Changes in glass consumption in Pergamon (Turkey) from Hellenistic to late Byzantine and Islamic times

We present compositional data for nearly 100 glass samples from Pergamon, western Turkey, spanning 1500 years from the Hellenistic to Late Byzantine and Islamic periods. The data shows the use of already-known Roman glass groups during the first half of the time frame, for imported vessels as well as locally worked glass. No compositional change is seen related to the introduction of glass blowing for either of the glass groups in use during this time. During the first half of the 1st millennium AD, two previously little-known boron- and alumina-rich compositional groups emerge. These glass groups, thought to be regionally produced, dominate glass compositions in Pergamon during the mid-to late Byzantine and Islamic periods, indicating a major shift in glass supply and a fragmentation of the economy into more regional units. Plant-ash glass, from the 9th century AD replacing mineral natron glass in the Levant, plays only a minor role in Byzantine and Islamic Pergamon

Accounting for the Decline in AFDC Caseloads: Welfare Reform or Economic Growth?

Nationwide, AFDC caseloads have decreased by about 18 percent since March 1994, while some states, such as Wisconsin, Indiana, and Oregon, have seen declines of 40 percent or more. Two factors are frequently suggested as possible causes: state-level experiments with welfare reform and strong economic growth. In this paper, we use state-level monthly panel data from 1987 to 1996 to assess the importance of each of these factors by estimating a model of AFDC caseloads as a dynamic function of time-dependent state welfare reform variables (welfare waivers) and economic variables such as per capita employment. Our results from the dynamic model suggest that the decline in per capita AFDC caseloads is attributable largely to the economic growth of states and not to waivers from federal welfare policies. In the 26 states experiencing at least a 20 percent decline in per capita AFDC caseloads between 1993 and 1996, we attribute 78 percent of the decline to business-cycle factors and 6 percent to welfare waivers.

The Statistical Approach to Quantifying Galaxy Evolution

Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a spectroscopic sample that is able to unambiguously disentangle these processes is currently excessively prohibitive due to the observational requirements. This paper extends and applies an alternative approach that relies on statistical estimates for both distance (z) and spectral type to a deep multi-band dataset that was obtained for this exact purpose. These statistical estimates are extracted directly from the photometric data by capitalizing on the inherent relationships between flux, redshift, and spectral type. These relationships are encapsulated in the empirical photometric redshift relation which we extend to z ~ 1.2, with an intrinsic dispersion of dz = 0.06. We also develop realistic estimates for the photometric redshift error for individual objects, and introduce the utilization of the galaxy ensemble as a tool for quantifying both a cosmological parameter and its measured error. We present deep, multi-band, optical number counts as a demonstration of the integrity of our sample. Using the photometric redshift and the corresponding redshift error, we can divide our data into different redshift intervals and spectral types. As an example application, we present the number redshift distribution as a function of spectral type.Comment: 40 pages (LaTex), 21 Figures, requires aasms4.sty; Accepted by the Astrophysical Journa

Anatomy of Cirrus Clouds: Results from the Emerald Airborne Campaigns

2000 FLORIDA AVE NW, WASHINGTON, USA, DC, 2000

Evaluation of the Fiscal Costs and Consequences of Alzheimer’s Disease in Germany:Microsimulation of Patients’ and Caregivers’ Pathways

Background: Alzheimer’s disease is a severe condition, impacting individual’s wellbeing and independence in daily activities. Informal care provision is common and of great value to societies but is not without negative externalities to households and the broader economy. Objectives: Estimate the lifetime incremental fiscal consequences of Alzheimer’s disease in community-based individuals and their informal caregivers. Setting: The fiscal consequences of Alzheimer’s disease was modeled using the German government and social security perspective. Participants: Synthetic cohort containing 1,000 pairs of people with Alzheimer’s disease and their informal caregivers, compared to 1,000 demographically identical pairs from the general population. Design: Disease progression was modeled using published equations and a state-transition microsimulation framework. Labor participation, financial support and paid taxes were estimated according to cognitive decline and caregiving responsibilities using German labor statistics and tax rates. Healthcare costs were sourced from several German publications. Costs and life-years were discounted at 3% annually. Measurements: Results are reported as lifetime incremental differences in total tax revenue and transfer payments between the cohort affected by Alzheimer’s disease and their general population analogues. Results: The Alzheimer’s disease-affected pair was associated with net incremental fiscal losses of €74,288 ($85,037) to the German government and social security over the lifetime of people with Alzheimer’s disease. Most costs were lost taxes on employment earnings (48.4$65,209) less than their general population analogues. Financial support for informal and formal care accounted for 20.4%, and medical healthcare costs represented 24.0% of the incremental fiscal losses. Sensitivity analyses confirmed the robustness of the model results. In a cohort with early onset Alzheimer’s disease, incremental fiscal losses were predicted to be €118,533 ($114,209) over the lifetime of people with Alzheimer’s disease. Conclusions: Alzheimer’s disease externalities profoundly impact public economics for governments and should be considered to inform policy making and healthcare planning

Image Coaddition with Temporally Varying Kernels

Large, multi-frequency imaging surveys, such as the Large Synaptic Survey Telescope (LSST), need to do near-real time analysis of very large datasets. This raises a host of statistical and computational problems where standard methods do not work. In this paper, we study a proposed method for combining stacks of images into a single summary image, sometimes referred to as a template. This task is commonly referred to as image coaddition. In part, we focus on a method proposed in previous work, which outlines a procedure for combining stacks of images in an online fashion in the Fourier domain. We evaluate this method by comparing it to two straightforward methods through the use of various criteria and simulations. Note that the goal is not to propose these comparison methods for use in their own right, but to ensure that additional complexity also provides substantially improved performance