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We adopted a spectral clustering algorithm to divide the document co-citation network of 1,776 papers in the field of Lancang-Mekong water, and 14 clusters were identified. For each cluster, the top-cited references construct the knowledge base, and the most-coverage cities are taken as the research frontier. Three indicators, namely betweenness centrality, citation burstness strength, and Sigma, were used to identify the research outputs with pioneering and transformative value. The changes in the research topics and hotspots are closely related to the planning, construction, and operation progress of hydropower engineering, that affected by the gaming results of all parties. The 2009–2010 is an important time boundary, with the original research hotspots including the impact of upstream reservoirs on the hydrological regime and sediment (Clu#3) and arsenic contamination of groundwater in the Lower Mekong (Clu#4) that obtained periodical achievements and reached consensus to some extent around 2008, and the new research boom turns to the Tonle Sap Lake and flood pulse (Clu#2) in short-term characterized literatures with the highest burstness strength mainly concentrated around 2012.

Dune field landscape patterns serve as an important signs of aeolian processes, such as wind conditions, sediment supply, and so on. A novel framework was proposed and evaluated for automatic dune detection and classification with remotely sensed images. The framework consists of two main steps: (1) The first step is to detect sand dunes from remote sensing images by SandUnet, which is firstly proposed in this paper. SandUnet, a Convolutional Neural Network (CNN), has a similar network structure with Attention U-net but modifies its attention gate module. In SandUnet, the input signals' information is not compressed as in the Attention U-net, therefore, the nuanced color and texture information of dunes are preserved. This paper demonstrated that SandUnet has better detection accuracy than other popular CNNs such as FCN, U-net, U-net++, and Attention U-net. (2) The second step is to compute the image similarity scores through MobileNet between each dune detection result image and the representative images of 6 different types of dunes. Then, each dune detection result image is classified into a dune type automatically. This paper applied the proposed framework to Taklimkan Desert in China. The average classification accuracy rate is around 80%, which proves the usefulness of this framework in automatic, no-cost, and accurate sand dune classification.

This paper addresses the doubts regarding the spatial characteristics of the commonly used rules for parallel reservoir system operation. The rules based on aggregation-decomposition determine the system total release first and then assign this release to individual reservoirs, without considering the water demand distribution in the river network. In this paper, a conceptual model for parallel reservoir systems with distributed water demands is proposed. Three specific optimality conditions are derived for determining the optimal analytical solution. A rigorous proof shows that the aggregation-decomposition-based rules are a special case of the derived rules. An efficient algorithm is then developed based on the optimality conditions and shortage allocation index (SAI), in which a larger SAI indicates taking a higher percentage of the system water shortage, as release or storage. Unlike traditional algorithms that modify the violated variables empirically, we propose a criterion in terms of relative deviation indicators to determine the crucial priority of variable modification. This criterion can effectively address constraint violations. The optimal rules along with the solution algorithm are then demonstrated by the operation of a parallel reservoir system in the Shiyang River Basin, China. The results show that the proposed rules and algorithm are more efficient and effective than traditional algorithms and aggregation-decomposition-based rules, especially in dry seasons with more binding constraints.

Soil salinity mapping is essential for sustainable land development and water resources management. In situ sampling is time-consuming, laborious, and restricted by geographical conditions. Therefore, an efficient and accurate model is necessary to monitor and assess the spatio-temporal dynamic salinization at regional a scale. In this study, Shule River Basin (SLRB) is taken as an example to develop the soil salinity mapping model based on Landsat 8 OLI images using random forest (RF) algorithms. A series of extended soil salinity indexes (ESSIs) were generated by combining any two, three, or four spectral bands were combined in expressions that include one or more of the arithmetic operations: addition, subtraction, multiplication, division, square and rooting form. The features selected from ESSIs outperformed the features selected from soil salinity indexes (SSIs) used in references. The best selected indexes are (B7^2-B5^2)^0.5, (B4^2+B5^2-B6^2)^0.5, (B1*B5-B4*B6/(B1*B5+B4*B6))^0.5,(B2*B6-B3*B7/( B2*B6+B3*B7))^0.5. In addition, three partition sampling methods of the training set and validation set for long-tail distribution problems are compared. The results showed that the resampling method considering the long-tail distribution performs better than systematic resampling and random k-fold cross-validation. The regional soil salinity mapping results showed that most areas are seriously salt-affected in the whole basin, especially along the river and the southeast mountainous area, where the soil salinity classes are highly and even over-extremely saline. This study could have implications for agricultural schemes planning and salinization control.

With the ongoing economic development and population growth, the shortage of water resources has become a severe problem which involves conflicts and tradeoffs among society, economy, environment, and ecology. Although previous researches proposed multi-objective optimization models, human-water coupled models, and hydro-economic models to deal with these conflicts and tradeoffs, they still did not address water demands’ integration and lacked future vision of water resource allocation. This paper proposed a Water Resource Allocation Model based on coupled Socio-economic-Environment-Ecology-Resources System (WRAM-SEERS) which considered integrally optimization objectives of socio-economic, environmental, and ecological subsystems under the constraints of water and land resources. The proposed model has the following advantages: (a) It could reflect all the closely related elements of the evolution of human society including urban and ecological space planning, cultivated structure and scale, population structure and size, industrial structure and scale, and so on, (b) It could generate the Pareto frontier surface, which maximized the socio-economic interest while minimizing the adverse externalities reacting in environment and ecology, and (c) It could forecast the future development range of each subsystem under hydrologic uncertainties. We applied WRAM-SEERS to allocate water resources of Yinchuan City in China in 2021-2035 and explained issues related the future perspective of Yinchuan: (a) “what is the lower and upper limits of subsystems’ development targets”, (b) “how to set targets consistent with sustainable development”, and (c) “how to achieve the settled targets”. The above explanations provided a scientific basis and decision-making reference for improving the water safety guarantee ability of Yinchuan's economic and social development and promoting a green, sustainable and high-quality development.

