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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]

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]

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]

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]

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]

In recent times, a new wave of scientific and technological advancements has significantly reshaped the global economic structure. This shift has redefined the role of regional innovation, particularly in its contribution to developing the Guangdong–Hong Kong–Macao Greater Bay area (GBA) into a renowned center for science, technology, and innovation. This study constructs a comprehensive evaluation system for the Regional Innovation Ecosystem (RIE). By applying the coupling coordination degree model and social network analysis, we have extensively analyzed the spatial structure and network attributes of the coupled and coordinated innovation ecosystem in the GBA from 2010 to 2019. Our findings reveal several key developments: (1) There has been a noticeable rightward shift in the kernel density curve, indicating an ongoing optimization of the overall coupling coordination level. Notably, the center of gravity for coupling coordination has progressively moved southeast. This shift has led to a reduction in the elliptical area each year, while the trend surface consistently shows a convex orientation toward the center. The most significant development is observed along the 'Guangdong–Shenzhen–Hong Kong–Macao Science and Technology Innovation Corridor', where the level of coupling coordination has become increasingly pronounced. (2) The spatial linkages within the GBA have been strengthening. There are significant spatial transaction costs in the regional innovation ecological network. In the context of the 2019 US-China trade war, the cities of Jiangmen and Zhaoqing experienced a notable decrease in connectivity with other cities, raising concerns about their potential marginalization. (3) Guangzhou, Shenzhen, and Hong Kong have emerged as core nodes within the network. The network exhibits a distinctive "core–edge" spatial structure, characterized by both robustness and vulnerability in various aspects. [ABSTRACT FROM AUTHOR]

To propel the green transformation of the transportation industry in Guangdong Province. Against the backdrop of the five-year plan, this study employs the Tapio decoupling model and the Logarithmic Mean Divisia Index decomposition method to analyze the decoupling status and driving factors of carbon emissions from transportation and economic growth in Guangdong Province from 2001 to 2020. The results show that:(1) Both the total volume of carbon emissions from transportation and per capita emissions exhibit an overall upward trend, with petroleum-based emissions accounting for an overwhelming 96%, with diesel emissions register the highest proportion and most substantial increase. (2) The decoupling status predominantly manifests as weak decoupling, with intermittent years expansive coupling,, expansive negative decoupling, strong decoupling, and recessive coupling, thus indicating a persistent state of decoupling instability. (3) The study introduces the urbanization effect, wherein the effects of income urbanization, as well as spatial urbanization, predominantly exert positive driving influences. Conversely, the effects of energy intensity, population urbanization, industry scale, and energy structure collectively exert negative driving influences. Notably, the effect of income urbanization emerges as the primary factor propelling the augmentation of carbon emissions, while the energy intensity effect serves as the primary factor curbing such escalation. Finally, pertinent policy recommendations are put forth. [ABSTRACT FROM AUTHOR]

Castanopsis fissa is a native, broadleaf tree species in Guangdong with characteristics of barrenness and fast growth and is often used as a pioneer species for vegetation restoration with excellent ecological benefits. To explore the response of C.fissa to drought, this study investigated the drought tolerance mechanism of C.fissa using physiological and proteomic assessments. Using a potted continuous drought experimental method with normal water supply as a control, we measured photosynthetic parameters, antioxidant enzyme activities, and osmoregulatory substances of C. fissa in response to drought stress for 1 to 4 weeks, respectively. In addition, we used TMT quantitative proteomics to identify differentially expressed proteins (DEPs) between the drought-stress-treated C. fissa leaves and the control leaves. With the extension of drought stress time, the photosynthetic indexes and peroxidase (POD) activity of C. fissa leaves showed a decreasing trend. The malondialdehyde (MDA) content; superoxide Dismutase (SOD) and catalase (CAT) activities; and proline (Pro), soluble sugar (SS) and soluble protein (SP) contents showed an overall increasing trend, all of which reached significant differences at 4 w of stress. We identified 177 and 529 DEPs in the 2 and 4 weeks drought-stress leaves, respectively, in reference to the control leaves. These DEPs were closely related to physiological metabolic processes such as photosynthesis, energy and carbohydrate metabolism, stress response and defense, transcriptional regulation, and signal ion transduction. Drought stress mainly affects photosynthesis, carbohydrate metabolism, and protein synthesis and degradation in C. fissa leaves. At 2 weeks of stress, the expression of carbon metabolism, pyruvate metabolism and ribosome-related proteins was significantly changed, however, and at 4 weeks of stress, protein processing in the endoplasmic reticulum and spliceosome-related proteins were significantly increased in plant leaves. To alleviate the effect of water unavailability, the drought-stressed C.fissa leaves increased its oxidative protective enzyme system to eliminate excess reactive oxygen species (ROS) and also increased its Pro and SP contents to maintain the intracellular osmotic potential balance. [ABSTRACT FROM AUTHOR]

Globally, cervical cancer, whose etiologic factor is Human papillomavirus (HPV), is the third most common cancer among women. In cervical cancer screening, HPV testing is important. However, the prevalence of HPV in northern Guangdong Province has not been conclusively determined. A total of 100,994 women attending Yuebei People's Hospital Affiliated to Shantou University Medical College between 2012 and 2020 were recruited. HPV was tested by a polymerase chain reaction (PCR)-based hybridization gene chip assay. The prevalence of HPV among these women was established to be19.04%. Peak prevalence was observed in women aged 40–49 (7.29%). Besides, the prevalence of single-type HPV infection (14.46%) was significantly high, compared to multiple-type infection (4.58%) (p < 0.01), while the prevalence of high-risk HPV infection (19.97%) was significantly higher than that of low-risk genotypes (5.48%) (p < 0.01). The most prevalent high-risk genotypes were HPV52 (4.16%), HPV16 (2.98%), HPV58 (2.15%), HPV53 (1.58%) and HPV68 (1.34%). HPV co-infection with up to 10 genotypes was reported for the first time. Our findings suggested a high burden of HPV infections among women in northern Guangdong. Establishing the prevalence and genotype distribution characteristics of HPV infections in the region can contribute to cervical cancer prevention through HPV vaccination. [ABSTRACT FROM AUTHOR]

With the increase in extremely low birth weight (ELBW) infants, their outcome attracted worldwide attention. However, in China, the related studies are rare. The hospitalized records of ELBW infants discharged from twenty-six neonatal intensive care units in Guangdong Province of China during 2008–2017 were analyzed. A total of 2575 ELBW infants were enrolled and the overall survival rate was 55.11%. From 2008 to 2017, the number of ELBW infants increased rapidly from 91 to 466, and the survival rate improved steadily from 41.76% to 62.02%. Increased survival is closely related to birth weight (BW), regional economic development, and specialized hospital. The incidence of complications was neonatal respiratory distress syndrome (85.2%), oxygen dependency at 28 days (63.7%), retinopathy of prematurity (39.3%), intraventricular hemorrhage (29.4%), necrotizing enterocolitis (12.0%), and periventricular leukomalacia (8.0%). Among the 1156 nonsurvivors, 90.0% of infants died during the neonatal period (≤ 28 days). A total of 768 ELBW infants died after treatment withdrawal, for reasons of economic and/or poor outcome. The number of ELBW infants is increasing in Guangdong Province of China, and the overall survival rate is improving steadily. [ABSTRACT FROM AUTHOR]

