitive bias and negative affect were examined in this paper; the examination revealed that neuroticism leads to depression by affecting the aspects of cognition and affect and providing a more comprehensive theoretical basis for depression research in adolescents. Method: In this study, the Beck Depression Invention, the Negative Cognitive Bias Questionnaire, the Positive and Negative Affect Schedule and the Neuroticism Questionnaire were used to evaluate the depression level, negative cognitive bias, negative affect and neuroticism of college students. The 1035 participants were undergraduate students from 3 universities across the Guangdong Province of China, specifically, 371 male students (35.8%) and 664 female students (64.2%). The students' ages ranged from 17 to 22 years old, with an average age of 19.54 ± 2.08. Result: (1) Neuroticism was positively correlated with the level of depression (γ =0.594, P < 0.05), which indicates that neuroticism has a positive predictive effect on the level of depression. (2) Neuroticism was positively correlated with negative cognitive bias (γ =0.715, P < 0.05), which indicates that neuroticism has a positive predictive effect on negative cognitive bias. Negative cognitive bias was positively correlated with the level of depression (γ =0.314, P < 0.05), which indicates that negative cognitive bias has a positive predictive effect on the level of depression. According to the mediating effect analysis, the mediating effect of negative cognitive bias between neuroticism and depression was statistically significant, and the mediating effect was 0.262. Negative cognitive bias played a mediating role between neuroticism and depression in college students. (3) Neuroticism was positively correlated with negative affect (γ =0.703, P < 0.05), which indicated that neuroticism has a positive predictive effect on negative affect. Negative affect was positively correlated with depression level (γ =0.307, P < 0.05), which indicated that negative affect has a positive predictive effect on depression level. According to the analysis of the mediating effect, the mediating effect of negative affect between neuroticism and depression level of college students was statistically significant, and the mediating effect was 0.307. Negative affect plays a mediating role between neuroticism and depression levels in college students. Conclusion: (1) Neuroticism has a direct positive predictive effect on college students' depression level, (2) negative cognitive bias plays a mediating role between neuroticism and depression level of college students, and (3) negative affect plays a mediating role between neuroticism and depression level of college students. Therefore, negative cognitive bias and negative affect play multiple mediating roles between neuroticism and depression levels in college students. [ABSTRACT FROM AUTHOR]

Purpose: Organic carbon (OC) plays an important role in the multimedium transport of pollutants and the carbon cycle. However, the distribution and fate of OC in coastal areas with multiple sedimentary environments, especially in underdeveloped coastal areas, have been underappreciated and lacked sufficient understanding. Materials and methods: In this paper, the characteristics and fate of OC in four sedimentary environments (mangrove, sandy coast, bay, and estuary) in a coastal area in Guangdong, China, were compared. Dissolved organic carbon (DOC) and suspended sediment (SPS) concentrations in water phases as well as total organic carbon (TOC) content and grain size distribution in sediments were determined. Results and discussion: The DOC concentrations and TOC contents were 0.006–13.66 mg L−1 and 0.04–9.51%, respectively, indicating a large spatial heterogeneity. The DOC levels showed an increasing trend into the bays and a decreasing trend along the estuaries, relating to hydrodynamic conditions for OC transport. The SPS concentrations were positively correlated with the TOC/DOC ratios in estuaries, confirming the carrier role of SPS in water–sediment systems. No significant differences in DOC concentrations were found under different water column depths, inferring that water–sediment ratios were not a limiting factor for DOC levels. The actual OC storage of the whole mangrove sedimentary environment was underestimated by 18.2% when calculated using the OC levels of the largest mangrove. Conclusion: Our results suggest that the OC storage estimation in multiple sedimentary environments could be underestimated. This study provides new insight for management and protection of coastline eco-environments and the estimation of carbon stock in the hopes of adapting to climate change. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has become frequently used in data and knowledge production in diverse domain studies. Scholars began to reflect on the plausibility of AI models that learn unexplained tacit knowledge, spawning the emerging research field, eXplainable AI (XAI). However, superior XAI approaches have yet to emerge that can explain the tacit knowledge acquired by AI models into human-understandable explicit knowledge. This paper proposes a novel eXplainable Dimensionality Reduction (XDR) framework, which aims to effectively translate the high-dimensional tacit knowledge learned by AI into explicit knowledge that is understandable to domain experts. We present a case study of recognizing the ethnic styles of village dwellings in Guangdong, China, via an AI model that can recognize the building footprints from satellite imagery. We find that the patio, size, length, direction and asymmetric shape of the village dwellings are the key to distinguish Canton, Hakka, Teochew or their mixed styles. The data-derived results, including key features, proximity relationships and geographical distribution of the styles are consistent with the findings of existing field studies. Moreover, an evidence of Hakka migration was also found in our results, complementing existing knowledge in architectural and historical geography. This proposed XDR framework can assist experts in diverse fields to further expand their domain knowledge. [ABSTRACT FROM AUTHOR]

