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The synergistic relation among land resources, water resources, and food production plays a crucial role in sustainable agricultural development. This research constructs a coupling coordination assessment system of the land–water–food (LWF) nexus from 2005 to 2020 for 31 provinces (municipal cities, autonomous regions) in China, and explores the current development status of land, water, and food systems at multiple scales as well as the coupling coordination characteristics of the LWF nexus. The exploring spatial data analysis and spatial Tobit model are used to explain the spatial correlations and influencing factors of coupling coordination development on the LWF nexus. On that basis, the gray GM (1,1) model is used to forecast the future development of the LWF nexus in China. The results show that the comprehensive development indexes of the land system, water system, food system, and LWF nexus are on the rise, but the land system lags behind the water system and food system. The coupling coordination degree of the LWF nexus in different regions ranges from 0.538 to 0.754, and the coupling coordination development of the LWF nexus in China has reached the preliminary coupled coordination type, with an evolutionary process similar to that of its comprehensive development level. Further empirical research shows that there is a significant positive spatial correlation between coupling coordination development levels for the LWF nexus in China. The level of urbanization and agricultural industry agglomeration have negative effects, while economic development, ecological environment, and scientific and technological progress have positive effects. The prediction results indicate that the coupling coordination degree of the LWF nexus in China will show a stable upward trend from 2024 to 2025, and most provinces will reach the intermediate coupled coordination type in 2025. This study can inform decision-making for policy-makers and practitioners and enrich the knowledge hierarchy of the LWF nexus' sustainable development on the national and regional scales. [ABSTRACT FROM AUTHOR]

Vegetation serves as a crucial indicator of ecological environment and plays a vital role in preserving ecosystem stability. However, as urbanization escalates rapidly, natural vegetation landscapes are undergoing continuous transformation. Paradoxically, vegetation is pivotal in mitigating the ecological and environmental challenges posed by urban sprawl. The middle and lower Yangtze River Basin (MLYRB) in China, particularly its economically thriving lower reaches, has witnessed a surge in urbanization. Consequently, this study explored the spatiotemporal variations of normalized difference vegetation index (NDVI) in the MLYRB, with an emphasis on elucidating the impact of climate change and urbanization on vegetation dynamics. The results indicate that a significant increasing trend in NDVI across the MLYRB from 2000 to 2020, a pattern that is expected to persist. An improvement in vegetation was observed in 94.12% of the prefecture-level cities in the study area, predominantly in the western and southern regions. Temperature and wind speed stand out as dominant contributors to this improvement. Nevertheless, significant vegetation degradation was detected in some highly urbanized cities in the central and eastern parts of the study area, mainly attributed to the negative effects of escalating urbanization. Interestingly, a positive correlation between NDVI and the urbanization rate was observed, which may be largely related to proactive ecological preservation policies. Additionally, global climatic oscillations were identified as a key force driving periodic NDVI variations. These findings hold significant importance in promoting harmonious urbanization and ecological preservation, thereby providing invaluable insights for future urban ecological planning efforts. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Critical thinking is an essential ability for 21st century talents. Blended learning is an emerging learning environment to support learners' cultivation of their critical thinking. Even though there are numerous researches about blended learning on critical thinking, there is lack of a clear summary about above study to provide teachers who are interested in critical thinking cultivation a broad understanding of this area. Thus the purpose of this study is to give lecturers a general guidance by bibliometrix about the trend of blended learning on critical thinking, the most influential journals, themes and nations in this field and a in-depth summary by systematic review about technology, pedagogy and subjects have been studied by scholars to facilitate the instructors to conduct their daily classroom teaching and to have some ideas about future research in the field. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease — COVID-19 is a historic catastrophe that has caused many devastating impacts on human life and wellness. Researchers in academia and industry strive to understand the causes of this pandemic disease and find new therapeutics combating it. Consequently, the number of COVID-19 related publications increases rapidly, and it is too difficult for medical researchers and practitioners to keep up with the latest research and development. Literature filtering and categorization, and knowledge discovery can use text mining as a powerful tool. In this paper, we propose a text mining method to explore the categories of COVID-19 related themes and identify the standard methodologies that have been used. We discuss the potential limitations of this preliminary study and present future perspectives related to COVID-19 research. This paper provides an quantitative and qualitative mixed analysis example of using some research papers by data mining method to dig out several hidden information and set up a foundation for data scientists to develop more effective algorithms to deal with COVID-19 related problems. [ABSTRACT FROM AUTHOR]