A large number of adverse drug reaction (ADR) reports are collected yearly through the spontaneous report system (SRS). However, experienced experts from ADR monitoring centers (ADR experts, hereafter) reviewed only a few reports based on current policies. Moreover, the causality assessment of ADR reports was conducted according to the official approach based on the WHO-UMC system, a knowledge- and labor-intensive task that highly relies on an individual's expertise. Our objective is to devise a method to automatically assess ADR reports and support the efficient exploration of ADRs interactively. Our method could improve the capability to assess and explore a large volume of ADR reports and aid reporters in self-improvement. We proposed a workflow for assisting the assessment of ADR reports by combining an automatic assessment prediction model and a human-centered interactive visualization method. Our automatic causality assessment model (ACA model)—an ordinal logistic regression model—automatically assesses ADR reports under the current causality category. Based on the results of the ACA model, we designed a warning signal to indicate the degree of the anomaly of ADR reports. An interactive visualization technique was used for exploring and examining reports extended by automatic assessment of the ACA model and the warning signal. We applied our method to the SRS report dataset of the year 2019, collected in Guangdong province, China. Our method is evaluated by comparing automatic assessments by the ACA model to ADR reports labeled by ADR experts, i.e., the ground truth results from the multinomial logistic regression and the decision tree. The ACA model achieves an accuracy of 85.99%, a multiclass macro-averaged area under the curve (AUC) of 0.9572, while the multinomial logistics regression and decision tree yield 80.82%, 0.8603, and 85.39%, 0.9440, respectively, on the testing set. The new warning signal is able to assist ADR experts to quickly focus on reports of interest with our interactive visualzation tool. Reports of interest that are selected with high scores of the warning signal are analyzed in details by an ADR expert. The usefulness of the overall method is further evaluated through the interactive analysis of the data by ADR expert. Our ACA model achieves good performance and is superior to the multinomial logistics and the decision tree. The warning signal we designed allows efficient filtering of the full ADR reports down to much fewer reports showing anomalies. The usefulness of our interactive visualization is demonstrated by examples of unusual reports that are quickly identified. Our overall method could potentially improve the capability of analyzing ADR reports and reduce human labor and the chance of missing critical reports. [ABSTRACT FROM AUTHOR]

The Eucalyptus spp. is fast-growing and is usually harvested at a young age, which enables efficient and sufficient timber supply. However, its negative impact on soil fertility incurs wide debates. Therefore it is necessary to study on the growing traits of eucalytpus to provide scientific guidance on its plantation management and associated policy-making. In this study, we collected the sample plot data from 9 National Forest Inventories (NFIs) during 1973–2018, China Forest-Land Database Map in 2003 and 2016, as well as climate and elevation data and analyzed how the spatial distribution of eucalyptus plantations in China changes with time. We quantitatively characterized and evaluated the productivity, carbon accumulation capacity, and abandonment rate of eucalyptus plantations. Statistical models on how eucalyptus productivity and abandonment rate change with time are established to evaluate the soil fertility and feasibility for growing eucalyptus plantations and predict the temporal productivity variation. The results show that regions with annual mean temperature of 19–21 °C, annual precipitation of 1400–1600 mm, and elevation of 0–300 m above sea level is most suitable for the growth of eucalyptus. The annual mean productivity of eucalyptus plantations ranges from 4.14–8.57 m3 hm−2 a−1. Higher productivity (9.32–10.88 m3 hm−2 a−1) could be reached in newly cultivated lands. Based on data from the 9th inventory (2014–2018), the mean carbon fixation of eucalyptus is 5.29 t hm−2 a−1, which is 2.95 and 2.18 times greater than Pinus massoniana Lamb. and Cunninghamia lanceolata Lamb. Its plantations area accounts for 6.85% of total plantations in China, but it contributes to more than 17.96% of total annual cut from plantations. In Guangdong and Guangxi provinces, areas of eucalyptus plantations are 30.32% and 34.91% of the total plantation area in each province respectively, but eucalyptus plantations contribute to 66.29% and 49.97% of harvested timber stock volume Eucalyptus pla consumes soil fertility significantly. The cumulative abandonment rate (based on area) is about 25%, 50%, and 75% after 5, 10, and 20 years of growing eucalyptus, respectively. The soil fertility decreases significantly after 50 years of growing eucalyptus continuously. In such case, it is difficult to restore the soil fertility. It is suggested that with improved management measures such as proper crop rotation rotating crops properly, it is possible for the abandoned plantations to be reused for growing eucalyptus. Currently the rates of replanting eucalyptus are still below 20% and 30% after 20 and 50 years of without growing eucalyptus, respectively. Although the proportion of eucalyptus area replanted to its abandoned area is now less than 20% in 20 years and less than 30% in 50 years, there is potential to keep increasing the replanting rate. We argue that developing eucalyptus plantations could contribute to global timber supply, help to protect natural forests, increase global carbon storage and fixation, and help to slow down global warming. In conclusion, we should not stop growing eucalyptus despite its high consumption of soil fertility. [ABSTRACT FROM AUTHOR]

The social contact patterns associated with the infectious disease transmitted by airborne droplets or close contact follow specific rules. Understanding these processes can improve the accuracy of disease transmission models, permitting their integration into model simulations. In this study, we performed a large-scale population-based survey to collect social contact patterns in three cities on the Pearl River Delta of China in winter and summer. A total of 5,818 participants were face-to-face interviewed and 35,542 contacts were recorded. The average number of contacts per person each day was 16.7 considering supplementary professional contacts (SPCs). Contacts that occurred on a daily basis, lasted more than 4 hours, and took place in households were more likely to involve physical contact. The seasonal characteristics of social contact were heterogeneous, such that contact in the winter was more likely to involve physical contact compared to summer months. The spatial characteristics of the contacts were similar. Social mixing patterns differed according to age, but all ages maintained regular contact with their peers. Taken together, these findings describe the spatiotemporal distribution of social contact patterns relevant to infections in the Guangdong Province of China. This information provides important parameters for mathematical models of infectious diseases. [ABSTRACT FROM AUTHOR]

Germplasm resource collection and utilization are important in forestry species breeding. High-through sequencing technologies have been playing increasing roles in forestry breeding. In this study, specific-locus amplified fragment sequencing (SLAF-seq) was employed to analyze 149 masson pine (Pinus massoniana) accessions collected from Guangdong in China. A large number of 471,660 SNPs in the total collection were identified from 599,164 polymorphic SLAF tags. Population structure analysis showed that 149 masson pines could not be obviously divided into subpopulations. Two core sets, containing 29 masson pine accessions for increasing resin and wood yield respectively, were obtained from the total collection. Phenotypic analyses of five traits showed abundant variations, 25 suggestive and 9 significant SNPs were associated with the resin-yielding capacity (RYC') and volume of wood (VW) using EMMAX and FaST-LMM; 22 suggestive and 11 significant SNPs were associated with RYC' and VW using mrMLM and FASTmrMLM. Moreover, a large number of associated SNPs were detected in trait HT, DBH, RW and RYC using mrMLM, FASTmrMLM, FASTmrEMMA and ISIS EM-BLASSO. The core germplasm sets would be a valuable resource for masson pine improvement and breeding. In addition, the associated SNP markers would be meaningful for masson pine resource selection. [ABSTRACT FROM AUTHOR]

Enterovirus A71 (EVA71) and Coxsackievirus A16 (CVA16) are regarded as the two major causative pathogens in hand, foot and mouth disease (HFMD) epidemics. However, CVA6, previously largely ignored, became the predominant pathogen in China in 2013. In this study, we describe the epidemiological trendsofCVA6 during the annual HFMD outbreaks from 2008 to 2013 in Guangdong, China. The study results show that CVA6 has been one of three major causative agents of HFMD epidemics since 2009. The periodic rotation and dominance of the three pathogens, EVA71, CVA16 and CVA6, may have contributed to the continuously increasing HFMD epidemics. Moreover, phylogenetic analysis of the VP1 gene shows that major circulating CVA6 strains collected from 2009 to 2013 are distinct from the earlier strains collected before 2009. In conclusion, the discovery from this research investigating epidemiological trends of CVA6 from 2008 to 2013 explains the possible pattern of the continuous HFMD epidemic in China. The etiological change pattern also highlights the need for improvement for pathogen surveillance and vaccine strategies for HFMD control in China. [ABSTRACT FROM AUTHOR]