Evaluating the Impact of Broadband Access and Internet Use in a Small Underserved Rural Community

Having adequate access to the internet at home enhances quality-of-life for households and facilitates economic and social opportunities. Despite increased investment in response to the COVID-19 pandemic, millions of households in the rural United States still lack adequate access to high-speed internet. In this study, we evaluate a wireless broadband network deployed in Turney, a small, underserved rural community in northwest Missouri. In addition to collecting survey data before and after this internet intervention, we collected pre-treatment and post-treatment survey data from comparison communities to serve as a control group. Due to technical constraints, some of Turney\u27s interested participants could not connect to the network, creating an additional comparison group. These comparisons suggest two primary findings, (1) changes in using the internet for employment, education, and health could not be directly attributed to the internet intervention, and (2) the internet intervention was associated with benefits stemming from the ability to use multiple devices at once. This study has implications for the design of future broadband evaluation studies, particularly those examining underserved rather than unserved communities. Recommendations for identifying appropriate outcome variables, executing recruitment strategies, and selecting the timing of surveys are made

Evaluating the Impact of Broadband Access and Internet Use in a Small Underserved Rural Community

Having adequate access to the internet at home enhances quality-of-life for households and facilitates economic and social opportunities. Despite increased investment in response to the COVID-19 pandemic, millions of households in the rural United States still lack adequate access to high-speed internet. In this study, we evaluate a wireless broadband network deployed in Turney, a small, underserved rural community in northwest Missouri. In addition to collecting survey data before and after this internet intervention, we collected pre-treatment and post-treatment survey data from comparison communities to serve as a control group. Due to technical constraints, some of Turney\u27s interested participants could not connect to the network, creating an additional comparison group. These comparisons suggest two primary findings, (1) changes in using the internet for employment, education, and health could not be directly attributed to the internet intervention, and (2) the internet intervention was associated with benefits stemming from the ability to use multiple devices at once. This study has implications for the design of future broadband evaluation studies, particularly those examining underserved rather than unserved communities. Recommendations for identifying appropriate outcome variables, executing recruitment strategies, and selecting the timing of surveys are made

Optimisation en fluage et fatigue-fluage d'aciers martensitiques à 9%Cr par traitement thermo-mécanique

National audienceL'utilisation des aciers martensitiques à 9-12%Cr est envisagée dans les futurs réacteurs nucléaires de génération IV. En service, ils seront soumis à du fluage à haute température ainsi qu'à des sollicitations de fatigue-fluage. Or de récents travaux sur l'acier commercial P91 ont montré que des sollicitations cycliques de fatigue combinées au fluage conduisent à un adoucissement rapide du matériau, lié à un grossissement de sa microstructure. Des traitements thermomécaniques ont donc été réalisés dans le but d'affiner et de stabiliser la microstructure de cet acier. Le traitement thermomécanique présenté ici conduit à une martensite plus fine, émaillée de nombreux et fins précipités de type MX. Le P91 optimisé montre un net gain en termes de propriétés mécaniques par rapport à l'acier P91 à réception : sa dureté est plus élevée de 100 Hv, sa limite d'élasticité conventionnelle est supérieure de 430 MPa à 20°C et de 220 MPa à 550°C, sa durée de vie en fluage à 650°C est 20 fois supérieure et son adoucissement à 650°C est légèrement moins rapide

Relationship between microstructure and mechanical behaviour of thermomechanically optimised 9-12% Cr steels

