The level of circulating nucleosomes in the serum has a predictive value for sepsis and organ dysfunction and may serve as a candidate biomarker for the diagnosis/prognosis of sepsis. Further studies are warranted to confirm the present findings.

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This paper provides a comprehensive security analysis of the Electric Vehicle (EV) charging service in Smart Grid (SG) environment (i.e. the "smart" EV charging application). It first describes three EV charging scenarios, at home, at work and at public places. Based on these use-case scenarios, the paper presents a model for smart EV charging, consisted of application entities and interactions among them. It then illustrates potential message types communicated among these entities. Based on this model and the exchanged messages, the paper analyses security problems and potential security threats imposed on the entities, which leads to the specification of a set of security and privacy requirements. These requirements could be used to guide the future design of solutions for secure smart EV charging systems and/or a risk/impact assessment of such systems.

Soil moisture monitoring networks can provide real-time and accurate soil moisture measurements; however, missing values and the lack of unified measurement depths across different networks impedes soil moisture applications at regional and national scales. Therefore, methods for vertical extrapolation of soil moisture, i.e., using shallow soil moisture measurements to estimate deeper soil moisture, are needed for standardizing measurements to a set of common depths. This study compared three methods, artificial neural network (ANN), linear regression (LR), and exponential filter (ExpF), for vertical extrapolation of soil moisture using data from the Oklahoma Mesonet. Based on our analysis of intra-annual variations in soil moisture, we divided each year into two seasons, warm and cool. Our results demonstrate that all methods perform better in the warm season than in the cool season, especially at deeper depths. The Kling-Gupta efficiency was used to assess the performance of each method. All methods had similar performance for near-surface extrapolation of soil moisture (top 25 cm). Although the accuracy of all models tended to decrease with depth, the ExpF outperformed the other methods at deeper depths. The soil water index (SWI) is preferred over volumetric water content as input to the ExpF. Incorporating air temperature and an antecedent precipitation index into the ANN and LR methods did not significantly improve their accuracy. We demonstrated that both ExpF and general LR can be used for SWI extrapolation at sites where only surface soil moisture data are available. Soil properties may be useful for further improving the accuracy of the general LR method.

In this article, the performance of the Visible and Shortwave infrared Drought Index (VSDI), a drought index recently developed and validated in Oklahoma, United States, is further explored and validated in China. The in-situ measured soil moisture from 585 weather stations across China are used as ground-truth data, and five commonly used drought indices are compared with VSDI for surface drought monitoring. The results reveal that VSDI is robust and reliable in the estimation of surface dryness-it has the highest correlation with soil moisture among the six indices when computed using both the original and cloud removed data. All six indices show the highest correlation with soil moisture at the 10 cm layer and the averaged 10-50 cm layer. The spatiotemporal patterns of surface moisture indicated by the MODIS-based VSDI are further compared with the precipitation-based drought maps and the Global Land Data Assimilation System (GLDAS) simulated surface soil moisture maps over five provinces located in the Middle-Lower Yangtze Plain of China. The results indicate that despite the difference between the spatial and temporal resolutions of the three products, the VSDI maps still show good agreement with the other two drought products through the rapidly alternating drought and flood events in 2011 in this region. Therefore, VSDI can be used as an effective surface wetness indicator at both the provincial and the national scales in China.

Precipitation plays an important role in the food production of Southern Africa. Understanding the spatial and temporal variations of precipitation is helpful for improving agricultural management and flood and drought risk assessment. However, a comprehensive precipitation pattern analysis is challenging in sparsely gauged and underdeveloped regions. To solve this problem, Version 7 Tropical Rainfall Measuring Mission (TRMM) precipitation products and Google Earth Engine (GEE) were adopted in this study for the analysis of spatiotemporal patterns of precipitation in the Zambezi River Basin. The Kendall's correlation and sen's Slop reducers in GEE were used to examine precipitation trends and magnitude, respectively, at annual, seasonal and monthly scales from 1998 to 2017. The results reveal that 10% of the Zambezi River basin showed a significant decreasing trend of annual precipitation, while only 1% showed a significant increasing trend. The rainy-season precipitation appeared to have a dominant impact on the annual precipitation pattern. The rainy-season precipitation was found to have larger spatial, temporal and magnitude variation than the dry-season precipitation. In terms of monthly precipitation, June to September during the dry season were dominated by a significant decreasing trend. However, areas presenting a significant decreasing trend were rare (<12% of study area) and scattered during the rainy-season months (November to April of the subsequent year). Spatially, the highest and lowest rainfall regions were shifted by year, with extreme precipitation events (highest and lowest rainfall) occurring preferentially over the northwest side rather than the northeast area of the Zambezi River Basin. A "dry gets dryer, wet gets wetter" (DGDWGW) pattern was also observed over the study area, and a suggestion on agriculture management according to precipitation patterns is provided in this study for the region. This is the first study to use long-term remote sensing data and GEE for precipitation analysis at various temporal scales in the Zambezi River Basin. The methodology proposed in this study is helpful for the spatiotemporal analysis of precipitation in developing countries with scarce gauge stations, limited analytic skills and insufficient computation resources. The approaches of this study can also be operationally applied to the analysis of other climate variables, such as temperature and solar radiation.

BACKGROUND Anticoagulation (AC) for stroke prevention in long‐term care (LTC) residents with atrial fibrillation (AF) involves a challenging risk‐benefit evaluation. We measured the association of geriatric conditions with discontinuation of AC. DESIGN Retrospective cohort analysis. SETTING LTC facilities across the United States. PARTICIPANTS A total of 48 545 individuals residing in LTC facilities in 2015 with AF and sufficient information to establish their status as someone who stopped AC vs someone who continued AC. MEASUREMENTS We measured the association of six geriatric conditions—recent fall, severe activity of daily living (ADL) dependency (21‐28 on a 28‐point scale), mobility impairment, cognitive impairment, body mass index (BMI) less than 18.5 kg/m2, and weight loss (≥5% in 1 month or ≥10% in 6 months)—with discontinuation of AC. To identify cases of discontinuation, we required a pattern of being on AC over two consecutive recordings of the Minimum Data Set, the nursing home quality control data set recorded every 90 days, followed by two assessments being off AC—pattern of “on‐on‐off‐off.” By contrast, we required a pattern of “on‐on‐on‐on” for continuers. We then constructed six logistic regression models to measure the independent association between each geriatric condition and discontinuation of AC, adjusted for CHA2DS2‐VASc stroke risk score, recent bleeding hospitalization, and other confounders. RESULTS There were 4172 discontinuers and 44 373 continuers. Recent fall predicted a 1.9‐fold increase in the odds of discontinuation (odds ratio = 1.91; 95% confidence interval = 1.66‐2.20), whereas mobility and cognitive impairment only increased the odds by 14% to 17%. Severe ADL dependency, BMI less than 18.5 kg/m2, and weight loss of 10% each increased odds of discontinuation by 55% to 68%. CHA2DS2‐VASc score did not predict discontinuation. CONCLUSION Several geriatric conditions predicted discontinuation of AC, whereas CHA2DS2‐VASc score did not. Future research should examine the association of geriatric conditions and discontinuation of warfarin discrete from newer anticoagulants and association of geriatric conditions with development of stroke and bleeding. J Am Geriatr Soc 68:717–724, 2020