In the development of meteorological detection technology and services, weather radar undoubtedly plays a pivotal role, especially in the monitoring and early warning of severe convective weather events, where it serves an irreplaceable function. This research delves into the landscape of weather radar research from 1945 to 2024, employing scientometric methods to investigate 13,981 publications from the Web of Science (WoS) core collection database. This study aims to unravel, for the first time, the foundational structures shaping the knowledge domain of weather radar over an 80-year period, exploring general features, collaboration, co-citation, and keyword co-occurrence. Key findings reveal a significant surge in both publications and citations post-1990, peaking in 2022 with 1083 publications and 13832 citations, signaling sustained growth and interest in the field after a period of stagnation. The United States, China, and European countries emerge as key drivers of weather radar research, with robust international collaboration playing a pivotal role in the field's rapid evolution. Analysis uncovers 30 distinct co-citation clusters, showcasing the progression of weather radar knowledge structures. Notably, deep learning emerges as a dynamic cluster, garnering attention and yielding substantial outcomes in contemporary research efforts. Over eight decades, the focus of weather radar investigations has transitioned from hardware and software enhancements to Artificial Intelligence (AI) technology integration and multifunctional applications across diverse scenarios. This study identifies four key areas for future research: leveraging AI technology, advancing all-weather observation techniques, enhancing system refinement, and fostering networked collaborative observation technologies. This research endeavors to support academics by offering an in-depth comprehension of the progression of weather radar research. The findings can be a valuable resource for scholars in efficiently locating pertinent publications and journals. Furthermore, policymakers can rely on the insights gleaned from this study as a well-organized reference point. [ABSTRACT FROM AUTHOR]

Vegetation serves as a crucial indicator of ecological environment and plays a vital role in preserving ecosystem stability. However, as urbanization escalates rapidly, natural vegetation landscapes are undergoing continuous transformation. Paradoxically, vegetation is pivotal in mitigating the ecological and environmental challenges posed by urban sprawl. The middle and lower Yangtze River Basin (MLYRB) in China, particularly its economically thriving lower reaches, has witnessed a surge in urbanization. Consequently, this study explored the spatiotemporal variations of normalized difference vegetation index (NDVI) in the MLYRB, with an emphasis on elucidating the impact of climate change and urbanization on vegetation dynamics. The results indicate that a significant increasing trend in NDVI across the MLYRB from 2000 to 2020, a pattern that is expected to persist. An improvement in vegetation was observed in 94.12% of the prefecture-level cities in the study area, predominantly in the western and southern regions. Temperature and wind speed stand out as dominant contributors to this improvement. Nevertheless, significant vegetation degradation was detected in some highly urbanized cities in the central and eastern parts of the study area, mainly attributed to the negative effects of escalating urbanization. Interestingly, a positive correlation between NDVI and the urbanization rate was observed, which may be largely related to proactive ecological preservation policies. Additionally, global climatic oscillations were identified as a key force driving periodic NDVI variations. These findings hold significant importance in promoting harmonious urbanization and ecological preservation, thereby providing invaluable insights for future urban ecological planning efforts.

The synergistic relation among land resources, water resources, and food production plays a crucial role in sustainable agricultural development. This research constructs a coupling coordination assessment system of the land–water–food (LWF) nexus from 2005 to 2020 for 31 provinces (municipal cities, autonomous regions) in China, and explores the current development status of land, water, and food systems at multiple scales as well as the coupling coordination characteristics of the LWF nexus. The exploring spatial data analysis and spatial Tobit model are used to explain the spatial correlations and influencing factors of coupling coordination development on the LWF nexus. On that basis, the gray GM (1,1) model is used to forecast the future development of the LWF nexus in China. The results show that the comprehensive development indexes of the land system, water system, food system, and LWF nexus are on the rise, but the land system lags behind the water system and food system. The coupling coordination degree of the LWF nexus in different regions ranges from 0.538 to 0.754, and the coupling coordination development of the LWF nexus in China has reached the preliminary coupled coordination type, with an evolutionary process similar to that of its comprehensive development level. Further empirical research shows that there is a significant positive spatial correlation between coupling coordination development levels for the LWF nexus in China. The level of urbanization and agricultural industry agglomeration have negative effects, while economic development, ecological environment, and scientific and technological progress have positive effects. The prediction results indicate that the coupling coordination degree of the LWF nexus in China will show a stable upward trend from 2024 to 2025, and most provinces will reach the intermediate coupled coordination type in 2025. This study can inform decision-making for policy-makers and practitioners and enrich the knowledge hierarchy of the LWF nexus’ sustainable development on the national and regional scales.

Increasing demands for livestock products have stimulated rapid increases in the number of livestock and the scale of farming, thus increasing pressure on resources and the environment. Coordinating the development of livestock production (LP) with residential consumption (RC), resources and the environmental carrying capacity (RECC) is important to ensure sustainable development. In this study, the entropy weight method and the improvedcoupling coordination degree (CCD) model were used to identify the spatial-- temporal coordination development characteristics of livestock productionresidential consumption-resource and environmental carrying capacity (LRRE). Furthermore, the spatial autocorrelation model (SAM) and gray model (GM) were used to analyze the spatial aggregation characteristics and future development trends of the CCDs of the LRRE in China. The findings show that the CCDs of the LRRE values in 31 Chinese provinces increased from 2005 to 2020, but no provinces reached a high coordination level. Specifically, the coordinated development level of LRRE is relatively high in the central, eastern and northeastern regions and relatively low in the western region. The spatial autocorrelation analysis confirmed that the high-high (H-H) aggregation areas were mainly distributed in the northeastern, eastern, and central regions, while low-high (L-H) agglomeration was distributed in the western region. This phenomenon is mainly attributed to the continuous expansion of the scale of livestock production in western China. Regions with relatively developed economies have more funds to invest in environmental protection projects. Using GM method, we find that the CCDs of LRRE in 31 provinces in China will increase from 2021 to 2030, and all provinces will reach the basic coordination level. However, most of the western regions will barely reach the basic coordination level. This result indicates that the low level of LRRE development in western China may be difficult to change in the short term. The level of coordinated LRRE development in the relatively developed eastern region is increasing. The spatial layout of China's livestock industry should be appropriately adjusted, its expansion rate in the western region should be decreased, and the ecological environment of the areas bordering the western and central regions should be improved. These findings have practical implications for other large livestock production countries. Promoting the coordinated development of LRRE is also an important condition for agricultural transformation in developing countries, especially for improving the environment in key areas of the livestock industry. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Vegetation plays a crucial role in nature, with intricate interactions between it and the geographical environment. The Yangtze River Basin (YRB) refers to the third largest river basin globally and an essential ecological security barrier in China. Monitoring vegetation dynamics in the basin is of profound significance for addressing climate change, soil erosion, and biodiversity loss in the basin's ecosystems. Here, we investigate the spatiotemporal variations of vegetation at both the basin and land cover scales in the YRB from 2000 to 2020. We elucidate the determinants driving the changes and explore future normalized difference vegetation index (NDVI) trends. The results indicate that NDVI in the YRB increased at a rate of 0.0032 year−1 (p < 0.01) over the past 21 years, and it is anticipated to maintain an upward trend in the future. Regions in the upper and middle reaches of the YRB demonstrated higher NDVI, whereas regions in the headwater area and the lower reaches showed lower NDVI. Significant vegetation improvement was primarily concentrated in the central part of the basin, while noticeable vegetation degradation was observed in the eastern region. Temperature and wind speed were identified as the primary controlling factors affecting vegetation greenness. Global‐scale climate oscillations played a significant role in driving periodic variations in NDVI, with La Niña events tending to increase NDVI, while El Niño events hindered its rise. Land cover types were influenced by long‐term interactions between natural factors and human activities, although short‐term vegetation variations might be more affected by the latter. Our findings provide valuable insights into the mechanisms behind vegetation variability driven by multiple variables, and the strong vegetation carbon sink capacity advances the conservation and development of ecosystems. [ABSTRACT FROM AUTHOR]

Abstract Vegetation plays a crucial role in nature, with intricate interactions between it and the geographical environment. The Yangtze River Basin (YRB) refers to the third largest river basin globally and an essential ecological security barrier in China. Monitoring vegetation dynamics in the basin is of profound significance for addressing climate change, soil erosion, and biodiversity loss in the basin's ecosystems. Here, we investigate the spatiotemporal variations of vegetation at both the basin and land cover scales in the YRB from 2000 to 2020. We elucidate the determinants driving the changes and explore future normalized difference vegetation index (NDVI) trends. The results indicate that NDVI in the YRB increased at a rate of 0.0032 year−1 (p

To investigate the potential impact of emission reduction measures on ozone (O3) formation under the carbon neutrality target, we examined the changes in O3 concentration and their sensitivity to various parameters in the urban and suburban areas of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). In this study, we used the Weather Research and Forecasting (WRF), the Sparse Matrix Operator Kernel Emissions (SMOKE) and the Community Multi-scale Air Quality Modeling system (CMAQ) air quality model to simulate O3 formation in three key years of 2020, 2030 and 2060, based on the Ambitious-pollution-Neutral-goal scenario data from the Dynamic Projection for Emissions in China (DPEC) model. The decoupled direct method (DDM) module embedded in CMAQ was used to calculate the first-order sensitivity coefficients of O3 to nitrogen oxides (SO3_NOx) and volatile organic compounds (SO3_VOC). The results show several important trends in the O3 concentrations and sensitivity. (1) For the changes in O3 concentrations, in terms of different seasons, the O3 concentration in the GBA region shows an increasing trend in winter in both 2030 and 2060 compared to 2020. In terms of different cities, the O3 concentration in Shenzhen shows a significant increasing trend compared to the other cities. (2) For changes in O3 sensitivity, SO3_NOx shows an increasing trend, with the negative area declining and the positive area increasing. In 2030, the negative absolute value of SO3_NOx is reduced, indicating that the NOx titration effect will be weakened. In 2060, SO3_NOx becomes positive in most areas of the GBA region. For SO3_VOC, the future scenario shows positive values throughout the study area for all years, but a decreasing trend. [ABSTRACT FROM AUTHOR]

Runoff variation is of significant importance to the current and future water availability of a region, particularly in arid regions, and plays a crucial role in economic and social development. The Tarim River Basin, spanning an area of approximately 102 × 104 km2, is the largest inland river basin in China. Due to the basin’s extremely dry climate, water shortage is the most critical natural factor restricting socio-economic development in the region. This study focuses on analyzing the historical and future runoff changes of the four headstreams (the Kaidu, Aksu, Yarkand, and Hotan rivers) in the Tarim River Basin with historical observations and multiple-model projections. The results indicate that the runoff of the Tarim’s four headstreams showed an increasing trend during 1957–2022, with a remarkable increment of 40.70 × 108 m3, or 18% in percentage. Rising temperatures and precipitation are the main reasons for the runoff’s increase. Higher temperature accelerates the melting of glaciers, leading to enhanced recharge of meltwater, while more precipitation also boosts the increase in river runoff. Based on the modelling results from the extended SWAT (Soil and Water Assessment Tool), the runoff in the Kaidu, Aksu, Yarkand, and Hotan rivers will remain at a high level in the near future (−2035), with an average increase of 3.2%–7.55%. In the mid 21st century (2036–2065), the runoff of the Yarkand and Hotan River originated from the Kunlun and Karakoram mountains is expected to continue increasing by around 6.25%–15.2%. Under SSP126, the tipping point of glacier melt runoff in the basin may happen by 2058, while under SSP370 and SSP585 scenarios, it may be around 2080. The timing of peak water aligns with projections in the mountainous Asia, but is later compared to the tropical Andes, Western Canada, and the Swiss Alps, whose peak water has already been reached. The results of this study can provide a scientific basis for the allocation and efficient utilization of water resources in the Tarim River Basin and offer valuable insights into the forthcoming runoff changes in mountainous regions.

