VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, ...process‐based, etc.). Here we describe the participating methods and first results from the first experiment, using “perfect” reanalysis (and reanalysis‐driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques.
Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method‐to‐method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor–predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO‐CORDEX initiative (where VALUE activities have merged and follow on).
Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value‐cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value‐cost.eu/validationportal.
The largest and most comprehensive to date intercomparison of statistical downscaling methods is presented, with a total of over 50 downscaling methods representative of the most common approaches and techniques. Overall, most of the downscaling methods greatly improve raw model biases and no approach is superior in general, due to the large method‐to‐method variability. The main factors influencing the results are the seasonal calibration of the methods and their stochastic nature, for biases in the mean and variance.
Accurate knowledge of the charge and Zemach radii of the proton is essential, not only for understanding its structure but also as input for tests of bound-state quantum electrodynamics and its ...predictions for the energy levels of hydrogen. These radii may be extracted from the laser spectroscopy of muonic hydrogen (μp, that is, a proton orbited by a muon). We measured the $2{\mathrm{S}}_{1/2}^{\mathrm{F}=0}-2{\mathrm{P}}_{3/2}^{\mathrm{F}=1}$ transition frequency in μp to be 54611.16(1.05) gigahertz (numbers in parentheses indicate one standard deviation of uncertainty) and reevaluated the $2{\mathrm{S}}_{1/2}^{\mathrm{F}=1}-2{\mathrm{P}}_{3/2}^{\mathrm{F}=1}$ transition frequency, yielding 49881.35(65) gigahertz. From the measurements, we determined the Zemach radius, r Z = 1.082(37) femtometers, and the magnetic radius, r M = 0.87(6) femtometer, of the proton. We also extracted the charge radius, r E = 0.84087(39) femtometer, with an order of magnitude more precision than the 2010-CODATA value and at 7σ variance with respect to it, thus reinforcing the proton radius puzzle.
In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with ...different configurations in microphysics, convection and radiation for the time period 1990–2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell–Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max −2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40–60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (−2.8 °C); this location suggests that land–atmosphere rather than cloud–radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain–Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15–30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.
Induction motors (IMs) are widely used in industrial applications due to their advantages over other motor types. However, the efficiency and lifespan of IMs can be significantly impacted by ...operating conditions, especially Unbalanced Supply Voltages (USV), which are common in industrial plants. Detecting and accurately assessing the severity of USV in real-time is crucial to prevent major breakdowns and enhance reliability and safety in industrial facilities. This paper presented a reliable method for precise online detection of USV by monitoring a relevant indicator, denominated by negative voltage factor (NVF), which, in turn, is obtained using the voltage symmetrical components. On the other hand, impedance estimation proves to be fundamental to understand the behavior of motors and identify possible problems. IM impedance affects its performance, namely torque, power factor and efficiency. Furthermore, as the presence of faults or abnormalities is manifested by the modification of the IM impedance, its estimation is particularly useful in this context. This paper proposed two machine learning (ML) models, the first one estimated the IM stator phase impedance, and the second one detected USV conditions. Therefore, the first ML model was capable of estimating the IM phases impedances using just the phase currents with no need for extra sensors, as the currents were used to control the IM. The second ML model required both phase currents and voltages to estimate NVF. The proposed approach used a combination of a Regressor Decision Tree (DTR) model with the Short Time Least Squares Prony (STLSP) technique. The STLSP algorithm was used to create the datasets that will be used in the training and testing phase of the DTR model, being crucial in the creation of both features and targets. After the training phase, the STLSP technique was again used on completely new data to obtain the DTR model inputs, from which the ML models can estimate desired physical quantities (phases impedance or NVF).
We perform a low-mass dark matter search using an exposure of 30 kg×yr with the XENON100 detector. By dropping the requirement of a scintillation signal and using only the ionization signal to ...determine the interaction energy, we lowered the energy threshold for detection to 0.7 keV for nuclear recoils. No dark matter detection can be claimed because a complete background model cannot be constructed without a primary scintillation signal. Instead, we compute an upper limit on the WIMP-nucleon scattering cross section under the assumption that every event passing our selection criteria could be a signal event. Using an energy interval from 0.7 keV to 9.1 keV, we derive a limit on the spin-independent WIMP-nucleon cross section that excludes WIMPs with a mass of 6 GeV/c2 above 1.4×10−41 cm2 at 90% confidence level.
In most of the Americas, the recommended treatment to prevent relapse of
malaria is primaquine at a total dose of 3.5 mg per kilogram of body weight, despite evidence of only moderate efficacy.