International audienceThe development of Generation IV fission nuclear reactors and fusion nuclear reactorsrequires materials able to resist to high temperature (650°C) creep, but also to creep-fatigue.Martensitic 9-12%Cr steels are candidate materials for these applications.Recent studies on commercial P91 steel showed that cyclic loadings coupled to high temperature creep loadings lead to a strong softening effect, which affects the steelmechanical strength. This effect is due to the decrease of the dislocations density and thecoarsening of martensitic microstructure.Thermomechanical treatments, including warm-rolling in austenitic phase and tempering,have been applied to P91 in order to refine its microstructure and to improve its precipitationstate. The temperature of rolling was set at 600°C, and those of annealing at 650°C and700°C, thanks to MatCalc calculations.Microstructural observations proved that the warm-rolling and the following tempering lead toa finer martensite pinned with numerous small precipitates. In terms of mechanical propertiesimprovement, the hardness of thermomechanically treated P91 is higher than that of asreceivedP91. The yield strengths are higher than that of P91 (around 400 MPa at 20°C; andmore than 200 MPa at 550°C). Preliminary creep resu lts show that these treatments improvethe creep lifetime by at least a factor 8

Multiple imputation in veterinary epidemiological studies: a case study and simulation

The problem of missing data occurs frequently in veterinary epidemiological studies. Most studies use a complete case (CC) analysis which excludes all observations for which any relevant variable have missing values. Alternative approaches (most notably multiple imputation (MI)) which avoid the exclusion of observations with missing values are now widely available but have been used very little in veterinary epidemiology.This paper uses a case study based on research into dairy producers' attitudes toward mastitis control procedures, combined with two simulation studies to evaluate the use of MI and compare results with a CC analysis. MI analysis of the original data produced results which had relatively minor differences from the CC analysis. However, most of the missing data in the original data set were in the dependent variable and a subsequent simulation study based on the observed missing data pattern and 1000 simulations showed that an MI analysis would not be expected to offer any advantages over a CC analysis in this situation. This was true regardless of the missing data mechanism (MCAR - missing completely at random, MAR - missing at random, or NMAR - not missing at random) underlying the missing values. Surprisingly, recent textbooks dealing with MI make little reference to this limitation of MI for dealing with missing values in the dependent variable.An additional simulation study (1000 runs for each of the three missing data mechanisms) compared MI and CC analyses for data in which varying levels (n = 7) of missing data were created in predictor variables. This study showed that MI analyses generally produced results that were less biased on average, were more precise (smaller SEs), were more consistent (less variability between simulation runs) and consequently were more likely to produce estimates that were close to the "truth" (results obtained from a data set with no missing values). While the benefit of MI varied with the mechanism used to generate the missing data, MI always performed as well as, or better than; CC analysis

A comprehensive modelling way for assessing real-time mixings of mineral and anthropogenic pollutants in East Asia

International audienceIn order to assess the complex mixing of atmospheric anthropogenic and natural pollutants over the East Asian region, we propose to take into account the main aerosols simultaneously present over China, Korea and Japan during the spring season. With the mesoscale RAMS (Regional Atmospheric Modeling System) tool, we present a simulation of natural (desert) dust events along with some of the most critical anthropogenic pollutants over East Asia: sulphur elements (SO2 and SO42-) and Black Carbon (BC). During a 2-week case study of dust events which occurred in April 2005 over an area extending from the Gobi deserts to the Japan surroundings, we retrieve the behaviours of the different aerosols plumes. We focus on possible dust mixing with the anthropogenic pollutants from megalopolis. For both natural and anthropogenic pollution, the model results are in general agreement with the horizontal and vertical distributions of concentrations as measured by remote data, in situ LIDAR, PM10 data and literature. In particular, we show that a simplified chemistry approach of this complex issue can be efficient enough to model this event, with a real-time step of 3 h. The model provides the good shapes and orders of magnitude for the Aerosol Optical Thickness (AOT) and species contributions (via the Angström Exponent) when compared with the AERONET data

Personalisation and recommender systems in digital libraries

Widespread use of the Internet has resulted in digital libraries that are increasingly used by diverse communities of users for diverse purposes and in which sharing and collaboration have become important social elements. As such libraries become commonplace, as their contents and services become more varied, and as their patrons become more experienced with computer technology, users will expect more sophisticated services from these libraries. A simple search function, normally an integral part of any digital library, increasingly leads to user frustration as user needs become more complex and as the volume of managed information increases. Proactive digital libraries, where the library evolves from being passive and untailored, are seen as offering great potential for addressing and overcoming these issues and include techniques such as personalisation and recommender systems. In this paper, following on from the DELOS/NSF Working Group on Personalisation and Recommender Systems for Digital Libraries, which met and reported during 2003, we present some background material on the scope of personalisation and recommender systems in digital libraries. We then outline the working group’s vision for the evolution of digital libraries and the role that personalisation and recommender systems will play, and we present a series of research challenges and specific recommendations and research priorities for the field

QuantUM: Quantitative Safety Analysis of UML Models

When developing a safety-critical system it is essential to obtain an assessment of different design alternatives. In particular, an early safety assessment of the architectural design of a system is desirable. In spite of the plethora of available formal quantitative analysis methods it is still difficult for software and system architects to integrate these techniques into their every day work. This is mainly due to the lack of methods that can be directly applied to architecture level models, for instance given as UML diagrams. Also, it is necessary that the description methods used do not require a profound knowledge of formal methods. Our approach bridges this gap and improves the integration of quantitative safety analysis methods into the development process. All inputs of the analysis are specified at the level of a UML model. This model is then automatically translated into the analysis model, and the results of the analysis are consequently represented on the level of the UML model. Thus the analysis model and the formal methods used during the analysis are hidden from the user. We illustrate the usefulness of our approach using an industrial strength case study.Comment: In Proceedings QAPL 2011, arXiv:1107.074

Widespread reorganisation of pluripotent factor binding and gene regulatory interactions between human pluripotent states.

The transition from naive to primed pluripotency is accompanied by an extensive reorganisation of transcriptional and epigenetic programmes. However, the role of transcriptional enhancers and three-dimensional chromatin organisation in coordinating these developmental programmes remains incompletely understood. Here, we generate a high-resolution atlas of gene regulatory interactions, chromatin profiles and transcription factor occupancy in naive and primed human pluripotent stem cells, and develop a network-graph approach to examine the atlas at multiple spatial scales. We uncover highly connected promoter hubs that change substantially in interaction frequency and in transcriptional co-regulation between pluripotent states. Small hubs frequently merge to form larger networks in primed cells, often linked by newly-formed Polycomb-associated interactions. We identify widespread state-specific differences in enhancer activity and interactivity that correspond with an extensive reconfiguration of OCT4, SOX2 and NANOG binding and target gene expression. These findings provide multilayered insights into the chromatin-based gene regulatory control of human pluripotent states

Sub-seasonal to seasonal climate predictions for wind energy forecasting

Both renewable energy supply and electricity demand are strongly influenced by meteorological conditions and their evolution over time in terms of climate variability and climate change. However, knowledge of power output and demand forecasting beyond a few days remains poor. Current methodologies assume that long-term resource availability is constant, ignoring the fact that future wind resources could be significantly different from the past wind energy conditions. Such uncertainties create risks that affect investment in wind energy projects at the operational stage where energy yields affect cash flow and the balance of the grid. Here we assess whether sub-seasonal to seasonal climate predictions (S2S) can skilfully predict wind speed in Europe. To illustrate S2S potential applications, two periods with an unusual climate behaviour affecting the energy market will be presented. We find that wind speed forecasted using S2S exhibits predictability some weeks and months in advance in important regions for the energy sector such as the North Sea. If S2S are incorporated into planning activities for energy traders, energy producers, plant operators, plant investors, they could help improve management climate variability related risks.We thank the S2S4E (GA776787), NEWA (PCIN-2014-012-C07-07), ERA4CS-INDECIS (GA690462) and ERA4CS-MEDSCOPE (GA690462) projects funding for allowing us to carry out this research. We acknowledge use of the s2dverification (http://cran.r-project.org/web/packages/s2dverification) and Specs-Verification (http://cran.r-project.org/web/packages/SpecsVerification)R-language-based software packages.We also acknowledge the ECMWF for the provision of the ECMWF SEAS5 and the Monthly Prediction Systemsand the ERA-Interim reanalysis datasets.Peer ReviewedPostprint (published version