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Abstract Historians and paleoclimatologists have long studied the connection between ecoclimatic changes and empire growth, transformation, and decline, but striking cases remain rare. Here, we introduce a tree-ring chronology from southern China to reconstruct changes in April-to-November water balance of the middle reaches of the Yangtze River over the last 464 years. The reconstruction supports a quantitative assessment of the spatiotemporal structure of the late Ming megadrought and potential effects on subsequent dynastic transitions. Our results indicate that the late Ming megadrought from 1625 – 1644 CE occurred in both the northern and southern parts of the East Asian monsoon region in China. However, variations in the onset, duration, and magnitude of this event differ between regions. The combination of factors such as Pacific sea surface temperature anomalies, weakened solar activity, and large-scale volcanic eruptions may have contributed to the occurrence of the late Ming megadrought. These factors are also identified as key drivers of interannual to decadal fluctuations in drought in the middle reaches of the Yangtze River. Our reconstruction provides an historical context for the development of adaptive measures to mitigate future drought impacts in the region.

Abstract Background Nonalcoholic fatty liver disease (NAFLD) is gradually becoming a huge threat to public health. With complex working characteristics, female nurses had been found with high risk of NAFLD. To develop and validate a prediction model to predict the prevalence of NAFLD based on demographic characteristics, work situation, daily lifestyle and laboratory tests in female nurses. Methods This study was a part of the Chinese Nurse Cohort Study (The National Nurse Health Study, NNHS), and data were extracted from the first-year follow data collected from 1st June to 1st September 2021 by questionnaires and physical examination records in a comprehensive tertiary hospital. The questionnaires included demographic characteristics, work situation and daily lifestyle. Logistic regression and a nomogram were used to develop and validate the prediction model. Results A total of 824 female nurses were included in this study. Living situation, smoking history, monthly night shift, daily sleep time, ALT/AST, FBG, TG, HDL-C, UA, BMI, TBil and Ca were independent risk factors for NAFLD occurance. A prediction model for predicting the prevalence of NAFLD among female nurses was developed and verified in this study. Conclusion Living situation, smoking history, monthly night shift, daily sleep time, ALT/AST, FBG, TG, UA, BMI and Ca were independent predictors, while HDL-C and Tbil were independent protective indicators of NAFLD occurance. The prediction model and nomogram could be applied to predict the prevalence of NAFLD among female nurses, which could be used in health improvement. Trial registration This study was a part of the Chinese Nurse Cohort Study (The National Nurse Health Study, NNHS), which was a ambispective cohort study contained past data and registered at Clinicaltrials.gov ( https://clinicaltrials.gov/ct2/show/NCT04572347 ) and the China Cohort Consortium ( http://chinacohort.bjmu.edu.cn/project/102/ ).

Study Region: The Jialing River, distinguished as the largest tributary of the Yangtze River by watershed area Study Focus: In the context of a major drought in the Yangtze River Basin in 2022, this study examines the extent of low discharge in its largest tributary, the Jialing River, in that year from the long-term perspective of tree-ring, then explores possible relationships between discharge changes and large-scale ocean-atmosphere circulation, and finally identifies possible future discharge trends and the risk of extreme high or low discharge based on CMIP6 multi-model mean discharge data. New Hydrological Insights for the Region: Over the past 301 years, the low discharge value in 2022 exceeded the range of normal runoff fluctuations. Simultaneously, the average runoff values for the recent years, 2019–2022, reached historical lows. These discharge variations are primarily influenced by the Tropical Pacific Index and the North Atlantic Oscillation. Climate model projections indicate that the risk of the upper reaches of the Jialing River regularly experiencing extreme low discharge (similar to 2022) is trending downward, with a probability of ∼15% per year by 2100, while the risk of experiencing extreme high discharge is trending upward, with a probability of ∼28% per year by 2100.

