2,650 research outputs found

    Publication Patterns of Male and Female Faculty Members in the Communication Discipline

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    This article presents a study on the publication patterns of male and female faculty members in the communication administration in the U.S. Male faculty published more than female faculty in multiple ways. Specifically, men were more frequently sole authors that women, and men were more often in the first and second position in cases of joint authorship. while no sex difference were found overall for frequency of co-authored articles, there were male-only than female-only co-authored publications. The implications of these findings, in terms of sex-based differences in publication patterns, are considerable. Research has become increasingly important in promotion and tenure decisions

    Faculty and Student Expectations/Perceptions of the Adviser-Advisee Relationship

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    This article discusses the importance of the relationship between faculty adviser and advisee. The faculty advising system is one of the principal ways provided for accomplishing improvement in faculty-student interaction. Direct contact with their advisees can benefit students in multiple ways. Contact with professional staff has been associated with increased retention among undergraduate university students. Students also benefit scholastically and affectively from such contact. Faculty and academic institutions also can derive benefits from the adviser-advisee relationship. The quality of the advising relationship is a major contributor to institutional holding power

    An Exploration of Target Event Encoding in a Predictive Learning Task with Humans: Integrated or Separable Processing?

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    A major theme in the study of Pavlovian learning explores how attributes of a predicted event are represented and encoded. In Pavlovian conditioning, the conditioned stimulus (CS) is frequently assumed to associate with one or more of the various attributes of a motivationally significant unconditioned stimulus (US, e.g. it’s hedonic, motivational, and/or sensory features). The present research asks whether humans learn to predict and encode different aspects of motivationally neutral target events, namely, their specific sensory and temporal features in a separable or integrated manner. This question of how target events are encoded has implications for associative and timing models of Pavlovian learning, and associative learning more generally. The associative approach assumes that a CS could enter into separate associations with distinctive aspects of the US, while other timing-focused models suggest that these aspects would be encoded in an integrated manner. To investigate this question, four predictive learning tasks with human participants were designed with the goal of seeking evidence to support one or the other of these encoding possibilities. In an initial experiment, subjects were trained with a single ISI and tested with multiple ISIs in a two alternative forced choice and a go/no go version of the task. In Experiment 2 subjects were presented with four cues and two targets, where two cue-target pairs were trained at a short ISI and two at a long ISI. Then valid and invalid cue-target pairs were tested at both ISIs. Experiment 3 presented four unique cue-target pairs trained in a four-alternative forced choice task. Two pairs were trained at a short ISI and two at a long ISI. During test, valid and invalid cue-target pairs were tested at both short and long ISIs. Experiment 4 employed a conditional discrimination training procedure, where one of two cues predicted target 1 after a short ISI and target 2 after a long ISI, and the other cue signaled target 2 after a short ISI and target 1 after a long ISI. In test, subjects received probe trials in which the cue-target relations were tested at their untrained ISIs. Results from all experiments reveal a consistent pattern – subjects’ reaction times were faster to validly than invalidly cued targets when these relations were tested at the training ISI, and the magnitude of this validity effect was not reduced when testing occurred with alternative ISIs. The outcome of this investigation, of how sensory and temporal attributes of the US are encoded, has resulted in support of the separable encoding account. These findings are at odds with the limited work on this problem. However, there is support in the associative literature for independent associations forming between a CS and the sensory and motivational attributes of the US, and recent evidence that the neural mechanisms mediating these two forms of learning are dissociable. The main implication of the present studies is that a similar dissociation may exist regarding learning about specific sensory and temporal features of the US

    Kinetic distance and kinetic maps from molecular dynamics simulation

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    Characterizing macromolecular kinetics from molecular dynamics (MD) simulations requires a distance metric that can distinguish slowly-interconverting states. Here we build upon diffusion map theory and define a kinetic distance for irreducible Markov processes that quantifies how slowly molecular conformations interconvert. The kinetic distance can be computed given a model that approximates the eigenvalues and eigenvectors (reaction coordinates) of the MD Markov operator. Here we employ the time-lagged independent component analysis (TICA). The TICA components can be scaled to provide a kinetic map in which the Euclidean distance corresponds to the kinetic distance. As a result, the question of how many TICA dimensions should be kept in a dimensionality reduction approach becomes obsolete, and one parameter less needs to be specified in the kinetic model construction. We demonstrate the approach using TICA and Markov state model (MSM) analyses for illustrative models, protein conformation dynamics in bovine pancreatic trypsin inhibitor and protein-inhibitor association in trypsin and benzamidine

    Coarse-graining the Dynamics of a Driven Interface in the Presence of Mobile Impurities: Effective Description via Diffusion Maps

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    Developing effective descriptions of the microscopic dynamics of many physical phenomena can both dramatically enhance their computational exploration and lead to a more fundamental understanding of the underlying physics. Previously, an effective description of a driven interface in the presence of mobile impurities, based on an Ising variant model and a single empirical coarse variable, was partially successful; yet it underlined the necessity of selecting additional coarse variables in certain parameter regimes. In this paper we use a data mining approach to help identify the coarse variables required. We discuss the implementation of this diffusion map approach, the selection of a similarity measure between system snapshots required in the approach, and the correspondence between empirically selected and automatically detected coarse variables. We conclude by illustrating the use of the diffusion map variables in assisting the atomistic simulations, and we discuss the translation of information between fine and coarse descriptions using lifting and restriction operators.Comment: 28 pages, 10 figure

    Ions in Fluctuating Channels: Transistors Alive

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    Ion channels are proteins with a hole down the middle embedded in cell membranes. Membranes form insulating structures and the channels through them allow and control the movement of charged particles, spherical ions, mostly Na+, K+, Ca++, and Cl-. Membranes contain hundreds or thousands of types of channels, fluctuating between open conducting, and closed insulating states. Channels control an enormous range of biological function by opening and closing in response to specific stimuli using mechanisms that are not yet understood in physical language. Open channels conduct current of charged particles following laws of Brownian movement of charged spheres rather like the laws of electrodiffusion of quasi-particles in semiconductors. Open channels select between similar ions using a combination of electrostatic and 'crowded charge' (Lennard-Jones) forces. The specific location of atoms and the exact atomic structure of the channel protein seems much less important than certain properties of the structure, namely the volume accessible to ions and the effective density of fixed and polarization charge. There is no sign of other chemical effects like delocalization of electron orbitals between ions and the channel protein. Channels play a role in biology as important as transistors in computers, and they use rather similar physics to perform part of that role. Understanding their fluctuations awaits physical insight into the source of the variance and mathematical analysis of the coupling of the fluctuations to the other components and forces of the system.Comment: Revised version of earlier submission, as invited, refereed, and published by journa

    Smoothness in n-hold hyperspaces

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    We prove that *-smoothness of a homogeneous continuum implies its indecomposability. We define the analogue of *-smoothness for n-fold hyperspaces and investigate its relation to *-smoothness. We characterize the class of hereditarily indecomposable continua in terms of n*-smoothness

    Hyperspaces with exactly two orbits

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    Let C(X) be the hyperspace of all subcontinua of a (metric) continuum X. It is known that C(X) is homogeneous if and only if C(X) is the Hilbert cube. We are interested in knowing when C(X) is 1/2-homogeneous, meaning that there are exactly two orbits for the action of the group of homeomorphisms of C(X) onto C(X). It is shown that if X is a locally connected continuum or a nondegenerate atriodic continuum, and if C(X) is 1/2-homogeneous, then X is an arc or a simple closed curve. We do not know whether an arc and a simple closed curve are the only continua X for which C(X) is 1/2-homogeneous

    Rejoinder of: Treelets--An adaptive multi-scale basis for spare unordered data

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    Rejoinder of "Treelets--An adaptive multi-scale basis for spare unordered data" [arXiv:0707.0481]Comment: Published in at http://dx.doi.org/10.1214/08-AOAS137REJ the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org
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