Streamline Integration using MPI-Hybrid Parallelism on a Large Multi-Core Architecture

Streamline computation in a very large vector field data set represents a significant challenge due to the non-local and datadependentnature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programmingand execution as applied to streamline integration on a large, multicore platform. With multi-core processors now prevalent in clustersand supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice.We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize-over-seeds and parallelize-overblocks,and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing betweencores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication andI/O bandwidth than a traditional, non-hybrid distributed implementation

Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas. ©2019. The Authors

Substantial Differences in Crop Yield Sensitivities Between Models Call for Functionality‐Based Model Evaluation

Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to understand differences in simulated responses per driver and their combinations rather than aggregated changes in yields as the result of simultaneous changes in various drivers. We find that models' sensitivities to the individual drivers are substantially different and often more different across models than across regions. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response types across models and their configurations suggests that models need to undergo further scrutiny. We suggest establishing standards in model evaluation based on emergent functionality not only against historical yield observations but also against dedicated experiments across different drivers to analyze emergent functional patterns of crop models

Women’s Fertility and Employment Decisions Under Two Political Systems – Comparing East and West Germany Before Reunification

Over the last decades fertility rates have decreased in most developed countries, while female labour force participation has increased strongly over the same time period. To shed light on the relationship between women's fertility and employment decisions, we analyse their transitions to the first, second, and third child as well as their employment discontinuities following childbirth. Using new longitudinal datasets that cover the work and family life of women in the Federal Republic of Germany (FRG) and the German Democratic Republic (GDR) allows for taking into account two political regimes and drawing conclusions about the relevance of institutional factors for fertility and employment decisions. Our results suggest that in both parts of Germany women's probability of having a first child is negatively correlated with both employment and educational achievement. Regarding second and third birth risks, this negative correlation weakens. Analysing women's time spent out of the labour market following childbirth we find that in the East almost all mothers return to work within 18 months after birth. In the West, however, this proportion is much smaller and at the age when the child starts nursery school or school, women re-enter the labour market at higher rates. These results point to a strong influence of institutional circumstances, specifically the extent of public daycare provision. A multivariate analysis reveals a strong correlation between a woman's employment status prior to birth and her probability of re-entering the labour market afterwards

Occam's Razor and Petascale Visual Data Analysis

One of the central challenges facing visualization research is how to effectively enable knowledge discovery. An effective approach will likely combine application architectures that are capable of running on today?s largest platforms to address the challenges posed by large data with visual data analysis techniques that help find, represent, and effectively convey scientifically interesting features and phenomena

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Climate control of terrestrial carbon exchange across biomes and continents

Peer reviewe