The multiphase rotodynamic pump is crucial for the multiphase blending transportation process. However, desigining such pump with high hydraulic performance and good blending transportation ability is quite challenging because of its unique structure. This study constructed a multi-objective optimization design system, which combines the 3D inverse design theory, response surface methodology, genetic algorithm, computational fluid dynamics simulation, and multi-objective optimization strategy, to improve the multiphase pump performance. Five optimization variables, namely the impeller loading parameters ( m1,S, m1,H, kS, kH) and the high-pressure edge angle ( θ), were selected in this study. Furthermore, two optimization objectives were considered at inlet gas void fraction ( IGVF) = 10%, namely the pump efficiency and the gas uniformity at the impeller outlet. The optimization results demonstrated that the pump efficiency and blending transportation ability would improve if the impeller blades had for-loaded loading distribution and the negative high-pressure edge angle. After optimization, the pump efficiency and the gas uniformity for the optimized impeller Opt1 improved by 2.6% and 18.2% at IGVF = 10%, respectively. Moreover, the internal flow pattern in the impeller was improved significantly, resulting in the maximum amplitude of pressure fluctuation in impeller Opt1 being 0.42 times that in the original test impeller.

In this work, an analytical model describing liquid wicking phenomenon in porous media was constructed, based on the statistical geometry theory and the fractal theory. In the model, a new structure-property relationship, depicted by specific surface, porosity, tortuosity, pore fractal dimension, maximum pore size of the porous media, was introduced into the energy conservation equation. According to the theoretical model, the accumulated imbibition weight in porous media was achieved, and the predictions were verified by available experimental data published in different literatures. Besides, structure parameters influencing the imbibition process upon approaching equilibrium height were discussed. The model and results in this work are useful for the application of porous media in scientific research and industry.

Purpose: This study aimed to investigate the value of combined detection of HCY and NRG4 in the diagnosis of early diabetic kidney disease (DKD) and to explore the association between the ratio of HCY/NRG4 and DKD. Methods: A total of 140 diabetic patients and 43 healthy people were prospectively enrolled. The plasma HCY level, NRG4 level and HCY/NRG4 of them were measured to compare their differences and analyze the correlation with DKD. The independent influencing factors of patients with DKD were screened, and the nomograph of DKD occurrence was constructed. Results: The levels of HCY and HCY/NRG4 in diabetic patients were significantly increased, while the level of NRG4 was significantly decreased (p < 0.01). The AUCs of HCY/NRG4 predicted for DKD were 0.961. HCY/NRG4 and the course of DM were independent risk factors for DKD. A predictive nomograph of DKD was constructed, and decision curve analysis (DCA) showed good clinical application value. HCY/NRG4 was positively correlated with Scr, UACR, TG, UA, BUN, TCHOL and LDL and negatively correlated with eGFR and HDL (p < 0.05). Conclusions: The level of HCY and NRG4 is closely related to the severity of DM, and combined detection of HCY/NRG4 can identify patients with DKD at an early stage.

Computing platforms providing cloud simulation services have raised new challenges on the model integration. Unlike calls to the model programs (components) in traditional simulation software, here the models should be dynamically integrated in the “plug and play” mode regardless of the differences in model type and developer. To this end two integration methods have been proposed, i.e., coarse-grained EXE integration and interactive integration. In an EXE integration method, the simulation program is directly called and thus only a data conversion interface is needed while rewriting of the model source code is not required. In contrast, an interactive integration method wraps the model components using the standard wrapper with communication interfaces, and therefore, it can communicate and exchange data with the platform in a real time. The first method is suitable for the integration of legacy models, while the second one can control the progress of simulation schemes and facilitate the scheduling of computing resources. Examples of the model integration and platform application have been presented in hydraulics/hydrodynamics to demonstrate the effectiveness of the integration method and the cloud computing platform.

The silicon carbide (SiC) devices have faster switching speed than that of the conventional silicon (Si) devices, which however may cause excessive device voltage overshoot. Larger gate resistance can help to restrain the overshoot, it however slows down the switching speed and increases switching losses. There are other methods that can mitigate the voltage overshoot, e.g., using low-inductance busbars, adding snubber circuits, etc. In this article, the busbar design for a 250-kW SiC three-level T-type inverter is investigated. The current commutation loops (CCLs) are first analyzed using a single-phase equivalent circuit. Then the detailed busbar design methods, especially a 3-D busbar design concept, are proposed to select the optimal stacking order for the multilayer laminated busbar and to address constraints posed by the physical terminal arrangements of SiC modules and dc-link capacitors. The stray inductance in each CCL is extracted via a finite element analysis and validated on the actual inverter busbar prototypes using an impedance analyzer. To further minimize the busbar stray inductance, a hybrid busbar structure with printed circuit board based buffer circuit using high-frequency decoupling capacitors is designed and evaluated in this article. Finally, the effectiveness of the designed busbars as well as the buffer circuit are validated using experimental studies.

Aims The objective of this study is to explore the relationship between red blood cell distribution and islet β-cell function indexes in patients with Latent Autoimmune Diabetes in Adults. Methods A total of 487 LADA patients were enrolled in this cross-sectional study. Patients were divided into three groups according to RDW tertiles. Clinical and laboratory measurements of age, height, weight, duration of diabetes, blood pressure, RDW, glycosylated hemoglobin A1c (HbA1c), C-peptide and blood lipids were performed. Homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β-cell function (HOMA-β) were assessed using homeostasis model assessment (HOMA) based on fasting blood glucose (FBG) and fasting C-peptide index (FCP). Correlations and multiple linear regressions were implemented to determine the association of RDW and islet function indexes. Results As the increase of serum RDW level, the presence of β-cell secretion increased(P

Although type 2 diabetes mellitus (T2DM) patients with coronavirus disease 2019 (COVID-19) develop a more severe condition compared to those without diabetes, the mechanisms for this are unknown. Moreover, the impact of treatment with antihyperglycemic drugs and glucocorticoids is unclear.From 1584 COVID-19 patients, 364 severe/critical COVID-19 patients with clinical outcome were enrolled for the final analysis, and patients without preexisting T2DM but elevated glucose levels were excluded. Epidemiological data were obtained and clinical status evaluation carried out to assess the impact of T2DM and its management on clinical outcomes.Of 364 enrolled severe COVID-19 inpatients, 114 (31.3%) had a history of T2DM. Twenty-seven (23.7%) T2DM patients died, who had more severe inflammation, coagulation activation, myocardia injury, hepatic injury, and kidney injury compared with non-DM patients. In severe COVID-19 patients with T2DM, we demonstrated a higher risk of all-cause fatality with glucocorticoid treatment (adjusted hazard ratio [HR], 3.61; 95% CI, 1.14-11.46; P = .029) and severe hyperglycemia (fasting plasma glucose ≥11.1 mmol/L; adjusted HR, 11.86; 95% CI, 1.21-116.44; P = .034).T2DM status aggravated the clinical condition of COVID-19 patients and increased their critical illness risk. Poor fasting blood glucose (≥ 11.1 mmol/L) and glucocorticoid treatment are associated with poor prognosis for T2DM patients with severe COVID-19.背景: 虽然2019冠状病毒病(COVID-19)合并2型糖尿病(T2DM)患者比未患糖尿病的患者病情更加严重, 但其发病机制尚不清楚。此外, 降糖药和糖皮质激素治疗对COVID-19的影响尚不清楚。 方法: 对我院1584例COVID-19住院患者的临床资料进行回顾性分析。我们排除了既往无T2DM但血糖升高的患者, 得到364例重型/危重型COVID-19患者作为最终分析对象, 收集其流行病学资料和临床转归, 以评估T2DM及其治疗对COVID-19临床预后的影响。 结果: 在364例重型/危重型COVID-19住院患者中, 114例(31.3%)有T2DM病史。27例(23.7%)T2DM患者死亡, 这些患者比非糖尿病患者具有更严重的炎症反应、凝血激活、心肌损伤、肝损伤和肾损伤。在T2DM合并COVID-19重症患者中, 糖皮质激素治疗(校正HR, 3.61；95%CI, 1.14-11.46；P=0.029)和严重高血糖(空腹血糖≥11.1 mmol/L；校正HR, 11.86；95%CI, 1.21-116.44；P=0.034)的全因死亡风险更高。 结论: T2DM加重COVID-19病情并增加其危重症风险。空腹血糖不良(≥11.1mmol/L)和糖皮质激素治疗与重症COVID-19患者预后不良相关。.

This article presents a comprehensive design and validation of a compact all-silicon carbide (SiC) 250-kW T-type traction inverter with a power density of 25 kW/l and 98.5% peak efficiency. All the operation modes and switching transitions in a T-type phase leg are analyzed to model the semiconductor power losses over a fundamental cycle. Special attention has been paid to investigate the behavior and losses due to the reverse conduction of the SiC MOSFETs. Then a loss model is built based upon this analysis to calculate the device loss distribution and system efficiency, which is further used to determine the optimal switching frequency. In addition, detailed inverter system design and prototyping procedure, including the selection of SiC modules and dc-link capacitors, and the optimization of a four-layer laminated busbar, are presented. In this article, the T-type phase leg is formed by a normal half-bridge module and a common-source module. The switching performance and losses in this configuration are different from two-level topology that only uses one SiC module. Therefore, the switching performance and the associated switching energy in each switch position are characterized using a custom clamped inductive load (CIL) test setup designed for a T-type phase leg. The performance of the full power traction inverter prototype has been verified experimentally using pulse testing and continuous power testing.

The impact of anthropogenic activity on chemical weathering is still an open and significant topic that requires clarification to improve the understanding of watershed evolution. We analyzed river water and rainwater samples to characterize the variation in hydrochemical characteristics and influencing factors. Samples were taken from the Liuxi River Basin (LRB), the only local drinking water supply for Guangzhou, and we studied geochemical parameters, major ions, and Si concentrations. Moreover, elemental ratios of end-members were determined and a modified-forward model was constructed to identify ion sources and estimate the chemical weathering rate (CWR) and anthropogenic input rate (AIR). Finally, we quantified the impacts of anthropogenic activity on the chemical weathering process. The results showed that the dominant hydrochemical type of river water was identified as HCO3-Ca, and rock weathering was the main contributor to river Na+, Mg2+, Ca2+ and HCO3-, whereas anthropogenic activity contributed the most to K+, Cl-, SO42-, and NO3-. The relatively high silicate weathering rate (SWR) (17.8-18.4 t per km2 per year) and AIR (37.8-60.3 t per km2 per year) were mainly attributed to erosion by nitric and sulfuric acid. The contribution rate of these acids to CWR could be regarded as a proxy quantifying the impact of anthropogenic activity on the chemical weathering process. This accounted for approximately 30% of the total SWR in the LRB. Our results demonstrate the effectiveness of hydrochemical source identification for quantifying the impacts of anthropogenic activity on chemical weathering.