Copyright of Journal of Xinyang Normal University Natural Science Edition is the property of Journal of Xinyang Normal University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The meteorological data of 38 meteorological stations in Xinjiang, Gansu and other regions in northwest China from 1971 to 2020 were used to analyze the temporal and spatial change characteristics of temperature by the Mann-Kendall test method, and the future change trend of temperature was evaluated by the Hurst index method, and the temporal and spatial changes of temperature in this region were compre)hensively analyzed according to the spatial changes. The results showed that overall, the temperature in the entire northwest region showed an increasing trend during the study period. From the perspective of future trend, the temperature in the northern part of Xinjiang also showed the opposite trend to the past, while other regions showed strong consistency with the past. According to the above results, in the 21st century, the temperature most area of Northwest China would continue to increase, only the Northern part of Xinjiang would become colder in the future. [ABSTRACT FROM AUTHOR]

Abstract Understanding the local needs and challenges is critical for technology adoption in the energy sector. However, it is still a big challenge for most ecosystem stakeholders. Furthermore, technology adoption theories have mainly focused on the technology itself, and the business ecosystem perspective has been neglected. Therefore, this paper proposes an ecosystem-driven business opportunity identification method, a systematic approach for ecosystem stakeholders to conduct business opportunity analysis and evaluation based on the CSTEP ecosystem analysis and evaluation method. This method includes four correlated steps: Step 1: Identify the five CSTEP dimensions of the business ecosystem; Step 2: Identify potential changes in the business ecosystem; Step 3: Identify future ecosystem trends and timeline; Step 4: Select business opportunities; and Step 5: Potential solution identification. A web-based tool called opportunity identifier is developed for implementing the proposed method. A case study of the electric vehicle (EV) home charging energy ecosystem in Denmark is applied and demonstrates the application of the proposed method and the implementation of the developed web-based tool. Three value propositions are identified in the case study: (1) EV users can have optimal EV charging cost and optimal CO2 emission consumption with the intelligent EV charging algorithms that consider electricity prices, tariffs, and CO2 emission; (2) DSOs can avoid grid overloads and postpone the grid upgrade by applying intelligent EV charging algorithms; (3) Independent aggregators can aggregate EVs and participate in the ancillary service market or provide Vehicle-to-Grid services by using intelligent EV charging algorithms. Moreover, three feasible decentralized EV charging strategies (Real Time Pricing, Time-of-Use Pricing, and Timed charging) are identified as the potential solutions targeting the first value proposition.

Groundwater is a critical resource for the development of any region. In Bhopal, groundwater is also used for various purposes, including domestic use and irrigation. Overexploitation due to increasing demand coupled with pollution raises concern about the sustainability of groundwater supplies in the future. This study aimed to analyze trends in groundwater parameters in Bhopal over 22 years using the Mann-Kendall (MK) and Modified Mann-Kendall (MMK) trend tests in MATLAB. The parameters SO42−, Ca2+, HCO3−, NO3−, and F− showed a decreasing trend, while the trends for pH were mixed. In contrast, the Na+ and Cl− levels significantly increased in both trend tests, suggesting the effects of various existing aquifer conditions and human activities whose long-term exposure may lead to harmful effects. The results showed that nitrate and electrical conductivity levels exceeded the permissible limits. The MMK method provided more accurate results than the traditional Mann-Kendall method. The findings of this study are valuable for policymakers and water resource managers. [ABSTRACT FROM AUTHOR]

