The Limitations of Regulatory Oversight on Online Video

Discussion in this paper focuses on the factors, attributes, and elements of telecom and broadcast regulation in Canada. Part I of this study briefly outlines the history of online video regulation in Canada to date. In Part II speculation as to how online video might be regulated, based on prior decisions of the CRTC, is presented. Part III considers the challenges of applying the Broadcasting Act to new media entities in order to create a regulatory framework for online video. Part IV looks at judicial decisions related to broadcast law that may be used to define the nature of the service, and therefore limit the application of the Broadcasting Act to specific types of technology. Part V examines the legal justification for the regu- lation of broadcast and telecommunications in Canada, as well as in other countries with similar regulatory frameworks, such as the United States. Finally, Part VI presents various legal difficulties for justifying the regulation of online video as a broadcast entity

Nearshore Sedimentology of Eroding Microtidal Estuaries: Bon Secour Bay, Alabama and Perdido Bay, Florida

Estuarine shorelines along the northern Gulf of Mexico are dynamic geologic settings that provide numerous ecological and economic benefits. By definition, estuaries are semi-enclosed bodies of water that receive sediment from two sources: (1) fluvial systems feeding into the estuary and (2) sediment transported by wave action and tidal currents from adjacent marine sources. Erosion of estuarine shorelines resulting from rising sea level, storm impact, and anthropogenic influence has been increasingly evident in the microtidal Gulf Coast over recent decades. This study collects quantitative and qualitative data to better understand sedimentary dynamics associated with contemporary estuarine shoreline erosion in Bon Secour Bay, Alabama and Perdido Bay, Florida. Historical aerial imagery compared with modern imagery indicates an average land loss rate of 0.30 – 0.67 m yr-1 at Bon Secour Bay (1992–2018) and 0.55 m yr-1 at Perdido Bay (1994–2018). Selection of these two sites is based on their similar microtidal, sandy, forested, undeveloped, northwest-to-southeast trending shorelines; albeit Bon Secour Bay has a considerably longer fetch and greater fluvial sediment input as it is part of the greater Mobile Bay estuarine system. Particle size of five nearshore sediment cores (~0.75 – 1.00 m below seafloor) are dominated by fine- to medium-grained sand with intervals of very fine and coarse sand and silt (rare). Sedimentological characteristics of nearshore cores and surface sediment suggest eroding shorelines are being directly deposited to the nearshore. Occurrences of shell material, wood fragments, coarser particles, and reduced sorting quality at the base of some core locations indicate facies change and possible ravinement surfaces that have been buried by sediment from a Holocene transgression

Determining the Dependence Structure of Multivariate Extremes

In multivariate extreme value analysis, the nature of the extremal dependence between variables should be considered when selecting appropriate statistical models. Interest often lies with determining which subsets of variables can take their largest values simultaneously, while the others are of smaller order. Our approach to this problem exploits hidden regular variation properties on a collection of non-standard cones and provides a new set of indices that reveal aspects of the extremal dependence structure not available through existing measures of dependence. We derive theoretical properties of these indices, demonstrate their value through a series of examples, and develop methods of inference that also estimate the proportion of extremal mass associated with each cone. We apply the methods to UK river flows, estimating the probabilities of different subsets of sites being large simultaneously

