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The "Yangtze River Economic Belt Development Strategy" is one of China's three major national development strategies. Enhancing the protection and quality of arable land in the Yangtze River Economic Belt (YEB) is pivotal for fostering regional growth. In this study, land use data spanning the years 1980 to 2020 in the YEB were extracted from the national land use database maintained by the Resource and Environment Data Center of the Chinese Academy of Sciences. Employing Geographic Information System (GIS) spatial analysis techniques and arable land change metrics, the study delineated the spatiotemporal characteristics of arable land alterations across the YEB for the period. Additionally, using grain output data at the prefecture level from 2011 to 2020, the paper calculated provincial grain output to analyze the impact of arable land changes over the last four decades on grain output. The findings revealed that: (1) From 1980 to 2020, the total arable land area in the YEB decreased by approximately 41,775 square kilometers, with the most significant decrease occurring in the downstream region. (2) From 1980 to 1990, the primary factor contributing to the decrease in arable land area was the expansion of water bodies, while from 1990 to 2020, the principal reason for the reduction in arable land area was the expansion of construction land. (3) From 1980 to 2020, the decrease in arable land area resulted in a net reduction of approximately 25.12 million tons in total grain output, with the largest decline observed in the downstream regions and the smallest decline in the upstream regions. (4) Consistent with the trends in arable land area reduction, the main reason for the decline in grain output from 1980 to 1990 was the expansion of water bodies encroaching upon arable land, whereas from 2000 to 2010, the primary cause of arable land reduction was the expansion of construction land areas. In conclusion, the research suggested that over the past four decades, the primary driver behind the reduction in arable land within the YEB has been the expansion of construction land areas. Particularly noteworthy was the period from 2000 to 2010, during which the impact of arable land reduction on grain output was most pronounced. This period coincided with the rapid economic development and accelerated urbanization process within the YEB. [ABSTRACT FROM AUTHOR]

Long waiting times and crowded services are the current medical situation in China. Especially in hierarchic healthcare systems, as high-quality medical resources are mainly concentrated in comprehensive hospitals, patients are too concentrated in these hospitals, which leads to overcrowding. This paper constructs a game-theoretical queueing model to analyze the strategic queueing behavior of patients. In such hospitals, patients are divided into first-visit and referred patients, and the hospitals provide patients with two service phases of "diagnosis" and "treatment". We first obtain the expected sojourn time. By defining the patience level of patients, the queueing behavior of patients in equilibrium is studied. The results suggest that as long as the patients with low patience levels join the queue, the patients with high patience levels also join the queue. As more patients arrive at the hospitals, the queueing behavior of patients with high patience levels may have a negative effect on that of patients with low patience levels. The numerical results also show that the equilibrium behavior deviates from a socially optimal solution; therefore, to reach maximal social welfare, the social planner should adopt some regulatory policies to control the arrival rates of patients. [ABSTRACT FROM AUTHOR]

With respect to a traditional point-to-point (P-P) network, a hub-and-spoke (H-S) network not only uses a smaller number of links/paths but also utilizes the scale economy advantage on consolidated flows on hub–hub links and at hubs. However, the inevitable delays through hubs have always been a critical concern. Therefore, this paper develops an H-S model considering flow delay costs and applies the model to a logistics case in Eastern China. The integer quadratic term in the model's objective function is linearized using the algebraic method. Our model is applied to develop an H-S network for its 13-node express package delivery operation, using the particle swarm optimization (PSO) algorithm. The results show using the H-S can save more than 14.1% of the total cost annually. The model also provides an applied case to the H-S configuration, especially for urban express delivery logistics in China. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we provide descriptions of three fossil species, Calamites cistii, Macrostachya sp., and Punctatisporites punctatus, discovered in the Cisuralian of the eastern Hexi Corridor, northwestern China. Our findings offer insights into the evolution of Calamitaceae strobili during the Late Paleozoic. Calamitaceae was the predominant arborescent element of the Late Paleozoic plant assemblages. However, there is currently controversy surrounding the evolutionary relationships of their four reproductive organs, and there is no unified understanding of the geographical distribution and species richness characteristics. This paper is based on the detailed description of the macro- and microstructures of Calamites and Macrostachya discovered in the Shanxi Formation of the Cisuralian in the eastern Hexi Corridor of northwestern China, and it discusses the evolutionary patterns of calamitean reproductive organs. The results indicate that the current specimens can be identified as the Calamites cistii and Macrostachya sp., and the in situ spores should exhibit distinct trilete marks, indicating that they belong to the Punctatisporites punctatus. The abundant fossil records suggest that the "Calamostachys" type should be considered as the ancestral type of strobili. Additionally, Calamitaceae was widely distributed in mid to low latitudes globally from the Pennsylvanian to the Cisuralian and coupled with paleogeographic distribution characteristics. [ABSTRACT FROM AUTHOR]

In this paper, a thorough investigation is presented on the static and dynamic behaviors of a short-span cable-stayed bridge (CSB) incorporating steel and carbon fiber reinforced polymer (CFRP) hybrid cables. The study focuses on the world's largest span and China's first highway, CFRP CSB. The performance of the CSB was compared using numerical simulations under four different cable patterns: steel cables, CFRP cables, and steel, and two types of hybrid cables with different structural arrangements. The results indicate that the use of the use of CFRP cables in the long cable region in the short-span CSB project investigated in this study offers improved performance in terms of stability, seismic response, and reduced displacements. In comparison to CFRP cables, hybrid cables have demonstrated a reduction of 12% in the maximum vertical displacement of the main girder. On the other hand, the hybrid cables result in reduced maximum internal forces and longitudinal and lateral displacements of the main girders and towers compared to steel cables. The difference in the arrangement of CFRP cables in the long cable region or short cable region is not obvious under dead loads, but significant differences still exist between the CFRP cable bridges in the short cable region and the long cable region in terms of live load effects, temperature effects, and dynamic characteristics. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has shown its effectiveness in handling multi-geoinformation. Yet, the black-box nature of ML algorithms has restricted their widespread adoption in the domain of mineral prospectivity mapping (MPM). In this paper, methods for interpreting ML model predictions are introduced to aid ML-based MPM, with the goal of extracting richer insights from the ML modeling of an exploration geochemical dataset. The partial dependence plot (PDP) and accumulated local effect (ALE) plot, along with the SHAP value analysis, were utilized to demonstrate the application of random forest (RF) modeling within both regression and classification frameworks. Initially, the random forest regression (RFR) model established the relationship between the concentrations of Au and those of elements such as As, Sb, and Hg in the study area, and from this model, the most important geochemical elements and their quantitative relationships with Au were revealed by their contributions in the modeling through PDP and ALE analyses. Secondly, the RF classification modeling established the relationships of mineralization occurrences (i.e., known mineral deposits) with geochemical elements (i.e., Au, As, Sb, Hg, Cu, Pb, Zn, and Ag), as did RFR modeling. The most important geochemical elements for indicating regional Au mineralization and the trajectories of PDP and ALE reached a consensus that As and Sb contributed the most, both in the regression and classification modeling, with regard to Au mineralization. Finally, the SHAP values illustrated the behavior of the training samples (i.e., known mineral deposits) in RF modeling, and the resulting prospectivity map was evaluated using receiver operating characteristics. [ABSTRACT FROM AUTHOR]