Urbanization is a crucial indicator which reflects the socio-economic development of a country or region. The regions across the Taiwan Strait (TSR) have garnered attention worldwide as being representative of typical urbanization development along the southeastern coast. Currently, research in the TSR predominantly focuses on individual regions, with limited academic achievements comparing urbanization paths across the strait. In particular, the domain of comparative analysis of the spatiotemporal characteristics of urbanization dynamics in TSR by using long time series of nighttime light data remains largely underexplored. Therefore, this study focused on comparing the urbanization paths in the TSR and analyzing the spatiotemporal characteristics of urbanization by using the long-term nighttime light data from 1992 to 2020. Additionally, some methods such as Theil–Sen median trend analysis, Mann–Kendall significance test, Hurst exponent, spatial statistics, and time series were used to quantitatively analyze the spatial distribution patterns and temporal trends of nighttime lights in the TSR since 1992. The results were as follows: (1) From 1992 to 2020, the spatial distribution of nighttime light data in TSR exhibited significant spatial heterogeneity, with high-value areas mainly located in southeastern Fujian and northwestern Taiwan, while low-value areas were concentrated in Fujian's inland regions; (2) During this period, nighttime lighting data increased from 729,863 in 1992 to 2,729,052 in 2020, and the percentage of its high-value (40–063) increased from 2.59% in 1992 to 12.22% in 2020; (3) Comparison of nighttime light data across representative cities from Taiwan (Taipei, Hsinchu) and Fujian (Xiamen, Fuzhou) uncovered distinct growth patterns—while Taiwanese cities had a high initial brightness value (the lowest value in the last 30 years was 518,379.4), their growth was relatively slow (average growth rate of 17%); Fujian cities, on the other hand, started from lower initial brightness value (the lowest value in the last 30 years was 35,123.1), but displayed substantial growth vigor (average growth rate of 222%); (4) During the study period, the nighttime light data of the vast majority of cities in the TSR demonstrated a significant increasing trend, particularly in coastal areas and urban centers; (5) Predictions of future trend variation suggest that the significantly increasing trend of cities surrounding Taiwan's primary metropolitan areas will intensify, whereas metropolitan regions such as Keelung may witness a decline in future trend variations. However, only a mere 0.03% of the nighttime light data show a significant decreasing trend. Additionally, there are distinct differences in the urbanization development stages of the TSR. Fujian is currently undergoing rapid urbanization, while Taiwan's urbanization has entered a stable stage. The study reveals that factors such as geographical location, natural resources, transportation infrastructure, population size, and industrial structure collectively influence the urbanization characteristics of the TSR. This research bears substantial significance for deepening the comprehension of the patterns and processes of urbanization development in the TSR and provides valuable insights for urban construction and development across the strait. [ABSTRACT FROM AUTHOR]

Copyright of Detergent & Cosmetics is the property of Detergent & Cosmetics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the third largest river basin in the world, the Yangtze River basin in China has vegetation ecosystems in its plain, mountain, and alpine regions. Studying the change characteristics of the vegetation's net primary productivity (NPP) and its relationship with natural factors and human activities can aid with understanding, to a certain extent, the response of the ecosystem to global climate change. Based on a total of 21 years of MOD17A3 data products from 2000 to 2020, this paper analyzed the spatial variation characteristics and future trends of the NPP in this region by using the coefficient of variation (CV), trend analysis (β), and Hurst index (H) methods. Meanwhile, correlation analysis was used to explore the influence of natural factors and human activities on the NPP. The results show the following: (1) the total amount of the NPP in the Yangtze River Basin was relatively high, and the overall change trend is rising, while the inter-annual fluctuation is evident. The total amount of NPP ranges from 0.786 PgC (2000) to 1.024 PgC (2020), and the annual average was 0.932 PgC. This increase was mainly caused by the increase in the average NPP of forest land, cultivated land, and construction land. (2) The mean value of the NPP in the different regions of the Yangtze River Basin ranged from 0 (construction land) to 1902.89 gC/m2·a. The mean value of the NPP in the Yangtze River Basin was high in the south and low in the north, as well as high in the middle and low in the east and west. The main high-value areas were located in the Hengduan Mountains and the Yunnan-Guizhou Plateau. The coefficient of variation (CV) was 0.0009–0.9980, and the mean CV was only 0.1126. Regarding the future development trend, 77.90% and 22.10% of the regions showed an increase, 22.10% showed a decrease, and 75.25% showed an anti-sustainable state. (3) The effect of human activities on the NPP was generally negative, and the loss of NPP due to land use change in 2020 was around 9.85 TgC when compared with the same in 2000. (4) The rainfall and temperature in the Yangtze River basin both showed a non-significant increase, and the correlation coefficient between the NPP and rainfall was between −0.874 and 0.910. Furthermore, the correlation coefficient of the temperature ranged from −0.928 to 0.929, with a positive correlation overall and a negative correlation locally, and the NPP changes were more susceptible to the influence of temperature than rainfall. [ABSTRACT FROM AUTHOR]

Understanding the local needs and challenges is critical for technology adoption in the energy sector. However, it is still a big challenge for most ecosystem stakeholders. Furthermore, technology adoption theories have mainly focused on the technology itself, and the business ecosystem perspective has been neglected. Therefore, this paper proposes an ecosystem-driven business opportunity identification method, a systematic approach for ecosystem stakeholders to conduct business opportunity analysis and evaluation based on the CSTEP ecosystem analysis and evaluation method. This method includes four correlated steps: Step 1: Identify the five CSTEP dimensions of the business ecosystem; Step 2: Identify potential changes in the business ecosystem; Step 3: Identify future ecosystem trends and timeline; Step 4: Select business opportunities; and Step 5: Potential solution identification. A web-based tool called opportunity identifier is developed for implementing the proposed method. A case study of the electric vehicle (EV) home charging energy ecosystem in Denmark is applied and demonstrates the application of the proposed method and the implementation of the developed web-based tool. Three value propositions are identified in the case study: (1) EV users can have optimal EV charging cost and optimal CO2 emission consumption with the intelligent EV charging algorithms that consider electricity prices, tariffs, and CO2 emission; (2) DSOs can avoid grid overloads and postpone the grid upgrade by applying intelligent EV charging algorithms; (3) Independent aggregators can aggregate EVs and participate in the ancillary service market or provide Vehicle-to-Grid services by using intelligent EV charging algorithms. Moreover, three feasible decentralized EV charging strategies (Real Time Pricing, Time-of-Use Pricing, and Timed charging) are identified as the potential solutions targeting the first value proposition. [ABSTRACT FROM AUTHOR]