Massive computational resources are required by a booming number of artificial intelligence (AI) services in the communication network of the smart grid. To alleviate the computational pressure on data centers, edge computing first network (ECFN) can serve as an effective solution to realize distributed model training based on data parallelism for AI services in smart grid. Due to AI services with diversified types, an edge data center has a changing workload in different time periods. Selfish edge data centers from different edge suppliers are reluctant to share their computing resources without a rule for fair competition. AI services-oriented dynamic computational resource scheduling of edge data centers affects both the economic profit of AI service providers and computational resource utilization. This letter mainly discusses the partition and distribution of AI data based on distributed model training and dynamic computational resource scheduling problems among multiple edge data centers for AI services. To this end, a mixed integer linear programming (MILP) model and a Deep Reinforcement Learning (DRL)-based algorithm are proposed. Simulation results show that the proposed DRL-based algorithm outperforms the benchmark in terms of profit of AI service provider, backlog of distributed model training tasks, running time and multi-objective optimization.

The construction of ecological livability plays a crucial role in achieving ecological civilization. During economic development, conflicts between urban populations, resources, and the environment have become increasingly prominent. Although China's efforts in building ecological livability have made certain achievements, they are still in the early stages, making research in this area very necessary. This study aims to establish an indicator system for the level of ecological livability construction from four aspects: ecology, society, residents' living conditions, and economy. Based on panel data from 2008 to 2021, the entropy-TOPSIS model was used to evaluate the level of ecological livability construction in Zhangjiajie City. Additionally, the coupling coordination degree model was employed to study the correlation and coordination among different indicators within the system. Furthermore, the obstacle degree model was introduced to explore the main factors affecting the improvement of ecological livability construction levels. The results show that, over the fourteen-year period, the proximity of Zhangjiajie City's ecological livability construction level decreased from 0.2712 in 2008 to 0.2547 in 2010, then rose to 0.7686 in 2021, reaching a medium coordination level, with the constraining effects among the ecological livability systems weakening. The average wage of employees, the proportion of social security and employment expenditure to fiscal expenditure, the per capita total postal and telecommunications business volume, the per capita number of public library collections, and the proportion of education expenditure to fiscal expenditure have become the main influencing factors of Zhangjiajie City's ecological livability construction level.

Summary: Purpose: Ankle pump exercises (APE) have been widely used in clinical practice. However, best practices for APE have not been established. Recognize the most effective frequency of APE for improving lower extremity hemodynamics and establish recommendations in clinical practice. Methods: Therefore, a systematic review and network meta-analysis (NMA) was performed according to PRISMA-NMA. Six English databases (Pubmed, Medline, CINAHL, Embase, the Cochrane library and ProQuest) and four Chinese databases (CNKI, Wanfang, VIP and Sinomed) were searched. Randomized controlled trials (RCTs) and quasi-experimental studies investigating the effects of different frequencies of APE on lower limb hemodynamics published before July 2022 were included. The reference list was also searched. Seven studies (one RCTs and six quasi-experimental studies) were included in the systematic review and five studies (one RCTs and four quasi-experimental studies) were included in the NMA. The risk of bias was assessed using the Cochrane and Joanna Briggs Institute tools. The NMA was performed using the R software (version 4.2.1) and OpenBUGS (version 3.2.3). Results: The results of the NMA showed that a frequency of every 3–4 s the most effective in improving lower extremity hemodynamics (P =.85), followed by every 1–2 s (P = .81), every 5–6 s (P=.32) and less than every 10 s (P =.02). Subgroup analysis failed to find a difference between healthy participants and those with unilateral total hip arthroplasty or fracture (MD = −0.23, 95% CI-5.92 to 4.61). Conclusions: Consequencely, for adult patients, with or without lower extremity disease, a frequency of every 3–4 s can be recommended as the optimal frequency of APE in clinical care practice. Registered number on PROSPERO: CRD42022349365. https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=349365.

Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to understand the current ecological status of the Ferghana Basin and to analyze the vegetation changes and drivers, with a view to providing a scientific basis for regional ecological and environmental management and planning. Based on GIMMS NDVI3g and meteorological data, the spatial and temporal evolution characteristics of NDVI were analyzed from multiple perspectives with the help of linear trend and Mann–Kendall (MK) test methods using arcgis and the R language spatial analysis module, combined with partial correlation coefficients and residual analysis methods to analyze the impacts of climate change and human activities on the regional vegetation cover of the Ferghana Basin from 1982 to 2015. NDVI driving forces. The results showed the following: (1) The growing season of vegetation NDVI in the Ferghana Basin showed an increasing trend in the 34-year period, with an increase rate of 0.0044/10a, and the spatial distribution was significantly different, which was high in the central part of the country and low in the northern and southern parts of the country. (2) Temperature and precipitation simultaneously co-influenced the vegetation NDVI growth season, with most of the temperature and precipitation contributing in the spring, most of the temperature in the summer being negatively phased and the precipitation positively correlated, and most of the temperature and precipitation in the fall inhibiting vegetation NDVI growth. (3) The combined effect of climate change and human activities was the main reason for the overall rapid increase and great spatial variations in vegetation NDVI in China, and the spatial distribution of drivers, namely human activities and climate change, contributed 44.6% to vegetation NDVI in the growing season. The contribution of climate change and human activities to vegetation NDVI in the Ferghana Basin was 62.32% and 93.29%, respectively. The study suggests that more attention should be paid to the role of human activities and climate change in vegetation restoration to inform ecosystem management and green development.

Abstract Understanding changes in water availability is critical for Central Asia; however, long streamflow reconstructions extending beyond the period of instrumental gauge measurements are largely missing. Here, we present a 785-year-long streamflow reconstruction from spruce tree rings from the Tien Shan Mountains. Although an absolute causal relationship can not be established, relatively high streamflow rates coincided roughly with the period of Mongol expansion from 1225 to 1260 CE and the rise of the Timurid Empire from 1361 to 1400 CE. Since overall wetter conditions were further found during the Zunghar Khanate period 1693–1705 CE, we argue that phases of streamflow surplus likely promoted oasis and grassland productivity, which was an important factor for the rise of inner Eurasian steppe empires. Moreover, we suggest that the streamflow variation might be critical for plague outbreaks in Central Asia, and propose several explanations for possible links with Europe’s repeated Black Death pandemics. We demonstrate that 20th-century low streamflow is unprecedented in the past eight centuries and exacerbated the Aral Sea crisis, which is one of the most staggering ecological disasters of the twentieth century.

Eastern Xinjiang, as a typical extremely arid area, exhibits a high sensitivity to climate change. Gaining a comprehensive understanding of the climatic changes in this region, along with their driving mechanisms, and comparing these with the broader trend of “warming and humidifying” in the Northwest can provide a scientific foundation for adapting to and addressing climate change. Based on a study of precipitation and temperature data from seven meteorological stations in Eastern Xinjiang from 1960 to 2022, the following findings were observed: (1) The climate of eastern Xinjiang is generally characterized by a warming and humidifying trend, with the rates of mean annual temperature and total annual precipitation being 0.39 °C/10 a and 3.32 mm/10 a. The eastern part of Xinjiang has less precipitation, with a lower growth rate than that of the neighboring regions, and higher temperatures, with a higher growth rate than that of the neighboring regions. (2) The first principal component of precipitation explains 47.85% of the variation in total precipitation, with a significant upward trend (p < 0.05) and an abrupt change in the late 1970s. It contains strong signals of regional precipitation, temperature, and dry and wet changes. (3) The increase in the first principal component of annual precipitation in eastern Xinjiang is mainly related to the warming of SSTs in the Indian Ocean and the central-eastern part of the tropical southern Pacific Ocean as well as the weakening of the Asian monsoon.

Snow is an important source of freshwater in the Tianshan Mountains of Central Asia. This study established 18 tree ring width chronologies and compound chronologies and analyzed the effects of snow depth, measured both by remote sensing and at meteorological stations, on the radial growth of spruce trees. The results showed that the established standard chronology of tree ring width is suitable for the analysis of tree ring climatology. The correlation coefficient of the ring width index (RWI) and the remote sensing snow depth was greater than that of the meteorological station snow depth. For the remote sensing snow depth, the correlation coefficients were greater in the winter and spring months compare to other periods, while the correlation coefficients of the meteorological stations were greater only in the winter. The nonlinear method (BRNN) showed good fitting in the reconstruction of the historical snow depth. The reconstructed snow depth exhibited a decreasing trend in the Bharakonu Mountains (BM), Narathi Mountains (NM), and Halke mountains (KM) sub-regions in the overall reconstructed period; however, the trends were inconsistent in both the historical and the observed periods, indicating the importance of reconstructing snow depth in the Tianshan Mountains.

Mid-to-high latitudes of Asia and its adjacent Arctic area are some of the most sensitive regions to climate warming in Eurasia, but spatio-temporal temperature variation over this region is still limited by a lack of long-term temperature records. Here, June-July temperature reconstructions are developed from a Larix sibirica composite chronology that presents a stable positive linkage with large-scale recorded temperatures and spans 1190–2019 CE for the source area of the Northern Asian great river Basins, northern Mongolian Plateau, Inner Asia. The warmest reconstructed period and low summer sea ice extent in the Arctic Ocean over the past 830 years was estimated to occur in the late twentieth century (1990s–present), with a mean temperature (15.2°C) higher than the long-term mean (13.9°C) of 1190–2019 CE, which is linked with the rapid increase in global temperature. A relationship also exists between the reconstructed temperature and the AMO index, suggesting that the atmospheric patterns over the Arctic and North Atlantic Oceans influence the temperature variations of northern Mongolian Plateau. In addition, we also propose that the warm climate promoted high vegetation productivity and favored the formation of power of the nomadic tribes in the Mongolian Plateau, such as the warm periods 1210s–1250s and 1400s–1430s. Our temperature reconstruction provides us with an opportunity to understand the regional effects of climate warming from multiple perspectives.

Introduction The physical and mental health of nurses may significantly impact the entire medical care group and directly affect the quality of medical services. Due to the intense emotional involvement and often problematic working conditions that characterise their profession, nurses appear to be especially susceptible to a complex set of stressors with repercussions to their health. Several landmark studies of nurses have provided an abundance of evidence on risk factors that influence the health status of nurses. However, few studies have investigated the health status of nurses who work in high-intensity work environments in China. The National Nurse Health Study (NNHS) objective is to build an ambispective cohort to gather web-based information on early-life events, daily habits, occupational and environmental risk factors, and health outcomes of a specific subset of healthcare professionals of Chinese nurses.Methods and analysis NNHS, which was developed at a tertiary hospital in Beijing, China, is a research initiative that enrolls registered nurses working at Peking University Third Hospital. A web-based self-administered system was designed to collect health-related data and link them with previous physical examination data. During the study period, participants with signed informed consent will be invited to annually repeat a similar procedure.Ethics and dissemination The NNHS research protocol was approved by the Institutional Ethics Committee and provides promising data that contribute to the understanding of pathophysiological links between early-life events, body composition, gut microbiota, and inflammatory and metabolic risk profiles. Moreover, the combination of a user-friendly tool with the innovative purposes of the NNHS offers a remarkable resource to test hypotheses about mechanisms of diseases, including work stress, and further plan preventive programmes in public health.Trial registration number The study was registered on Clinicaltrials.gov (https://clinicaltrials.gov/ct2/show/NCT04572347) and the China Cohort Consortium (http://chinacohort.bjmu.edu.cn/project/102/).

