Is there any Evidence for Regional Atmospheric 14C Offsets in the Southern Hemisphere?

Center for Accelerator Mass Spectrometry (CAMS) Tasmanian huon pine (Lagarostrobos franklinii) decadal measurements for the interval AD 745–855 suggest a mean interhemispheric radiocarbon offset (20 ± 5 yr), which is considerably lower than the previously reported mean interhemispheric offset for the last 2 millennia (44 ± 17 yr). However, comparable University of Waikato (Wk) New Zealand kauri (Agathis australis) measurements show significantly higher values (56 ± 6 yr), suggesting the possibility of a temporary geographic (intrahemispheric) offset between Tasmania, Australia, and Northland, New Zealand, during at least 1 common time interval. Here, we report 9 new Wk Tasmanian huon pine measurements from the decades showing the largest huon/kauri difference. We show statistically indistinguishable Wk huon and Wk kauri 14C ages, thus dispelling the suggestion of a 14C geographic offset between Tasmania and Northland

Inter-decadal climate variability in the Southern Hemisphere: evidence from Tasmanian tree rings over the past three millennia

EXTRACT (SEE PDF FOR FULL ABSTRACT): The characterization of inter-decadal climate variability in the Southern Hemisphere is severely constrained by the shortness of the instrumental climate records. To help relieve this constraint, we have developed and analyzed a reconstruction of warm-season (November-April) temperatures from Tasmanian tree rings that now extends back to 800 BC. A detailed analysis of this reconstruction in the time and frequency domains indicates that much of the inter-decadal variability is principally confined to four frequency bands with mean periods of 31, 57, 77, and 200 years. ... In so doing, we show how a future greenhouse warming signal over Tasmania could be masked by these natural oscillations unless they are taken into account

Game and training load differences in elite junior Australian football

Game demands and training practices within team sports such as Australian football (AF) have changed considerably over recent decades, including the requirement of coaching staff to effectively control, manipulate and monitor training and competition loads. The purpose of this investigation was to assess the differences in external and internal physical load measures between game and training in elite junior AF. Twenty five male, adolescent players (mean ±SD: age 17.6 ± 0.5 y) recruited from three elite under 18 AF clubs participated. Global positioning system (GPS), heart rate (HR) and rating of perceived exertion (RPE) data were obtained from 32 game files during four games, and 84 training files during 19 training sessions. Matched-pairs statistics along with Cohen\u27s d effect size and percent difference were used to compare game and training events. Players were exposed to a higher physical load in the game environment, for both external (GPS) and internal (HR, Session-RPE) load parameters, compared to in-season training. Session time (d = 1.23; percent difference = 31.4% (95% confidence intervals = 17.4 - 45.4)), total distance (3.5; 63.5% (17.4 - 45.4)), distance per minute (1.93; 33.0% (25.8 - 40.1)), high speed distance (2.24; 77.3% (60.3 - 94.2)), number of sprints (0.94; 43.6% (18.9 - 68.6)), mean HR (1.83; 14.3% (10.5 - 18.1)), minutes spent above 80% of predicted HRmax (2.65; 103.7% (89.9 - 117.6)) and Session-RPE (1.22; 48.1% (22.1 - 74.1)) were all higher in competition compared to training. While training should not be expected to fully replicate competition, the observed differences suggest that monitoring of physical load in both environments is warranted to allow comparisons and evaluate whether training objectives are being met. Key pointsPhysical loads, including intensity, are typically lower in training compared to competition in junior elite Australian football.Monitoring of player loads in team sports should include both internal and external measures.Selected training drills should look to replicate game intensities, however training is unlikely to match the overall physical demands of competition

Paleoclimate histories improve access and sustainability in index insurance programs

Proxy-based climate reconstructions can extend instrumental records by hundreds of years, providing a wealth of climate information at high temporal resolution. To date, however, their usefulness for informing climate risk and variability in policy and social applications has been understudied. Here, we apply tree-ring based reconstructions of drought for the last 700 years in a climate index insurance framework to show that additional information from long climate reconstructions significantly improves our understanding of the underlying climate distributions and variability. We further show that this added information can be used to better characterize risk to insurance providers, in many cases providing meaningful reductions in long-term contract costs to farmers in stand-alone policies. The impact of uncertainty on insurance premiums can also be reduced when insurers diversify portfolios, and the availability of long-term climate information from tree rings across a broad geographic range provides an opportunity to characterize spatial correlation in climate risk across geographic regions. Our results are robust to the range of climate variability experienced over the last 400 years and in model simulations of the twenty-first century, even within the context of changing baselines due to low frequency variability and secular climate trends. These results demonstrate the utility of longer-term climate histories in index insurance applications. Furthermore, they make the case from a climate-variability perspective for the continued importance of such approaches to improving the instrumental climate record, even into a non-stationary climate future