Purpose: This study intends to reveal the existing research stream and predict future research avenues for lean healthcare (LH). This paper analyzes the progress of LH research and identifies key trends, research gaps and future directions. By mapping the knowledge structure, the study offers insights into the effects of LH on healthcare efficiency, patient care and organizational performance., Design/methodology/approach: The review used the bibliometric approach, involving 319 journal articles retrieved from the Web of Science database. Two science mapping approaches (i.e. bibliographic coupling and co-word analysis) were performed to investigate the current knowledge structure and future research direction in LH., Findings: The current research trend in LH focuses on developing frameworks and strategic implementation by considering critical determinants and decision-making strategies. In the future, the research on LH will emphasize the holistic frameworks and efficient strategies for healthcare excellence, along with strategies to overcome barriers to its implementation., Research Limitations/implications: This study will benefit researchers and practitioners by advancing their understanding and applying LH principles., Originality/value: This study provides valuable practical implications for healthcare managers to navigate the complexities of lean implementation, optimize processes and drive sustainable improvements in the healthcare context., (© Emerald Publishing Limited.)

Study region: Dongting Lake Basin of China. Study focus: This study aimed to analyze the nonstationary characteristics and future trends of flood extremes in the Dongting Lake Basin. The spatiotemporal variations in the flood extremes that occurred over the past 60 years were explored using the trend-free prewhitening-MK (TFPW-MK) method, the nonstationary characteristics of flood extremes were detected using the Pettitt test, and the nonstationarity analysis was performed using the GAMLSS model. Furthermore, a combination of TFPW-MK and the Hurst exponent was employed to predict the future trends in flood extremes. New hydrological insights for the region: (1) Evident variations were observed in the flood extremes from most hydrometric stations. Among the 10 stations with a decreasing extreme trend, seven exhibited evident decreases. Such decreases probably result from the impact of water conservancy projects. Among the remaining six stations with an increasing extreme trend, two exhibited evident increases. Such increases probably result from the effect of highly extreme precipitation. (2) Flood extremes from most (9 of 16) stations showed nonstationarity. The lognormal distribution was the optimal distribution of extreme values for nonstationary stations, whereas the Gamma distribution was the optimal distribution of extreme values for stationary stations. Despite the preferable fitting efficiency of the GAMLSS model, its simulation performance for nonstationary stations that showed significant trends must be improved. (3) The flood extremes of the 14 stations will maintain existing trends in the future. The Xiangtan Station exhibited anti-persistence and might show a decreasing trend in the future, whereas Shimen Station did not show persistence.

Copyright of Journal of Shenzhen University Humanities & Social Sciences is the property of Journal of Shenzhen University (Humanities & Social Sciences) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Polarimetric Synthetic Aperture Radar (PolSAR) uses two-dimensional pulse compression to obtain high-resolution images containing polarimetric information. PolSAR has been widely used in military reconnaissance, topographic mapping, environmental and natural disaster monitoring, marine ship detection, and related fields. Addressing the problems associated with sea-clutter modelling and parameter estimation, slow and small target detection, dense target detection, as well as other issues, still remains a challenge in PolSAR ship detection. In this paper, four main classes for PolSAR ship detection are summarized: target polarimetric feature detection, slow and small target detection, ship wake detection, and deep learning detection. In addition, the possible solutions to existing problems in each class are given, and their future development trends are predicted, which can provide some valuable suggestions for interested researchers.

Land use is closely related to the sustainability of ecological development. This paper employed a patch-generating land use simulation (PLUS) model for the multi-scenario simulation of urban agglomerations. In addition, mathematical analysis methods such as Theil-Sen Median trend analysis, R/S analysis, Getis-Ord Gi* index and unary linear regression were used to study the temporal and spatial evolution characteristics of net primary productivity (NPP) for the impact of land use changes on NPP in urban agglomerations from 2000 to 2020 and to forecast the future trend of NPP. The results indicate that urban expansion is obvious in the baseline scenario and in the ecological protection scenario. In the scenario of cropland protection, the urban expansion is consistent with the land use plan of the government for 2035. The NPP in Beijing decreased gradually from northwest to southeast. The hot spot areas are concentrated in the densely forested areas in the mountainous areas of northwest. The cold spot areas are mainly concentrated in the periphery of urban areas and water areas. The NPP will continue to increase in forest and other areas under protection and remain stable in impervious surfaces. The NPP of Beijing showed a strong improvement trend and this trend will continue with the right ecological management and urban planning of the government. The study of land use in urban agglomeration and the development trend of vegetation NPP in the future can help policymakers rationally manage future land use dynamics and maintain the sustainable development of urban regional ecosystems. [ABSTRACT FROM AUTHOR]