Iron is one of the most important trace elements in life activities. It participates in a variety of important physiological processes in the body through oxidation-reduction reaction. A large number of studies show that iron overload (IO) is closely related to the progression of diabetes and its various chronic complications. However, the mechanism of iron overload in the pathogenesis of diabetes and the mechanism of iron overload in atherosclerosis (AS) are still controversial, and the relationship between iron overload and diabetic lower extremity arterial disease (LEAD) remains still unclear. Some recent reviews and original research articles suggest further studies to explain the complex relationship between iron metabolism and atherosclerosis. This article reviews the relationship between iron overload and diabetes and its relationship with LEAD, and discusses its mechanisms from various aspects, such as lipid peroxidation induced by iron overload, so as to provide clinical diagnosis and treatment ideas for diabetic lower extremity arterial disease. It is hoped that early evaluation, diagnosis and treatment of LEAD will be inspired.

Maintaining the integrity and stability of oasis ecosystems is an important topic in the field of ecological research. Assessment of ecosystem services and their changes can provide important support for the sustainable development of oases. This study took the Dunhuang oasis in the hyper-arid area as the research object and used 1990, 2010, and 2020 Landsat series satellite images to complete the land use interpretation by random forest classification. Then we estimated the ecosystem services value (ESV) by using benefit transfer method, and predicted the trend of ecosystem service value changes under three scenarios using the Analytic Hierarchy Process method and the patch generation land use simulation model (AHP-PLUS model). The results showed that the vegetation areas of the Dunhuang Oasis first decreased and then increased during 1990–2020. The decrease was largely due to the expansion of built-up land and farmland, and the increase was mainly contributed by the implementation of ecological protection policies. The path of changes in the ESV of the Dunhuang Oasis during 1990–2020 was well consistent with that of vegetation areas, with a maximum of 9068.15×106 yuan (in 1990) and a minimum of 6271.46×106 yuan (in 2010). Spatial autocorrelation analysis showed that urbanization reduced ESV, and the implementation of ecological policies enhanced ESV. The ESV of the Dunhuang Oasis for the year 2030 under the ecological conservation scenario could reach 7631.07×106 yuan, which is 381.1×106 yuan higher that under the economic development scenario. The ecological conservation scenario is the optimal option to achieve sustainable development of the Dunhuang Oasis. We suggested that the government should continuously enhance the protection of forests and waterbodies, reasonably restrict production and domestic water consumption, and efficiently increase the proportion of ecological water consumption. In addition, this study improved the evaluation method of oasis ESV based on the proportion of Normalized Difference Vegetation Index (NDVI) of grasslands with different coverage, which is important for improving the environment in arid areas.

BACKGROUND: To evaluate the use of the diagnosis-related groups (DRGs) tool to promote the diagnosis/treatment ability and quality of the endocrinology department under the new policy of grouping payment-related to disease diagnosis. METHODS: We compared the income structure of the endocrinology department in a 3a general hospital between the first half of 2019 and the same period in 2021. We also observed the changes in cost efficiency indexes (CEIs), time efficiency indexes (TEIs), case-mix index (CMI), number of DRGs, risk weight (RW) proportion, and surgery number in the inpatient department. Furthermore, the distribution of inpatients with diabetes of the whole hospital and the improvement of treatment efficiency indexes of the sub-specialty department were analyzed. RESULTS: In the first half of 2021, compared with the same period of 2019, the total revenue of the endocrinology department decreased by 20.05%, the average hospitalization cost decreased by 11.72%, the CEI decreased from 1.31 to 1.06, and the TEI decreased from 0.74 to 0.64. Additionally, the number of DRGs increased from 162 to 176, the average CMI value increased from 0.80 to 0.84, and the proportion of RW 1–5 cases increased. Moreover, the number of surgical cases increased by 60.50%, minimally invasive surgery increased by 53.54%, grade 4 surgery increased by 66.67%, and the proportion of entering the clinical pathway increased from 77.76% to 86.64%. From May to August, 2021, the admission rate of endocrinology sub-specialty increased significantly, the number of DRGs showed an increasing trend, and the CEI and TEI decreased significantly. In the first half of 2021, inpatients with diabetes in the departments of rehabilitation, neurology, nephropathy, ophthalmology, and general administration accounted for 21.99–38.54%. CONCLUSIONS: The DRGs tool can be used to improve the clinical diagnosis and treatment ability of the endocrinology department, as well as optimize the CEI, TEI, CMI, and RW values. It is an effective way to promote the development of the endocrinology department under the new DRGs payment policy, carry out blood glucose management in the hospital, build endocrinology sub-specialties, and improve surgical and operation capacity.

Monitoring and predicting temperatures at critical locations of a power electronic system is important for safety, reliability, and efficiency. As the market share of vehicles with electric powertrains continues to increase, there is also an important economic cost of failing electronic components. For inverters present in such a drive system, exceeding the temperature limit for certain critical components, such as DC-link capacitors and Silicon carbide MOSFETs, can lead to failure of the system. In such an application, extracting the temperatures using sensors from locations such as dies and capacitors require expensive modifications and poses technical challenges. It is therefore necessary to create a thermal model for the inverter system to estimate the temperature at various components in order to ensure operation within temperature limits. The model approach is also suitable for predicting the effect on the component temperature and reliability of boundary conditions such as coolant, ambient temperature, and mission profile. This study assesses the reliability of a 250 kW liquid cooled inverter system designed for traction application. The critical failure areas are the DC-link capacitors, and the SiC MOSFET dies, which are rated at 175 °C. The system is modeled as a compact system by reasonably considering each component as a lumped capacitance and estimating the thermal resistance using physical dimensions. Results from the model are then compared against experimental data from constant power testing, and good agreement is observed for the cold plate and gate driver temperatures. With the model fidelity established, the model is then used to implement drive cycles from the Environmental Protection Agency for nonroad applications. The resulting temperature profile for each component is a series of temperature peaks and troughs that contribute to damage and failure. Rainflow counting algorithm is then used to quantify the damage per mini-cycles and used to estimate the predicted life for each component based on their manufacturer provided reliability qualification, and the mission profile is executed on the test bench for validation. The results are then used to generate a system risk matrix that relates the failure risk associated with a certain mission profile and the cooling scheme. It therefore demonstrates that an automotive inverter with SiC switching devices can be credibly assessed for failure risk using a compact model that is independent of boundary conditions, in combination with established reliability correlations and techniques.

