The Advantage of Foraging Myopically

We study the dynamics of a \emph{myopic} forager that randomly wanders on a lattice in which each site contains one unit of food. Upon encountering a food-containing site, the forager eats all the food at this site with probability $p<1$; otherwise, the food is left undisturbed. When the forager eats, it can wander $\mathcal{S}$ additional steps without food before starving to death. When the forager does not eat, either by not detecting food on a full site or by encountering an empty site, the forager goes hungry and comes one time unit closer to starvation. As the forager wanders, a multiply connected spatial region where food has been consumed---a desert---is created. The forager lifetime depends non-monotonically on its degree of myopia $p$, and at the optimal myopia $p=p^*(\mathcal{S})$, the forager lives much longer than a normal forager that always eats when it encounters food. This optimal lifetime grows as $\mathcal{S}^2/\ln\mathcal{S}$ in one dimension and faster than a power law in $\mathcal{S}$ in two and higher dimensions.Comment: 10 pages, 1o figure

The Advantage of Foraging Myopically

We study the dynamics of a \emph{myopic} forager that randomly wanders on a lattice in which each site contains one unit of food. Upon encountering a food-containing site, the forager eats all the food at this site with probability $p<1$; otherwise, the food is left undisturbed. When the forager eats, it can wander $\mathcal{S}$ additional steps without food before starving to death. When the forager does not eat, either by not detecting food on a full site or by encountering an empty site, the forager goes hungry and comes one time unit closer to starvation. As the forager wanders, a multiply connected spatial region where food has been consumed---a desert---is created. The forager lifetime depends non-monotonically on its degree of myopia $p$, and at the optimal myopia $p=p^*(\mathcal{S})$, the forager lives much longer than a normal forager that always eats when it encounters food. This optimal lifetime grows as $\mathcal{S}^2/\ln\mathcal{S}$ in one dimension and faster than a power law in $\mathcal{S}$ in two and higher dimensions.Comment: 10 pages, 1o figure

Is there an independent effect of polycystic ovary syndrome (PCOS) and menopause on the prevalence of subclinical atherosclerosis in middle aged women?

Polycystic ovary syndrome (PCOS), a common reproductive endocrine condition manifests at puberty, and is characterized by hyperandrogenism, chronic anovulation, and obesity. PCOS cases exhibit an adverse coronary heart disease (CHD) profile at an early age, including insulin resistance, dyslipidemia and increased central adiposity. It can be hypothesized that the menopausal transition, whether natural or surgical, may provide an additional “insult”, resulting in greater cumulative risk to their vasculature. Coronary artery calcification (CAC), a measure of subclinical atherosclerosis (SCA), was measured by electron beam tomography in 149 PCOS cases and 166 controls (mean age 47.3 and 49.4 respectively). Cases had a higher prevalence of CAC (63.1%) compared to controls (41.0%), (p = 0.037) after adjustment for age and BMI. A total of 22 cases and 39 controls had undergone natural menopause, 12 cases and 26 controls underwent surgical menopause (with biochemical confirmation) and 115 cases and 101 controls reported being currently premenopausal. There was a significant difference in CAC values between cases and controls in all three-menopause categories including pre-menopausal, surgically induced and natural menopause (p < 0.001). Duration since menopause (years) and use of hormone replacement therapy were not different between cases and controls for the two menopause groups. Logistic regression was carried out with CAC ( ≤10 vs >10) as the dependent variable, and independent variables: PCOS status, current age, BMI, and menopausal status, (pre-menopause, surgical and natural menopause) and selected CHD risk factors. The data indicate that women with PCOS exhibit significantly increased CAC compared to controls after adjustment for age and BMI and menopausal status. PCOS status and fasting glucose were significant risk factors for CAC (p < 0.05). Both natural and surgical menopause were independent risk factors for CAC as well (p < 0.01). HDLT was of borderline significance, p < 0.10. Further follow-up of this cohort will be valuable in determining whether PCOS status continues to affect cardiovascular risk as they undergo the menopausal transition

Developing consistent data and methods to measure the public health impacts of ambient air quality for Environmental Public Health Tracking: progress to date and future directions

Environmental Public Health Tracking (EPHT) staff at the state and national levels are developing nationally consistent data and methods to estimate the impact of ozone and fine particulate matter on hospitalizations for asthma and myocardial infarction. Pilot projects have demonstrated the feasibility of pooling state hospitalization data and linking these data to The United States Environmental Protection Agency (EPA) statistically based ambient air estimates for ozone and fine particulates. Tools were developed to perform case-crossover analyses to estimate concentration–response (C-R) functions. A weakness of analyzing one state at a time is that the effects are relatively small compared to their confidence intervals. The EPHT program will explore ways to statistically combine the results of peer-reviewed analyses from across the country to provide more robust C-R functions and health impact estimates at the local level. One challenge will be to routinely share data for these types of analyses at fine geographic and temporal scales without disclosing confidential information. Another challenge will be to develop C-R estimates which take into account time, space, or other relevant effect modifiers

How can ski resorts get smart? Transdisciplinary approaches to sustainable winter tourism in the European Alps

Climate change and the call for reduction of greenhouse gas emissions, the efficient use of (renewable) energy, and more resilient winter tourism regions, forces ski resorts across the European Alps to look for \u201csmart\u201d approaches to transition towards a sustainable, low-carbon economy. Drawing on the smart-city concept and considering the different historical developments of Alpine resorts, the Smart Altitude Decision-Making Toolkit was developed using a combination of an energy audit tool, a WebGIS, and collaborative and innovative living labs installed in Les Orres (France), Madonna di Campiglio (Italy), Krvavec (Slovenia), and Verbier (Switzerland). This step-by-step Decision-Making Toolkit enables ski resorts to get feedback on their energy demand, an overview of the locally available sources of renewable energy, and insights regarding their potential for improving their energy efficiency by low-carbon interventions. The Decision-Making Toolkit is suitable for knowledge transfer between stakeholders within living labs and moreover provides the flexibility for tailor-made low-carbon strategies adapting to the unique assets and situatedness of ski resorts

Do US Ambient Air Lead Levels Have a Significant Impact on Childhood Blood Lead Levels: Results of a National Study

Introduction. Although lead paint and leaded gasoline have not been used in the US for thirty years, thousands of US children continue to have blood lead levels (BLLs) of concern. Methods. We investigated the potential association of modeled air lead levels and BLLs ≥ 10 μg/dL using a large CDC database with BLLs on children aged 0–3 years. Percent of children with BLLs ≥ 10 μg/dL (2000–2007) by county and proportion of pre-50 housing and SES variables were merged with the US EPA's National Air Toxics Assessment (NATA) modeled air lead data. Results. The proportion with BLL ≥ 10 μg/dL was 1.24% in the highest air lead counties, and the proportion with BLL ≥ 10 μg/dL was 0.36% in the lowest air lead counties, resulting in a crude prevalence ratio of 3.4. Further analysis using multivariate negative binomial regression revealed that NATA lead was a significant predictor of % BLL ≥ 10 μg/dL after controlling for percent pre-l950 housing, percent rural, and percent black. A geospatial regression revealed that air lead, percent older housing, and poverty were all significant predictors of % BLL ≥ 10 μg/dL. Conclusions. More emphasis should be given to potential sources of ambient air lead near residential areas