Intangible cultural heritage (ICH) terms are unique expressions of cultural knowledge and practices that are deeply rooted in a particular region or community. Accurately translating ICH terms is crucial for sharing this knowledge and promoting cross-cultural understanding. However, the complex nature of ICH terms, including their regional and cultural specificity, means that mistranslations can easily occur during the translation process. In addition to linguistic and cultural barriers, psychological factors can also impact the accuracy of translations. Translation psychology, a new discipline that examines the psychological process of bilingual conversion and its cognitive mechanisms, can provide insights into the translation of ICH terms. This paper proposes an information processing model of translating ICH terms based on translation psychology, which examines the psychological processes of translators during the translation of Chinese ICH terms into English. Through questionnaires and translation exercises, the study compares and analyzes the psychological activity process of the translators, verifies the expression of translation psychology in the translation of ICH terms, and identifies the characteristics of students' translations. The study's subjects were non-English major sophomores with diverse academic backgrounds, randomly sampled from a representative polytechnic university in Guangdong. The findings of this study are significant for improving the quality of translations and promoting cross-cultural understanding of ICH terms. By understanding the psychological factors involved in the translation of ICH terms, we can overcome language and cultural barriers and accurately convey the rich cultural heritage embodied in these terms. [ABSTRACT FROM AUTHOR]

To ensure pavement maintenance funds are reasonably allocated, it is necessary to comprehensively and effectively rank pavement sections based on multidimensional condition data to determine priority for rehabilitation. This paper proposes an unsupervised multidimensional performance data-driven model for evaluating road maintenance priority based on comprehensive multidimensional indicators, which solves the issues of a single decision index and inflexibility of traditional models. In this hybrid model, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is first used to cluster the similar pavement performance properties and identify noise in the data, then the support vector machine (SVM) is employed to assess the rank and priority of different pavement section clusters. Model's effectiveness was verified through a case study of a highway in Guangdong Province, China, in which data from 290 pavement sections were ranked according to five attributes. Six clusters and five maintenance levels were obtained, and the model was used to evaluate overall pavement performance and assign specific rehabilitation measures to different clusters. The results confirm that the proposed hybrid model requires almost no human intervention and can contribute to big data approaches to road maintenance management. [ABSTRACT FROM AUTHOR]

Using the quantile GARCH model estimators to gauge the bidirectional risk magnitude and the Granger causality test in risk distributions to detect the existence of risk spillovers, this paper explores the extreme risk spillovers of China's regional carbon markets to local listed firm's stock returns. From the perspectives of macro region level and micro firm level, the findings are outlined as follows. First, among the top three active carbon trading pilots (Hubei, Guangdong, and Shenzhen), Hubei pilot exhibits significant "low risk and high profit" features. Second, the predominant risk spillover effects to local listed firms are heterogeneous across pilots. Specifically, Hubei pilot is dominated by "up-to-down" effect, and Guangdong pilot is dominated by "down-to-down" effect, while Shenzhen pilot has no predominant effect. The heterogeneous risk spillover performance may be caused by the regional divergence in economic development, industry structure, and cap setting concerning each pilot. Third, the risk transmission performance from carbon allowance price to local listed firm's stock returns depends on the firm's belonging sector. That is, environment-related firms, either environment-friendly firms or pollution-intensive firms, are more susceptible to carbon markets' risks compared with environment-unrelated firms. This paper supplies novel information on the risk transmission from carbon markets to local economic entities, which proves valuable not only for firms to improve risk aversion ability but also for policy-makers to perfect carbon markets' mechanism. [ABSTRACT FROM AUTHOR]

By establishing an objective and effective indicator system, we can accurately estimate the economic losses inflicted by typhoon storm surge. With Guangdong selected as the area for our case study, we used confirmatory factor analysis to identify and select three types of risk factors generating economic losses from such disasters: hazard, vulnerability, and disaster resilience. Moreover, by dividing the study area into three time periods in based on economic development conditions, we analyzed the indicator changes in various risk factors within them. Studies have shown that impact indicators from various risk factors at different time periods have not changed significantly, while their degree of relevance has varied with each risk factor. Compared with the traditionally established indicator systems, the basic indicators based on historical cases in this paper are more factual, and the application of confirmatory factor analysis in the selection of indicators has eliminated the interference of subjective factors, rendering the results more rational and scientific. [ABSTRACT FROM AUTHOR]

Accurate carbon price prediction is a crucial task for the carbon trading market. Previous studies have ignored the impact of online data and are limited to point predictions, which brings challenges to the accurate forecasting of carbon prices. To address those issues, this paper proposes an interval-valued carbon price forecasting method based on web search data and social media sentiment. First, we collect web search data and social media sentiment to improve prediction performance by synthesizing multiple types of data information. Second, we employ principal component analysis (PCA) to preprocess high-dimensional web search data, and utilize BosonNLP for quantifying social media information, thereby enhancing the predictability of the dataset. Subsequently, a variational mode decomposition (VMD) is applied to the carbon price and online data, followed by utilizing particle swarm optimization support vector regression (PSO-SVR) to predict each sub-modes and summing them up to obtain the ultimate forecasting outcome. Finally, using carbon prices in Guangdong and Hubei provinces as case studies, the experimental results demonstrate that web search data and social media sentiment significantly enhance the predictive accuracy of interval-valued carbon prices. Furthermore, the proposed VMD-PSO-SVR outperforms other comparative models in the accuracy and reliability of interval-valued forecasting. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most significant increasing areas for summer precipitation extremes in China. In this paper, the number of very heavy precipitation days (R20day) is selected as a representative variable to explore the probable causes of abnormal changes in summer precipitation extremes in recent decades by using the gridded 0.25° × 0.25° observation dataset of CN05.1, NCEP/NCAR Reanalysis 1 with a horizontal resolution of 2.5° × 2.5° and NOAA Extended Reconstructed Sea Surface Temperature (ERSST) V5 with a horizontal resolution of 2.0° × 2.0°. The onset of the South China Sea summer monsoon was early (late), and the R20day in summer was more (less) on both interannual and interdecadal scales. In recent decades, the East Asian summer monsoon and the western North Pacific monsoon weakened, and the R20day in the GBA increased. When the Eurasian teleconnection pattern is in the positive (negative) phase, positive (negative) height anomalies occur in Mongolia and North Central China, and negative (positive) height anomalies occur in South China, which enhances (weakens) vertical upward movements and the south wind anomaly in the lower troposphere in South China, resulting in strong (weak) humidity and more (less) R20day in the GBA. The influences of the Silk Road teleconnection pattern, East Asia/Pacific teleconnection pattern, North Pacific decadal oscillation and western Pacific warm pool strength on R20day are only significant on an interdecadal scale. The North Pacific gyre oscillation has significant effects on the interdecadal change and weakly significant effects on the interannual variation of R20day in the GBA. On an interannual scale, the south-north oscillation of sea surface temperature in the North Pacific and Indian Ocean dipole plays a significant role. [ABSTRACT FROM AUTHOR]

Aiming at the ecological footprint model, the traditional trade adjustment method only considered the international trade process at the urban scale, ignoring the trade footprint generated by domestic trade and indirect trade in various products. This paper adopts the urban-scale ecological footprint model based on the macro-trade adjustment method to calculate the trade adjustment coefficient of biological products and the energy trade adjustment coefficient respectively to correct the trade footprint. The results showed that the per capita ecological deficit showed a straight upward trend, from 0.07351 hm2 in 2013 to 0.15472 hm2 in 2018. From 2013 to 2018, the per capita ecological footprint of Guangdong Province was greater than the per capita ecological carrying capacity, and the ecological economic system of Guangdong Province was in an unsustainable state. According to the trade ecological footprint, Guangdong Province was a completely foreign resource and service exporting city, which was consistent with Guangdong Province's own economic development direction; the analysis results of the ecological product trade footprint were more consistent with the current city positioning of biological resource products of each city, and the energy indirect trade footprint. The improved ecological footprint model could more accurately assess the true status of ecological vitality above the urban scale. [ABSTRACT FROM AUTHOR]

From June 10th to 13th, 2019, a continuous heavy rainfall occurred in Longchuan County, Guangdong Province, causing many landslide hazards. Among Longchuan County districts, Mibei Village is one of the hardest-hit areas and suffered severe losses. In this paper, field investigation, remote sensing image interpretation, and UAV aerial photography were used to investigate and analyze hazard characteristics. Combined with rainfall monitoring data, laboratory and field tests data, and existing research results, the characteristics and failure mechanism of group-occurring landslides in Mibei Village were studied. Because of the continuous heavy rainfall, 327 landslides occurred in the study area, mainly distributed in the north of the Mibei River and along the X158 road. The terrain slope of landslide hazards ranged from 35° to 45°, and the slope structure can be divided into two types. Granite residual soil was the main part of landslide mass, and sliding surface developed along with the interface between bedrock and covering layer. The continuous heavy rainfall from June 10th to 13th was the main triggering factor of the disaster. The total precipitation was 281.3 mm, and the rainfall on June 10th was 153.5 mm. The rain led to the continuous increase in volume water content in granite residual soil and completely weathered granite. The shear strength and parameters of the two materials changed differently, and slope stability continued to decrease, and then landslides occurred under terrain conditions and engineering excavation space. Untimely support and unreasonable support measures for the excavation slope exacerbated the disaster. The development degree of debris flows in the study area was very low, and debris flows were shown as the secondary disaster of landslides. The branch gully terrain is the key to transforming the landslide into the debris flow, and a large amount of loose deposits in the main gully will become the potential source of debris flow in the future. [ABSTRACT FROM AUTHOR]

Simplicity, efficiency and precision are basic principles for modeling and analyzing of coal-fired boilers data. However, the load fluctuations, system delay, multi-variable coupling pose great challenges to the high-precision modeling for NOx emission. A hybrid feature selection method for boiler data is proposed to predict accurately NOx emission. Firstly, the mechanism analysis is used to narrow the feature scope, and the feature set is selected preliminarily. Secondly, maximum information coefficient (MIC) method is introduced to calculate the correlation between features and NOx information to eliminate boiler system delay. Thirdly, a combined feature evaluation method is developed, which integrates Filter and Embedded method to obtain feature ranking, then the ranking information is regarded as priori knowledge to improve the genetic algorithm. Finally, a fitness function to maximize prediction accuracy and minimize feature dimension is constructed based on hybrid method to realize feature subset selection and NOx emission prediction. Original data are collected from one 1000 MW coal-fired unit in the Guangdong province of China. Experimental results show that the number of features is reduced by nearly 70%, the MAPE of LightGBM regression model is no more than 2%. Higher prediction accuracy can be obtained using the features extracted through the proposed hybrid method. [ABSTRACT FROM AUTHOR]

With the rapid development of e-commerce, the backlog of distribution orders, insufficient logistics capacity and other issues are becoming more and more serious. It is very significant for e-commerce platforms and logistics enterprises to clarify the demand of logistics. To meet this need, a forecasting indicator system of Guangdong logistics demand was constructed from the perspective of e-commerce. The GM (1, 1) model and Back Propagation (BP) neural network model were used to simulate and forecast the logistics demand of Guangdong province from 2000 to 2019. The results show that the Guangdong logistics demand forecasting indicator system has good applicability. Compared with the GM (1, 1) model, the BP neural network model has smaller prediction error and more stable prediction results. Based on the results of the study, it is the recommendation of the authors that e-commerce platforms and logistics enterprises should pay attention to the prediction of regional logistics demand, choose scientific forecasting methods, and encourage the implementation of new distribution modes. [ABSTRACT FROM AUTHOR]

This paper takes energy consumption PM2.5 emission as research object, and quantitatively analyzes the PM2.5 emission level in Hunan and Guangdong provinces from 2012 to 2017. We build a PM2.5 emission decomposition model divided by five sectors, including industry, transportation, construction, resident, and other, and use attribution method and Tapio decoupling index to analyze the relationship between economic development and PM2.5 emission level. The results show that (1) the difference in PM2.5 emissions between the two provinces appeared in 2015; (2) the contribution rate of total PM2.5 emissions is 83.1%, and coal consumption is the determine factor of PM2.5 emissions; industry is the main source of sector contribution with rate of 70.91%; (3) Guangdong's pollution control capacity is much higher than that of Hunan, while Hunan's PM2.5 marginal emission-reduction potential is much higher than that of Guangdong; (4) economic growth is the first increasing emission reason of PM2.5 emission changes, while the intensity of industrial energy consumption is the first reduction emission reason; (5) there is a big difference between the economic development of the two provinces and the decoupling of PM2.5 pollution. [ABSTRACT FROM AUTHOR]

This paper constructs an embodied carbon model in inter-provincial trade based on China's inter-provincial multi-regional input-output table. By analyzing the embodied carbon emissions for Guangdong with the forefront of economic development, this research reveals the impact of trade scale and structure between Guangdong Province and other provinces on embodied carbon emissions, and finds out key provinces and sectors for emission reduction. It can enable national and regional economic and environmental policies to be implemented into specific industries, guide capital flow to key sectors for emission reduction, provide comments for relevant national and provincial decision-making sectors to adjust trade structure, and play the role of inter-provincial trade in energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

Fatal landslides cause severe disasters to human lives and socioeconomic costs in China. In this study, the data non-seismically fatal landslides were collected between 2004 and 2016 in China. The hazard and life risk criteria of these fatal landslides were assessed, and the government's investment and ecological influencing factors for landslide prevention and mitigation were analyzed. There were more fatal landslides in Sichuan, Guizhou, Yunnan, Hunan, and Guangdong provinces. High landslide density value focused on Guizhou, Hunan, and Guangdong province had very high landslide density value, while Gansu held the biggest fatality density value as a result of a few huge fatal landslide events. The Chinese life risk evaluation criterion was higher than those in other countries because there was a greater population density in landslide-prone areas. Nevertheless, the government has invested a great deal of human and financial resources for landslide mitigation over the past 13 years. In total, 244,559 engineering projects were carried out and $15,920.89 million was spent. Thus, a total of 13,603 landslides were successfully predicted and 641,333 persons and $1,372.94 million has been saved. Additionally, the types of land use, afforestation area, and soil erosion management have a positive effect on landslides. However, a trend of reverse increase was presented in fatal landslides. This paper gives a detailed examination of the non-seismically fatal landslide hazard and proves an evaluation of the Chinese government's contribution to landslide mitigation by integrating engineering and ecological measures. [ABSTRACT FROM AUTHOR]

Promoting the use of reusable takeaway food container (RTFC) in takeaway industry is an effective way to reduce the negative environmental impacts caused by single-use plastic containers. This study intended to figure out the barriers to the new business model deployment through evaluating the economic costs and benefits of RTFC from a stakeholder's perspective. Taking the pilot RTFC project at a university in Guangdong province as a case, we established a holistic cost and benefit analysis framework from a stakeholder's perspective. Both the costs and benefits with and without a market price of each stakeholder were evaluated using market price method and contingent valuation method. The analysis result shows that while shifting to reusable takeaway food container, the costs and benefits of all the main stakeholders changed. The net benefit of consumers is positive about 360 thousand yuan during 2020–2025, while the platform company, the university and the restaurants gain negative net benefits ranging from − 20 to − 470 thousand yuan under current operation situation, which may hinder the sustainable development of this new business model. However, the sensitivity analysis shows that all the stakeholders could gain a positive net benefit by adjusting the rental price, cleaning price and packaging price, as well as optimizing the location of recycling cabinets. [ABSTRACT FROM AUTHOR]

How do Chinese provinces perform in their commitments to carbon emission responsibility? This study extends the carbon emission responsibility allotment proposed by Dietzenbacher et al. (Nat Commun 11:1130, 2020) to a national multi-region setting to analyze provincial, industrial, and bilateral trade emission responsibility allotment in China. This paper uses China's latest multi-region input-output tables in 2012 and 2015, and finds that based on the total amount of ERA carbon emissions, the province with the largest carbon emission responsibility in 2012 is Shandong, followed by Jiangsu and Hebei. From the perspective of industry, the construction is the highest carbon emissions in each province, followed by general and specialist machinery. In the allocation of carbon emissions responsibility in 2015, the credit between Xinjiang and Jiangsu is the largest; Guangdong and Jiangsu have the largest penalty. Among total credits which the province's trade with others, Xinjiang has the highest credit, followed by Shanghai and Jiangsu; among total penalties which the province trade with others, Guangdong Province is the largest penalty province, followed by Guangxi. [ABSTRACT FROM AUTHOR]

Red beds cover approximately 9.5% of China, and are home to approximately 144 million people. In total, 83% of these lands are distributed in humid regions making it an important part of research on red bed soil erosion in China in these areas. This paper presents the main types of land degradation in red bed landscapes and the status of current soil erosion in a typical red bed basin, the Nanxiong Basin located in the north of Guangdong Province, China, and establishes the connection between management strategies and regional economic development in humid red bed regions of China. The soil erosive modulus was calculated in the Nanxiong Basin by using RUSLE (The Revised Universal Soil Loss Equation). The results of overlapping analyses demonstrated that appropriate measures, such as the Return Farmland to Forests initiative, should be taken at the junction of central red bed areas and mountainous areas in order to mitigate current soil erosion. Two examples are presented to demonstrate this: the tourism development in Mt. Danxiashan, a noted scenic mountainous area near Nanxiong Basin, and the land degradation mitigation in the Nanxiong Basin. Both examples promote local economic growth while simultaneously protecting the environment. A 'stakeholder' strategy is pursued at Mt. Danxiashan, which can help residents to understand their positive effects on the environment as well as increase their income. The second example, in Nanxiong City, showcases how local farmers became stakeholders by implementing contract responsibility and self-support systems for economic forests and terraced land in the 1980s. [ABSTRACT FROM AUTHOR]