Dew has been considered a supplementary water resource as it constitutes an important water supply in many ecosystems, especially in arid and semiarid areas. Remote sensing allows large-scale surface observations, offering the possibility to estimate dew in such arid and semiarid regions. In this study, by screening and combining different remote sensing variables, we obtained a well-performing monthly scale dew yield estimation model based on the support vector machine (SVM) learning method. Using daytime and nighttime land surface temperatures (LST), the normalized difference vegetation index (NDVI), and three emissivity bands (3.929–3.989 µm, 10.780–11.280 µm, and 11.770–12.270 µm) as the model inputs, the simulated site-scale monthly dew yield achieved a correlation coefficient (CC) of 0.89 and a root mean square error (RMSE) of 0.30 (mm) for the training set, and CC = 0.59 and RMSE = 0.55 (mm) for the test set. Applying the model to the Heihe River Basin (HRB), the results showed that the annual dew yield ranged from 8.83 to 20.28 mm/year, accounting for 2.12 to 66.88% of the total precipitation, with 74.81% of the area having an annual dew amount of 16 to 19 mm/year. We expanded the model application to Northwest China and obtained a dew yield of 5~30 mm/year from 2011 to 2020, indicating that dew is a non-negligible part of the water balance in this arid area. As a non-negligible part of the water cycle, the use of remote sensing to estimate dew can provide better support for future water resource assessment and analysis.

The variability of the natural environment and the complexity of human activities result in dynamic changes in oasis areas, which is directly related to the sustainable development of arid and semi-arid areas. In order to better balance economic development and environmentally sustainable development, based on land use data and social and economic data from 1980 to 2015, this paper analyzed the oasis change characteristics under natural and human factors in the Shiyang River Basin in Northwest China. The results indicated that the oasis in the Shiyang River Basin showed an expansion trend from 1980 to 2015, with the expansion mainly occurring in the diluvial and alluvial fan, and along the middle and lower reaches of the river. The oasis changed actively in areas at an elevation of 1350 m, with a slope of 2°, at the distance of 1500 m to rivers, and with precipitation of 120 mm and temperature of 15 °C. Furthermore, the oasis mainly evolved towards gentler slopes and lower altitudes, and migrated closer to rivers before 1992 and farther away from rivers afterwards. Population growth and economic development were the important inducers of oasis change, and government policies on agricultural benefits and ecological conservation also influenced the oasis change, especially after 2000. The evolution patterns of oasis distribution revealed in this study can provide a reference for promoting oasis ecological restoration and sustainable development.

Monitoring and predicting temperatures at critical locations of a power electronic system is important for safety, reliability and efficiency. As the market share of vehicles with electric powertrains continue to increase, there is also an important economic cost of failing electronic components. For inverters present in such a drive system, exceeding the temperature limit for certain critical components, such as DC-link capacitors and Silicon carbide MOSFETs, can lead to failure of the system. In such an application, extracting the temperatures using sensors from locations such as dies and capacitors require expensive modifications and poses technical challenges. It is therefore necessary to create a thermal model for the inverter system to estimate the temperature at various components in order to ensure operation within temperature limits. The model approach is also suitable for predicting the effect on the component temperature and reliability of boundary conditions such as coolant, ambient temperature and mission profile. This study assesses the reliability of a 250 kW liquid cooled inverter system designed for traction application. The critical failure areas are the DC-link capacitors, and the SiC MOSFET dies which are rated at 175 degrees C. The system is modeled as a compact system by reasonably considering each component as a lumped capacitance and estimating the thermal resistance using physical dimensions. Results from the model are then compared against experimental data from constant power testing, and good agreement is observed for the cold plate and gate driver temperatures. With the model fidelity established, the model is then used to implement drive cycles from the Environmental Protection Agency for nonroad applications. The resulting temperature profile for each component are a series of temperature peaks and troughs that contribute to damage and failure. Rainflow counting algorithm is then used to quantify the damage per mini-cycles, and used to estimate the predicted life for each component based on their manufacturer provided reliability qualification and the mission profile is executed on the test bench for validation. The results are then used to generate a system risk matrix that relates the failure risk associated with a certain mission profile and the cooling scheme. It therefore demonstrates that an automotive inverter with SiC switching devices can be credibly assessed for failure risk using a compact model that is independent of boundary conditions, in combination with established reliability correlations and techniques.

Building water dissipation (BWD) refers to the change of water into vapour during water use activities in the building. The intention of the work described in this paper was to explore the BWD mechanism and establish a calculation model for BWD. The main research methods included experimental monitoring, a questionnaire survey and data mining. The results of this work showed that the capacity of buildings and the building area determine the type of water dissipation whereas the building population determines the BWD volume. The BWD calculation model was thus built based on two key parameters – building area and building population. Multi-variate regression fitting was used to analyse and study the other factors that influence BWD, such as water consumption, number of floors and so on. Using cluster analysis, 100 sample buildings were divided into different categories. Ordinary least squares regression was used to fit the multi-variate regression for the BWD of sample buildings. The results showed that the classification of buildings by cluster analysis can enhance the fitting effect of multi-variate regression of BWD.