Estrogen Metabolism, Breast Density, and Breast Cancer

BACKGROUND: Estrogen metabolites, sex-steroid hormones, and breast density are associated with breast carcinogenesis. OBJECTIVE: Complete a systematic study of the contribution of two biological measures (breast density and hormone metabolism) to an endocrine-based model of breast cancer risk.METHODS: The study groups included breast cancer-free participants (N=282) in the Study of Osteoporotic Fractures (SOF), and participants in the Mammogram and Masses Study (MAMS), inclusive of 176 cases (55 pre-menopausal, 121 post-menopausal) and 380 controls (124 pre-menopausal, 256 postmenopausal). Sex-steroid hormones, percent breast density, serum concentrations of 2-hydroxyestrone (2-OH) and 16 alpha-hydroxyestrone (16alfa-OH), and breast cancer risk factors were evaluated to determine associations.RESULTS: In SOF,16alfa-OH was positively associated with body mass index (BMI) (r=0.162); however, this association was not significant in multivariate analyses that controlled for the serum sex-steroid hormone concentrations (total estradiol, total testosterone, SHBG). Women who reported a surgical menopause were significantly more likely to have higher levels of 16alfa-OH (OR=(tertile 3 vs tertile 1) 7.37, 95% Confidence Interval (CI) 2.20-24.70), but there was no type of menopause difference with respect to 2-OH tertile. In all MAMS control subjects (N=380), breast density correlated weakly with log-transformed serum concentrations of 16alfa-OH (Pearson correlation coefficient = 0.10, p-value < 0.1). Stratification according to menopausal status substantially reduced or eliminated associations between breast density and the estrogen metabolite concentrations. Logistic regression analyses showed a 3-4 fold increased risk of breast cancer among pre-menopausal women in the highest tertile of breast density compared with those in the lowest tertile of density, even with adjustment for the estrogen metabolites. A statistically non-significant 1.5-fold increased risk of breast cancer in high vs. low tertile of density was observed among post-menopausal women taking hormone therapy (HT) after adjusting for estrogen metabolites, BMI, and age. Breast density did not appear to substantially increase breast cancer risk among post-menopausal women not taking HT. CONCLUSION: In SOF, results did not show consistent associations between risk factors and estrogen metabolites except for a positive association between BMI and 16alfa-OH and surgical menopause and 16alfa-OH. With respect to MAMS, menopausal status may influence substrate estrogen hormone levels primarily, and, estrogen hormone levels may influence breast density secondarily, through pathways not involving the estrogen metabolites. The breast density-breast cancer association remains significant even with adjustment for the estrogen metabolites, at least in pre-menopausal women, suggesting that breast density may relate to breast cancer risk through pathways not involving estrogen metabolism.PUBLIC HEALTH SIGNIFICANCE: Understanding factors that affect breast density and their underlying mechanism is an important public health issue. Such an understanding will help us improve breast cancer screening and may help us identify women who are at an increased risk of breast cancer and for whom prevention strategies may be useful

2019 IODE Update: AIUs, ODISCat, OceanDocs

This presentation gives an overview of current IODE projects that intersect with IAMSLIC interests. This includes an update on the Associated Data Units program for eligible Library and Information Centers

Mental health legislation: does it protect the rights of people with mental health problems?

The International Federation of Social Work places a concern with human rights and social justice at the core of its definition of social work. Social work values are based on “respect for the equality, dignity and worth of all people” (IFSW, 2000), and social work practice has a special concern for vulnerable and oppressed people. People with mental health problems are amongst the most vulnerable members of society and in South Africa they comprise a considerable proportion of our society. According to the South African Stress and Health Survey (Herman, Steyn, Seedat, Heeringa, Moonal & Williams, 2009), the lifetime prevalence for any mental health problems in South Africa is 30.3% and neuropsychiatric disorders rank third in their contribution to the burden of disease in South Africa (Bradshaw, Norman & Schneider, 2007).Department of HE and Training approved lis

MENTAL HEALTH LEGISLATION: DOES IT PROTECT THE RIGHTS OF PEOPLE WITH MENTAL HEALTH PROBLEMS?

The International Federation of Social Work places a concern with human rights and social justice at the core of its definition of social work. Social work values are based on “respect for the equality, dignity and worth of all people” (IFSW, 2000), and social work practice has a special concern for vulnerable and oppressed people. People with mental health problems are amongst the most vulnerable members of society and in South Africa they comprise a considerable proportion of our society. According to the South African Stress and Health Survey (Herman, Steyn, Seedat, Heeringa, Moonal &amp; Williams, 2009), the lifetime prevalence for any mental health problems in South Africa is 30.3% and neuropsychiatric disorders rank third in their contribution to the burden of disease in South Africa (Bradshaw, Norman &amp; Schneider, 2007)

Conditional Modelling of Spatio-Temporal Extremes for Red Sea Surface Temperatures

Recent extreme value theory literature has seen significant emphasis on the modelling of spatial extremes, with comparatively little consideration of spatio-temporal extensions. This neglects an important feature of extreme events: their evolution over time. Many existing models for the spatial case are limited by the number of locations they can handle; this impedes extension to space-time settings, where models for higher dimensions are required. Moreover, the spatio-temporal models that do exist are restrictive in terms of the range of extremal dependence types they can capture. Recently, conditional approaches for studying multivariate and spatial extremes have been proposed, which enjoy benefits in terms of computational efficiency and an ability to capture both asymptotic dependence and asymptotic independence. We extend this class of models to a spatio-temporal setting, conditioning on the occurrence of an extreme value at a single space-time location. We adopt a composite likelihood approach for inference, which combines information from full likelihoods across multiple space-time conditioning locations. We apply our model to Red Sea surface temperatures, show that it fits well using a range of diagnostic plots, and demonstrate how it can be used to assess the risk of coral bleaching attributed to high water temperatures over consecutive days