Currently, fiber optic communication has become the primary means of communication within China's telecommunications network. Both domestic and international scholars have conducted extensive research on various types of optical cables, achieving significant results. However, to date, there has been no research, either domestically or internationally, addressing the discharge issues associated with the insulated optical-unit phase conductor (IOPPC) in 110-kV transmission lines. In the course of promoting the use of 110-kV lines, there was an incident in Guangdong Province, China, involving the fracture of an IOPPC downlead cable. This paper proposes a modified structure for the IOPPC downlead cable to address the aforementioned fracture incident. First, the finite element method is utilized to calculate the electric field intensity of both the traditional and modified IOPPC downlead cable structures under a voltage of 110-kV. Preliminary verification of the effectiveness of the modified structure is then conducted. Subsequently, the proposed modified structure is verified and further optimized through power frequency withstand voltage tests. Simulation results indicate that the traditional structure exhibits a high electric field intensity in the air region near the PVC cube. In contrast, the addition of a semiconductor shielding layer in the modified structure effectively suppresses the increase in electric field intensity in this area. Power frequency withstand voltage test results further confirm the effectiveness of the semiconductor shielding layer in suppressing the electric field intensity. However, it was observed that discharge phenomena still occurred at the cutoff point of the semiconductor shielding layer. Finally, the modified structure is optimized to effectively eliminate the discharge phenomena at the cutoff point of the semiconductor shielding layer. [ABSTRACT FROM AUTHOR]

This study examines the effectiveness of court-appointed lawyers in comparison to private attorneys within China's criminal justice system, focusing on the "Lawyers for All" program. Utilizing data from Guangdong courts between 2018 and 2021 and covering five types of crimes, the research employs propensity score matching to evaluate sentencing lengths and probation rates. The findings indicate that defendants represented by court-appointed lawyers typically receive shorter sentences than those with private counsel, but they are less likely to be granted probation. Additionally, an innovative metric—"actual time served in prison"—suggests a reduced incarceration period for defendants with court-appointed attorneys. The study proposes that the collaborative role of court-appointed lawyers within the Chinese courtroom workgroup potentially influences these outcomes, contrasting with the adversarial nature of private attorneys. This analysis contributes to the broader understanding of legal representation in authoritarian regimes, highlighting the unique dynamics within China's legal system. [ABSTRACT FROM AUTHOR]

With the rapid development of infrastructure, more and more coal-bearing soil are encountered in the southern mountain area of China, the property of coal-bearing soil has a great impact on the safety of the projects. Taking powdery coal-bearing soil along the Guangdong distract of Wushen Expressway as research object in this paper, the images of powdery coal-bearing soil microstructure were obtained by using Environmental Scanning Electron Microscopy (ESEM) under different water content (10%, 15%, 20% and 25%) after direct shear test. The microstructural morphology characterization of shear plane are analyzed by MATLAB, and the microstructure parameters of coal-bearing soil are measured by Image Pro-Plus (IPP) software. Based on the fractal theory, the fractal model of coal-bearing soil microstructure is established, and the fractal dimensions of pore profile and number and size distribution of pores of coal-bearing soil are obtained in two-dimensional space. The fractal dimension of pore profile and porosity changing with pore size are analyzed. The results show that the basic unit of the microstructure of coal-bearing soil is schistose aggregated particles. The contact relationship is mainly surface–surface contact and face-side contact. The shape of the flaky granule aggregated body is irregular and the orientation is not obvious. The shape of pores is anisometric and slotted. With the increase of water content, the roughness and fluctuation degree of the shear plane first increase and then decrease. The connectivity between the pores is improved and the shearing strength parameters also increases first and then decreases. The turning point is near the optimum moisture content (between 10 and 15%). The microstructure of coal-bearing soil is more complex and has obvious fractal characteristics. It is described by the fractal models of the equivalent area and equivalent perimeter of pores and number and size distribution of pores, and the fractal dimension is between 1 and 2 in two dimensional space. The fractal model of the microstructure morphology of shear plane is established, and the height and length of micro-convex bodies can be calculated by mathematical equation. [ABSTRACT FROM AUTHOR]

