A Review of Previous Research in Direct Energy Conversion Fission Reactors

From the earliest days of power reactor development, direct energy conversion was an obvious choice to produce high efficiency electric power generation. Directly capturing the energy of the fission fragments produced during nuclear fission avoids the intermediate conversion to thermal energy and the efficiency limitations of classical thermodynamics. Efficiencies of more than 80% are possible, independent of operational temperature. Direct energy conversion fission reactors would possess a number of unique characteristics that would make them very attractive for commercial power generation. These reactors would be modular in design with integral power conversion and operate at low pressures and temperatures. They would operate at high efficiency and produce power well suited for long distance transmission. They would feature large safety margins and passively safe design. Ideally suited to production by advanced manufacturing techniques, direct energy conversion fission reactors could be produced more economically than conventional reactor designs. The history of direct energy conversion can be considered as dating back to 1913 when Moseleyl demonstrated that charged particle emission could be used to buildup a voltage. Soon after the successful operation of a nuclear reactor, E.P. Wigner suggested the use of fission fragments for direct energy conversion. Over a decade after Wigner's suggestion, the first theoretical treatment of the conversion of fission fragment kinetic energy into electrical potential appeared in the literature. Over the ten years that followed, a number of researchers investigated various aspects of fission fragment direct energy conversion. Experiments were performed that validated the basic physics of the concept, but a variety of technical challenges limited the efficiencies that were achieved. Most research in direct energy conversion ceased in the US by the late 1960s. Sporadic interest in the concept appears in the literature until this day, but there have been no recent significant programs to develop the technology

Recent Patterns in Population-Based HIV Prevalence in Swaziland

Background: The 2011 Swaziland HIV Incidence Measurement Survey (SHIMS) was conducted as part of a national study to evaluate the scale up of key HIV prevention programs. Methods: From a randomly selected sample of all Swazi households, all women and men aged 18-49 were considered eligible, and all consenting adults were enrolled and received HIV testing and counseling. In this analysis, population-based measures of HIV prevalence were produced and compared against similarly measured HIV prevalence estimates from the 2006-7 Swaziland Demographic and Health. Also, measures of HIV service utilization in both HIV infected and uninfected populations were documented and discussed. Results: HIV prevalence among adults aged 18-49 has remained unchanged between 2006-2011 at 31-32%, with substantial differences in current prevalence between women (39%) and men (24%). In both men and women, between since 2006-7 and 2011, prevalence has fallen in the young age groups and risen in the older age groups. Over a third (38%) of the HIV-infected population was unaware of their infection status, and this differed markedly between men (50%) and women (31%). Of those aware of their HIV-positive status, a higher percentage of men (63%) than women (49%) reported ART use. Conclusions: While overall HIV prevalence remains roughly constant, age-specific changes strongly suggest both improved survival of the HIV-infected and a reduction in new HIV infections. Awareness of HIV status and entry into ART services has improved in recent years but remains too low. This study identifies opportunities to improve both HIV preventive and care services in Swaziland

Endogenous Risks and Learning in Climate Change Decision Analysis

We analyze the effects of risks and learning on climate change decisions. A two-stage, dynamic, climate change stabilization problem is formulated. The explicit incorporation of ex-post learning induces risk aversion among ex-ante decisions, which is characterized in linear models by VaR- and CVaR-type risk measures. Combined with explicit introduction of "safety" constraints, it creates a "hit-or-miss" type decision-making situation and shows that, even in linear models, learning may lead to either less-or more restrictive ex-ante emission reductions. We analyze stylized elements of the model in order to identify the key factors driving outcomes, in particular, the critical role of quantiles of probability distributions characterizing key uncertainties

Prevalence of and factors associated with late diagnosis of HIV in Malawi, Zambia, and Zimbabwe: Results from population-based nationally representative surveys

Introduction Late diagnosis of HIV (LD) increases the risk of morbidity, mortality, and HIV transmission. We used nationally representative data from population-based HIV impact assessment (PHIA) surveys in Malawi, Zambia, and Zimbabwe (2015–2016) to characterize adults at risk of LD and to examine associations between LD and presumed HIV transmission to cohabiting sexual partners. Methods We estimated the prevalence of LD, defined as CD4 count <350 cells/μL, among adults newly diagnosed with HIV during the surveys and odds ratios for associated factors. We linked newly diagnosed adults (index cases) to their household sexual partners and calculated adjusted odds ratios for associations between LD of the index case, viral load of the index case, and duration of HIV exposure in the relationship, and the HIV status of the household sexual partner. Results Of 1,804 adults who were newly diagnosed with HIV in the surveys, 49% (882) were diagnosed late. LD was associated with male sex, older age, and almost five times the odds of having an HIV-positive household sexual partner (adjusted odds ratio [aOR], 4.65 [95% confidence interval: 2.56–8.45]). Longer duration of HIV exposure in a relationship and higher viral load of the index case were both independently associated with higher odds of having HIV-positive household sexual partners. Individuals with HIV exposure of more than 5 years had more than three times (aOR 3.42 [95% CI: 1.63–7.18]) higher odds of being HIV positive than those with less than 2 years HIV exposure. The odds of being HIV positive were increased in individuals who were in a relationship with an index case with a viral load of 400–3499 copies/mL (aOR 4.06 [95% CI 0.45–36.46]), 3,500–9,999 copies/mL (aOR 11.32 [95% CI: 4.08–31.39]), 10,000–49,999 copies/mL (aOR 17.07 [95% CI: 9.18–31.72]), and ≥50,000 copies/mL (aOR 28.41 [95% CI: 12.18–66.28]) compared to individuals who were in a relationship with an index case with a viral load of <400 copies/mL. Conclusions LD remains a challenge in Southern Africa and is strongly associated with presumed HIV transmission to household sexual partners. Our study underscores the need for earlier HIV diagnosis, particularly among men and older adults, and the importance of index testing

Disruption of semantic metwork in mild Alzheimer's disease revealed by resting-state fMRI

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing

Sequential climate change policy

Successfully managing global climate change will require a process of sequential, or iterative, decision‐making, whereby policies and other decisions are revised repeatedly over multiple decades in response to changes in scientific knowledge, technological capabilities, or other conditions. Sequential decisions are required by the combined presence of long lags and uncertainty in climate and energy systems. Climate decision studies have most often examined simple cases of sequential decisions, with two decision points at fixed times and initial uncertainties that are resolved at the second decision point. Studies using this formulation initially suggested that increasing uncertainty favors stronger immediate action, while the prospect of future learning favors weaker immediate action, but subsequent work with more general formulations showed that the direction of either effect is indeterminate, depending on multiple elements of model structure and parameter values. Current issues in sequential climate decision‐making include assessing responses to potential slow learning or negative learning, and examining the implications of various mechanisms by which current decision‐makers may seek to influence future decisions by altering the choice sets, knowledge states, marginal costs and benefits, or default procedural requirements faced by future decision‐makers. WIREs Clim Change 2011 2 744–756 DOI: 10.1002/wcc.128 For further resources related to this article, please visit the WIREs websitePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86798/1/128_ftp.pd

Optimal learning on climate change: Why climate skeptics should reduce emissions

Climate skeptics typically argue that the possibility that global warming is exogenous, implies that we should not take additional action towards reducing emissions until we know what drives warming. This paper however shows that even climate skeptics have an incentive to reduce emissions: such a directional change generates information on the causes of global warming. Since the optimal policy depends upon these causes, they are valuable to know. Although increasing emissions would also generate information, that option is inferior due its irreversibility. We show that optimality can even imply that climate skeptics should actually argue for lower emissions than believers

Genetics of Dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.Peer reviewe