Freeze–thaw (FT) erosion intensity may exhibit a future increasing trend with climate warming, humidification, and permafrost degradation in the Qinghai–Tibet Plateau (QTP). The present study provides a reference for the prevention and control of FT erosion in the QTP, as well as for the protection and restoration of the regional ecological environment. FT erosion is the third major type of soil erosion after water and wind erosion. Although FT erosion is one of the major soil erosion types in cold regions, it has been studied relatively little in the past because of the complexity of several influencing factors and the involvement of shallow surface layers at certain depths. The QTP is an important ecological barrier area in China. However, this area is characterized by harsh climatic and fragile environmental conditions, as well as by frequent FT erosion events, making it necessary to conduct research on FT erosion. In this paper, a total of 11 meteorological, vegetation, topographic, geomorphological, and geological factors were selected and assigned analytic hierarchy process (AHP)-based weights to evaluate the FT erosion intensity in the QTP using a comprehensive evaluation index method. In addition, the single effects of the selected influencing factors on the FT erosion intensity were further evaluated in this study. According to the obtained results, the total FT erosion area covered 1.61 × 106 km2, accounting for 61.33% of the total area of the QTP. The moderate and strong FT erosion intensity classes covered 6.19 × 105 km2, accounting for 38.37% of the total FT erosion area in the QTP. The results revealed substantial variations in the spatial distribution of the FT erosion intensity in the QTP. Indeed, the moderate and strong erosion areas were mainly located in the high mountain areas and the hilly part of the Hoh Xil frozen soil region. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Suite-Nadir (OMS-N) instrument is the first hyperspectral remote sensor in the ultraviolet band of China's Fengyun series satellites. It can be used to detect several kinds of atmospheric constituents. This paper describes the prelaunch spectral calibration of the OMS-N onboard FengYun 3F. Several critical spectral parameters including the spectral resolution, spectral dispersion, and the instrument spectral response function were determined through laser-based measurements. A secondary peak of the instrument spectral response function from the short wavelength side of the ultraviolet band was found, and the possible influence on data applications was analyzed using a reference solar model and radiative transfer model. The results indicate that the spectral resolution and spectral accuracy of OMS-N meet the mission requirements. However, the asymmetries in the instrument spectral response function in the ultraviolet band were found near nadir rows, which are expressed as the "asymmetric central peak" and "secondary peak". The analysis results show that if the influences of the instrument spectral response function "asymmetric central peak" and "secondary peak" in the ultraviolet band are ignored, they will bring an error as large as 5% at the center of the absorption line. [ABSTRACT FROM AUTHOR]

Research on wildlife monitoring methods is a crucial tool for the conservation of rare wildlife in China. However, the fact that rare wildlife monitoring images in field scenes are easily affected by complex scene information, poorly illuminated, obscured, and blurred limits their use. This often results in unstable recognition and low accuracy levels. To address this issue, this paper proposes a novel wildlife identification model for rare animals in Giant Panda National Park (GPNP). We redesigned the C3 module of YOLOv5 using NAMAttention and the MemoryEfficientMish activation function to decrease the weight of field scene features. Additionally, we integrated the WIoU boundary loss function to mitigate the influence of low-quality images during training, resulting in the development of the NMW-YOLOv5 model. Our model achieved 97.3% for mAP50 and 83.3% for mAP50:95 in the LoTE-Animal dataset. When comparing the model with some classical YOLO models for the purpose of conducting comparison experiments, it surpasses the current best-performing model by 1.6% for mAP50:95, showcasing a high level of recognition accuracy. In the generalization ability test, the model has a low error rate for most rare wildlife species and is generally able to identify wildlife in the wild environment of the GPNP with greater accuracy. It has been demonstrated that NMW-YOLOv5 significantly enhances wildlife recognition accuracy in field environments by eliminating irrelevant features and extracting deep, effective features. Furthermore, it exhibits strong detection and recognition capabilities for rare wildlife in GPNP field environments. This could offer a new and effective tool for rare wildlife monitoring in GPNP. [ABSTRACT FROM AUTHOR]

The economic operation of hydropower stations has the potential to increase water use efficiency. However, there are some challenges, such as the fixed and unchangeable flow characteristic curve of the hydraulic turbines, and the large number of variables in optimal load distribution, which limit the progress of research. In this paper, we propose a new optimal method of the economic operation of hydropower stations based on improved Long Short-Term Memory neural network (I-LSTM) and Random Forest (RF) algorithm. Firstly, in order to accurately estimate the water consumption, the LSTM model's hyperparameters are optimized using improved particle swarm optimization, and the I-LSTM method is proposed to fit the flow characteristic curve of the hydraulic turbines. Secondly, the Random Forest machine learning algorithm is introduced to establish a load-distribution model with its powerful feature extraction and learning ability. To improve the accuracy of the load-distribution model, we use the K-means algorithm to cluster the historical data and optimize the parameters of the Random Forest model. A Hydropower Station in China is selected for a case study. It is shown that (1) the I-LSTM method fits the operating characteristics under various working conditions and actual operating characteristics of hydraulic turbines, ensuring that they are closest to the actual operating state; (2) the I-LSTM method is compared with Support Vector Machine (SVM), Extreme Learning Machine (ELM) and Long Short-Term Memory neural network (LSTM). The prediction results of SVM have a large error, but compared with ELM and LSTM, MSE is reduced by about 46% and 38% respectively. MAE is reduced by about 25% and 21%, respectively. RMSE is reduced by about 27% and 24%, respectively; (3) the RF algorithm performs better than the traditional dynamic programming algorithm in load distribution. With the passage of time and the increase in training samples, the prediction accuracy of the Random Forest model has steadily improved, which helps to achieve optimal operation of the units, reducing their average total water consumption by 1.24%. This study provides strong support for the application of intelligent low-consumption optimization strategies in hydropower fields, which can bring higher economic benefits and resource savings to renewable energy production. [ABSTRACT FROM AUTHOR]

Accurate short-term electrical load forecasting is crucial for the stable operation of power systems. Given the nonlinear, periodic, and rapidly changing characteristics of short-term power load forecasts, this paper introduces a novel forecasting method employing an Extreme Learning Machine (ELM) enhanced by an improved Dwarf Mongoose Optimization Algorithm (Local escape Dwarf Mongoose Optimization Algorithm, LDMOA). This method addresses the significant prediction errors of conventional ELM models and enhances prediction accuracy. The enhancements to the Dwarf Mongoose Optimization Algorithm include three key modifications: initially, a dynamic backward learning strategy is integrated at the early stages of the algorithm to augment its global search capabilities. Subsequently, a cosine algorithm is employed to locate new food sources, thereby expanding the search scope and avoiding local optima. Lastly, a "madness factor" is added when identifying new sleeping burrows to further widen the search area and effectively circumvent local optima. Comparative analyses using benchmark functions demonstrate the improved algorithm's superior convergence and stability. In this study, the LDMOA algorithm optimizes the weights and thresholds of the ELM to establish the LDMOA-ELM prediction model. Experimental forecasts utilizing data from China's 2016 "The Electrician Mathematical Contest in Modeling" demonstrate that the LDMOA-ELM model significantly outperforms the original ELM model in terms of prediction error and accuracy. [ABSTRACT FROM AUTHOR]

Due to the increasing development of highway reconstruction and expansion projects in China, many large-span highway tunnels are being constructed near existing highway tunnels. Tunneling underneath will inevitably cause variation in the surrounding rock displacement and may even lead to collapse. In this study, based on an analysis of extensive field monitoring data from the Gucheng tunnel, the variation law for the surrounding rock full-displacement and the influence of the tunnel-face spatial effect in a large-span mudstone tunnel are analyzed. The change in the full displacement experienced the following sequence: slow pre-displacement growth → rapid increase → slow increase → gradual stability. The displacement released by the excavation of the tunnel construction accounts for 40~60% of the total displacement, and the closer to the excavation contour, the more obvious the displacement release. The final convergence value of vertical displacement is obtained by hyperbolic function regression prediction analysis. Based on this value, Lee and Hoek equations are used for parameter analysis and field-data fitting. It is concluded that the larger the proportion of the early displacement of the surrounding rock before construction to the total displacement, the smaller the influence of the tunnel-face spatial effect on the surrounding rock. The numerical simulation results are compared with actual monitoring results, and good agreement is observed. The larger the burial depth of the tunnel, the smaller the influence range in the tunnel-face spatial effect, and the more concentrated the displacement release. The variation law and the influential range for the surrounding rock full-displacement described in this paper can provide a reference for predicting and controlling the deformation during the construction of future large-span mudstone tunnels. [ABSTRACT FROM AUTHOR]

