Experience rating in Massachusetts.

Thesis (M.A.)--Boston UniversityExperience rating is not an idea that was conceived in this country. Great Britain and Germany both experimented with the idea before this country even had an unemployment insurance law. The plan was soon found to be unsuccessful by both countries, and it was dropped from the law in order to protect the benefit fund and to prevent some industries from paying outrageously high tax rates. The United States incorporated experience rating in its unemployment insurance law and by 1948 every state had some type of merit rating provision. There are five distinct experience ratings in use in this country - the payroll decline, compensable-separations, reserve-ration, benefit-ration, and benefit-wage ration plans. All the plans have certain things in common in spite of essential differences. They are all devised to establish the relative experience of individual employers with unemployment or benefit costs.[TRUNCATED] Employers must remember that the structure of industry in Massachusetts does not permit the fund to be adequately financed by experience rating. Unemployment will be higher here than in other sections of the country. An attempt to cut into workers' benefits is no solution, for it does not attack the cause of the dilemma. Unless the economy of this state can be re-vitalized, experience rating must be abolished so that the fund will be adequate to meet the claims of the unemployed

Corticosteroids for the management of cancer-related pain in adults (Review)

Background: One of the most feared symptoms associated with cancer is pain. Opioids remain the mainstay of pain treatment but corticosteroids are often used concurrently as co- or adjuvant analgesics. Due to their anti-inflammatory mechanism of action, corticosteroids are said to provide effective analgesia for pain associated with inflammation and in the management of cancer-related complications such as brain metastasis and spinal cord compression. However, corticosteroids have a wide range of adverse effects that are dose and time dependent. Objectives: To evaluate the efficacy of corticosteroids in treating cancer-related pain in adults. Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL 2014, Issue 4), MEDLINE (OVID) (1966 to 29 September 2014), EMBASE (OVID) (1970 to 29 September 2014), CINAHL (1982 to 29 September 2014), Science Citation Index (Web of Science) (1899 to 29 September 2014) and Conference Proceedings Citation Index - Science (Web of Science) (1990 to 29 September 2014). Selection criteria: Any randomised or prospective controlled trial that included patients over 18 years with cancer-related pain were eligible for the review. Corticosteroids were compared to placebo or usual treatment and/or supportive care. Data collection and analysis: All review authors independently assessed trial quality and extracted data. We used arithmetic means and standard deviations for each outcome to report the mean difference (MD) with 95% confidence interval (CI). Main results: Fifteen studies met the inclusion criteria, enrolling 1926 participants. The trial size varied from 20 to 598 patients. Most studies compared corticosteroids, particularly dexamethasone, to standard therapy. We included six studies with data at one week in the meta-analysis for pain intensity; no data were available at that time point for the remaining studies. Corticosteroid therapy resulted in less pain (measured on a scale of 0 to 10 with a lower score indicating less pain) compared to control at one week (MD 0.84 lower pain, 95% CI 1.38 to 0.30 lower; low quality evidence). Adverse events were poorly documented. Factors limiting statistical analysis included the lack of standardised measurements of pain and the use of different agents, dosages, comparisons and routes of drug delivery. Subgroup analysis according to type of cancer was not possible. The quality of this evidence was limited by the risk of bias of the studies and small sample size. The results were also compromised by attrition, with data missing for the enrolled patients. Authors' conclusions: The evidence for the efficacy of corticosteroids for pain control in cancer patients is weak. Significant pain relief was noted in some studies, albeit only for a short period of time. This could be important for patients with poor clinical status. Further trials, with increased numbers of participants, are needed to evaluate the safety and effectiveness of corticosteroids for the management cancer pain in adults, and to establish an ideal dose, duration of therapy and route of administration

Relative age effects on academic achievement in the first ten years of formal schooling: A nationally representative longitudinal prospective study

