How Does Agricultural Green Transformation Improve Residents’ Health? Empirical Evidence from China

Promoting green and sustainable agriculture is of great significance for ensuring food security and addressing global challenges. Meanwhile, health has increasingly become a global concern. Nutrition and health are the purpose of agricultural production. As two major global issues, how agriculture empowers human health has long been discussed. Based on the provincial panel data of China from 2003 to 2021, this paper studies the impact of agricultural green transformation (AGT) on residents’ health and explores its impact mechanism. The empirical results show that: (1) AGT in China has significantly reduced the average mortality rate and maternal mortality rate and significantly increased the average life expectancy, indicating that AGT in China has significantly improved the health level. The conclusions of robustness testing methods such as replacing AGT indicators and controlling endogeneity are still valid; and (2) The impact of AGT on residents’ health depends on the regional economic level, and there is a threshold effect. Compared with low-income areas, the positive effects of AGT in high-income areas on residents’ health are more pronounced; and (3) Agricultural carbon emissions play an intermediary effect between AGT and residents’ health, and AGT can improve residents’ health by reducing carbon emissions. The level of local education development plays a moderating role in the relationship between AGT and residents’ health. Agricultural policy implications include enhancing the ability to protect and utilize agricultural resources, promoting the green and low-carbon transformation of agriculture, and taking a more scientific and systematic approach towards the complex diversity of health risk factors

Influence of ground-surface deformation in pipe jacking construction with parallel differential section

The development of urban underground space and traffic promotes the wide application of large section pipe jacking technology in urban tunnel construction.The functional requirements of parallel pipe jacking tunnel are different, so shapes and sizes of the section are also different.Based on the double-line parallel pipejacking tunnel with difference large section under through the main road in the city, a three-dimensional finite element calculation model is established for systematic analysis.At the same time, combined with the measured results of the field pipe jacking project, the characteristics and influencing factors of ground-surface deformation under different sections and different construction sequence of parallel pipe jacking are studied.The results show that the surface deformation curve caused by parallel differential section pipe jacking construction is Ⅴ-curve, and the peak point of the surface deformation curve gradually shifts from the large section rectangular pipe jacking axis to the two pipe centers.The surface settlement on the left side of the axis of the small section rectangular pipe jacking is larger than that on the right side of the axis.Construction of large section rectangular pipe jacking on the left line is more beneficial to control surface deformation.The influence of section size change on surface deformation is 30%, and the influence of process on surface deformation is 8%.The influence of section size difference on surface deformation is greater than that of process difference.The study on the influence of parallel differential section pipe jacking construction on surface deformation can provide theoretical basis and experience for future related parallel large section pipe jacking projects

Using Earth Observation for Monitoring SDG 11.3.1-Ratio of Land Consumption Rate to Population Growth Rate in Mainland China

Urban sustainable development has attracted widespread attention worldwide as it is closely linked with human survival. However, the growth of urban areas is frequently disproportionate in relation to population growth in developing countries; this discrepancy cannot be monitored solely using statistics. In this study, we integrated earth observation (EO) and statistical data monitoring the Sustainable Development Goals (SDG) 11.3.1: “The ratio of land consumption rate to the population growth rate (LCRPGR)”. Using the EO data (including China’s Land-Use/Cover Datasets (CLUDs) and the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data) and census, we extracted the percentage of built-up area, disaggregated the population using the geographically weighted regression (GWR) model, and depicted the spatial heterogeneity and dynamic tendency of urban expansion and population growth by a 1 km × 1 km grid at city and national levels in mainland China from 1990 to 2010. Then, the built-up area and population density datasets were compared with other products and statistics using the relative error and standard deviation in our research area. Major findings are as follows: (1) more than 95% of cities experienced growth in urban built-up areas, especially in the megacities with populations of 5–10 million; (2) the number of grids with a declined proportion of the population ranged from 47% in 1990–2000 to 54% in 2000–2010; (3) China’s LCRPGR value increased from 1.69 in 1990–2000 to 1.78 in 2000–2010, and the land consumption rate was 1.8 times higher than the population growth rate from 1990 to 2010; and (4) the number of cities experiencing uncoordinated development (i.e., where urban expansion is not synchronized with population growth) increased from 93 (27%) in 1990–2000 to 186 (54%) in 2000–2010. Using EO has the potential for monitoring the official SDGs on large and fine scales; the processes provide an example of the localization of SDG 11.3.1 in China

Remote Sensing for Lithology Mapping in Vegetation-Covered Regions: Methods, Challenges, and Opportunities

Remote sensing (RS) technology has significantly contributed to geological exploration and mineral resource assessment. However, its effective application in vegetated areas encounters various challenges. This paper aims to provide a comprehensive overview of the challenges and opportunities associated with RS-based lithological identification in vegetated regions which includes the extensively reviewed prior research concerning the identification of lithology in vegetated regions, encompassing the utilized remote sensing data sources, and classification methodologies. Moreover, it offers a comprehensive overview of the application of remote sensing techniques in the domain of lithological mapping. Notably, hyperspectral RS and Synthetic Aperture Radar (SAR) have emerged as prominent tools in lithological identification. In addition, this paper addresses the limitations inherent in RS technology, including issues related to vegetation cover and terrain effects, which significantly impact the accuracy of lithological mapping. To propel further advancements in the field, the paper proposes promising avenues for future research and development. These include the integration of multi-source data to improve classification accuracy and the exploration of novel RS techniques and algorithms. In summary, this paper presents valuable insights and recommendations for advancing the study of RS-based lithological identification in vegetated areas

Review of operations for multi-energy coupled virtual power plants participating in electricity market

The application projects of traditional virtual power plants generally have some significant problems, such as single energy structure, insufficient participation in the market, sparse energy coupling relationship and lack of new loads, which lead to poor operation stability, low economic benefits and difficult risk management of traditional virtual power plants. With the development of distributed energy resources such as electric vehicles, air conditioners, and electric heating loads and the advancement of information and communication technologies, virtual power plants have gradually evolved from aggregating a single type of energy resource to having the ability to meet the aggregation and management of multiple types of energy resources. Virtual power plant technology provides an effective means to aggregate distributed energy and user-side resources to participate in energy market transactions. A virtual power plant with multiple energy sources such as electricity, heat and gas coupling can effectively avoid the lack of system stability and security caused by a single resource structure, and effectively meet the needs of users for multiple types of energy. This paper focuses on multi-energy coupled virtual power plants, summarizes the current status of research on multi-energy coupled virtual power plants participating in power market operation from the aspects of multi-energy coupling mechanism and operation optimization in power market, and finally provides an outlook on the research direction of multi-energy coupled virtual power plants

A Fire Reconnaissance Robot Based on SLAM Position, Thermal Imaging Technologies, and AR Display

Due to hot toxic smoke and unknown risks under fire conditions, detection and relevant reconnaissance are significant in avoiding casualties. A fire reconnaissance robot was therefore developed to assist in the problem by offering important fire information to fire fighters. The robot consists of three main systems, a display operating system, video surveillance, and mapping and positioning navigation. Augmented reality (AR) goggle technology with a display operating system was also developed to free fire fighters’ hands, which enables them to focus on rescuing processes and not system operation. Considering smoke disturbance, a thermal imaging video surveillance system was included to extract information from the complicated fire conditions. Meanwhile, a simultaneous localization and mapping (SLAM) technology was adopted to build the map, together with the help of a mapping and positioning navigation system. This can provide a real-time map under the rapidly changing fire conditions to guide the fire fighters to the fire sources or the trapped occupants. Based on our experiments, it was found that all the tested system components work quite well under the fire conditions, while the video surveillance system produces clear images under dense smoke and a high-temperature environment; SLAM shows a high accuracy with an average error of less than 3.43%; the positioning accuracy error is 0.31 m; and the maximum error for the navigation system is 3.48%. The developed fire reconnaissance robot can provide a practically important platform to improve fire rescue efficiency to reduce the fire casualties of fire fighters

Automatic seeded region growing for thermography debonding detection of CFRP

The carbon fiber reinforced polymer (CFRP) has been widely used in aerospace, automobile and sports industries. In laminated composite materials, cyclic stresses and impact will cause internal defects such as delamination and debonding. In order to guarantee internal quality and safety, optical pulsed thermography (OPT) nondestructive testing has been used to detect the internal defects. However, current OPT methods cannot efficiently tackle the influence from uneven illumination, and the resolution enhancement of the defects detection remains as a critical challenge. In this paper, a hybrid of thermographic signal reconstruction (TSR) and automatic seeded region growing (ASRG) algorithm is proposed to deal with the thermography processing of CFRP. The proposed method has the capability to significantly minimize uneven illumination and enhance the detection rate. In addition, it has the capacity to automate segmentation of defects. It also overcomes the crux issues of seeded region growing (SRG) which can automatically select the growth of image, seed points and thresholds. The probability of detection (POD) has been derived to measure the detection results and this is coupled with comparison studies to verify the efficacy of the proposed method

Arabidopsis ETHYLENE RESPONSE FACTOR 8 (ERF8) has dual functions in ABA signaling and immunity

Background: ETHYLENE RESPONSE FACTOR (ERF) 8 is a member of one of the largest transcription factor families in plants, the APETALA2/ETHYLENE RESPONSIVE FACTOR (AP2/ERF) superfamily. Members of this superfamily have been implicated in a wide variety of processes such as development and environmental stress responses. Results: In this study we demonstrated that ERF8 is involved in both ABA and immune signaling. ERF8 overexpression induced programmed cell death (PCD) in Arabidopsis and Nicotiana benthamiana. This PCD was salicylic acid (SA)-independent, suggesting that ERF8 acts downstream or independent of SA. ERF8-induced PCD was abolished by mutations within the ERF-associated amphiphilic repression (EAR) motif, indicating ERF8 induces cell death through its transcriptional repression activity. Two immunity-related mitogen-activated protein kinases, MITOGEN-ACTIVATED PROTEIN KINASE 4 (MPK4) and MPK11, were identified as ERF8-interacting proteins and directly phosphorylated ERF8 in vitro. Four putative MPK phosphorylation sites were identified in ERF8, one of which (Ser103) was determined to be the predominantly phosphorylated residue in vitro, while mutation of all four putative phosphorylation sites partially suppressed ERF8-induced cell death in N. benthamiana. Genome-wide transcriptomic analysis and pathogen growth assays confirmed a positive role of ERF8 in mediating immunity, as ERF8 knockdown or overexpression lines conferred compromised or enhanced resistance against the hemibiotrophic bacterial pathogen Pseudomonas syringae, respectively. Conclusions: Together these data reveal that the ABA-inducible transcriptional repressor ERF8 has dual roles in ABA signaling and pathogen defense, and further highlight the complex influence of ABA on plant-microbe interactions.Other UBCNon UBCReviewedFacult