To See without Being Seen: Contemporary Art and Drone Warfare

Review of To See without Being Seen: Contemporary Art and Drone Warfare, Reviewed November 2016 by Ryan McNally, Technical Services Librarian, Philadelphia Museum of Art Library & Archives, [email protected]

UnderConsideration

Review of UnderConsideration, Reviewed August 2015 by Ryan McNally, Cataloging and Electronic Services Librarian Philadelphia Museum of Art [email protected]

Common Grounds

Review of Common Grounds, Reviewed November 2015 by Ryan McNally, Cataloging and Electronic Services Librarian, Philadelphia Museum of Art Library, [email protected]

HrcU and HrpP are pathogenicity factors in the fire blight pathogen Erwinia amylovora required for the type III secretion of DspA/E

Table S1. Description of data: Sequences of oligonucleotide primers used in this study. (DOCX 109 kb

Executive Functioning, Treatment Adherence, and Glycemic Control in Children With Type 1 Diabetes

The primary aim of the study was to investigate the relationship among executive functioning, diabetes treatment adherence, and glycemic control. Two hundred and thirty-five children with type 1 diabetes and their primary caregivers were administered the Diabetes Self-Management Profile to assess treatment adherence. Executive functioning was measured using the Behavior Rating Inventory of Executive Functioning and glycemic control was based on A1C. Structural equation modeling indicated that a model in which treatment adherence mediated the relationship between executive functioning and glycemic control best fit the data. All paths were significant at P < 0.01. These results indicate that executive functioning skills (e.g., planning, problem-solving, organization, and working memory) were related to adherence, which was related to diabetes control. Executive functioning may be helpful to assess in ongoing clinical management of type 1 diabetes

Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases, like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number $R_0$. However, understanding the mechanisms linking $R_0$ and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this we show how a Bayesian approach can help identify critical uncertainties in components of $R_0$ and how this uncertainty is propagated into the estimate of $R_0$. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15-25$^\circ$ C; fecundity across all temperatures, but especially $\sim$25-32$^\circ$ C; mortality from 20-30$^\circ$ C; parasite development rate at $\sim$15-16$^\circ$C and again at $\sim$33-35$^\circ$C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of $R_0$. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.Comment: 27 pages, including 1 table and 3 figure

Mapping Physiological Suitability Limits for Malaria in Africa Under Climate Change

We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control