China‘s rivers are highly regulated. The biodiversity and ecosystems of these rivers are threatened by barriers restricting fish movements for reproduction and foraging. To overcome this challenge,...

Dissipation of water (evapotranspiration and water vapor conversion in human water use activities) is one of the significant hydrological processes in urban area, which becomes more complicated with rapid urbanization. However, there are few systematic studies on water dissipation problems in urban area, and even the related concepts are unclear. This paper proposed the concept of urban water dissipation (UWD) to describe water vapor conversion in urban areas, and presented analysis on mechanism of UWD based on observing and monitoring experiments. The urban underlying surface was divided into five categories: buildings, paved ground, vegetation, water surface, and soil, in which the buildings have been scarcely discussed in terms of water dissipation. The dissipation of water in buildings plays a more and more important role in the urban water circulation system, as the water supply increases in urban areas. To reveal how much water is dissipated in the buildings, the main water dissipation processes in different kinds of buildings were analyzed, and the quantitative model was proposed. Based on the traditional evapotranspiration models for urban underlying surface and the proposed model for water dissipation in buildings, a new modelling system was built to simulate the total UWD. The new model system reflects the impact of human water use activities on urban water dissipation. It was applied in Xiamen city to simulate the UWD in 2000, 2005, 2010, and 2015. The results show that the UWD intensity increased with the urbanization process in Xiamen urban area in past 15 years. The UWD contribution rate increased for most land use types, except green land. For example, the water dissipation on residential land is the fastest growing one of all land use types, and its contribution rate surpassed that of green land to become the largest contributor in 2010. Because of the interference of strong human activities, the contribution rate of water dissipation on the social side continues increasing. The contribution rate of UWD on the social side was more than 40% in 2015, and it is still increasing.

Wide bandgap (WBG) devices usually have much faster switching speed than that of the traditional silicon devices, which, however, may pose challenges to the design of the power loop and gate loop. Extensive research has been done to address the drain-source voltage overshoot and oscillation issues by reducing the power loop stray inductance. To further enable higher switching frequency, the issues on the gate driver side still need to be addressed. The crosstalk phenomenon on gate-source voltage, as one of the major issues, has attracted lots of attention and can be mitigated by various approaches. In addition, when dv/dt is extremely high, the common-mode (CM) noise may deteriorate the control signals through the capacitive coupling, which still need to be addressed, considering just 1.5V voltage noise can lead to false triggering on the PWM input of digital isolators. In this work, four gate driver architectures in the existing literature are studied and compared in terms of the CM noise immunity. LT-spice small-signal models are utilized for simulation studies to compare the CM noise immunity of different gate driver designs quantitatively. The prototype of the optimal design was built and experimentally tested using a 3.3 kV SiC MOSFET to validate its CM noise immunity under the extremely high dv/dt, even beyond 240 V/ns.

Parasitic inductance of power modules is one nonnegligible part of inductance on converters’ current commutation loop (CCL). Larger CCL inductance leads to higher switching oscillation, voltage overshoot, electromagnetic interference (EMI), and larger power losses. This paper uses two-port scattering (S) parameter measurement to extract the parasitic inductance of the power module. The innovation of this paper is that it considered the impact of mutual inductance and fixture printed circuit board (PCB) when using S-parameter approach. Accurate internal parasitic inductance values can be obtained by logic analysis, no matter used in a traditional two-level (2-L) inverter or three-level (3-L) T-type inverter. And it provides the guidance to build the fixture PCB board to connecting vector network analyzer (VNA) and the module, which has not been discussed in the existing literature. The approach is experimentally validated by a commercial 1200V SiC half-bridge power module.

The parasitic impedance in a current commutation loop (CCL) is a major factor for the switching performance of power electronics especially the wide bandgap (WBG) devices, which usually generate high di/dt. The terminals of components in a CCL may not always be standard. The fixture adapter with clip lead may not be accurate enough for WBG application, while the commercial high bandwidth fixture adapters are not always available. Therefore, it is critical to design fixture adapter boards to make a better interface and mitigate measurement errors. In this work, detailed fixture design procedures are presented. These design methods were validated by comparing with the commercial fixture adapters. In addition, various considerations to further improve the measurement accuracy are discussed, summarized, and evaluated through tests. The dc-link capacitors and the busbar for a half-bridge module are regarded as the device under test, whose impedance is extracted using the proposed fixture design. Finally, the experimental results from the double pulse test verified the accuracy of the proposed fixture design, with an error of less than 1%.

Three-level T-type neutral-point-clamped converters (3L-TNPC) are widely used in motor drive and PV applications because of the higher efficiency, improved output THD, and lower common-mode noise. But such topology suffers from high stray inductance because of the complicated power loop structure. This paper proposes a SiC-MOSFET based 3L-TNPC power module with a hybrid packaging method. The module has a printed circuit board (PCB) directly soldered on top of direct bounding copper (DBC), with bare dies soldered on DBC and connecting to PCB by bonding wires. Such a structure allows the power loop on both DBC and PCB. This reduces stray inductance through enhanced mutual-inductance cancellation. The introduced PCB can provide extra flexibility in gate-loop optimization, enabling synchronous gate drive between parallel dies. The heat from dies can also be directly dissipated through DBC and the proposed direct-soldered coldplate. A 1.2 kV, 400 A SiC 3L-TNPC module is fabricated with measured loop inductance of 2.5 nH. Faster driving speed by using 0.33Ω gate resistance is enabled to reduce switching loss. Eventually, double-pulse tests and continuous tests are carried out to evaluate the module.