This paper illustrates two species in the lichen-forming family Arthoniaceae from southern China, including a new species of Herpothallon, H. fibrosum L.L. Liu & Lu L. Zhang and a new record of Cryptothecia, C. striata G. Thor for China. Herpothallon fibrosum has fluffy, cylindrical pseudoisidia, like a bundle of fiber, and psoromic acid and confluentic acid are present. Furthermore, the new record of Cryptothecia striata has been identified by morphological, anatomical, chemical, and molecular studies. The systematic position of the two species was clarified by the molecular sequence data from the small subunit of the mitochondrial ribosomal DNA (mtSSU). Detailed taxonomic descriptions, chemical characters, comparisons, and discussion of the characteristics of similar species are provided for the two species; the relationship between Cryptothecia and Herpothallon is also discussed here. [ABSTRACT FROM AUTHOR]

Airborne wind measurement is of great significance for understanding atmospheric motion and meteorological monitoring. In this paper, we present the development and verification of an airborne Doppler wind lidar (ADWL), featuring an approach proposed to integrate a real-time wind retrieval method with an intelligent processing method for automatic adaptive wind detection. Several verification experiments were conducted to evaluate the measurement effectiveness, including comparisons with a calibrated ground-based Doppler wind lidar (GDWL) and a sounding balloon. Compared with the sounding balloon, the ADWL demonstrated mean errors of 0.53 m/s for horizontal wind velocity and 4.60° for wind direction. The correlation coefficients consistently exceeded 0.98 in all linear analyses. Employed in multiple airborne wind detection events in North China at altitudes up to 6600 m, the ADWL provided effective wind field results with a vertical resolution of 50 m and a data rate of 2 Hz. The wind field results obtained during the detection events validate the ADWL's capabilities in diverse environments and underscore its potential for the comprehensive detection of meteorological information. [ABSTRACT FROM AUTHOR]

A reasonable allocation of production schedules and savings in overall electricity costs are crucial for large manufacturing conglomerates. In this study, we develop an optimization model of off-site industrial production scheduling to address the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's power supply, and the difficulty in promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and variations in electricity prices in different places to optimize the scheduling of industrial production in various locations. The model is embedded with two sub-models, i.e., an electricity price prediction model and a distributed photovoltaic power cost model to complete the model parameters, in which the electricity price prediction model utilizes a Long Short-Term Memory (LSTM) neural network. Then, the particle swarm optimization algorithm is used to solve the optimization model. Finally, the production data of two off-site pharmaceutical factories belonging to the same large group of enterprises are substituted into the model for example analysis, and it is concluded that the optimization model can significantly reduce the electricity consumption costs of the enterprises by about 7.9%. This verifies the effectiveness of the optimization model established in this paper in reducing the cost of electricity consumption on the demand side. [ABSTRACT FROM AUTHOR]

Ensuring optimal building performance is vital for enhancing student activity comfort and fostering energy-saving initiatives toward low-carbon objectives. This paper focuses on university student centers in China, aiming to diminish building energy consumption while enhancing indoor thermal comfort. Parametric modeling of typical cases is executed using the Grasshopper 1.0.0007 software package, and the simulation of building energy consumption and indoor thermal comfort relies on the Ladybug and Honeybee plug-in. Employing a multi-objective optimization design method and the Octopus multi-objective optimization algorithm, this study integrates numerical simulations and on-site surveys to analyze how factors like building form, orientation, envelope structure, and others impact the indoor and outdoor environment. A comprehensive optimization design approach is implemented for the building's exterior components, including the walls, windows, roof, and shading system. After conducting a comparative analysis of the annual comprehensive energy consumption and indoor thermal comfort before and after the optimization plan, it is determined that implementing these measures reduces the annual comprehensive energy consumption of the building under study by 58.8% and extends the duration of indoor thermal comfort by 53.0%. This study presents a practical optimization design methodology for university student center architecture in China, aiding architects in decision making and advocating for energy-efficient building designs. [ABSTRACT FROM AUTHOR]

With a significant share of renewable power generation integrated into the power supply, it is crucial to timely adjust the regulating peak load for coal-fired power plants equipped with CO2 capture to ensure the stable operation of the multi-energy supply system. In this paper, the effects of varying boiler loads on the techno-economic performance of the retrofitted power plant were studied. Furthermore, the potential for reducing the cost of CO2 capture was investigated, and early opportunities for demonstration were discussed. Results showed that when the boiler load decreased from 100% turbine heat acceptance condition to 50% turbine heat acceptance condition, the cost of CO2 capture increased from 37.0 $/t CO2 to 57.0 $/t CO2, cost contribution of energy penalty and extra capital investment also increased from 20.6 $/t-CO2 to 25.7 $/t-CO2, and from 16.4 $/t-CO2 to 31.3 $/t-CO2, respectively. Furthermore, by improving separation efficiency from 0.15 to 0.5, a 25% to 30% reduction in CO2 capture cost can be achieved. The cost of CO2 capture could decrease by 42.2–50.5% when the cumulative capacity reaches 250 GW under the high investment learning rate scenario. According to the distribution of coal prices and renewable energy sources in China, the early demonstration projects of multi-energy supply systems should prioritize the northern region. The results of this work can provide informative references for making roadmaps and policies for CO2 emission reduction toward carbon neutrality. [ABSTRACT FROM AUTHOR]

This paper takes a low-energy building in Changchun, China, as an object to test and study the characteristics of two heating modes, AC/DC (Alternative current/Direct current) switching and AC/DC synthesis, from the perspectives of temperature change, irradiation intensity, power generation, electricity consumption, etc. Firstly, the experimental research was conducted under two heating cable modes by establishing mathematical models and a test rig, and it was found that the photoelectric conversion efficiency on sunny, cloudy, and overcast days was 18%, 14.5%, and 12%, respectively. A simulation model was established by TRNSYS to run an ultra-low-energy building throughout the year. It was found that the highest and lowest monthly power generation occurred in February and July, respectively. The annual power generation of the system was 6614 kWh, and the heating season power generation was 3293.42 kWh. In the current research, the DC electricity consumption was slightly higher than the AC electricity consumption. Under conditions of similar radiation intensity and power generation, the indoor temperature of the AC/DC synthesis cable heating mode were 1.38% higher than the AC/DC switching heating able mode, and the electricity consumption were 10.9% and 4.76% higher, respectively, than those of the AC switching heating cable mode. This is of great significance for clean-energy heating, energy savings, and emissions reduction in northern China. [ABSTRACT FROM AUTHOR]

Amid China's pursuit of a green and low-carbon transition, corporate social responsibility (CSR) is facing new challenges. Our research delves into the influencing factors and mechanisms for CSR reputation under green and low-carbon transition and provides practical enlightenment for enterprises to achieve sustainable development. This paper constructs a comprehensive index system of CSR from five dimensions (innovation, coordination, sustainability, openness, and sharing), and CSR reputation of China's A-share listed companies is comprehensively estimated by using an entropy method and data from 2013 to 2021. Then, from the perspective of external supervision and internal governance, we discuss the influence factors of CSR reputation, with an emphasis on the impact of public environmental concerns. Finally, the realization mechanism of CSR is further revealed. It is found that public environmental concern and the expansion of the enterprise scale boost the enhancement of CSR reputation. However, a higher proportion of female managers tends to hinder CSR reputation. Furthermore, public environmental concern plays a more prominent role in improving CSR reputation of non-state-owned and eastern enterprises. Additionally, public environmental concern significantly enhances CSR reputation through green technology innovation and executive environmental awareness. This research provides valuable insights for improving CSR reputation and optimizing regulatory compliance and governance practices. [ABSTRACT FROM AUTHOR]

