Reconstructing the Accretion History of the Galactic Stellar Halo from Chemical Abundance Ratio Distributions

Observational studies of halo stars during the last two decades have placed some limits on the quantity and nature of accreted dwarf galaxy contributions to the Milky Way stellar halo by typically utilizing stellar phase-space information to identify the most recent halo accretion events. In this study we tested the prospects of using 2-D chemical abundance ratio distributions (CARDs) found in stars of the stellar halo to determine its formation history. First, we used simulated data from eleven "MW-like" halos to generate satellite template sets of 2-D CARDs of accreted dwarf satellites which are comprised of accreted dwarfs from various mass regimes and epochs of accretion. Next, we randomly drew samples of $\sim10^{3-4}$ mock observations of stellar chemical abundance ratios ([$\alpha$/Fe], [Fe/H]) from those eleven halos to generate samples of the underlying densities for our CARDs to be compared to our templates in our analysis. Finally, we used the expectation-maximization algorithm to derive accretion histories in relation to the satellite template set (STS) used and the sample size. For certain STS used we typically can identify the relative mass contributions of all accreted satellites to within a factor of 2. We also find that this method is particularly sensitive to older accretion events involving low-luminous dwarfs e.g. ultra-faint dwarfs - precisely those events that are too ancient to be seen by phase-space studies of stars and too faint to be seen by high-z studies of the early Universe. Since our results only exploit two chemical dimensions and near-future surveys promise to provide $\sim6-9$ dimensions, we conclude that these new high-resolution spectroscopic surveys of the stellar halo will allow us to recover its accretion history - and the luminosity function of infalling dwarf galaxies - across cosmic time.Comment: Article contains 18 pages total (16 pages of main text + 2 pages of Appendix) with 12 figures; accepted for publication in Ap

The loss control approach to industrial safety

Bibliography: p. 175-191.Because industrial accident rates in many industrialized countries are apparently worsening, efforts are being made to devise new accident prevention techniques. One recent development is Loss Control, which involves a new management approach in which safety is incorporated in an integrated cost reduction programme to reduce all types of non-speculative risks incurred by the business. Shifting the appeal away from the traditional goal of preventing injuries, Loss Control attempts to lower accident rates through improved measures to raise productivity, and thus protect the safety of employees indirectly, by making the business more efficient. Since Loss Control emerged in the United States and Canada during the 1960's, it has been adopted by many firms in various countries throughout the world. Books and articles on the theory of Loss Control have challenged previous assumptions about the best ways to manage industrial safety, but unfortunately, no one has analyzed very carefully the advantages of the new approach over traditional methods, or published any detailed descriptions of specific firms to show how Loss Control has been implemented and what outcome it has actually had. The main objective here is to correct this deficiency, and evaluate Loss Control in both theory and practice

Flood Insurance Demand along the Gulf and Florida Coast

The objective of this research is to identify factors that influence both the decision (yes or no) and level of flood insurance among coastal homeowners in the southeast U.S. Recently flood damage has dramatically increased (Flood), and Crossett et al. (2004) report that coastal populations are growing. And in spite of rising costs of living in coastal areas, people are willing to pay more for access to ocean views and other natural amenities associated with coastal living (Bin and Kruse, 2006). Although the federal government provides flood insurance programs and encourages at-risk residents to insure their property from flood, rates of uptake remain low (Burby, 2001; Kunreuther, 2006; Landry and Jahan-Parvar, 2009). The National Flood Insurance Program (NFIP) was created to provide often subsidized premiums to cover losses which private insurance markets failed to offer. However, as Kunreuther et al.(1978) argue, many people do not bother to prepare, and have a low willingness to pay for coverage, even if subsidized (Kunreuther 1996). However, of those who have previously experienced flooding, they tend to insure their properties more (McClelland, Schulze, and Coursey 1993). Based on previous literature, we identified key factors to establish testable hypotheses regarding effect on flood insurance demand. These include: income, previous flood experience, the presence of a mortgage, home location (both flood zone status and distance from the shore), participation in CRS, the distance from the coast, the house construction year as well as measures of respondent risk preferences and perceptions. Data on flood coverage level and the above explanatory variables were obtained via revealed-preference online survey method, contracted through Knowledge Networks (KN) during August-September 2010. We chose to contract with KN for several reasons. First, they are, to our knowledge, the only survey firm that can legitimately say they have a true probability based sample for an online survey because they recruit by phone and/or mail (randomly selected using random-digit dialing (RDD) or by using address-based sampling); additionally they provide internet access to households that do not have it. KN was also contracted to overcome the typical of low response rate when surveying the general public. KN uses an online panel (called the “Knowledge Panel”). KN Panel members that were homeowners were sampled from 95 counties in Gulf Coast and Florida Atlantic Coast counties in AL, FL, LA, MS, and TX, with an 47% response rate (720 observations), with 67% from FL, 24% from TX, 5% from LA, and 4% collectively from AL and MS. As expected, insurance purchase is positively affected by the individual’s risk perception, their risk preference, whether or not they have a mortgage, flood zone residence, their income, CRS, previous flood experience, and the year of construction of house. Coefficients of mortgage and risk perception, income, flood zone are significant at 0.05 the level. Additionally, the coefficient of distance from the coast is only significant at the 0.1 level.Flood Insurance, Risk, Insurance Demand, Environmental Economics and Policy, Risk and Uncertainty,

Theories and Practices of Emotion, Movement, and Embodiment in Mathematical Learning

Physical movements, emotion, and embodiment are fundamental to mathematical learning. Problem: Lack of study in collaborative embodiment. Identified applications of embodiment using virtual reality. An exploratory analysis of a set of videos for an embodied mathematical game was conducted

Mammy\u27s lullaby : a dreamy southern waltz / by Lee S. Roberts ; with words by J. Will Callahan.

https://digitalcommons.library.umaine.edu/mmb-vp/2077/thumbnail.jp

A Little Birch Canoe And You : Song

https://digitalcommons.library.umaine.edu/mmb-vp/1994/thumbnail.jp

You Don\u27t Know

https://digitalcommons.library.umaine.edu/mmb-vp/3452/thumbnail.jp

America the Beautiful

https://digitalcommons.library.umaine.edu/mmb-me/1311/thumbnail.jp

Mammy\u27s Lullaby

[Verse 1]Close yoh dreamy eyes an’ lay yoh head on Mammy’s breat,Stahs ah in de skies an birds ah sleein’ in de nest,Night time is heah, honey don’t feah,Yoh on Mammy’s ahm;Great big yallah moon a shinin’ down upon de stream,Mammy’s little coon will soon be floatin’ in a dream,Slumabh ashile, mah honey chile,Yoh mammy will keep yoh from hahm, [Chorus]Go to sleep,Wiv yoh head in yoh mammy’s breastCause Mammy knows her dusky rose tiahed an’ longin’ fo’ rest;Go to sleep while de shadders creep,Des dream away till break ob day,An doan yoh eben peep [Verse 2]In dah sugah cane de owl’s a hootin’ to de moon,Down along de lane I heah de darkies softly cronn,Now hushabye, honey, don’t cry,But des close yoh eyes;When de mawnin’ come an’ all de birds begin to cheepMammy’s sugah plum a goin’ to waken from his sleepDes like a flow’h kissed by de show’h when rain drops come down from de skyYoh Mammy’s pickaniny,De finest an’ de best,De pride of old VirginnySo slumbah, my honey, an’ restGo to sleep,Go to sleep