The paper introduces a three-dimensional numerical technique to assess typhoon hazards in China coastal regions based on a series of full-set numerical meteorology simulations. The boundary and initial conditions of the simulations are provided by adding pseudorandom fluctuations, which represent the localized, short-term meteorological variations, to synoptic fields, which show the large-scale, long-term meteorological patterns. A series of bogus typhoons are inserted into the initial field to provide the "seeds" from which the artificial typhoons could grow. The initial positions and intensities of the bogus typhoons are drawn from the random variables whose statistics agree with those derived from historical typhoon track data. In the present study, 1503 full-set meteorology simulations of artificial typhoons are conducted. The extreme wind speeds versus return periods calculated from the simulation results are compared to not only the specifications in the load code, but also the results from the previous studies. It is found that the extreme wind speeds in the Pearl-River Delta are, contradicting to the common expectation, higher than at the mainland side of the Taiwan Strait, which imply that the typhoons hitting Guangdong are, on average, more intense than those influencing Fujian. Given the possibility to improve the three-dimensional meteorology model in the future, the simulation technique proposed in the present study provides a novel direction to assess the meteorological hazards, including threads posted by typhoons. [ABSTRACT FROM AUTHOR]

There is evidence showing that vertical transmission of dengue virus exists in Aedes mosquitoes. In this paper, we propose a deterministic dengue model with vertical transmission in mosquitoes by including aquatic mosquitoes (eggs, larvae and pupae), adult mosquitoes (susceptible, exposed and infectious) and human hosts (susceptible, exposed, infectious and recovered). We first analyze the existence and stability of disease-free equilibria, calculate the basic reproduction number and discuss the existence of the disease-endemic equilibrium. Then, we study the impact of vertical transmission of the virus in mosquitoes on the spread dynamics of dengue. We also use the model to simulate the reported infected human data from the 2014 dengue outbreak in Guangdong Province, China, carry out sensitivity analysis of the basic reproduction number in terms of the model parameters, and seek for effective control measures for the transmission of dengue virus. [ABSTRACT FROM AUTHOR]

Environmental degradation and climate change are two important issues that threaten human survival and sustainable social development. Based on the characteristics of the same source of sulfur dioxide and greenhouse gases, we analyze the collaborative governance mechanism of carbon emission trading on sulfur dioxide. The results show that carbon emission reduction trading may not necessarily deliver sulfur dioxide reduction co-benefits. Then, we conduct an empirical using data of 30 regions in China from 1998 to 2017. The results show that the co-benefits of carbon emission trading in terms of the reduction of sulfur dioxide are regionally heterogeneous. The carbon emission trading policies implemented in Beijing, Chongqing, Hubei, and Guangdong have realized collaborative governance on sulfur dioxide. However, the carbon emission trading policies implemented in Tianjin and Shanghai have not realized collaborative governance on sulfur dioxide. Moreover, Chongqing has the highest average annual sulfur dioxide reduction co-benefits, followed by Guangdong. The gap of sulfur dioxide reduction co-benefits between Beijing and Hubei's synergistic emission reduction effect is small. Moreover, the sulfur dioxide reduction co-benefits of carbon emission trading are mainly achieved by reducing fossil energy consumption. Meanwhile, the carbon emission trading implemented in Beijing also delivers sulfur dioxide reduction co-benefits by improving pollution reduction technology. [ABSTRACT FROM AUTHOR]

Guangdong is the most economically developed province in China, which is a large CO emitter and hence is faced with severe carbon reduction pressures. In this paper, a cost assessment methodology based on scenario analysis is presented. A CO source and sink database was built at Guangdong after detailed investigations on the point sources and sedimentary basins. Fifteen transport and five storage scenarios were defined and studied, respectively. Cost estimates based on these scenarios show that during its lifetime, the costs of both transport and storage depend on the amount of CO processed. More CO being processed will bring down the unit costs of both transport and storage. However, it was observed that there is a cost inflection point between the storage amount of 35.2 and 52.8 Mt/year, which means that as the storage amount increases, the storage cost will first decrease and then increase. Source region S1 in Guangdong has been recommended for an early chance of CO storage. Preliminary cost comparisons have shown that the results presented in this study are reasonable, but to improve the cost assessment accuracy of offshore CO storage, a methodology based on a CO storage design that can integrate local prices needs to be further developed. [ABSTRACT FROM AUTHOR]

To meet the challenge of sustainable development, sustainability must be made. Ecological network analysis (ENA) was introduced in this paper as an approach to quantitatively measure the growth, development, and sustainability of an economic system. The Guangdong economic networks from 1987 to 2010 were analyzed by applying the ENA approach. Firstly, a currency flow network among economic sectors was constructed to represent the Guangdong economic system by adapting the input-output (I-O) table data. Then, the network indicators from the ENA framework involving the total system throughput (TST), average mutual information (AMI), ascendency (A), redundancy (R) and development capacity (C) were calculated. Lastly, the network indicators were analyzed to acquire the overall features of Guangdong’s economic operations during 1987-2010. The results are as follows: the trends of the network indicators show that the size of the Guangdong economic network grows exponentially at a high rate during 1987-2010, whereas its efficiency does not present a clear trend over its whole period. The growth is the main characteristic of the Guangdong economy during 1987-2010, with no clear evidence regarding its development. The quantitative results of the network also confirmed that the growth contributed to a great majority of the Guangdong economy during1987-2010, whereas the development’s contribution was tiny during the same period. The average value of the sustainability indicator (α) of the Guangdong economic network was 0.222 during 1987-2010, which is less than the theoretically optimal value of 0.37 for a sustainable human-influenced system. The results suggest that the Guangdong economic system needs a further autocatalysis to improve its efficiency to support the system maintaining a sustainable evolvement. [ABSTRACT FROM AUTHOR]

There is growing evidence that levels of fear and anxiety have increased during the COVID-19 pandemic. However, given regular epidemic prevention and control measures, longitudinal changes and causal factors in the incidence of fear and anxiety need to be measured and explored. College students completed online surveys in two wave studies a year apart. The participants who completed both of the surveys numbered 22,578. The online surveys were completed at the pandemic's normalization/prevention stage (T1, from June 1 to 15, 2020) and during a phase of new local transmission of the disease in Guangdong Province (T2, from June 10 to 18, 2021). Multiple linear regressions were used to examine fear and anxiety predictors from demographic characteristics. Fear related to COVID-19 had significantly decreased at T2 (t = 66.64, p < 0.001), however, anxiety had significantly increased at T2 (t = -5.03, p < 0.001). In particular, not implementing preventive measures (e.g., handwashing) during the COVID-19 pandemic had the greatest impact in predicting the change in fear levels. By contrast, prior poor mental health status contributed the most in predicting the change in degree of anxiety. These results suggest different changes in anxiety levels (deterioration) and degree of fear (mitigation) occurred as the COVID-19 pandemic progressed. These findings have implications for planning mental health crisis provisions and have long-term impact beyond this pandemic. [ABSTRACT FROM AUTHOR]

As a major carbon emitter, the power sector plays a crucial role in realizing the goal of carbon peaking and carbon neutrality. This study constructed a low-carbon power system based on the LEAP model (LEAP-GBA) with 2020 as a statistic base aiming of exploring the low-carbon transformation pathway of the power sector in the Guangdong–Hong Kong, and Macao Greater Bay Area (GBA). Five scenarios are set up to simulate the demand, power generation structure, carbon emissions, and power generation costs in the power sector under different scenarios. The results indicate that total electricity demand will peak after 2050, with 80% of it coming from industry, buildings and residential use. To achieve net-zero emissions from the power sector in the GBA, a future power generation mix dominated by nuclear and renewable energy generation and supplemented by fossil energy generation equipped with CCUS technologies. BECCS technology and nuclear power are the key to realize zero carbon emissions from the power sector in the GBA, so it should be the first to promote BECCS technology testing and commercial application, improve the deployment of nuclear power sites, and push forward the construction of nuclear power and technology improvement in the next 40 years. [ABSTRACT FROM AUTHOR]

Defensive capability is one of the essential attributes of traditional military settlements. In the Ming dynasty, coastal Wei fort was the one of the most functionally complex and wide-ranging fortifications in the military defense system of China. Because many factors affect their defensive capacities, including three dimensions: individual construction, synergistic links, and regional jurisdiction, it is not easy to compare different settlements' defensive capacities or to judge the degrees of different factors' influences. Through principal component analysis, this study determines the weights of each minor factor. It constructs a model for evaluating traditional Chinese military settlements' defensive capabilities, to quantify the defensive capability. The results show that the synergistic relationship between the settlements, especially settlement accessibility, has the most significant impact on defensive capability, much higher than a single castle's defensive construction. The defensive capability index of the Wei forts in Guangdong is the highest, consistent with the highest rate of victory in the wars fought on the coast during the Ming dynasty. The defensive capacity is directly proportional to the rate of victory, which validates this evaluation model's soundness. This study not only comprehensively evaluates the coastal Wei forts' defensive capacity in the Ming Dynasty, but also provides new methods for the quantitative or comparative analysis of military settlements at other temporal and spatial scales. [ABSTRACT FROM AUTHOR]