As a critical specification for the dc-link design of a voltage source inverter (VSI), the root-mean-square (RMS) value of the capacitor current should be accurately determined. Various work has been done on the modeling and analysis for the dc-link current, however an accurate model for the dc-link capacitor current still needs to be developed, especially for multilevel inverters. In this work, a detailed model for the dc-link capacitor current of a three-level VSI is proposed, and based on the model, the closed-form expression of dc-link capacitor RMS current is derived from the switching states of space vector pulse width modulation (SVPWM). The expression is a function of the modulation index and power factor, and can be used to estimate the maximum dc-link capacitor RMS current. Both simulation and experimental results are presented to validate the accuracy of the proposed model and the derived expression of the dc-link capacitor RMS current.

This paper proposes an insulation design and optimization methodology for laminated busbars in more-electric aircraft (MEA) motor drive system. The design assumes that the converter works at around 11-km altitude with decompressed air pressure, which expedites partial discharge (PD) compared to it at sea-level. The trade-off between the insulation margin and power-loop stray inductance is revealed and optimized. By using the method, a busbar for a 450-kVA 3-level T-type neutral-point-clamped (3L-TNPC) converter is designed. Its partial discharge inception voltage (PDIV) is 43% higher than the rated voltage at the air pressure of 0.2 atm and 170% higher at normal air pressure. Busbar stray inductance of 12.0 nH is achieved, lower than published literature of 3-level converters.

Parasitic capacitance in power loop can impact switching performance of converters. Depending on the locations of those capacitors, they can mitigate switching stress if paralleled to DC-link capacitors, or introduce additional switching loss if paralleled to device output capacitance, Coss, or intensify common-mode EMI noise if paralleled to switching-node stray capacitance. Thus high-accuracy characterization of parasitic capacitance is necessary to estimate the performance of converter. This paper proposes novel method to measure stray capacitance in laminated busbar. Such method is based on a vector network analyzer (VNA). The direct assessment of each node-to-node capacitance is the key advantage compared to the traditional method. It also simplifies measurement process, avoids complicated math operation, and improves measurement accuracy in applications of assessing capacitance of the multiple-node systems, for example, three-level converters. This paper illustrates proposed method by measuring a laminated busbar. Design of customized fixtures is discussed for improving measurement consistency and accuracy. Measurement results are compared to the traditional method and ANSYS Q3D simulation to prove its accuracy.

The Qaidam Basin is a unique and complex ecosystem, wherein elevation gradients lead to high spatial heterogeneity in vegetation dynamics and responses to environmental factors. Based on the remote sensing data of Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS), we analyzed the spatiotemporal variations of vegetation dynamics and responses to precipitation, accumulative temperature (AT) and soil moisture (SM) in the Qaidam Basin from 2001 to 2016. Moreover, the contribution of those factors to vegetation dynamics at different altitudes was analyzed via an artificial neural network (ANN) model. The results indicated that the Normalized Difference Vegetation Index (NDVI) values in the growing season showed an overall upward trend, with an increased rate of 0.001/year. The values of NDVI in low-altitude areas were higher than that in high-altitude areas, and the peak values of NDVI appeared along the elevation gradient at 4400–4600 m. Thanks to the use of ANN, we were able to detect the relative contribution of various environmental factors; the relative contribution rate of AT to the NDVI dynamic was the most significant (35.17%) in the low-elevation region (

Objective To investigate the correlation between the platelet‐to‐lymphocyte ratio (PLR) and diabetic foot ulcer (DFU) in patients with type 2 diabetes mellitus (T2DM). Method From January 2018 to August 2019, 206 patients with T2DM admitted to the Central Hospital of Wuhan, China, were enrolled in this study, including 104 patients with DFU (DFU group) and 102 patients without DFU (T2DM group). During the same period, 90 healthy subjects were randomly screened as normal controls (NC group). The correlation between PLR and DFU in patients with T2DM was explored by comparing the PLR of the subjects in the three groups. Results The PLRs of the DFU and T2DM groups were higher than that of the NC group, whereas the PLR of the DFU group was higher than that of the T2DM group (p, The platelet to lymphocyte ratio (PLR) is significantly elevated in diabetic foot ulcer (DFU) patients and positively correlated with the Wagner DFU grade.

Over the last few decades, China has greatly expanded its scope of stem cell research, generating various scientific advances and medical applications. However, knowledge of the extent and characteristics of domestic stem cell development, particularly medical workers’ opinions, is lacking. This study’s purposes were to analyze the growth trends of China’s stem cell community and identify the knowledge and attitudes held by Chinese medical workers regarding stem cell research. We found that there are currently 13 high-quality stem cell research centers with more than 400 PhD-level researchers across Mainland China. These centers feature many high-caliber scientists from the stem cell research community. From 1997 through 2019, the National Natural Science Foundation of China allocated roughly $576 million to 8,050 stem cell programs at Chinese universities and research institutions. China’s annual publications on stem cells increased from less than 0.6% of the world’s total stem cell publications in 1999 to more than 14.1% in 2014. Our survey also revealed that most participants held positive attitudes toward stem cell research, supported further funding, and had high general awareness about stem cells.

The pump back test is popular in the industry for high power characterization since it does not have the requirement for high-power DC power supply and AC load. The configuration of the pump back test includes two converters, with the dc side connecting to the common dc power supply and ac side connecting each other through an ac filter. One problem of the pump back test is that the circulating loop provides a flow path for the zero-sequence current. Therefore zero sequence current (ZSC) is obvious, especially when the zero sequence component is injected. To solve this problem, a novel zero-sequence current control method is proposed in this paper, which not only can be used for sine pulse width modulation (SPWM) but also suitable for zero-sequence injection pulse width modulation. With the help of this control method, total harmonic distortion (THD) can be largely mitigated in ac current. Simulation results and experimental validation are shown to demonstrate the performance of the proposed control method.