In ...this trial conducted in Brazil, we evaluated three primaquine regimens to prevent relapse of
malaria in children at least 5 years of age and in adults with microscopy-confirmed
monoinfection. All the patients received directly observed chloroquine for 3 days (total dose, 25 mg per kilogram). Group 1 received a total primaquine dose of 3.5 mg per kilogram (0.5 mg per kilogram per day) over 7 days with unobserved administration; group 2 received the same regimen as group 1 but with observed administration; and group 3 received a total primaquine dose of 7.0 mg per kilogram over 14 days (also 0.5 mg per kilogram per day) with observed administration. We monitored the patients for 168 days.
We enrolled 63 patients in group 1, 96 in group 2, and 95 in group 3. The median age of the patients was 22.4 years (range, 5.4 to 79.8). By day 28, three
recurrences were observed: 2 in group 1 and 1 in group 2. By day 168, a total of 70 recurrences had occurred: 24 in group 1, 34 in group 2, and 12 in group 3. No serious adverse events were noted. On day 168, the percentage of patients without recurrence was 58% (95% confidence interval CI, 44 to 70) in group 1, 59% (95% CI, 47 to 69) in group 2, and 86% (95% CI, 76 to 92) in group 3. Survival analysis showed a difference in the day 168 recurrence-free percentage of 27 percentage points (97.5% CI, 10 to 44; P<0.001) between group 1 and group 3 and a difference of 27 percentage points (97.5% CI, 12 to 42; P<0.001) between group 2 and group 3.
The administration of primaquine at a total dose of 7.0 mg per kilogram had higher efficacy in preventing relapse of
malaria than a total dose of 3.5 mg per kilogram through day 168. (Supported by the U.S. Agency for International Development; ClinicalTrials.gov number, NCT03610399.).
The aim of this study was to evaluate the therapeutic effects of ultrasound (US)-mediated phonophoresis alone or in association with diclofenac diethylammonium (DCF) administered topically in animal ...models of inflammation. A pre-clinical, prospective, and randomized experimental study of quantitative and qualitative nature was carried out. Phonophoresis was performed using a therapeutic ultrasound apparatus in two distinct models of acute inflammation. Edema was induced by an intraplantar injection of carrageenan and measured by plethysmography. The Hargreaves test was used to evaluate the antinociceptive activity and investigate the action of phonophoresis on tumor necrosis factor (TNF)-α production. A histological analysis with hematoxylin-eosin was used to evaluate tissue repair, and the expression of COX-2 was determined by immunohistochemical analysis. At the peak of inflammatory activity (3 h), treatment with US, US+DCF, and DCF significantly reduced edema formation compared to the control group. Treatment with US+DCF was more effective than treatment with US alone at both analyzed times. In the analysis of the antinociceptive activity, the treatments significantly increased the latency time in response to the thermal stimulus. Histopathological analysis revealed a reduction of the inflammatory infiltrates and immunohistochemistry demonstrated that the association was effective in reducing COX-2 expression compared to the control group. The association of DCF with US produced anti-inflammatory and antinociceptive effects in rat models of inflammation, which may be associated with inhibition of COX-2 and TNF-α production.
Abstract Background Although most patients in the PARADIGM-HF (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) trial had mild ...symptoms, there is a poor correlation between reported functional limitation and prognosis in heart failure. Objectives The aim of this study was to examine the spectrum of risk in PARADIGM-HF and the effect of LCZ696 across that spectrum. Methods This study analyzed rates of the primary composite outcome of cardiovascular death or heart failure hospitalization, its components, and all-cause mortality using the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure) and EMPHASIS-HF (Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure) risk scores to categorize patients. The authors determined whether risk, on the basis of these scores, modified the treatment effect of LCZ696. Results The complete MAGGIC risk score was available for 8,375 of the 8,399 patients in PARADIGM-HF. The median MAGGIC score was 20 (IQR: 16 to 24). An increase of 1 point was associated with a 6% increased risk for the primary endpoint (p < 0.001) and a 7% increased risk for cardiovascular death (p < 0.001). The benefit of LCZ696 over enalapril for the primary endpoint was similar across the spectrum of risk (p = 0.159). Treating 100 patients for 2 years with LCZ696 instead of enalapril led to 7 fewer patients in the highest quintile of risk experiencing primary outcomes, compared with 3 in the lowest quintile. Analyses using the EMPHASIS-HF risk score gave similar findings. Conclusions Although most PARADIGM-HF patients had mild symptoms, many were at high risk for adverse outcomes and obtained a large absolute benefit from LCZ696, compared with enalapril, over a relatively short treatment period. LCZ696’s benefit was consistent across the spectrum of risk. (PARADIGM-HF trial Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure; NCT01035255 )
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