Paleoclimate histories improve access and sustainability in index insurance programs

Proxy-based climate reconstructions can extend instrumental records by hundreds of years, providing a wealth of climate information at high temporal resolution. To date, however, their usefulness for informing climate risk and variability in policy and social applications has been understudied. Here, we apply tree-ring based reconstructions of drought for the last 700 years in a climate index insurance framework to show that additional information from long climate reconstructions significantly improves our understanding of the underlying climate distributions and variability. We further show that this added information can be used to better characterize risk to insurance providers, in many cases providing meaningful reductions in long-term contract costs to farmers in stand-alone policies. The impact of uncertainty on insurance premiums can also be reduced when insurers diversify portfolios, and the availability of long-term climate information from tree rings across a broad geographic range provides an opportunity to characterize spatial correlation in climate risk across geographic regions. Our results are robust to the range of climate variability experienced over the last 400 years and in model simulations of the twenty-first century, even within the context of changing baselines due to low frequency variability and secular climate trends. These results demonstrate the utility of longer-term climate histories in index insurance applications. Furthermore, they make the case from a climate-variability perspective for the continued importance of such approaches to improving the instrumental climate record, even into a non-stationary climate future

Novel genetic markers improve measures of atrial fibrillation risk prediction

Aims Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. Methods and results We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684–0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709–0.774); P = 0.001], the category-less net reclassification [0.490 (0.301–0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033–0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1–5, and 5+% [0.041 (−0.044–0.12); P = 0.33]. Conclusion: Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categories

Drivers and Barriers to Rural Bioenergy Entrepreneurships - The Case of Biogas in Vietnam

Poverty reduction, first on the list of Millennium Development Goals, requires access to modernized, stable energy to be realized. Rural areas are especially vulnerable, which is why renewable energy technologies (RETs) illustrate a promising solution for modernized energy access. Entrepreneurs play an important role in these sustainable development projects by helping build up an entire sector of services. Acting as indicators for a project s stability, entrepreneurs provide a needed service (energy) while stimulating the local economy. In order to realize their potential, drivers and barriers are to be identified to assess their current situation. Entrepreneurs in Vietnam have had limited time to develop in this contemporary age, however, rapid changes have been occurring they have emerged as key movers in rural bioenergy. This thesis looks at Biogas in Vietnam as a case study towards understanding the key drivers and barriers to bioenergy entrepreneurs in rural areas and their project dissemination models. The project's surveys rural bioenergy entrepreneurs, households and key informants in the projects. The purpose of this study is to explore what critical factors to bring about the creation of a new business in the developing rural energy sector by identifying the key drivers and barriers to biogas entrepreneurs and the dissemination approaches of each case s development project. Using several analytical frameworks, two programs are analyzed, the Biogas Programme and the Vietnamese Women s Union s (VWU) energy project, with three separate cases conducted in the northern part of Vietnam. The study highlights drivers and barriers and compares dissemination models to aid future research, while making important recommendations for future rural bioenergy entrepreneurs

Novel genetic markers improve measures of atrial fibrillation risk prediction

Aims Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. Methods and results We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684-0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709-0.774); P = 0.001], the category-less net reclassification [0.490 (0.301-0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033-0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1-5, and 5+% [0.041 (−0.044-0.12); P = 0.33]. Conclusion Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categorie

Rates of convergence for the continuum limit of nondominated sorting

Nondominated sorting is a discrete process that sorts points in Euclidean space according to the coordinatewise partial order, and is used to rank feasible solutions to multiobjective optimization problems. It was previously shown that nondominated sorting of random points has a Hamilton-Jacobi equation continuum limit. We prove quantitative error estimates for the convergence of nondominated sorting to its continuum limit Hamilton-Jacobi equation. Our proof uses the maximum principle and viscosity solution machinery, along with new semiconvexity estimates for domains with corner singularities