Texas A&M University

About: Texas A&M University is a education organization based out in College Station, Texas, United States. It is known for research contribution in the topics: Population & Finite element method. The organization has 72169 authors who have published 164372 publications receiving 5764236 citations.

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

Abstract: Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has been an area of research focus for many decades. However, in the absence of detailed driving data that would help improve the identification of cause and effect relationships with individual vehicle crashes, most researchers have addressed this problem by framing it in terms of understanding the factors that affect the frequency of crashes - the number of crashes occurring in some geographical space (usually a roadway segment or intersection) over some specified time period. This paper provides a detailed review of the key issues associated with crash-frequency data as well as the strengths and weaknesses of the various methodological approaches that researchers have used to address these problems. While the steady march of methodological innovation (including recent applications of random parameter and finite mixture models) has substantially improved our understanding of the factors that affect crash-frequencies, it is the prospect of combining evolving methodologies with far more detailed vehicle crash data that holds the greatest promise for the future.

The Development of Organizational Social Capital: Attributes of Family Firms*

Abstract: We develop and extend social capital theory by exploring the creation of organizational social capital within a highly pervasive, yet often overlooked organizational form: family firms. We argue that family firms are unique in that, although they work as a single entity, at least two forms of social capital coexist: the family's and the firm's. We investigate mechanisms that link a family's social capital to the creation of the family firm's social capital and examine how factors underlying the family's social capital affect this creation. Moreover, we identify contingency dimensions that affect these relationships and the potential risks associated with family social capital. Finally, we suggest these insights are generalizable to several other types of organizations with similar characteristics.

Influence of attachment styles on romantic relationships.

Abstract: This investigation examined the impact of secure, anxious, and avoidant attachment styles on romantic relationships in a longitudinal study involving 144 dating couples. For both men and women, the secure attachment style was associated with greater relationship interdependence, commitment, trust, and satisfaction than were the anxious or avoidant attachment styles. The anxious and avoidant styles were associated with less frequent positive emotions and more frequent negative emotions in the relationship, whereas the reverse was true of the secure style. Six-month follow-up interviews revealed that, among those individuals who disbanded, avoidant men experienced significantly less post-dissolution emotional distress than did other people. In recent years, a growing number of researchers have become interested in the processes by which people develop, maintain, and dissolve affectional bonds within close relationships (see Bretherton, 1985; Clark & Reis, 1988). Empirical research in this area was spawned by the pioneering theoretical work of John Bowlby (1969,1973,1980), who sought to determine how and why infants become emotionally attached to their primary caregivers and why they often experience emotional distress when physically separated from them. Bowlby identified a clear sequence of three emotional reactions that typically occur following the separation of an infant from its primary caregiver: protest, despair, and detachment. Given the remarkably reliable nature of this sequence across a variety of different species, Bowlby developed a theory of attachment grounded in evolutionary principles. Specifically, he argued that an attachment system composed of specific behavioral and emotional propensities designed to keep infants in close physical proximity to their primary caregivers might have been selected during evolutionary history. By remaining in close contact with caregivers who could protect them from danger and predation, infants who possessed these attachment propensities would have been more likely to survive to reproductive age, reproduce, and subsequently pass these propensities on to future generations. Empirical research examining tenets of Bowlby's theory has focused mainly on different styles or patterns of attachment in young children. Ainsworth, Blehar, Waters, & Wall (1978) have identified three primary attachment styles: anxious/ambivalent

Fluorescent indicators for intracellular pH.

Abstract: 5. Cyanine-Based pHi Indicators 2717 5.1. Design of pH-Sensitive Cyanine Dyes 2717 5.2. Near-Neutral Cyanine-Based pH Indicators 2718 5.3. Acidic Cyanine-Based pH Indicators 2719 6. Miscellaneous Small Molecule pHi Indicators 2719 6.1. Various Indicators for Near-Neutral pH Values 2719 6.1.1. Europium Complex 2719 6.1.2. Fluorene Derivative 2719 6.1.3. 1,4-Dihydroxyphthalonitrile (1,4-DHPN) 2720 6.1.4. 8-Hydroxypyrene-1,3,6-trisulfonic acid (HPTS) 2720

Rising Temperatures Reduce Global Wheat Production

Abstract: Crop models are essential tools for assessing the threat of climate change to local and global food production(1). Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature(2). Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degrees C of further temperature increase and become more variable over space and time.