With the increasing pressure from population growth and economic development, northern China (NC) faces a grand challenge of water scarcity, which can be further exacerbated by climatic and societal changes. The South‐to‐North Water Diversion (SNWD) project is designed to mitigate the water scarcity in NC. However, few studies have quantified the impact of the SNWD on water scarcity within the context of climatic and societal changes and its potential effects on economic and agricultural food in the region. We used water supply stress index (WaSSI) to quantify water scarcity within the context of environmental change in NC and developed a method to estimate the economic and agricultural impacts of the SNWD. Focuses were put on alleviating the water supply shortage and economic and agricultural benefits for the water‐receiving NC. We find that societal changes, especially economic growth, are the major contributors to water scarcity in NC during 2009–2099. To completely mitigate the water scarcity of NC, at least an additional water supply of 13 billion m3/year (comparable to the annual diversion water by SNWD Central Route) will be necessary. Although SNWD alone cannot provide the full solution to NC's water shortage in next few decades, it can significantly alleviate the water supply stress in NC (particularly Beijing), considerably increasing the agricultural production (more than 115 Tcal/year) and bringing economic benefits (more than 51 billion RMB/year) through supplying industrial and domestic water use. Additionally, the transfer project could have impacts on the ecological environment in the exporting regions.

More electric aircrafts (MEA) recently attracts increasing attention due to improvements to efficiency, reduce weight, fuel cost, and carbon emissions. High-specific-power machines, and corresponding integrated motor drives have been identified as the crucial enabling technology for the realization of more electric aircraft propulsion. Such a concept requires converter working under depressurized environments, which poses challenges to the electric insulation due to partial discharge (PD). This threatens the reliability of the drive system. This paper proposes an insulation design and optimization methodology for a laminated busbar in a 450-kVA electric-aircraft motor drive. The design aims to avoid any partial discharge in the insulation and also achieves optimized busbar stray inductance. To achieve the targets, partial discharge inception voltage (PDIV) with respect to air pressure was obtained by the experiment, and the experimental results were used as PD -free design criteria in electric field simulation of the laminated busbar. Then, the insulation structure regarding insulation material selection and thickness selection was optimized by taking both the PD-free criteria and parasitic inductance into consideration. The proposed design procedure provides valuable references for future laminated busbar design, which is used for the MEA system.

In this paper, a fast space-vector modulation (SVM) scheme is proposed for a hybrid 7-level (7-L) converter, i.e., cascaded T-type converter and H-bridge converters, for grid-tied applications. Using oblique coordinate reference, the proposed SVM can quickly locate the switching triangle enclosing the reference vector in the 7-L space vector diagram. Then all available switching sequences and vector duty cycles are acquired by straightforward calculation without using any look-up tables, which significantly reduces the computational cost. The floating capacitor voltages are also stabilized by using the proposed SVM. Experimental studies on a scale-down prototype are presented in this work to validate the effectiveness of the proposed scheme.

Background: Globally environmental pollution is an important cancer risk factor. The study of cancer clusters in a tributary of Huai River Basin (HRB) provides a unique opportunity to examine the association between water pollution and cancer clusters. Methods: We selected QS County of the HRB as a representative region as it has emerged as a high-cancer-risk area from a low-cancer-risk area in the past four decades, thus creating an ideal ‘self-control study’. Spatial pattern analysis for geographic clusters of cancer mortality was performed and we excluded the low-cancer-risk areas to recalculate cancer mortality. We then integrated pollutant-fingerprint-tree analysis, hydrography modeling, and mathematical simulation to confirm the relationship between water pollution and cancer clusters. Findings: Standardized mortality rates for cancers of the esophagus, stomach and liver in the QS County significantly shifted from 42.01/100,000 in 1973-1975 to 93.17/100,000 in 2015. Cancer mortality in polluted areas was 1.7-fold higher than that in areas without irrigation canals. After excluding villages in the three high cancer mortality (HCM) clusters, the average cancer mortality of the remaining villages was 57.67/100,000, comparable to the national average. We attribute the HCM in villages in the region to local water pollution (F = 36.82, P < 0.001; r = 0.856). The three independent HCM clusters demonstrated similarity in pollutant fingerprints and were linked by irrigation canals. Modeling analysis indicated that even one irrigation canal is enough to contaminate groundwater leading to pollutant transfer. Interpretation: Irrigation canals affect the trans-regional redistribution of cancer clusters, which triggers the trans-regional transportation of cancer risk, and the migration of water pollution leads to the convergence of cancer occurrence among distant populations. Our novel method provides a tool for the study of environmental pollution on cancer occurrence and offers a foundation for developing cancer intervention strategies. Funding: This project was supported by the Chinese National Natural Science Foundation (81325017, 30972438, 81202165 & 81930094), The Key Project of National High-tech R&D Program of China - 863 Program (2013AA065204), National Key R&D Program of China (No.2017YFC1600200), National Key Technology R&D Program in the 12th Five Year Plan (2012BAJ25B05 & 2013BAI12B03), National Key Technology R&D Program in the 11th Five Year Plan (No. 2006BAI19B02), Shanghai Municipal Health Bureau Leading Academic Discipline Project (No. 08GWD14), and ‘Dawn’ Program of Shanghai Education Commission (No. 07SG01). Declaration of Interests: The authors declare that they have no conflict of interest.