The Location-Routing Problem (LRP) becomes a more intricate subject when the limits of capacities of vehicles and warehouses are considered, which is an NP-hard problem. Moreover, as the number of vehicles increases, the solution to LRP is exacerbated because of the complexity of transportation and the combination of routes. To solve the problem, this paper proposed a Discrete Assembly Combination-Delivery (DACA) strategy based on, the Binary Equilibrium Optimizer (BiEO) algorithm, in addition, this paper also proposes a mixed-integer linear programming model for the problem of this paper. Our primary objective is to address both the route optimization problem and the assembly group sum problem concurrently. Our BiEO algorithm was designed as discrete in decision space to meet the requirements of the LRP represented by the DACA strategy catering to the multi-vehicle LRP scenario. The efficacy of the BiEO algorithm with the DACA strategy is demonstrated. through empirical analysis utilizing authentic data from Changchun City, China, Remarkably, the experiments reveal that the BiEO algorithm outperforms conventional methods, specifically GA, PSO, and DE algorithms, resulting in reduced costs. Notably, the results show the DACA strategy enables the simultaneous optimization of the LRP and the vehicle routing problem (VRP), ultimately leading to cost reduction. This innovative algorithm proficiently tackles both the assembly group sum and route optimization problems intrinsic to multi-level LRP instances. [ABSTRACT FROM AUTHOR]

Simple Summary: Anteon Jurine, 1807 is a cosmopolitan genus of dryinid parasitoids that attack leafhoppers. Sexual dimorphism is extreme in Anteon species, rendering the morphological taxonomy of these parasitoids difficult. This paper employs an integrated taxonomic approach that combines morphology with DNA barcoding to investigate the species delimitation of Anteon from China. Of the twenty-nine morphospecies examined, twenty-four species were identified as previously known species and five were described here as new species. The sexual association of six species was confirmed by DNA barcoding, indicating that such tools are powerful to tackle the taxonomic challenges in parasitoids with sexual dimorphism. Species of Anteon Jurine, 1807 are a large group of parasitoids attacking leafhoppers, which are important insect pests. Despite their great potential in pest biological control, the taxonomy and biology of these parasitoids are far from clear. Sexual dimorphism is extreme in Anteon species and has hampered the taxonomy of these parasitoids, resulting in many species described based on a single sex. In this paper, we employed an integrated taxonomic approach for delimitating species, combining morphological examinations with DNA barcoding, to investigate Anteon species from China. In total, 53 COI sequences representing 29 species of Anteon were obtained and analyzed. On the basis of both morphology and DNA barcoding, five new species of Anteon were discovered and described: A. clariclypeum sp. nov., A. maguanense sp. nov., A. parafidum sp. nov., A. shaanxianum sp. nov., and A. shandonganum sp. nov. The neotype of A. claricolle Kieffer is designated. The sexual association of six species was confirmed by DNA barcoding, which led to the synonymy of Anteon liui Xu, Olmi & He 2010, new syn., under Anteon meifenganum Olmi, 1991. Keys to species of Anteon from the Oriental and Eastern Palaearctic are updated to contain the five new species. Our study demonstrates that DNA barcoding is a potent tool for tackling the taxonomic challenges in parasitoids with extreme sexual dimorphism. [ABSTRACT FROM AUTHOR]

The maritime route connecting the Chinese continent and the Japanese archipelago facilitated a significant exchange of commercial goods and sociocultural knowledge throughout the Southern Song dynasty. Within this context, Japanese pilgrim monks traveling along this route acted as key conduits for the transmission of Buddhist teachings. Their journeys profoundly influenced the establishment and development of new Buddhist monasteries in Japan. Focusing on biographical accounts that portray the experiences of these pilgrim monks during their twelfth- and thirteenth-century sea voyages, this paper aims to explore how these accounts drew on intertextual links with existing Buddhist records to fulfill the compilers' intentions. Specifically, this paper examines the structure and sources of biographical accounts detailing miraculous encounters between pilgrim monks and Buddhist deities during perilous situations at sea. By interpreting the role of these deities in the corpus of Buddhist literature and within Japanese Buddhist monasteries founded by pilgrim monks, this paper argues that the increasing emphasis on pilgrim monks' attainment of divine protection in their biographical records suggests a growing concern for reinforcing the authority of their dharma lineages. Moreover, the composition and reception of these miraculous accounts reflected the changing religious needs and reshaped strategies for promoting specific Buddhist sects in subsequent periods. [ABSTRACT FROM AUTHOR]

Recent research has played a pivotal role in advancing our understanding of cloisonné enamel production in China during the 19th and 20th centuries. However, Christian workshops, whether operating under missionary subcontracting or owned by the Catholic Church, have yet to be accurately identified and contextualized. This article delves into three significant contexts. Firstly, it identifies and contextualizes the Christian connections and interactions of the Decheng private cloisonné workshop, involving the French Lazarist Bishop Alphonse Favier, in Beijing. Secondly, it identifies the cloisonné workshop stablished by the Lazarists in the Beitang complex in Beijing and elucidates the role it played. Finally, this paper presents new evidence concerning cloisonné Christian objects crafted by the Tushanwan Jesuit workshop in Shanghai. Some of the primary works of these three workshops are identified for the first time. Additionally, this paper shows that certain cloisonné crosses, some of them thought to be originally Japanese, including those referred to as Namban, were, in fact, crafted in Beijing during the 1920s. These preliminary results will contribute to placing Chinese Christian cloisonné within the history of Chinese Art and its interactions at a global level in the context of evangelization in China, the production of the so-called export art, and the processes of indigenization carried out by the Lazarists and the Jesuits. [ABSTRACT FROM AUTHOR]

Microplastics have been widely detected in the natural water environment, which brings inevitable risks to the water ecosystem and human health. However, the understanding of the potential impact of microplastics on aquatic animals, plants, and human health is still limited, and technical methods to control microplastic pollution in natural water are still rare. Hence, this paper summarizes the progress of research on microplastic pollution in water systems in terms of microplastic source, attributes, distribution characteristics, environmental effects, and prevention and control methods according to the relevant research reports on water microplastic pollution. It also expounds the basic ways for the prevention, control, and treatment of water microplastics, and looks forward to the research direction of water microplastic pollution in the future. The results show that the abundance of fresh water microplastics in China is higher than that in other regions, but the pollution level of marine microplastics is at the middle level. Compared with other countries, the pollution degree of microplastics in aquatic organisms in China is at the middle and lower level, but the spatial heterogeneity is more obvious. Through hydraulic control and the substitution of degradable plastic products, water microplastic pollution can be greatly reduced. This paper can provide a reference basis for the formulation of microplastic pollution prevention and control in China. [ABSTRACT FROM AUTHOR]

The unsustainable demand for wildlife and its derivatives poses a threat to global biodiversity, requiring attention and intervention. This study investigates the intent to purchase medicines containing saiga antelope horn among respondents in China. Drawing on an expanded theoretical framework rooted in a planned behavior model, and analyzing 576 valid data points collected through online research, this paper employs a structural equation model to consider influencing factors across six dimensions: attitude, subjective norm, perceived behavioral control, consumption experience, protective cognitive level, and personal characteristics. The findings reveal that 31.25% of respondents harbor a positive purchase intention toward medicines containing saiga antelope horn. Additionally, attitude, subjective norm, perceived behavioral control, and consumption experience exhibit positive associations with the purchase intention, while the protective cognitive level demonstrates a negative impact. A significant gender gap was identified, with women displaying a greater inclination to purchase compared to men. To support the global conservation efforts of the saiga antelope, this paper advocates for strategic interventions. Recommendations include reinforcing public science education, fostering awareness, advancing the research and development of alternative medicines, strengthening internal market controls, and employing targeted marketing strategies to shift consumer preferences. These measures collectively contribute to a holistic approach aimed at reducing the demand for wildlife products and safeguarding the saiga antelope population. [ABSTRACT FROM AUTHOR]