In the wireless Internet of Things (IoT) networks with resource-constrained devices, fog computing has been introduced to deal with the computation-intensive applications at the edges of the networks. While fog computing decreases the computation delay and fronthaul traffic data, it also brings the severe challenge on complex resource allocation of the available computation and communication resources under the stringent quality of service (QoS) requirements. In this paper, we investigate the problem of tasks scheduling and heterogeneous resource allocation for multiple devices in the wireless IoT networks. The IoT devices that collect a massive amount of data need to make proper offloading decision to transfer the data to the fog computing nodes (FNs). Moreover, to support a massive number of device connections and transfer a huge amount of data with low latency and limited resource, we consider the deployment of non-orthogonal multiple access (NOMA) in IoT networks, which enables multiple IoT devices to simultaneously transmit data to the same FN at the same time, frequency, and code domain. We jointly optimize the allocation of resource blocks and transmit power of multiple IoT devices, subject to the respective QoS requirements. Furthermore, the optimization problem is formulated as a mixed-integer nonlinear programming problem to minimize the system energy consumption. Since it is an NP-hard problem, we introduce an improved genetic algorithm (IGA) to solve it. The simulation results show that the proposed scheme achieves good performance in throughput, delay, outage probability, and energy consumption.

Unmanned aerial vehicles (UAVs) have the advantages of flexibility, low cost, and good communication channel gain. In recent years, the inspection of power grid systems supported by UAVs has been widely used. However, due to the constraint of wireless channels and UAVs, it is impossible to transmit video content to the surveillance center. To solve this problem, in this study, a new mobile edge computing (MEC) technology-enabled power line inspection scheme for smart grid networks was designed. Within this scheme, a double-layer MEC architecture is proposed. In the upper-level layer, several UAVs installed with MEC equipment can locally process inspection videos with higher propriety. At the same time, the remaining tasks with lower priority are performed by the terrestrial base stations. In addition, a cost minimization problem is proposed and solved by the alternating optimization algorithm. The simulation results show that the proposed algorithm can significantly reduce the energy consumption of the system.

Via processing the computation intensive applications (apps) at the network edge, mobile edge computing (MEC) becomes a promising technology to enhance the ability of the user equipments (UEs). Most existing works usually focus on whether to offload or where to offload the apps under the premise that sufficient resources are owned by the network edge. However, the demand heterogeneity of UEs and the limitation of resources are usually failed to be considered. Since the limited resources may constrain the number of accessed UEs, how the MEC service providers (SPs) choose the UEs to serve while ensuring UEs' Quality of Service (QoS) is a key issue. Under this context, in this paper, we study the matching problem between the MEC SPs and the UEs in a multi-MEC and multi-UE scenario. Within this scenario, MEC SPs are equipped with limited wireless and computational resources. Auction theory is utilized to model the matching relationship between MEC SPs and UEs as the commodity trading. With this trading, UEs can obtain MEC service from SPs, when they successfully purchase the combinational resources (including computational and wireless resources) from SPs. To complete the auction process, a multi-round-sealed sequential combinatorial auction mechanism is proposed. The properties of the auction are proved and various simulation results are done to show that the proposed approach has better system performance compared with the existing algorithms.

Hydroclimatic conditions and related water resources change in the Tibetan Plateau is one of the main concerns for future sustainable development in China. This study presents a 254-year precipitation reconstruction from August of the previous year to June of the current year for the northeastern Tibetan Plateau based on tree-ring width data of tree-ring cores of Picea crassifolia from three sampling sites. The precipitation reconstruction explained 51.4% of the variance in instrumental precipitation during the calibration period 1958–2013. Dry periods with precipitation below the 254-year average value occurred during 1848–1865, 1873–1887, 1898–1923, and 1989–2003, and wet periods (precipitation above the mean) occurred during 1769–1785, 1798–1833, 1924–1938, 1957–1968, and 2004–2013. Spatial correlation analyses with the precipitation gridded dataset showed that our reconstruction contains some strong regional-scale precipitation signals for the upper Yellow River Basin. Our precipitation reconstruction also agreed in general with other dendroclimatic precipitation reconstructions from surrounding regions. In addition, reconstructed precipitation changes were consistent with the streamflow variation of the Yellow River.

