A hiatus in the stratosphere?

Rapid CommunicationCopyright © 2015 Nature Publishing GroupTo the Editor — Since the turn of the twenty-first century there has been a hiatus in the cooling of the lower stratosphere (Fig. 1a). This 'stratospheric hiatus' is happening at the same time as the well-documented hiatus in global surface warming1, during a time of increasing CO2 concentrations ('Surface' line in Fig. 1a). Although CO2 acts to warm the surface and troposphere by decreasing outgoing radiative flux at the tropopause, it cools the stratosphere by increasing net infrared emission, so we might expect the continued increase in CO2 concentrations to have produced lower-stratospheric cooling, as observed through much of the depth of the stratosphere2. Why, then, do we observe a hiatus in the lower stratosphere?NER

Ten Years of Experience Training Non-Physician Anesthesia Providers in Haiti.

Surgery is increasingly recognized as an effective means of treating a proportion of the global burden of disease, especially in resource-limited countries. Often non-physicians, such as nurses, provide the majority of anesthesia; however, their training and formal supervision is often of low priority or even non-existent. To increase the number of safe anesthesia providers in Haiti, Médecins Sans Frontières has trained nurse anesthetists (NAs) for over 10 years. This article describes the challenges, outcomes, and future directions of this training program. From 1998 to 2008, 24 students graduated. Nineteen (79%) continue to work as NAs in Haiti and 5 (21%) have emigrated. In 2008, NAs were critical in providing anesthesia during a post-hurricane emergency where they performed 330 procedures. Mortality was 0.3% and not associated with lack of anesthesiologist supervision. The completion rate of this training program was high and the majority of graduates continue to work as nurse anesthetists in Haiti. Successful training requires a setting with a sufficient volume and diversity of operations, appropriate anesthesia equipment, a structured and comprehensive training program, and recognition of the training program by the national ministry of health and relevant professional bodies. Preliminary outcomes support findings elsewhere that NAs can be a safe and effective alternative where anesthesiologists are scarce. Training non-physician anesthetists is a feasible and important way to scale up surgical services resource limited settings

Survival Analysis Part I: Basic concepts and first analyses

Survival analysis is a collection of statistical procedures for data analysis where the outcome variable of interest is time until an event occurs. Because of censoring - the nonobservation of the event of interest after a period of follow-up - a proportion of the survival times of interest will often be unknown. It is assumed that those patients who are censored have the same survival prospects as those who continue to be followed, that is, the censoring is uninformative. Survival data are generally described and modelled in terms of two related functions, the survivor function and the hazard function. The survivor function represents the probability that an individual survives from the time of origin to some time beyond time t. It directly describes the survival experience of a study cohort, and is usually estimated by the KM method. The logrank test may be used to test for differences between survival curves for groups, such as treatment arms. The hazard function gives the instantaneous potential of having an event at a time, given survival up to that time. It is used primarily as a diagnostic tool or for specifying a mathematical model for survival analysis. In comparing treatments or prognostic groups in terms of survival, it is often necessary to adjust for patient-related factors that could potentially affect the survival time of a patient. Failure to adjust for confounders may result in spurious effects. Multivariate survival analysis, a form of multiple regression, provides a way of doing this adjustment, and is the subject the next paper in this series

Volatility forecasting in the Chinese commodity futures market with intraday data

Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms

Measuring and Modeling Risk Using High-Frequency Data

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns. In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures of systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorporation and of the DJIA index

A common framework for approaches to extreme event attribution

The extent to which a given extreme weather or climate event is attributable to anthropogenic climate change is a question of considerable public interest. From a scientific perspective, the question can be framed in various ways, and the answer depends very much on the framing. One such framing is a risk-based approach, which answers the question probabilistically, in terms of a change in likelihood of a class of event similar to the one in question, and natural variability is treated as noise. A rather different framing is a storyline approach, which examines the role of the various factors contributing to the event as it unfolded, including the anomalous aspects of natural variability, and answers the question deterministically. It is argued that these two apparently irreconcilable approaches can be viewed within a common framework, where the most useful level of conditioning will depend on the question being asked and the uncertainties involved

A new approach to bad news effects on volatilit y: the multiple-sign-volume sensitive regime EGARCH model (MSV-EGARCH)

In this paper, using daily data for six major international stock market indexes and a modified EGARCH specification, the links between stock market returns, volatility and trading volume are investigated in a new nonlinear conditional variance framework with multiple regimes and volume eff ects. Volatility forecast comparisons, using the Harvey-Newbold test for multiple forecasts encompassing, seem to demonstrate that the MSV- EGARCH complex threshold structure is able to correctly fit GARCH- type dynamics of the series under study and dominates competing standard asymmetric models in several of the considered stock indexes.info:eu-repo/semantics/publishedVersio

Asymmetry, realised volatility and stock return risk estimates

In this paper we estimate minimum capital risk requirements for short and long positions with three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes. We also address the problem of the extremely high estimated persistence of the GARCH model to generate observed volatility patterns by including realised volatility as an explanatory variable into the model’s variance equation. The results suggest that the inclusion of realised volatility improves the GARCH forecastability as well as its ability to calculate accurate minimum capital risk requirements and makes it quite competitive when compared with asymmetric conditional heteroscedastic models such as the GJR and the EGARCH.info:eu-repo/semantics/publishedVersio

Low correlation between visit-to-visit variability and 24-h variability of blood pressure

Visit-to-visit variability (VVV) of clinic systolic blood pressure (SBP) has been associated with cardiovascular disease risk. Given the need for obtaining blood pressure (BP) at multiple visits to calculate VVV, substituting BP variability from ambulatory blood pressure monitoring (ABPM) may be a practical alternative. We assessed the correlation between VVV of BP and BP variability from ABPM using data from 146 untreated, mostly normotensive participants (mean age 47.9 years) in a substudy of the ongoing Masked Hypertension Study. VVV of SBP and diastolic blood pressure (DBP) was estimated by the standard deviation (SDvvv) and average real variability (ARVvvv) from 6 study visits over a median of 216 days. ABPM data were used to calculate the day-night SD (SDdn) and the ARV of SBP and DBP over 24 hours (ARV24). For SBP, the mean SDvvv and SDdn were 6.3 (SD=2.5) and 8.8 (SD=1.8) mmHg, respectively, and mean ARVvvv and ARV24 were 7.2 (SD=3.2) and 8.4 (SD=2.1) mmHg, respectively. The Spearman correlation coefficient between SDvvv and SDdn of SBP was rs=0.25 and between ARVvvv and ARV24 was rs=0.17. Participants in the highest quartile of SDdn of SBP were 1.66 (95% CI: 0.93 – 2.75) times more likely to be in the highest quartile of SDvvv of SBP. The observed-to-expected ratio between the highest quartiles of ARVvvv and ARV24 of SBP was 0.89 (95% CI: 0.41 – 1.69). The correlations for SDvvv and SDdn and ARVvvv and ARV24 of DBP were minimal. These data suggest VVV and 24-hour variability are weakly correlated and not interchangeable