Complex copula systems as suppletive alomorphy

Languages are known to vary in the number of verbs they exhibit corresponding to English "be", in the distribution of such copular verbs, and in the presence or absence of a distinct verb for possession sentences corresponding to English "have". This paper offers novel arguments for the position that such differences should be modeled in terms of suppletive allomorphy of the same syntactic element (here dubbed v BE), employing a Late Insertion- based framework. It is shown that such a suppletive allomorphy approach to complex copula systems makes three predictions that distinguish it from non-suppletion-based alternatives (concerning decomposition, possible and impossible syncretisms, and Impoverishment), and that these predictions seem to be correct (although a full test of the possible and impossible syncretisms prediction is not possible in the current state of knowledge)

Any Data, Any Time, Anywhere: Global Data Access for Science

Data access is key to science driven by distributed high-throughput computing (DHTC), an essential technology for many major research projects such as High Energy Physics (HEP) experiments. However, achieving efficient data access becomes quite difficult when many independent storage sites are involved because users are burdened with learning the intricacies of accessing each system and keeping careful track of data location. We present an alternate approach: the Any Data, Any Time, Anywhere infrastructure. Combining several existing software products, AAA presents a global, unified view of storage systems - a "data federation," a global filesystem for software delivery, and a workflow management system. We present how one HEP experiment, the Compact Muon Solenoid (CMS), is utilizing the AAA infrastructure and some simple performance metrics.Comment: 9 pages, 6 figures, submitted to 2nd IEEE/ACM International Symposium on Big Data Computing (BDC) 201

Estimating Consumers' Willingness-To-Pay for Country-Of-Origin Labels in Fresh Apples and Tomatoes: A Double-Hurdle Probit Analysis of American Data Using Factor Scores

Data are collected from primary shoppers in Gainesville Florida, Atlanta Georgia and Lansing Michigan using a Vickrey (fifth-priced sealed bid) experimental auction and a survey questionnaire to provide a sample of 311 observations useable for analysis. The average willingness to pay (WTP) for country of origin labeling (COOL) "Grown in the U.S." in apples and tomatoes are calculated then tested for equivalence to assess if WTP is produce specific. A double-hurdle probit model is then estimated to ascertain the prominent determinants of WTP for COOL. Independent variables include demographics, food safety and factor scores derived from a factor analysis of food quality and food preference variables. Results show that on average consumers are willing to pay $0.49 and$0.48 for COOL in apples and tomatoes respectively with 79% of the consumers willing to pay more than $0.00 for apples labeled "Grown in the U.S." and 72% in the case of tomatoes. Premiums are found to be statistically equivalent suggesting that WTP for COOL is not produce specific. The double hurdle probit estimation finds most independent variables insignificant with the exception of the food quality factor scores and consumer trust levels for information they receive from U.S. government agencies. Location, age and income also turn out to be significant factors in the case of the truncated part of the estimation as do food quality and food safety concerns.Consumer/Household Economics,

Privacy-preserving data outsourcing in the cloud via semantic data splitting

Even though cloud computing provides many intrinsic benefits, privacy concerns related to the lack of control over the storage and management of the outsourced data still prevent many customers from migrating to the cloud. Several privacy-protection mechanisms based on a prior encryption of the data to be outsourced have been proposed. Data encryption offers robust security, but at the cost of hampering the efficiency of the service and limiting the functionalities that can be applied over the (encrypted) data stored on cloud premises. Because both efficiency and functionality are crucial advantages of cloud computing, in this paper we aim at retaining them by proposing a privacy-protection mechanism that relies on splitting (clear) data, and on the distributed storage offered by the increasingly popular notion of multi-clouds. We propose a semantically-grounded data splitting mechanism that is able to automatically detect pieces of data that may cause privacy risks and split them on local premises, so that each chunk does not incur in those risks; then, chunks of clear data are independently stored into the separate locations of a multi-cloud, so that external entities cannot have access to the whole confidential data. Because partial data are stored in clear on cloud premises, outsourced functionalities are seamlessly and efficiently supported by just broadcasting queries to the different cloud locations. To enforce a robust privacy notion, our proposal relies on a privacy model that offers a priori privacy guarantees; to ensure its feasibility, we have designed heuristic algorithms that minimize the number of cloud storage locations we need; to show its potential and generality, we have applied it to the least structured and most challenging data type: plain textual documents

Selected Challenges From Spatial Statistics For Spatial Econometricians

Griffith and Paelinck (2011) present selected non-standard spatial statistics and spatial econometrics topics that address issues associated with spatial econometric methodology. This paper addresses the following challenges posed by spatial autocorrelation alluded to and/or derived from the spatial statistics topics of this book: the Gaussian random variable Jacobian term for massive datasets; topological features of georeferenced data; eigenvector spatial filtering-based georeferenced data generating mechanisms; and, interpreting random effects.Artykuł prezentuje wybrane, niestandardowe statystyki przestrzenne oraz zagadnienia ekonometrii przestrzennej. Rozważania teoretyczne koncentrują się na wyzwaniach wynikających z autokorelacji przestrzennej, nawiązując do pojęć Gaussowskiej zmiennej losowej, topologicznych cech danych georeferencyjnych, wektorów własnych, filtrów przestrzennych, georeferencyjnych mechanizmów generowania danych oraz interpretacji efektów losowych

Understanding Linkages among Food Availability, Access, Consumption, and Nutrition in Africa: Empirical Findings and Issues from the Literature

This paper starts with the unsurprising observations that (1) having enough food available at national and local levels is necessary but not sufficient for ensuring that households have adequate access to food; (2) having adequate household access to food is necessary but not sufficient for ensuring that all household members consume an adequate diet; and (3) consuming an adequate diet is necessary but not sufficient for maintaining a healthy nutritional status. Recognizing that the links from food availability to access to consumption to nutritional status are not automatic, the challenge for policy makers and analysts concerned with achieving food and nutrition security is to understand how these variables are linked to one another, how closely they are related in various contexts, and what the important intervening variables are which affect the linkages among these variables. Unfortunately, however, our ability to understand the nature and extent of the relationships among these variables in detail has been hampered by a lack of information as well as by concerns over the appropriateness of the analytical approaches and indicators that have been used in empirical studies of these issues.food security, food policy, Food Security and Poverty, Downloads July 2008-July 2009: 14, Q18,

THE IMPACT OF NEW INDUSTRY ON COUNTY GOVERNMENT PROPERTY TAX REVENUE

Public Economics,