The coupling coordination of agricultural technology innovation with food security is of great significance for high-quality agricultural development. By identifying the coupling coordination relationship between the two systems and the influencing factors, this paper aims to promote the virtuous cycle of coordinated development between regional agriculture and technology, as well as accelerate the realisation of high-quality development of Chinese agriculture. Therefore, this paper explores the spatial and temporal coupling characteristics of the two using the entropy value method, coupling coordination degree model, and exploratory spatial data analysis, and it screens for important influencing factors using the grey correlation model. The main results show that ① the coupling coordination relationship between agricultural technology innovation and food security in China is at a dissonant stage, but the value of the coupling coordination degree increases from 0.2076 to 0.3437 during the period of study, and the level of coordination gradually improves. ② The degree of coupling coordination in the provincial space exhibits a distribution pattern of "high in the east and low in the west". The areas of high value are primarily situated in the provinces of Shandong, Jiangsu, and other provinces along the southeastern coast of China, while the areas of low value are mainly located in the provinces of Qinghai, Ningxia, and other provinces in inland northwest China. ③ The Moran's index of provincial coupling coordination is greater than 0, showing a certain positive correlation, and there is a significant pattern of spatial aggregation. ④ The correlation coefficients between the influencing factors and the degree of coupling coordination are all greater than 0.35, indicating a moderate or high correlation, but the significance of technological support capacity and food distribution security increased over time. [ABSTRACT FROM AUTHOR]

Apples are rich in vitamins and dietary fiber and are one of the essential fruits in people's daily diet. China has always been a big apple consumer, and with the improvement of people's life quality, nutrition, and health requirements, the demand for high-quality apples has increased year by year. Apple mold heart disease is one of the main diseases affecting apple quality. However, this disease cannot be easily detected from the surface, so it is difficult to detect mold heart disease. Therefore, this paper focuses on the analysis of seven non-destructive detection technologies, including near infrared spectroscopy technology, hyperspectral technology, Raman spectroscopy technology, electronic nose technology, acoustic technology, electrical technology, and magnetic technology, summarizes their application status in the detection of apple mold heart disease, and then analyzes their advantages and disadvantages. Combined with the current rapid development of artificial intelligence (AI) technology, this paper proposes the future development trends of using non-destructive technologies to detect apple mold heart disease. It is expected to provide basic theory and application references for the intelligent detection of apple mold heart disease. [ABSTRACT FROM AUTHOR]

Land desertification is a key environmental problem in China, especially in Northwest China, where it seriously affects the sustainable development of natural resources. In this paper, we combine high-resolution satellite remote sensing images and UAV (unmanned aerial vehicle) visible light images to extract desert vegetation data and quickly locate and accurately monitor land desertification in relevant areas according to changes in vegetation coverage. Due to the strong light and dry climate of deserts in Northwest China, which results in deeper vegetation shadow texture and mostly dry shrubs with fewer stems and leaves, the accuracy of the vegetation index commonly used in visible remote sensing image classification is not able to meet the requirements for monitoring and evaluating land desertification. For this reason, in this paper, we took the Hangjin Banner in Bayannur as an example and constructed a new vegetation index, the HSVGVI (hue–saturation–value green enhancement vegetation index), based on the HSV (hue–saturation–value) color space using channel enhancement that can improve the extraction accuracy of desert vegetation and reduce misclassification. In addition, in order to further test the extraction accuracy, samples of densely vegetated and multi-shaded areas were divided in the study area according to the accuracy-influencing factors. At the same time, the HSVGVI was compared with the vegetation indices EXG (excess green index), RGBVI (red–green–blue vegetation index), MGRVI (modified green–red vegetation index), NGBDI (normalized green–red discrepancy index), and VDVI (visible-band discrepancy vegetation index) constructed based on the RGB (red–green–blue) color space. The experimental results show that the extraction accuracy of the EXG and other vegetation indices constructed in RGB color space can only reach 70%, while the extraction accuracy of the HSVGVI can reach more than 95%. In summary, the HSVGVI proposed in this paper can better realize the extraction of desert vegetation data and can provide a reliable technical tool for monitoring and evaluating land desertification. [ABSTRACT FROM AUTHOR]

The high-quality development of the industrial software industry is of strategic significance to enhancing the core competitiveness of the manufacturing industry and promoting the high-quality development of China's industrial economy. By integrating the "capital-technology-environment-human" production factor theory and configuration perspective, this paper constructs a comprehensive analysis framework that drives the total factor productivity (TFP) of the industrial software industry. This paper uses 40 typical industrial software firms in 2018–2020 as case samples and uses fuzzy set Qualitative Comparative Analysis (fsQCA) to empirically explore the influencing factors and complex mechanisms that achieve high-quality development of the industrial software industry. It is found that: (1) a single industrial factor is hardly a necessary condition to drive the industrial software industry; (2) there are four paths to achieving high TFP, which are summarized as "technical-human-environmental" balanced driving type, "capital-human-environmental" balanced driving type, "technical-capital" dual driving type, and "capital" single driving type. There are four driving mechanisms. There are also four not-high TFP configurations with asymmetric characteristics; (3) under certain conditions, the combination of capital factors, technical factors, environmental factors, and human factors can drive TFP in an "all roads lead to Rome". In this process, the government's attention plays a more universal role. The study not only expands the application scenarios of fsQCA but also provides decision guidelines for the practice of strategic emerging industrialization represented by the industrial software industry. [ABSTRACT FROM AUTHOR]

Throughout the last decades, engaging with cultural landscapes has been a scientific, social, ethical, political, and economic imperative that calls for novel theoretical approaches, effective strategies and, above all, participatory action. Facing this multifarious challenge, academic disciplines have to redefine their traditional methods and aims, and demonstrate an openness towards new and risky paths of scientific pursuits. The present paper arose from interdisciplinary cooperation between the humanities and social sciences with the main objective to explore the potential of cultural landscapes as resources for social innovation in rural regions, addressing issues such as out-migration of original inhabitants, unemployment, and an overaging population. Based on an overview of landscape semantics and theoretical approaches, the paper first analyzes (cultural) landscape and social innovation as applied concepts. In a second step, both disciplinary angles mingle into a joint approach. Moving from methodologies to challenges, the authors discuss the Social Grid Model, which allows for an integrated analysis of social networks, institutions, and cognitive frames. They also delve into the Structured Democratic Dialogue as a tool for the revitalization of 'active' and 'inactive' cultural landscapes by reinforcing the role of local communities. Finally, the authors investigate how such novel ideas for the promotion of tangible and intangible heritage in rural habitats can be employed by example of two intervention regions in Greece (Koumasa) and the People's Republic of China (Honghe Hani Rice Terraces), and as part of an orchestrated collective action. [ABSTRACT FROM AUTHOR]

This paper investigates whether and how tax and fee support policies at the firm level in China influence the total factor energy productivity of enterprises. Using panel data from Chinese public trading companies for the period 2004–2020, this study employs a panel model for estimation. The findings suggest that tax rebates contribute to the improvement of the total factor energy productivity of enterprises. Specifically, a 1% increase in tax refunds leads to a growth of approximately 0.008% in total factor energy productivity. Robustness tests and endogeneity checks confirm the validity of the results. Heterogeneity analysis reveals that tax rebates have a significant impact on state-owned enterprises, small- and medium-sized enterprises, and non-technology firms in terms of enhancing their total factor energy productivity. Mechanism analysis indicates that tax rebates facilitate firms in alleviating financing constraints and enhancing their innovation capabilities, thereby improving energy efficiency. The research findings of this paper provide empirical support for optimizing policy supply, improving energy usage efficiency, and promoting the development of a globally sustainable economy. [ABSTRACT FROM AUTHOR]

In the coastal areas of China, the eutrophication of seawater leads to the continuous occurrence of red tide, which has caused great damage to Marine fisheries and aquatic resources. Therefore, the detection and prediction of red tide have important research significance. The rapid development of optical remote sensing technology and deep-learning technology provides technical means for realizing large-scale and high-precision red tide detection. However, the difficulty of the accurate detection of red tide edges with complex boundaries limits the further improvement of red tide detection accuracy. In view of the above problems, this paper takes GOCI data in the East China Sea as an example and proposes an improved U-Net red tide detection method. In the improved U-Net method, NDVI was introduced to enhance the characteristic information of the red tide to improve the separability between the red tide and seawater. At the same time, the ECA channel attention mechanism was introduced to give different weights according to the influence of different bands on red tide detection, and the spectral characteristics of different channels were fully mined to further extract red tide characteristics. A shallow feature extraction module based on Atrous Spatial Pyramid Convolution (ASPC) was designed to improve the U-Net model. The red tide feature information in a multi-scale context was fused under multiple sampling rates to enhance the model's ability to extract features at different scales. The problem of limited accuracy improvement in red tide edge detection with complex boundaries is solved via the fusion of deep and shallow features and multi-scale spatial features. Compared with other methods, the method proposed in this paper achieves better results and can detect red tide edges with complex boundaries, and the accuracy, precision, recall, and F1-score are 95.90%, 97.15%, 91.53%, and 0.94, respectively. In addition, the red tide detection experiments in other regions with relatively concentrated distribution also prove that the method has good applicability. [ABSTRACT FROM AUTHOR]

Based on authorized patents of China's artificial intelligence industry from 2013 to 2022, this paper constructs an Industry–University–Research institution (IUR) collaboration network and an Inter-Firm (IF) collaboration network and used the entropy weight method to take both the quantity and quality of patents into account to calculate the innovation performance of firms. Through the hierarchical clustering algorithm and classification and regression trees (CART) algorithm, in-depth analysis has been conducted on the intricate non-linear influence mechanisms between multiple variables and a firm's innovation performance. The findings indicate the following: (1) Based on the network centrality (NC), structural hole (SH), collaboration breadth (CB), and collaboration depth (CD) of both IUR and IF collaboration networks, two types of focal firms are identified. (2) For different types of focal firms, the combinations of network characteristics affecting their innovation performance are various. (3) In the IUR collaboration network, focal firms with a wide range of heterogeneous collaborative partners can obtain high innovation performance. However, focal firms in the IF collaboration network can achieve the same aim by maintaining deep collaboration with other focal firms. This paper not only helps firms make scientific decisions for development but also provides valuable suggestions for government policymakers. [ABSTRACT FROM AUTHOR]

Short-season cotton is a type of cotton variety characterized by its abbreviated cycle, rapid development, and concentrated flowering and boll setting. Compared with full-season cotton, short-season cotton facilitates an easier attainment of desirable maturation even when sown relatively late. This advantage of late sowing and early maturation eliminates the necessity for plastic film mulching, thereby creating opportunities for diversified double cropping, such as cotton–wheat, cotton–garlic, cotton–rape, and cotton–triticale systems. This paper provides a comprehensive review of the morphological, physiological, and molecular biological mechanisms underlying early maturity in short-season cotton. Furthermore, the significance and application of short-season cotton is discussed in relation to optimizing planting patterns and methods, promoting its cultivation in saline fields, developing machine-harvested cotton, and encouraging plastic mulch-free cotton planting. Based on these analyses and discussions, the paper proposes future strategies aimed at enhancing the breeding and cultivation of short-season cotton. These findings serve as valuable references for global breeding and cultivation research, and application of short-season cotton in the future. [ABSTRACT FROM AUTHOR]

Moslae Herba (MH) can be used for both medicine and food and has a long history of medicine. MH has the effects of sweating and relieving the exterior, removing dampness and harmonizing, and is mainly used for colds caused by damp heat in summer. It is called "Xiayue Zhi Mahuang" in China. So far, 123 chemical compounds have been isolated and identified from MH, including flavonoids, terpenoids, phenolic acids, phenylpropanoids, and other chemical compounds. Its chemical components have a wide range of pharmacological activities, including antibacterial, antiviral, anti-inflammatory, antioxidant, analgesic sedation, antipyretic, immune regulation, insecticidal, and other effects. In addition, because of its aromatic odor and health care function, MH also has development and utilization value in food, chemical, and other fields. This paper reviewed the research progress of MH in botany, traditional uses, phytochemistry, and pharmacology and provided a possible direction for further research. [ABSTRACT FROM AUTHOR]

Simple Summary: In response to the quantitative demand for the practical deployment of applications and the need to enhance the detection accuracy of wildlife in complex field environments in southwest China and neighboring regions, we have refined the wildlife detection algorithm based on re-parameterized convolution. This refinement is specifically targeted at addressing the challenges posed by the low quality of wildlife images captured by camera traps and the limitations of traditional object detection algorithms in feature extraction capability. To address these issues, we have introduced a series of improvement schemes. As a result of these enhancements, there has been a noteworthy improvement in both the accuracy of wildlife detection and the speed of model inference. This advancement offers a convenient and efficient method for the preliminary detection in the context of automated wildlife monitoring. To autonomously detect wildlife images captured by camera traps on a platform with limited resources and address challenges such as filtering out photos without optimal objects, as well as classifying and localizing species in photos with objects, we introduce a specialized wildlife object detector tailored for camera traps. This detector is developed using a dataset acquired by the Saola Working Group (SWG) through camera traps deployed in Vietnam and Laos. Utilizing the YOLOv6-N object detection algorithm as its foundation, the detector is enhanced by a tailored optimizer for improved model performance. We deliberately introduce asymmetric convolutional branches to enhance the feature characterization capability of the Backbone network. Additionally, we streamline the Neck and use CIoU loss to improve detection performance. For quantitative deployment, we refine the RepOptimizer to train a pure VGG-style network. Experimental results demonstrate that our proposed method empowers the model to achieve an 88.3% detection accuracy on the wildlife dataset in this paper. This accuracy is 3.1% higher than YOLOv6-N, and surpasses YOLOv7-T and YOLOv8-N by 5.5% and 2.8%, respectively. The model consistently maintains its detection performance even after quantization to the INT8 precision, achieving an inference speed of only 6.15 ms for a single image on the NVIDIA Jetson Xavier NX device. The improvements we introduce excel in tasks related to wildlife image recognition and object localization captured by camera traps, providing practical solutions to enhance wildlife monitoring and facilitate efficient data acquisition. Our current work represents a significant stride toward a fully automated animal observation system in real-time in-field applications. [ABSTRACT FROM AUTHOR]

Microwave hyperspectral instruments represent one of the main atmospheric sounders of China's next-generation Fengyun meteorological satellites. In order to better apply microwave hyperspectral observations in the fields of atmospheric parameter retrieval and data assimilation, this paper analyzes the sensitivity of trace gases to five selected bandwidth channels using a radiative transfer model based on the simulated data of microwave hyperspectral radiances at 50–60 GHz. This method uses information entropy and a weighting function to select channels and analyze the impact of this on the retrieval accuracy of atmospheric profiles before and after channel selection. The experimental results show that channel selection can reduce the number of channels by approximately 74.05% while maintaining a large amount of information content, and this retrieval effect is significantly better than that of MWTS-III. After channel selection, the 10 MHz, 30 MHz, and 50 MHz bandwidths have the best retrieval results in the stratosphere, whole atmosphere, and troposphere, respectively. When considering the number of channels, computational scale, and retrieval results comprehensively, the channel selection method is effective. [ABSTRACT FROM AUTHOR]

The investigation of reactivated landslides in the alpine-canyon areas suffers the difficult accessibility of precipitous terrain. In particular, when reactivated landslides occur along the major roads, efforts are focused on measuring ground surface displacements during road construction. Nevertheless, the ancient landslide deposits may reactivate after several years of road operation, while they show a stable state during the road construction. The characterization of this type of reactivated landslides is challenging, due to their complex mechanism and the limited monitoring data. Appropriate multi-source data can provide insights into deformation fields and enhance the understanding of landslide mechanisms, ensuring the outperformance of remedial works. This paper reports a recent Tangjiawan reactivated landslide along the Wenchuan-Maerkang Highway in Li County, China. The outcomes, including satellite InSAR, in situ real-time monitoring, and detailed ground and UAV investigation, conducted at this landslide are presented. Early deformation of the reactivated landslide began from 2019, with an InSAR-derived velocity of −11.7 mm/year, furthermore, a significant subsidence of about 21.2 mm, which occurred within a span of only 12 days from 3 June 2020 to 15 June 2020, was observed. The deformation characteristics derived from in situ monitoring during the remedial works were likely firstly associated with the initial unreinforced slope condition and the heavy rainfall. Subsequently, the displacement evolution transformed into deformation induced by time-dependent reduction in slope strength under rainfall conditions. The existing of unconsolidated deposits derived from ancient landslides, along with a fragile geo-structure consisting of rock blocks and gravels interlayered with breccias, exacerbated by large relief created a predisposition for landslide reactivation. Furthermore, 13 days of antecedent cumulative rainfall totaling 224.5 mm directly triggered the occurrence of a landslide event. The significance and implications of integrating multiple monitoring techniques are emphasized. [ABSTRACT FROM AUTHOR]

The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS's robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS's robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power. [ABSTRACT FROM AUTHOR]

Heating buildings with solar energy is challenged by the seasonal mismatch between solar availability and heating demand. Thermochemical energy storage is a promising technology to overcome this challenge because of its high energy density. In building applications, space requirement is also an important consideration. Therefore, both the storage space and collector areas are important considerations, with only the latter often being neglected in previous studies. This paper proposes a novel two-stage thermochemical heat pump heating system based on the working pair of NaOH/H2O. We demonstrate that this system can work with a concentration difference (70% wt–30% wt) for the climate in hot summer and cold winter regions in China. The energy storage density based on the discharged solution is 363 kWh/m3. With this solar-driven thermochemical heat pump heating system, 35.13 m2 of collectors and 10.48 tons of 70% wt NaOH solution are sufficient to complete a full charge–discharge cycle and meet the heating demand of a single-family house (winter space heating + DHW: 9370 kWh, summer DHW: 2280 kWh). The theoretical maximum storage for solution (discharged + water tank) is 32.47 m3. Compared with the sensible seasonal storage alternative, the collector area is reduced by 12.5% and the storage space is reduced by 59%, with a possible further reduction through optimization. With the potential to be further optimized for space saving, the two-stage solar–NaOH heat pump heating system is an energy-efficient and space-efficient heating system for buildings in the hot summer and cold winter regions of China. [ABSTRACT FROM AUTHOR]

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

In recent years, atmospheric composite pollution has become increasingly serious, and accelerating VOC governance has become the focus of and difficulty in atmospheric governance. Volatile organic compounds (VOCs) come from a wide range of sources, and industrial sources are the main source of anthropogenic VOC emissions in China. Chemicals, oil refining, and solvents are three typical VOC-emitting industries, and their control is an important part of accelerating and optimizing VOC governance. It can be controlled by source control, process control, and pipe end treatment; among these, pipe end treatment is divided into recovery technology and destruction technology. In pipeline end treatment, with the key materials of adsorption, absorption, catalytic oxidation, and catalytic combustion, the research and development of adsorbents, absorbents and catalysts has become a hot spot in recent years. This paper summarizes the chemical materials used in typical VOC pipe end-treatment technology (including adsorbents used in the adsorption method, absorbents used in the adsorption method, and catalysts used in the catalytic oxidation and catalytic combustion methods), summarizes the advantages and disadvantages of various materials and their application range, and looks forward to the direction of future developments. [ABSTRACT FROM AUTHOR]

Vegetables have a short period of freshness, and therefore, the purchase of vegetables has to be carefully matched with sales, especially in the "small production and big market" setting prevalent in China. Therefore, it is worthwhile to develop a systematic and comprehensive mathematical model of replenishment plans and pricing strategies for each category of vegetables and individual products. In this paper, we analyze the following three questions: Question One: What is the distribution law and relationship between the sales volume of vegetable categories and single products? Question Two: What is the relationship between total sales volume and cost-plus pricing of vegetable categories? And is it possible to provide the daily total replenishment and pricing strategy of each vegetable category for the following week to maximize supermarket profit? Question Three: How can we incorporate the market demand for single vegetable products into a profit-maximizing program for supermarkets? Is it possible to further formulate the replenishment plan requirements for single products? To answer the first question, we created pivot tables to analyze occupancy. We found that mosaic leaves, peppers, and edible mushrooms accounted for a larger proportion of occupacy, while cauliflowers, aquatic rhizomes, and eggplants accounted for a smaller proportion. For the single items, lettuce, cabbage, green pepper, screw pepper, enoki mushroom, and shiitake mushroom accounted for a large proportion of their respective categories. We used the Pearson correlation coefficient and the Mfuzz package based on fuzzy c-means (FCM) algorithm to analyze the correlation between vegetable categories and single products. We found that there was a strong correlation between vegetable categories. Moreover, the sale of vegetable items belonging to the same category exhibited the same patterns of change over time. In order to address the second question, we established the LightGBM sales forecasting model. Combined with previous sales data, we forecasted and planned an efficient daily replenishment volume for each vegetable category in the coming week. In addition, we developed a pricing strategy for vegetable categories to maximize supermarket profits. For the third question, we built a dynamic programming model combining an optimal replenishment volume with a product pricing strategy for single items, which let the supermarket maximize its expected profits. [ABSTRACT FROM AUTHOR]

In recent years, caffeic acid and its derivatives have received increasing attention due to their obvious physiological activities and wide distribution in nature. In this paper, to clarify the status of research on plant-derived caffeic acid and its derivatives, nuclear magnetic resonance spectroscopy data and possible biosynthetic pathways of these compounds were collected from scientific databases (SciFinder, PubMed and China Knowledge). According to different types of substituents, 17 caffeic acid and its derivatives can be divided into the following classes: caffeoyl ester derivatives, caffeyltartaric acid, caffeic acid amide derivatives, caffeoyl shikimic acid, caffeoyl quinic acid, caffeoyl danshens and caffeoyl glycoside. Generalization of their 13C-NMR and 1H-NMR data revealed that acylation with caffeic acid to form esters involves acylation shifts, which increase the chemical shift values of the corresponding carbons and decrease the chemical shift values of the corresponding carbons of caffeoyl. Once the hydroxyl group is ester, the hydrogen signal connected to the same carbon shifts to the low field (1.1~1.6). The biosynthetic pathways were summarized, and it was found that caffeic acid and its derivatives are first synthesized in plants through the shikimic acid pathway, in which phenylalanine is deaminated to cinnamic acid and then transformed into caffeic acid and its derivatives. The purpose of this review is to provide a reference for further research on the rapid structural identification and biofabrication of caffeic acid and its derivatives. [ABSTRACT FROM AUTHOR]

Tumors have a huge impact on human life and are now the main cause of disease-related deaths. The main means of treatment are surgery and radiotherapy, but they are more damaging to the organism and have a poor postoperative prognosis. Therefore, we urgently need safe and effective drugs to treat tumors. In recent years, Chinese herbal medicines have been widely used in tumor therapy as complementary and alternative therapies. Medicinal and edible herbs are popular and have become a hot topic of research, which not only have excellent pharmacological effects and activities, but also have almost no side effects. Therefore, as a typical medicine and food homology, some components of Paeoniae Radix Alba (PRA, called Baishao in China) have been shown to have good efficacy and safety against cancer. Numerous studies have also shown that Paeoniae Radix Alba and its active ingredients treat cancer through various pathways and are also one of the important components of many antitumor herbal compound formulas. In this paper, we reviewed the literature on the intervention of Paeoniae Radix Alba in tumors and its mechanism of action in recent years and found that there is a large amount of literature on its effect on total glucosides of paeony (TGP) and paeoniflorin (PF), as well as an in-depth discussion of the mechanism of action of Paeoniae Radix Alba and its main constituents, with a view to promote the clinical development and application of Paeoniae Radix Alba in the field of antitumor management. [ABSTRACT FROM AUTHOR]

