HIL: designing an exokernel for the data center

We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or

Foundations and Applications of Theory in the First Impressions Program

The First Impressions program was designed to help communities learn about their strengths and shortcomings through the fresh eyes of first-time visitors. This Extension-led community assessment program has been implemented in over 500 communities since the 1990s, yet scant literature exists regarding the program\u27s theoretical foundations or best practices for implementation or evaluation. To address increasing interest in the program among Extension professionals nationwide, we aim to encourage new scholarship regarding the program\u27s use and impacts by providing an overview of how the program works; a discussion of theoretical foundations of the program from geography, urban planning, and psychology literature; and suggestions for improving program efficacy

Negative mood reverses devaluation of goal-directed drug-seeking favouring an incentive learning account of drug dependence.

BACKGROUND: Two theories explain how negative mood primes smoking behaviour. The stimulus–response (S-R) account argues that in the negative mood state, smoking is experienced as more reinforcing, establishing a direct (automatic) association between the negative mood state and smoking behaviour. By contrast, the incentive learning account argues that in the negative mood state smoking is expected to be more reinforcing, which integrates with instrumental knowledge of the response required to produce that outcome. OBJECTIVES: One differential prediction is that whereas the incentive learning account anticipates that negative mood induction could augment a novel tobacco-seeking response in an extinction test, the S-R account could not explain this effect because the extinction test prevents S-R learning by omitting experience of the reinforcer. METHODS: To test this, overnight-deprived daily smokers (n = 44) acquired two instrumental responses for tobacco and chocolate points, respectively, before smoking to satiety. Half then received negative mood induction to raise the expected value of tobacco, opposing satiety, whilst the remainder received positive mood induction. Finally, a choice between tobacco and chocolate was measured in extinction to test whether negative mood could augment tobacco choice, opposing satiety, in the absence of direct experience of tobacco reinforcement. RESULTS: Negative mood induction not only abolished the devaluation of tobacco choice, but participants with a significant increase in negative mood increased their tobacco choice in extinction, despite satiety. CONCLUSIONS: These findings suggest that negative mood augments drug-seeking by raising the expected value of the drug through incentive learning, rather than through automatic S-R control

Farms of the future guidelines

The farms of the future (FOTF) approach is an interactive climate adaptation, knowledge sharing and learning experience that transforms climate forecasts into field-based realities by physically taking participants on a journey to areas that already experience climatic conditions that represent plausible future climate scenarios. The hypothesis behind this is that the knowledge exchange process can enhance a farmer’s/village’s capacity to adapt to changing climatic conditions by exposing them to innovative farming communities that have already successfully adapted their agricultural practices to various distinct climatic conditions the reference village might experience

Expertise and the interpretation of computerized physiological data: implications for the design of computerized monitoring in neonatal intensive care

This paper presents the outcomes from a cognitive engineering project addressing the design problems of computerized monitoring in neonatal intensive care. Cognitive engineering is viewed, in this project, as a symbiosis between cognitive science and design practice. A range of methodologies has been used: interviews with neonatal staff, ward observations and experimental techniques. The results of these investigations are reported, focusing specifically on the differences between junior and senior physicians in their interpretation of monitored physiological data. It was found that the senior doctors made better use of the different knowledge sources available than the junior doctors. The senior doctors were able to identify more relevant physiological patterns and generated more and better inferences than did their junior colleagues. Expertise differences are discussed in the context of previous psychological research in medical expertise. Finally, the paper discusses the potential utility of these outcomes to inform the design of computerized decision support in neonatal intensive care

Priming Cross-Protective Bovine Viral Diarrhea Virus-Specific Immunity Using Live-Vectored Mosaic Antigens

Bovine viral diarrhea virus (BVDV) plays a key role in bovine respiratory disease complex, which can lead to pneumonia, diarrhea and death of calves. Current vaccines are not very effective due, in part, to immunosuppressive traits and failure to induce broad protection. There are diverse BVDV strains and thus, current vaccines contain representative genotype 1 and 2 viruses (BVDV-1 & 2) to broaden coverage. BVDV modified live virus (MLV) vaccines are superior to killed virus vaccines, but they are susceptible to neutralization and complement-mediated destruction triggered by passively acquired antibodies, thus limiting their efficacy. We generated three novel mosaic polypeptide chimeras, designated NproE2123; NS231; and NS232, which incorporate protective determinants that are highly conserved among BVDV-1a, 1b, and BVDV-2 genotypes. In addition, strain-specific protective antigens from disparate BVDV strains were included to broaden coverage. We confirmed that adenovirus constructs expressing these antigens were strongly recognized by monoclonal antibodies, polyclonal sera, and IFN-γ-secreting T cells generated against diverse BVDV strains. In a proof-of-concept efficacy study, the multi-antigen proto-type vaccine induced higher, but not significantly different, IFN-γ spot forming cells and T-cell proliferation compared to a commercial MLV vaccine. In regards to the humoral response, the prototype vaccine induced higher BVDV-1 specific neutralizing antibody titers, whereas the MLV vaccine induced higher BVDV-2 specific neutralizing antibody titers. Following BVDV type 2a (1373) challenge, calves immunized with the proto-type or the MLV vaccine had lower clinical scores compared to naïve controls. These results support the hypothesis that a broadly protective subunit vaccine can be generated using mosaic polypeptides that incorporate rationally selected and validated protective determinants from diverse BVDV strains. Furthermore, regarding biosafety of using a live vector in cattle, we showed that recombinant human adenovirus-5 was cleared within one week following intradermal inoculation

Climate adaptation and agriculture: Solutions to successful national adaptation plans

The purpose of this brief is to share insights on agriculture and NAPs with national-level decision makers in developing countries and Least Developed Countries (LDCs), multilateral agencies, UNFCCC negotiators and donors. This brief explores how countries are overcoming the biggest challenges in developing NAPs, outlines examples of successful cross-sector adaptation planning, explores influence and leverage necessary for successful NAP processes, and offers specific recommendations

Friday Convocation

Program listing performers and works performe

Identification of Amazonian Trees with DNA Barcodes

International audienc

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments