The entropy puzzle and the quark combination model

We use two available methods, the Duhem-Gibbs relation and the entropy formula in terms of particle phase space distributions, to calculate the entropy in a quark combination model. The entropy of the system extracted from the Duhem-Gibbs relation is found to increase in hadronization if the average temperature of the hadronic phase is lower than that of the quark phase. The increase of the entropy can also be confirmed from the entropy formula if the volume of the hadronic phase is larger than 2.5-3.0 times that of the quark phase. So whether the entropy increases or decreases during combination depends on the temperature before and after combination and on how much expansion the system undergoes during combination. The current study provides an example to shed light on the entropy issue in the quark combination model.Comment: RevTex 4, 4 pages, 2 tables, 4 figures, discussions and references added, to appear in PR

Measurement-induced integer families of critical dynamical scaling in quantum many-body systems

A quantum many-body system can undergo transitions in the presence of continuous measurement. In this work, we find that a generic class of critical dynamical scaling behavior can emerge at these measurement-induced transitions. Remarkably, depending on the symmetry that can be respected by the system, different integer families of dynamical scaling can emerge. The origin of these scaling families can be traced back to the presence of hierarchies of high order exceptional points in the effective non-Hermitian descriptions of the systems. Direct experimental observation of this class of dynamical scaling behavior can be readily achieved using ultracold atoms in optical lattices or through intermediate-scale quantum computing systems.Comment: 4.5 pages (3 figures) + supplemental material (7 figures

Threat appeals in public service announcements: Effects of message framing and relationship norms.

Threat appeals have been widely utilized in numerous types of public service announcements (PSAs), and previous research has focused on the impact of the inherent messages in these announcements. By examining the research on the effects of framing PSAs in terms of the threat of the message to oneself or others, we proposed a clear conceptualization of "threat-target framing." The first two studies addressed the direct effects of threat-target framing and found that other-oriented threat appeals can evoke more guilt than can self-oriented threat appeals. Moreover, self-oriented threat appeals can evoke more fear and immediately direct recipients’ attention to the smoker than can other-oriented threat appeals. Study 3 reported that a contextual factor-relationship norms-was introduced as a potential moderating factor. Results showed that relationship norms had the potential to moderate the effect of threat-target framing on recipients’ fear response, but not the effect on recipients’ guilt and coping response. In sum, the results highlighted the importance of message framing of advertising copies and the placement context. Our findings may be useful in understanding the antecedents of the persuasiveness of PSAs

Outlier-Detection Based Robust Information Fusion for Networked Systems

We consider state estimation for networked systems where measurements from sensor nodes are contaminated by outliers. A new hierarchical measurement model is formulated for outlier detection by integrating the outlier-free measurement model with a binary indicator variable. The binary indicator variable, which is assigned a beta-Bernoulli prior, is utilized to characterize if the sensor's measurement is nominal or an outlier. Based on the proposed outlier-detection measurement model, both centralized and decentralized information fusion filters are developed. Specifically, in the centralized approach, all measurements are sent to a fusion center where the state and outlier indicators are jointly estimated by employing the mean-field variational Bayesian inference in an iterative manner. In the decentralized approach, however, every node shares its information, including the prior and likelihood, only with its neighbors based on a hybrid consensus strategy. Then each node independently performs the estimation task based on its own and shared information. In addition, an approximation distributed solution is proposed to reduce the local computational complexity and communication overhead. Simulation results reveal that the proposed algorithms are effective in dealing with outliers compared with several recent robust solutions

Consensus disturbance rejection for Lipschitz nonlinear multi-agent systems with input delay: a DOBC approach

