The U.S. National Football League Scheduling Problem

Abstract We describe the problem of scheduling the television broadcasts of the U.S. National Football League (NFL). Unlike traditional round-robin tournament scheduling, the NFL problem involves assigning games to broadcast slots under various complex constraints while attempting to satisfy a set of user preferences. As well, a mixed-initiative functionality was required to allow the user to control and assist in the scheduling process. A prototype system was developed for the NFL which produced schedules satisfying many of these constraints and preferences. In this paper, we provide an overview of the constraint solving methodology employed and the implementation of the NFL prototype system

Approximating Input Data to a Snowmelt Model Using Weather Research and Forecasting Model Outputs in Lieu of Meteorological Measurements

Forecasting the timing and magnitude of snowmelt and runoff is critical to managing mountain water resources. Warming temperatures are increasing the rain–snow transition elevation and are limiting the forecasting skill of statistical models relating historical snow water equivalent to streamflow. While physically based methods are available, they require accurate estimations of the spatial and temporal distribution of meteorological variables in complex terrain. Across many mountainous areas, measurements of precipitation and other meteorological variables are limited to a few reference stations and are not adequate to resolve the complex interactions between topography and atmospheric flow. In this paper, we evaluate the ability of the Weather Research and Forecasting (WRF) Model to approximate the inputs required for a physics-based snow model, iSnobal, instead of using meteorological measurements, for the Boise River Basin (BRB) in Idaho, United States. An iSnobal simulation using station data from 40 locations in and around the BRB resulted in an average root-mean-square error (RMSE) of 4.5 mm compared with 12 SNOTEL measurements. Applying WRF forcings alone was associated with an RMSE of 10.5 mm, while including a simple bias correction to the WRF outputs of temperature and precipitation reduced the RMSE to 6.5 mm. The results highlight the utility of using WRF outputs as input to snowmelt models, as all required input variables are spatiotemporally complete. This will have important benefits in areas with sparse measurement networks and will aid snowmelt and runoff forecasting in mountainous basins

Why are the oldest old less generous? Explanations for the unexpected age-related drop in charitable giving

ABSTRACT Previous research has demonstrated that the generally positive relationship between age and the presence of charitable giving becomes negative at the oldest ages. We investigate potential causes of this drop in charitable giving among the oldest old including changes in health, cognition, egocentric networks, religious attendance, and substitution of charitable bequest planning. A longitudinal analysis of data from the United States Health and Retirement Survey indicates that the drop in charitable giving is mediated largely by changes in the frequency of church attendance, with only modest influences from changes in health and cognition

Toxic metal enrichment and boating intensity: sediment records of antifoulant copper in shallow lakes of eastern England

Tributyltin (TBT), an aqueous biocide derived from antifouling paint pollution, is known to have impacted coastal marine ecosystems, and has been reported in the sediment of the Norfolk and Suffolk Broads, a network of rivers and shallow lakes in eastern England. In the marine environment, the 1987 TBT ban has resulted in expanded use of alternative biocides, raising the question of whether these products too have impacted the Broads ecosystem and freshwaters in general. Here we examine the lake sediment record in the Norfolk and Suffolk Broads for contamination by copper (Cu) (as an active biocide agent) and zinc (Zn) (as a component of booster biocides), to assess their occurrence and potential for causing environmental harm in freshwater ecosystems. We find that, after the introduction of leisure boating, there is a statistically significant difference in Cu enrichment between heavily and lightly boated sites, while no such difference exists prior to this time. At the heavily boated sites the onset of Cu enrichment coincides with a period of rapid increase in leisure boating. Such enrichment is maintained to the present day, with some evidence of continued increase. We conclude that Cu-based antifouling has measurably contaminated lakes exposed to boating, at concentrations high enough to cause ecological harm. Similar findings can be expected at other boated freshwater ecosystems elsewhere in the world

Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes

The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of re!ectance at 710 and 670 nm (R2=0.832; RMSE=29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R2=0.984; RMSE=3.98 mg m−3). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R2=0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R2=0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales

Production studies, transformations in children’s television and the global turn

Moving away from the dominant discourse of US experience, this article looks at how the production of local content for children remains a central issue in many parts of the world, in spite of the growth of transnational media and the apparent abundance of content for children worldwide. Drawing on a pre-summit workshop on Children’s Content at the Core of Public Service Media, held at the 2014 World Summit on Media for Children, it considers the lack of academic perspectives on production, before exploring with workshop participants the regulatory and funding frameworks for quality children’s content, and the conditions for their successful implementation. There is a continuing problem about producing sustainable children’s content, and western models are not always the most appropriate at providing solutions, which need to be nuanced and tailored to different national, regional and local contexts

Optimising observing strategies for monitoring animals using drone-mounted thermal infrared cameras

The proliferation of relatively affordable off-the-shelf drones offers great opportunities for wildlife monitoring and conservation. Similarly the recent reduction in cost of thermal infrared cameras also offers new promise in this field, as they have the advantage over conventional RGB cameras of being able to distinguish animals based on their body heat and being able to detect animals at night. However, the use of drone-mounted thermal infrared cameras comes with several technical challenges. In this paper we address some of these issues, namely thermal contrast problems due to heat from the ground, absorption and emission of thermal infrared radiation by the atmosphere, obscuration by vegetation, and optimizing the flying height of drones for a best balance between covering a large area and being able to accurately image and identify animals of interest. We demonstrate the application of these methods with a case study using field data, and make the first ever detection of the critically endangered riverine rabbit (Bunolagus monticularis) in thermal infrared data. We provide a web-tool so that the community can easily apply these techniques to other studies (http://www.astro.ljmu.ac.uk/~aricburk/uav_calc/)