The effects of school starting age and relative age effects (RAEs) have generated much interest from parents, teachers, policymakers, and educational researchers. Our 10-year longitudinal study is based on a nationally representative (N = 4,983) prospective sample from the Longitudinal Study of Australian Children. The primary outcomes are results from the high-stake, Australia-wide National Assessment Program-Literacy and Numeracy tests in Years 3, 5, 7, and 9, controlling for demographic characteristics (gender, socioeconomic status, school type, and childhood cognition measured before the start of kindergarten). We evaluated how direct and mediated RAEs vary over the first 10 years of schooling for these longitudinal data. Results revealed significant RAEs in primary school years for both numeracy and literacy test outcomes. Effects were large in primary school years but declined in secondary school years. Although the direct effects of RAEs declined over time, there continued to be significant indirect effects over the whole 10-year period. RAEs in primary school had enduring effects that were mediated through the effects of earlier achievement. We juxtapose our results with previous RAE research on achievement and a range of other noncognitive outcomes where the RAEs are enduring into adolescence and even adulthood. We position our research within this broader research literature and discuss implications for educational policy, practice, theory, and future research

Million km² large-extent snowdrift-permitting snowpack predictions

Global Water Future

Impact of measured and simulated tundra snowpack properties on heat transfer

Snowpack microstructure controls the transfer of heat to, as well as the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow micropenetrometer profiles allowed for snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n=1050) compared to traditional snowpit observations (3 cm vertical resolution; n=115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE=5.8 ∘C). Two different approaches were taken to reduce this bias: alternative parameterisations of snow thermal conductivity and the application of a correction factor. All the evaluated parameterisations of snow thermal conductivity improved simulations of wintertime soil temperatures, with that of Sturm et al. (1997) having the greatest impact (RMSE=2.5 ∘C). The required correction factor is strongly related to snow depth () and thus differs between the two snow seasons, limiting the applicability of such an approach. Improving simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures are an important control on subnivean soil respiration and hence impact Arctic winter carbon fluxes and budgets

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Impact of measured and simulated tundra snowpack properties on heat transfer

Snowpack microstructure controls the transfer of heat to, as well as the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow micropenetrometer profiles allowed for snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n = 1050) compared to traditional snowpit observations (3 cm vertical resolution; n = 115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE = 5.8 °C). Two different approaches were taken to reduce this bias: alternative parameterisations of snow thermal conductivity and the application of a correction factor. All the evaluated parameterisations of snow thermal conductivity improved simulations of wintertime soil temperatures, with that of Sturm et al. (1997) having the greatest impact (RMSE = 2.5 °C). The required correction factor is strongly related to snow depth (R2 = 0.77, RMSE = 0.066) and thus differs between the two snow seasons, limiting the applicability of such an approach. Improving simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures are an important control on subnivean soil respiration and hence impact Arctic winter carbon fluxes and budgets

Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site

Estimates of winter (snow-covered non-growing season) CO2 fluxes across the Arctic region vary by a factor of 3.5, with considerable variation between measured and simulated fluxes. Measurements of snow properties, soil temperatures, and net ecosystem exchange (NEE) at Trail Valley Creek, NWT, Canada, allowed for the evaluation of simulated winter NEE in a tundra environment with the Community Land Model (CLM5.0). Default CLM5.0 parameterisations did not adequately simulate winter NEE in this tundra environment, with near-zero NEE (< 0.01 ) simulated between November and mid-May. In contrast, measured NEE was broadly positive (indicating net CO2 release) from snow-cover onset until late April. Changes to the parameterisation of snow thermal conductivity, required to correct for a cold soil temperature bias, reduced the duration for which no NEE was simulated. Parameter sensitivity analysis revealed the critical role of the minimum soil moisture threshold of decomposition (Ψmin) in regulating winter soil respiration. The default value of this parameter (Ψmin) was too high, preventing simulation of soil respiration for the vast majority of the snow-covered season. In addition, the default rate of change of soil respiration with temperature (Q10) was too low, further contributing to poor model performance during winter. As Ψmin and Q10 had opposing effects on the magnitude of simulated winter soil respiration, larger negative values of Ψmin and larger positive values of Q10 are required to simulate wintertime NEE more adequately

The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding

Natural Sciences and Engineering Research Council of Canada, Environment Canada, Indian and Northern Affairs Canada, Yukon Environment, the Forest Resource Improvement Association of Alberta, Alberta Agriculture and Forestry, Alberta Environment, Ducks Unlimited Canada, Water Security Agency of Saskatchewan, Natural Environment Research Council (UK), IPE-CSIC (Spain), Canada Research Chair and Canada Excellence Research Chairs programmes, Canada First Research Excellence Fund’s Global Water Futures programmePeer ReviewedCold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM’s capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations