Numerical Modeling of Pulse-Periodic Nanosecond Discharges

The first results of the numerical simulation of the Pulse-Periodic Nanosecond discharge in pin-to-pin configuration in 2Dt approximation of the full self-consist system of Navier-Stocks equation for real thermo-chemically non-equilibrium gases, drift-diffusion approximation of the low temperature plasma evolution in external electric and magnetic field and, alternative – arc (spark) discharge model of high-density energy input discharge. The intuitive criteria of the alternative discharge models re-switch are proposed and tested. The pin-to-pin the pulse-periodic nanosecond 5-MHz discharge has been considered for 1 microsecond interval. It was found that rather strong longitudinal non-uniformities of main physical parameters are created at the first corona stage of the interelectrode conducting channel. These nonuniformities reveal long-lived features that have define strong effect on the discharge performance

Identifying Children at Readmission Risk: At-Admission Versus Traditional At-Discharge Readmission Prediction Model

The timing of 30-day pediatric readmissions is skewed with approximately 40% of the incidents occurring within the first week of hospital discharges. The skewed readmission time distribution coupled with delay in health information exchange among healthcare providers might offer a limited time to devise a comprehensive intervention plan. However, pediatric readmission studies are thus far limited to the development of the prediction model after hospital discharges. In this study, we proposed a novel pediatric readmission prediction model at the time of hospital admission which can improve the high-risk patient selection process. We also compared proposed models with the standard at-discharge readmission prediction model. Using the Hospital Cost and Utilization Project database, this prognostic study included pediatric hospital discharges in Florida from January 2016 through September 2017. Four machine learning algorithms—logistic regression with backward stepwise selection, decision tree, Support Vector machines (SVM) with the polynomial kernel, and Gradient Boosting—were developed for at-admission and at-discharge models using a recursive feature elimination technique with a repeated cross-validation process. The performance of the at-admission and at-discharge model was measured by the area under the curve. The performance of the at-admission model was comparable with the at-discharge model for all four algorithms. SVM with Polynomial Kernel algorithms outperformed all other algorithms for at-admission and at-discharge models. Important features associated with increased readmission risk varied widely across the type of prediction model and were mostly related to patients’ demographics, social determinates, clinical factors, and hospital characteristics. Proposed at-admission readmission risk decision support model could help hospitals and providers with additional time for intervention planning, particularly for those targeting social determinants of children’s overall health.

Estimation of Flow Discharge Model at Temef Watershed - East Nusa Tenggara Using TRMM Satellite Data

Data collection based on satellite TRMM (Tropical Rainfall Measuring Mission) presents one of the good alternatives in estimating rainfall. TRMM technology can minimize manual rainfall recording errors and improve rainfall accuracy for hydrological analysis. The analysis method used in this research is divided into 3 (three) stages, namely Hydrology analysis, Statistical Analysis and Artificial Neural Network Analysis. From the results of TRMM JAXA analysis in the Temef Watershed Area of East Nusa Tenggara Province obtained TRMM JAXA satellite rainfall relationship to observation data shows rainfall patterns between the two data are interconnected but for cases with very high observation rainfall, TRMM rainfall data tends to be low. From statistical method analysis, the relationship between observation rainfall and TRMM JAXA rainfall obtained results with a "Very Strong" interpretation indicated by the results of 9 years calibration and 1 year validation where the selected equation is a polynomial equation (y=-0,0123x2 + 1,5553x + 20,222). Rain data correction results simulated with Debit data to see the relationship between rain and discharge that occurred, this analysis using Artificial Neural Network with Backpropagation method, the results showed a "Strong" interpretation where statistically the value of Nash-Sutcliffe Efficiency (NSE) 0.920, the coefficient value of correlation of field discharge and TRMM rainfall is 0,877 % and the relative error occurred is 2,62%

Theoretical Study on Characteristics of Glow Discharged Neon Gas and Its Interaction With Terahertz Waves

Discharge gases have been used to detect terahertz (THz) waves, however, there are few relevant theoretical studies. The neon glow discharge model is established by COMSOL Multiphysics software, the characteristics of glow discharged neon and the interaction of the discharged gas with THz waves were investigated. The results show that with the increase of THz wave’s frequency, the transmittance increases, the change of plasma discharge characteristics caused by THz wave can be used for THz wave detection. The results provide a theoretical basis for the development of cheap, room temperature THz wave detector with fast response speed, and high sensitivity.

Drives

This chapter is concerned with Nietzsche’s mature notion of drives. After some preliminary considerations on Nietzsche’s usage of the term ‘drive’, it considers the conception of drives held by Schopenhauer and by Georg Schneider, whose work is the most important scientific source on which Nietzsche relies to elaborate his psychology of drives. It then moves on to Nietzsche’s own views about drives, investigating how such views emerge by the time he was working on Daybreak and how he later attempts to refine them by engaging with Schneider’s work in 1883. This refinement results in the notion of drives that Nietzsche employs more or less consistently in his mature works: drives are behavioural dispositions; they are genuinely psychological/mental (evaluative); and due to their urging nature Nietzsche conceives of them according to a proto-Freudian discharge model. The chapter also addresses the relation Nietzsche sometimes attempts to draw between the notion of ‘drive’ and that of ‘will to power’.

Validation of GRACE and GRACE-FO Mascon Data for the Study of Polar Motion Excitation

In this study, we calculate the hydrological plus cryospheric excitation of polar motion (hydrological plus cryospheric angular momentum, HAM/CAM) using mascon solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We compare and evaluate HAM/CAM computed from GRACE and GRACE-FO mascon data provided by the Jet Propulsion Laboratory (JPL), the Center for Space Research (CSR), and the Goddard Space Flight Center (GSFC). A comparison with HAM obtained from the Land Surface Discharge Model is also provided. An analysis of HAM/CAM and HAM is performed for overall variability, trends, and seasonal and non-seasonal variations. The HAM/CAM and HAM estimates are validated using the geodetic residual time series (GAO), which is an estimation of the hydrological plus cryospheric signal in geodetically observed polar motion excitation. In general, all mascon datasets are found to be equally suitable for the determination of overall, seasonal, and non-seasonal HAM/CAM oscillations, but some differences in trends remain. The use of an ellipsoidal correction, implemented in the newest solution from CSR, does not noticeably affect the consistency between HAM/CAM and GAO. Analysis of the data from the first two years of the GRACE-FO mission indicates that the current accuracy of HAM/CAM from GRACE-FO mascon data meets expectations, and the root mean square deviation of HAM/CAM components are between 5 and 6 milliarcseconds. The findings from this study can be helpful in assessing the role of satellite gravimetry in polar motion studies and may contribute towards future improvements to GRACE-FO data processing.