Exploring Entrepreneurial Skills and Competencies in Farm Tourism

Diversification to farm tourism is increasingly seen as a viable development strategy to promote a more diverse and sustainable rural economy and to counter declining farm incomes. However, our understanding of the dynamics of the modern farm tourism business and the entrepreneurial and competitive skills farmers require in making the transition from agriculture to a diversified - and service based - enterprise remains limited. Hence, the aim of this paper is to explore the range of skills and competencies that farmers in the North West of England identify as important when adopting a diversification strategy to farm tourism. With the findings indicating that that whilst a range of managerial skills are valued by farmers, they lack many of the additional business and entrepreneurial competencies required for success. Moreover, this paper acknowledges the need to generate consensus on the requisite skill-set that farm tourism operators require, along with a need for a currently fragmented rural tourism literature to acknowledge the significance of rural entrepreneurship and the characteristics of successful farmers and farm tourism ventures

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically

Restrictive ID policies: implications for health equity

We wish to thank Synod Community Services for their critical work to develop, support, and implement a local government-issued ID in Washtenaw County, MI. We also thank Yousef Rabhi of the Michigan House of Representatives and Janelle Fa'aola of the Washtenaw ID Task Force, Lawrence Kestenbaum of the Washtenaw County Clerk's Office, Sherriff Jerry Clayton of the Washtenaw County Sherriff's Office, and the Washtenaw ID Task Force for their tireless commitment to developing and supporting the successful implementation of the Washtenaw ID. Additionally, we thank Vicenta Vargas and Skye Hillier for their contributions to the Washtenaw ID evaluation. We thank the Curtis Center for Research and Evaluation at the University of Michigan School of Social Work, the National Center for Institutional Diversity at the University of Michigan, and the University of California-Irvine Department of Chicano/Latino Studies and Program in Public Health for their support of the Washtenaw ID community-academic research partnership. Finally, we thank the reviewers for their helpful comments on earlier drafts of this manuscript. (Curtis Center for Research and Evaluation at the University of Michigan School of Social Work; National Center for Institutional Diversity at the University of Michigan; University of California-Irvine Department of Chicano/Latino Studies; Program in Public Health)https://link.springer.com/content/pdf/10.1007/s10903-017-0579-3.pdfPublished versio

Lack of Evidence for an Association between Iridovirus and Colony Collapse Disorder

Colony collapse disorder (CCD) is characterized by the unexplained losses of large numbers of adult worker bees (Apis mellifera) from apparently healthy colonies. Although infections, toxins, and other stressors have been associated with the onset of CCD, the pathogenesis of this disorder remains obscure. Recently, a proteomics study implicated a double-stranded DNA virus, invertebrate iridescent virus (Family Iridoviridae) along with a microsporidium (Nosema sp.) as the cause of CCD. We tested the validity of this relationship using two independent methods: (i) we surveyed healthy and CCD colonies from the United States and Israel for the presence of members of the Iridovirus genus and (ii) we reanalyzed metagenomics data previously generated from RNA pools of CCD colonies for the presence of Iridovirus-like sequences. Neither analysis revealed any evidence to suggest the presence of an Iridovirus in healthy or CCD colonies

Toric Construction of Global F-Theory GUTs

We systematically construct a large number of compact Calabi-Yau fourfolds which are suitable for F-theory model building. These elliptically fibered Calabi-Yaus are complete intersections of two hypersurfaces in a six dimensional ambient space. We first construct three-dimensional base manifolds that are hypersurfaces in a toric ambient space. We search for divisors which can support an F-theory GUT. The fourfolds are obtained as elliptic fibrations over these base manifolds. We find that elementary conditions which are motivated by F-theory GUTs lead to strong constraints on the geometry, which significantly reduce the number of suitable models. The complete database of models is available at http://hep.itp.tuwien.ac.at/f-theory/. We work out several examples in more detail.Comment: 35 pages, references adde

A massive proto-cluster of galaxies at a redshift of z {\approx} 5.3

Massive clusters of galaxies have been found as early as 3.9 Billion years (z=1.62) after the Big Bang containing stars that formed at even earlier epochs. Cosmological simulations using the current cold dark matter paradigm predict these systems should descend from "proto-clusters" - early over-densities of massive galaxies that merge hierarchically to form a cluster. These proto-cluster regions themselves are built-up hierarchically and so are expected to contain extremely massive galaxies which can be observed as luminous quasars and starbursts. However, observational evidence for this scenario is sparse due to the fact that high-redshift proto-clusters are rare and difficult to observe. Here we report a proto-cluster region 1 billion years (z=5.3) after the Big Bang. This cluster of massive galaxies extends over >13 Mega-parsecs, contains a luminous quasar as well as a system rich in molecular gas. These massive galaxies place a lower limit of >4x10^11 solar masses of dark and luminous matter in this region consistent with that expected from cosmological simulations for the earliest galaxy clusters.Comment: Accepted to Nature, 16 Pages, 6 figure

A frequentist framework of inductive reasoning

Reacting against the limitation of statistics to decision procedures, R. A. Fisher proposed for inductive reasoning the use of the fiducial distribution, a parameter-space distribution of epistemological probability transferred directly from limiting relative frequencies rather than computed according to the Bayes update rule. The proposal is developed as follows using the confidence measure of a scalar parameter of interest. (With the restriction to one-dimensional parameter space, a confidence measure is essentially a fiducial probability distribution free of complications involving ancillary statistics.) A betting game establishes a sense in which confidence measures are the only reliable inferential probability distributions. The equality between the probabilities encoded in a confidence measure and the coverage rates of the corresponding confidence intervals ensures that the measure's rule for assigning confidence levels to hypotheses is uniquely minimax in the game. Although a confidence measure can be computed without any prior distribution, previous knowledge can be incorporated into confidence-based reasoning. To adjust a p-value or confidence interval for prior information, the confidence measure from the observed data can be combined with one or more independent confidence measures representing previous agent opinion. (The former confidence measure may correspond to a posterior distribution with frequentist matching of coverage probabilities.) The representation of subjective knowledge in terms of confidence measures rather than prior probability distributions preserves approximate frequentist validity.Comment: major revisio