The large-sized Tarangaole uranium deposit and its neighboring Daying and Nalinggou deposits, located in the northeastern margin of the Ordos Basin, constitutes a major uranium resource base in northern China. In order to further clarify the sedimentary material source, uranium source and regional sediment–tectonic setting of the uranium-fed clastic rocks (i.e., Zhiluo Formation(J2z)) in the district, this paper carried out whole-rock geochemistry, heavy minerals composition and in situ U-Pb dating of detrital zircons for sandstones from the lower section of the Zhiluo Formation. The results have shown that the average chemical differentiation index (CIA) for the host rocks is 73.16 and the chemical weathering degree is moderate. Heavy minerals are mainly composed of ilmenite, garnet, chlorpyrite, zircon, pyrite, apatite, hematite, etc. The U-Pb dating of detrital zircon generally indicates three age peaks, i.e., 260~Ma, 1850~Ma and 2450~Ma, respectively. In conclusion, the source rocks may have been formed at active continental margins, e.g., in a continental margin arc environment. The sedimentary materials mainly come from khondalite series, TTGs, granulite, and mafic–ultramafic intrusive rocks distributed among the Daqing–Ula Mountains and adjacent areas, etc. The Late Paleozoic U-rich intermediate and acidic magmatic rocks spreading over the eastern part of the Ula–Daqing and Wolf mountains have provided the main uranium sources for the formation of major U deposits in the northern Ordos Basin. [ABSTRACT FROM AUTHOR]

Research on the provenance of sedimentary systems is key to better understanding the sedimentary framework and improving exploration-associated decision-making and deployment. With regard to the provenance of sedimentary systems, there is still poor understanding in the initial rifting stage due to imbalanced and insufficient exploration and a common lack of seismic data, which have seriously hindered oil exploration in the Qintong Sag, Subei Basin. This study aimed at investigating the provenance in the direction of the fault-terrace zone in the southeast part of the Qintong Sag and aimed to examine whether large-scale sedimentary systems are formed by these sediment sources. Integrated analysis of heavy minerals, sandstone petrologic maturity, drilling cutting dates, 3D seismic data, and well logs was employed to identify the provenance. This study is the first time that large-scale provenance from the direction of the fault-terrace zone has been discovered in the third member of the Paleocene Funing Formation (referred to as the third Mbr of the Funing Fm in this paper) in the Subei Basin, east China. The documentation shows that sediments from the northwest Wubao Low Uplift and the southeast Taizhou Uplift can be distinguished in the Qintong Sag, with the large-scale delta system in the central and eastern part of the Qintong Sag comprising sediments from the Taizhou Uplift, improving upon previous understanding of the sedimentary framework. The deposition formed by the Taizhou Uplift provenance system was characterized by gradual weakening of the hydrodynamic forces, a decreasing sediment supply, and shrinking of the retrogradational delta depositional systems with good reservoir qualities, which are characterized by high-quality source–reservoir–cap combinations and are likely to develop into a hydrocarbon-rich belt. The discovery of the Taizhou Uplift provenance proves that there may be major provenance and large-scale sedimentary systems from the fault-terrace zone of the rift basins in the initial rifting stage. The experience of rapid retrogradation showed that these large-scale delta systems are likely to only flourish in the initial rifting stage. This study is helpful for improving the understanding of sediment provenance and the sedimentary framework of lacustrine rift basins in the initial rifting stage. [ABSTRACT FROM AUTHOR]

This paper presents the zonal geochemistry and elasticity characteristics of gallium- and lithium-rich No. 6 coalbed in the Haerwusu mine and discusses interpretation methodologies of coal-hosted gallium and lithium resources using lab-measured samples and field-measured wireline logs. The results demonstrate that both coal-composition-based and elastic-parameter-based classifications yield similar results, categorizing the coalbed into subzones related to coal quality. Material compositions, elastic properties, critical metals, and host minerals exhibit zonal distribution characteristics within the ultrathick No. 6 coalbed. Three-class classifications significantly enhance correlations among host minerals, elastic parameters, and critical metals, albeit with differing trends among classes. In classes II and III (ultralow- and low-ash-yield coals), boehmite and kaolinite primarily host gallium and lithium, respectively. In class I (medium-ash-yield coal), gallium is associated with kaolinite, while lithium lacks specific mineral associations. Constrained by wireline logs, a rock physics modeling strategy is proposed to link mesoscale coal compositions to macroscale elastic responses. Moreover, explicit correlations between host minerals and critical metals are established, connecting macroscale elastic responses to microscale gallium and lithium enrichments and exploring interpretation methods of coal-hosted critical metals. Preferred lithium interpretation methods include compositional ternary plots and elastic parameter cross plots, while preferred gallium interpretation methods involve boehmite-gallium and elastic parameter-gallium fitting. These findings may contribute to understanding the enrichment mechanisms and interpretation technologies of coal-hosted critical metals in ultrathick low-rank coalbeds. [ABSTRACT FROM AUTHOR]

Currently, in some domestic and foreign mines, the backfill drilling pipeline experiences a rupture phenomenon even when the wear degree is low. This results in a delay in production due to the filling becoming 'sick'. This paper presents, for the first time, the damage mechanism from a mechanical perspective and re-derives the anti-extrusion strength model of the backfill drilling pipeline. We investigate the influence of the law on the anti-extrusion strength of pipelines from the perspective of strata and cement rings. We then verify the theoretical and simulation results through engineering examples. The results demonstrate that the Mises stress criterion is a suitable modification principle for the anti-extrusion strength model of the backfill drilling pipeline. The anti-extrusion strength of the pipeline is related to the elastic modulus and Poisson's ratio of the stratum, and the thickness of the cement ring. It is negatively affected by the depth of the stratum. For hard strata, a cement ring with a smaller elastic modulus is suitable, while for soft stratum, a cement ring with a larger elastic modulus is recommended. When the missing angle of the cement ring is less than 60°, the stress concentration factor increases up to 2.2. The stress unloading capacity of the cement ring ranges from 32.7% to 37.8%, and optimal performance of the cement ring is achieved when it has high strength and low rigidity. The backfill filling pipeline of a copper mine abroad was destroyed due to external extrusion force exceeding its anti-extrusion strength value. The modified pipeline anti-extrusion strength model is 18.2% higher than the pipeline API strength value. This finding can inform the design of the backfill filling pipeline for China's kilometer-deep wells in the future. [ABSTRACT FROM AUTHOR]

Precipitation is the basic component of the Earth's water cycle. Obtaining high-resolution and high-precision precipitation data is of great significance. This paper establishes a precipitation retrieval model based on a random forest classification and regression model during the day and at night with FY-4B/AGRI Level1 data on China from July to August 2022. To evaluate the retrieval effect of the model, the GPM IMERG product is used as a reference, and the retrieval results are compared against those of the FY-4B/AGRI operational precipitation product. In addition, the retrieval results are analyzed according to different underlying surfaces. The results showed that compared with the FY-4B/AGRI operational precipitation product, the retrieval model can better identify precipitation and capture precipitation areas of light rain, moderate rain, heavy rain and torrential rain. Among them, the probability of detection (POD) of the day model increased from 0.328 to 0.680, and the equitable threat score (ETS) increased from 0.252 to 0.432. The POD of the night model increased from 0.337 to 0.639, and the ETS score increased from 0.239 to 0.369. Meanwhile, the precipitation estimation accuracy of the day model increased by 38.98% and that of the night model increased by 40.85%. Our results also showed that due to the surface uniformity of the ocean, the model can identify precipitation better on the ocean than on the land. Our findings also indicated that for the different underlying surfaces of the land, there is no significant difference in each evaluation index of the model. This is a strong argument for the universal applicability of the model. Notably, the results showed that, especially for more vegetated areas and areas covered by water, the model is capable of estimating precipitation. In conclusion, the precipitation retrieval model that is proposed herein can better determine precipitation regions and estimate precipitation intensities compared with the FY-4B/AGRI operational precipitation product. It can provide some reference value for future precipitation retrieval research on FY-4B/AGRI. [ABSTRACT FROM AUTHOR]