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.

Evidence from d + Au measurements for final state suppression of high p(T) hadrons in Au+Au collisions at RHIC

Abstract: We report measurements of single-particle inclusive spectra and two-particle azimuthal distributions of charged hadrons at high transverse momentum (high p(T)) in minimum bias and central d+Au collisions at sqrt[s(NN)]=200 GeV. The inclusive yield is enhanced in d+Au collisions relative to binary-scaled p+p collisions, while the two-particle azimuthal distributions are very similar to those observed in p+p collisions. These results demonstrate that the strong suppression of the inclusive yield and back-to-back correlations at high p(T) previously observed in central Au+Au collisions are due to final-state interactions with the dense medium generated in such collisions.

Room-temperature coherent coupling of single spins in diamond

Abstract: Coherent coupling between single quantum objects is at the very heart of modern quantum physics. When the coupling is strong enough to prevail over decoherence, it can be used to engineer quantum entangled states. Entangled states have attracted widespread attention because of applications to quantum computing and long-distance quantum communication. For such applications, solid-state hosts are preferred for scalability reasons, and spins are the preferred quantum system in solids because they offer long coherence times. Here we show that a single pair of strongly coupled spins in diamond, associated with a nitrogen-vacancy defect and a nitrogen atom, respectively, can be optically initialized and read out at room temperature. To effect this strong coupling, close proximity of the two spins is required, but large distances from other spins are needed to avoid deleterious decoherence. These requirements were reconciled by implanting molecular nitrogen into high-purity diamond.

Perceiving interpersonal conflict and reacting to it: the case for agreeableness.

Abstract: Two converging, multimethod studies probed the hypothesis that individual differences in Agreeableness are related to patterns of interpersonal conflict. In Study 1, participants (N = 263) evaluated the efficacy of 11 modes of conflict resolution within the context of 5 different interpersonal relationships. Across all relationships, high- and low-agreeable participants rated negotiation and disengagement tactics as better choices that power assertion tactics. However, low-agreeable participants rated power assertion as a better choice than did high-agreeable participants. In Study 2, participants (N = 124) were assigned partners and were asked to resolve jointly 2 social conflict problems. Partners were videotaped, and observers coded behaviors. Participants also completed ratings of perceived conflict, partner perception, and liking of their partner. Agreeableness differences, sex of participant, and type of dyad partner were related to patterns of interpersonal conflict. Results were discussed in terms of personality and social influences during interpersonal conflict.

Data and Statistics

Abstract: Publisher Summary This chapter defines the components of a dataset, presents tools that are used to describe a dataset, and briefly discusses methods of data collection. A set of data is defined as a collection of observed values representing one or more characteristics of some objects or units. Data are obtained from two broad categories of sources: (1) primary data are collected as part of the study and (2) secondary data are obtained from published sources such as journals, governmental publications, news media, or almanacs. The observations can be classified according to a standard measurement scale that goes from strong to weak depending on the amount or precision of information available in the scale. The nature of the data description and statistical inference is dependent on the type of variable being studied. The ratio scale of measurement uses the concept of a unit of distance or measurement and requires a unique definition of a zero value, whereas the interval scale of measurement also uses the concept of distance or measurement and requires a “zero” point, but the definition of zero may be arbitrary. There are also the ordinal scale and the nominal scale that distinguishes among measurements on the basis of the relative amounts of some characteristic they possess and identifies observed values by name or classification, respectively.