Based on the humidity index, using the daily climate data of 113 meteorological stations in and adjacent the Yellow River Basin(YRB) from 1960 to 2020, climate trend rate, Morlet wavelet, simple correlation analysis, and Hurst index were used to analysis the spatiotemporal characteristics of dry-wet condition in the YRB in the latest 61 years and to predict the future trend of dry-wet changes in the YRB, to provide scientific basis for drought prevention and mitigation and rational utilization of climate resources in the YRB. The results showed that: (1) among all the geographic zones, the annual and seasonal humidity index in the YRB was high in the southeastern YRB and low in the northwestern YRB. Spatially, the climate of the annual, spring and autumn in the YRB was mainly dry, the proportions of stations with significant decrease of humidity index of the total stations were 5.31%, 7.96% and 6.19%, respectively. The climate of summer and winter was mainly wet, the proportions of stations with significant increase of humidity index were 10.62% and 13.27%, respectively. (2) As for the interannual change, the annual and seasonal humidity index of the YRB from 1960 to 2020 showed no significant change. Semi-humid, semi-drought, semi-humid, semi-humid, semi-drought were found in entire year, spring, summer, autumn, and winter, respectively. The annual and seasonal humidity index of the YRB had periodic oscillation characteristics at multiple time scales, and the first main period was 3 years, 26 years, 14 years, 3 years and 15 years, respectively. (3) The change of humidity index in the YRB was extremely significantly positively correlated with precipitation and relative humidity. There was a extremely significant negative correlation between sunshine duration and humidity index. Precipitation, relative humidity, and sunshine duration were the main factors affecting the change of humidity index in the YRB. (4) The Hurst index of annual and seasonal humidity index in the YRB were larger than 0.50, indicating that the climate of annual, spring, and autumn of the YRB would continue to be drying, the summer and winter climate would continue to be wetting. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) is an all-weather and all-time imaging radar with high resolution, which is widely used for enemy reconnaissance to provide timely and accurate intelligence for taking decisions during wars. It has become a hot issue in the contemporary electronic warfare to suppress and disorder the reconnaissance imaging of SAR equipment for protecting high-value targets and important strategic areas. This study discusses the development and future trend of SAR jamming techniques. First, the history of development of SAR jamming techniques is discussed and explained in detail. Then, the advantages and disadvantages of the typical SAR jamming models are comparatively analyzed together with simulation experiments. Finally, the current defects of the SAR jamming techniques are summarized and the future trend of the SAR jamming techniques is also pointed out, providing some reference for experts and scholars.

Global changes have significant impacts on changes in ecosystem services (ESs) and their interrelationships. The Yellow River Basin (YRB) is an important ecological barrier in China, and it is important for ecological decision-making and management in the basin by quantitatively assessing the trends and drivers of ESs and analyzing the trade-offs and synergies among them. In this study, the food production model, InVEST model, and RUSLE model were used to quantitatively assess three ESs (food production, water yield, and soil conservation) in the YRB from 2000 to 2018. The spatio-temporal trends and future trends were quantified using Theil-Sen Median trend analysis and Hurst exponent. Correlation analysis was used to determine the main influencing factors of the spatio-temporal changes of ESs and analyze the trade-offs and synergies among ESs. The research results show that during 2000–2018, in terms of spatial distribution, food production in the YRB gradually decreases from east to west, water yield gradually decreases from south to north, and the dominant areas of soil conservation are mainly distributed in the plateau areas in the upper and middle reaches of the basin; in terms of temporal changes, food production shows a continuous increase, while water yield and soil conservation generally show an increasing trend in fluctuation. Excluding areas with no significant change and random change, food production will mainly show improvement in the future, and water yield and soil conservation will show some degree of decline in the future. Food production is mainly influenced by the type of land use, water yield is mainly influenced by precipitation, and soil conservation is influenced by a combination of slope and land use type. ESs in the YRB were generally dominated by synergy but locally dominated by trade-offs. Our results will provide reference for policymakers in ecological construction, and analyze trade-offs and synergies of regional ESs in a holistic and local context based on the assessment results and change trends of ESs, thus providing a basis for formulating scientific and reasonable ecological protection policies, and will promote the high-quality development of the YRB.

Based on literature measurement and knowledge graph, this paper systematically sorted out and analyzed 2 563 articles on theme of 􀆳natural resources􀆳 published in China Population, Resources and Environment from 1991 to 2021. It was found that the amount of published articles experienced three rising periods and one falling period, research popularity showed an upward trend, and the pro⁃ portion of published articles tended to be stable. From a longitudinal perspective, there existed research hotspots such as resources and sustainable development, natural resources utilization and protection, 􀆳resource curse􀆳, resource⁃based cities, energy resources and car⁃ bon emissions. Current research hotspots are mainly distributed in water resources, land resources, energy resources and carbon emis⁃ sions. In the early stage, the research tended to focus on macro, qualitative and normative analysis, with topics mainly on resource poli⁃ cies and strategies under the concept of sustainable development. With the gradual deepening of the research, micro, quantitative and empirical analysis took the leading position, with conclusions becoming more targeted. In terms of content, the published articles show four salient features: ① The articles focus on the forefront of international sustainable development and natural resources; ② Most of the published articles carry out analysis integrating theories and methods of economics, management, law, sociology, security science and other disciplines; ③ The articles pay attention to theoretical innovation, the use of new methods and the production of new conclu⁃ sions; ④ The articles focus on solving practical problems, and the subject of each article is a practical scientific proposition. It is sug⁃ gested that future improvement needs to pay attention to the following aspects: focus on the forefront of international sustainable devel⁃ opment, and explore new research fields based on the important goal of sustainable use of global natural resources; closely follow the na⁃ tional resource policies, and accurately target and serve the national strategic needs for major resources; focus on comprehensive re⁃ search results on resource issues; focus on the combination of natural and economic laws of various resources and the systematic correla⁃ tion mechanism between them, the asset of various natural resources under the market economy system, and other related research re⁃ sults. It is up to the journal to discover and even actively explore, so as to present more high⁃quality research results to the academic community. [ABSTRACT FROM AUTHOR]

The objective of this study was to reconstruct the long-term drought and flood time series to analyze their changing characteristics in Hengshui City of North China. Disaster records of the city for 550 years (1649–2018) were collected from different sources and sorted to reconstruct the sequences of droughts and floods. Advanced statistical methods for climate data analysis, including the Mann-Kendall test, Sen's slope estimator, Morlet wavelet analysis, mutation point tests, and Rescaled range analysis, were used to analyze the historical changes and predict the direction of possible future changes in droughts and floods. The results showed an increased frequency of droughts and a decreased frequency of floods in Hengshui City, making drought occurrence significantly higher than flood occurrence in the twentieth century. The solar activity cycle of 11-year and its multiple showed the association with 10–15 years and 25 years cycles of droughts and floods, respectively. The mutation points in drought and flood sequences during 1559–1568 and 1909–1918 showed insignificant downward (upward) and upward (downward) trends, respectively, in the drought (flood) subsequence before and after the mutation point. The rescaled range analysis revealed an insignificant decreasing trend in droughts and the continuation of the present decreasing trend in floods in the forthcoming years. [ABSTRACT FROM AUTHOR]

The energy internet is the fulcrum of the new energy revolution,which will vigorously promote the high-quality and sustainable development of China’s energy industry.In order to comprehensively analyze the development of energy internet of China from the national level,the development background of energy internet was firstly reviewed,and then the connotation and extension was analyzed.On this basis,the index system of energy internet development was constructed from six aspects:policy,industry,technology,innovation,construction and public ecology.By means of literature search and analysis,official website crawler and authoritative document search,the basic status of energy internet development in China was analyzed.It was pointed out that under the multi-sectoral and multi-level policy guarantee,energy internet of China has shown a good development trend as a whole,with the healthy and prosperous development of industry,construction,technology and innovation.

Copyright of China Surfactant Detergent & Cosmetics (1001-1803) is the property of China Surfactant Detergent & Cosmetics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High voltage circuit breakers (HVCBs) play a critical role on providing the desired reliability, and resiliency in power systems. In order to extend their lifetime and predict the failures, various maintenance policies could be applied on these critical components. Amongst these strategies, condition-based maintenance (CBM) provides a satisfactory agreement with future smart environment. This paper aims to provide an insight into the relevant developments in this subject and to explore the viable visions compatible with future research stream. Accordingly, three directions, i.e., diagnostic signals, intelligent modelling and using monitoring data in asset management have been addressed in this paper. It presents challenges dealing with real-time assessment of the diagnostic signals relating to measurements, and analyses. Subsequently, the issues associated with using artificial intelligent (AI) and Machine learning for providing intelligent algorithms have been discussed. Finally, the connection between the monitoring data and the asset management approach is investigated. The latter is looking for the subjects including remaining lifetime estimation, prioritization, and health index definitions. This paper has attempted to make a bridge from past to future research trends in the failure diagnosis of HVCBs. [ABSTRACT FROM AUTHOR]

The increasingly meagre copper ore resources constitute one of the decisive factors influencing the price of this commodity. The demand for copper has been showing an accelerating trend since the Covid pandemic broke out. It is thereby imperative to estimate the future price movement of this material. The article focuses on a daily prediction of the forthcoming change in prices of copper on the commodity market. The research data were gathered from day-to-day closing historical prices of copper from commodity stock COMEX converted to a time series. The price is expressed in US Dollars per pound. The data were processed using artificial intelligence, recurrent neural networks, including the Long Short Term Memory layer. Neural networks have a great potential to predict this type of time series. The results show that the volatility in copper price during the monitored period was low or close to zero. We may thereby argue that neural networks foresee the first three months more accurately than the rest of the examined period. Neural structures anticipate copper prices from 4.5 to 4.6 USD to the end of the period in question. Low volatility that would last longer than one year would cut down speculators' profits to a minimum (lower risk). On the other hand, this situation would bring about balance which the purchasing companies avidly seek for. However, the presented article is solely confined to a limited number of variables to work with, disregarding other decisive criteria. Although the very high performance of the experimental prediction model, there is always space for improvement - e.g. effectively combining traditional methods with advanced techniques of artificial intelligence. [ABSTRACT FROM AUTHOR]

With the emerging of new media and hybrid publishing, the huge increase in the number of Chinese books published, the rise in the unit price of books, the readers' diversified demand for books and the change of library space, it is required that the library designed the development strategy of transformation in the construction of Chinese collections, especially with the problems exposed in the use of Chinese books during the epidemic period of COVID-19. The library should recognize the direction and clarify the ideas in order to better promote the transformation of library services. We should adapt to the situation, speed up the construction of the hybrid collection development system of printed and electronic books. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)