Given the reported increasing trends in high Asian streamflow and rapidly increasing water demand in the Indian subcontinent, it is necessary to understand the long‐term changes and mechanisms of snow- and glacier-melt-driven streamflow in this area. Thus, we have developed a June–July streamflow reconstruction for the upper Indus River watershed located in northern Pakistan. This reconstruction used a temperature-sensitive tree-ring width chronology of Pinus wallichiana , and explained 40.9% of the actual June–July streamflow variance during the common period 1970–2008. The high level of streamflow (1990–2017) exceeds that of any other time and is concurrent with the impact of recent climate warming that has resulted in accelerated glacier retreats across high Asia. The streamflow reconstruction indicated a pronounced reduction in streamflow in the upper Indus River basin during solar minima (Maunder, Dalton, and Damon). Shorter periods (years) of low streamflow in the reconstruction corresponded to major volcanic eruptions. Extreme low and high streamflows were also linked with sea surface temperature. The streamflow reconstruction also provides a long-term context for recent high Asian streamflow variability resulting from seasonal snow and glaciers that is critically needed for water resources management and assessment.

Our understanding of Central Asian historical streamflow variability is still limited because of short instrumental hydrologcial records. Based on tree-ring cores collected from three sampling sites in Kaiken River basin near Tien Shan, a regional tree-ring width chronology were developed. The correlation analysis showed that the runoff of Kaiken River from previous August to current June was significantly correlated with the regional chronology, and the high correlation coefficient was 0.661 (P < 0.01). Based on the regional chronology, the August-June runoff of Kaiken River has been reconstructed over the past 422 year, and it accounted for 43.7% of actual runoff variance during the common period 1983–2013. The reconstruction model is reliable, and the trend of observed and reconstructed data is relatively consistent. The results of multi-taper spectral analysis for the runoff reconstruction indicated some remarkable cycles for the past 422 years; the 11.5-year cycles correspond to the solar cycle and is found widely in runoff reconstructions in Central Asia. This may imply a solar influence on the hydroclimate variations of Tien Shan. The runoff reconstruction of Kaiken River compares well with runoff reconstructions the Urumqi River and Manas River, and implies that there is a common driving factor for the runoff in central Tien Shan, China. The analysis of linkages between climate variation and the runoff reconstruction of Kaiken River shows that there is a relationship between extremes in runoff variation and abnormal atmospheric circulations. Our 422-year steamflow reconstruction provides long-term perspective on current and 20th century hydrological events in central Tien Shan, is useful for aids sustainable water management and addresses regional climate change challenges.

Background: The aim of this study was to clarify the relationship among Rac1 expression and activation, oxidative stress and β cell dysfunction in obesity. Methods: In vivo, serum levels of glucose, insulin, oxidative stress markers and Rac1 expression were compared between ob/ob mice and C57BL/6J controls. Then, these variables were rechecked after the administration of the specific Rac1 inhibitor-NSC23766 in ob/ob mice. In vitro, NIT-1 β cells were cultured in a hyperglycemic and/or hyperlipidemic state with or without NSC23766, and the differences of Rac1 expression and translocation, NADPH oxidase(Nox) enzyme activity, reactive oxygen species (ROS) and insulin mRNA were observed. Results: ob/ob mice displayed abnormal glycometabolism, oxidative stress and excessive expression of Rac1 in the pancreas. NSC23766 injection inhibited the expression of Rac1 in the pancreas, along with amelioration of oxidative stress and glycometabolism in obese mice. Under hyperglycemic and/or hyperlipidemic conditions, Rac1 translocated to the cellular membrane, induced activation of the NADPH oxidase enzyme and oxidative stress, and simultaneously reduced the insulin mRNA expression in NIT-1 β cells. Inhibiting Rac1 activity could alleviate oxidative stress and meliorate the decline of insulin mRNA in β cells. Conclusions: Rac1 might contribute to oxidative stress systemically and locally in the pancreas in obesity. The excessive activation and expression of Rac1 in obesity were associated with β cell dysfunction through ROS production.