A relativistically covariant version of Bohm's quantum field theory for the scalar field

We give a relativistically covariant, wave-functional formulation of Bohm's quantum field theory for the scalar field based on a general foliation of space-time by space-like hypersurfaces. The wave functional, which guides the evolution of the field, is space-time-foliation independent but the field itself is not. Hence, in order to have a theory in which the field may be considered a beable, some extra rule must be given to determine the foliation. We suggest one such rule based on the eigen vectors of the energy-momentum tensor of the field itself.Comment: 1 figure. Submitted to J Phys A. 20/05/04 replacement has additional references and a few minor changes made for clarity. Accepted by J Phys

A self-study course in FORTRAN programming. Volume 2 - Workbook

Self study workbook for course in FORTRAN programming - Vol.

Using evidence to inform health policy: case study

No abstract available

Greater data science at baccalaureate institutions

Donoho's JCGS (in press) paper is a spirited call to action for statisticians, who he points out are losing ground in the field of data science by refusing to accept that data science is its own domain. (Or, at least, a domain that is becoming distinctly defined.) He calls on writings by John Tukey, Bill Cleveland, and Leo Breiman, among others, to remind us that statisticians have been dealing with data science for years, and encourages acceptance of the direction of the field while also ensuring that statistics is tightly integrated. As faculty at baccalaureate institutions (where the growth of undergraduate statistics programs has been dramatic), we are keen to ensure statistics has a place in data science and data science education. In his paper, Donoho is primarily focused on graduate education. At our undergraduate institutions, we are considering many of the same questions.Comment: in press response to Donoho paper in Journal of Computational Graphics and Statistic

The why's the limit: curtailing self-enhancement with explanatory introspection

Self-enhancement is linked to psychological gains (e.g., subjective well-being, persistence in adversity) but also to intrapersonal and interpersonal costs (e.g., excessive risk taking, antisocial behavior). Thus, constraints on self-enhancement may sometimes afford intrapersonal and interpersonal advantages. We tested whether explanatory introspection (i.e., generating reasons for why one might or might not possess personality traits) constitutes one such constraint. Experiment 1 demonstrated that explanatory introspection curtails self-enhancement. Experiment 2 clarified that the underlying mechanism must (a) involve explanatory questioning rather than descriptive imagining, (b) invoke the self rather than another person, and (c) feature written expression rather than unaided contemplation. Finally, Experiment 3 obtained evidence that an increase in uncertainty about oneself mediates the effect

A self-study course in FORTRAN programming. Volume 1 - Textbook

Self study textbook for course in FORTRAN programming - Vol.

FORTRAN programming - A self-taught course

Comprehensive programming course begins with numerical systems and basic concepts, proceeds systematically through FORTRAN language elements, and concludes with discussion of programming techniques. Course is suitable either for individual study or for group study on informal basis

Community-level characteristics of high infant mortality: A tool to identify at-risk communities

Infant mortality (IM) rate is a key indicator of population health and has been gradually improving in the United States. However, it is still a public health problem among minority and low-income communities. Maternal factors explain some of the variation, but community-level factors may also be a contributor. This study examines measures to identify a set of indicators that explain variations in IM at the community-level. Data for 77 communities in a city were obtained from local health databases. We used multivariable linear regression models to examine the strength of the association between IM and maternal, population, community wealth, and social capital characteristics. Community-level IM rates ranged from 2.1 – 25.6 deaths per 1,000 live births in 2000-2002. The final model explained 75% of the variation in IM rates at the community-level (R2=0.75). The model included a high percentage of low birth weight babies, a decline in mothers who began prenatal care in the second trimester, an increase in the percentage of Hispanics, increased unemployment rates, an increase in the percentage of veterans, an increased rate of foreign-born residents, and smaller average family sizes. Social capital variables, homicide rate and vacant housing, were also significant in the final model. Identifying communities at risk for high IM rates is imperative to improve maternal and child health outcomes because of shortages in public health resources. The development of a parsimonious set of community-level indicators can assist public health practitioners in targeting their resources to prevent infant mortality in high-risk communities