In this paper, a new predictor-based consensus disturbance rejection method is proposed for high-order multi agent systems with Lipschitz nonlinearity and input delay. First, a distributed disturbance observer for consensus control is developed for each agent to estimate the disturbance under the delay constraint. Based on the conventional predictor feedback approach, a non-ideal predictor based control scheme is constructed for each agent by utilizing the estimate of the disturbance and the prediction of the relative state information. Then, rigorous analysis is carried out to ensure that the extra terms associated with disturbances and nonlinear functions are properly considered. Sufficient conditions for the consensus of the multi-agent systems with disturbance rejection are derived based on the analysis in the framework of Lyapunov-Krasovskii functionals. A simulation example is included to demonstrate the performance of the proposed control scheme. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.National Natural Science Foundation of China [61673034]SCI(E)ARTICLE1,SI298-31535

Differential impact of affective and cognitive attributes on preference under deliberation and distraction

Two experiments were designed to test the hypothesis that affective information looms relatively larger than cognitive information when individuals are distracted for a period of time compared to when they engage in deliberative thinking. In two studies, participants were presented with information about 4 decision alternatives: An affective alternative that scored high on affective attributes but low on cognitive attributes, a cognitive alternative with the opposite trade-off, and two fillers. They were then asked to indicate their attitudes toward each of four decision alternatives either immediately, after a period of deliberation, or after a period of distraction. The results of both experiments demonstrated that participants significantly preferred the affective alternative to the cognitive alternative after distraction, but not after deliberation. The implications for understanding when and how unconscious thought may lead to better decisions are being discussed

Close-knit ties through thick and thin: sharing social exclusion and acceptance enhances social bond

Three experiments investigated whether and why sharing experiences of social exclusion or social acceptance with others strengthens social bonds. Participants experienced either social exclusion or social acceptance alongside another co-participant who either also experienced the same outcome, or experienced a different outcome, as them. Multilevel modeling results showed that participant dyads who shared the experience of social exclusion or social acceptance felt closer to each other than those who experienced different outcomes, and that perceived similarity mediated the effect of shared experiences on social bonds. Interestingly, participants felt closer to one another after having shared social acceptance, more so than when they have shared social exclusion. Implications of the present findings are interpreted in light of theories of social exclusion, shared experiences, and social bonding

Multiple Events of Allopolyploidy in the Evolution of the Racemose Lineages in Prunus (Rosaceae) Based on Integrated Evidence from Nuclear and Plastid Data.

Prunus is an economically important genus well-known for cherries, plums, almonds, and peaches. The genus can be divided into three major groups based on inflorescence structure and ploidy levels: (1) the diploid solitary-flower group (subg. Prunus, Amygdalus and Emplectocladus); (2) the diploid corymbose group (subg. Cerasus); and (3) the polyploid racemose group (subg. Padus, subg. Laurocerasus, and the Maddenia group). The plastid phylogeny suggests three major clades within Prunus: Prunus-Amygdalus-Emplectocladus, Cerasus, and Laurocerasus-Padus-Maddenia, while nuclear ITS trees resolve Laurocerasus-Padus-Maddenia as a paraphyletic group. In this study, we employed sequences of the nuclear loci At103, ITS and s6pdh to explore the origins and evolution of the racemose group. Two copies of the At103 gene were identified in Prunus. One copy is found in Prunus species with solitary and corymbose inflorescences as well as those with racemose inflorescences, while the second copy (II) is present only in taxa with racemose inflorescences. The copy I sequences suggest that all racemose species form a paraphyletic group composed of four clades, each of which is definable by morphology and geography. The tree from the combined At103 and ITS sequences and the tree based on the single gene s6pdh had similar general topologies to the tree based on the copy I sequences of At103, with the combined At103-ITS tree showing stronger support in most clades. The nuclear At103, ITS and s6pdh data in conjunction with the plastid data are consistent with the hypothesis that multiple independent allopolyploidy events contributed to the origins of the racemose group. A widespread species or lineage may have served as the maternal parent for multiple hybridizations involving several paternal lineages. This hypothesis of the complex evolutionary history of the racemose group in Prunus reflects a major step forward in our understanding of diversification of the genus and has important implications for the interpretation of its phylogeny, evolution, and classification