The effect of flaming on computer-mediated negotiations

There is an increasing use of computer media for negotiations. However, the use of computer-mediated channels increases the hostile expressions of emotion, termed flaming. Although researchers agree that flaming has important effects on negotiation, predictions concerning these effects are inconsistent, suggesting a need for further investigation. We address this need by extending current flaming and negotiation research in two ways. First, we identify two different types of flaming: that which is motivated by perceptions concerning the negotiating opponent (e.g., he/she is unfair) and that which is motivated by perceptions concerning the negotiating context (e.g., the communication channel is too slow). Second, we differentiate between the effects of flaming on the concession behaviors of the flame sender and the flame recipient, and the effects of these behaviors on negotiated agreement. Via a laboratory study, we demonstrate that flames directed at the negotiation opponent slightly decrease the likelihood of reaching an agreement, and when an agreement is reached, it result in outcomes significantly favoring the flame recipient rather than the flame sender. In contrast, flames directed at the negotiation context significantly increase the likelihood of agreement, although outcomes still favor the flame recipient over the flame sender. These results suggest that flame senders are generally worse off than flame recipients, which provides an important basis for the strategic use of flaming in negotiations.     

Survey of modular ontology techniques and their applications in the biomedical domain

In the past several years, various ontologies and terminologies such as the Gene Ontology have been developed to enable interoperability across multiple diverse medical information systems. They provide a standard way of representing terms and concepts thereby supporting easy transmission and interpretation of data for various applications. However, with their growing utilization, not only has the number of available ontologies increased considerably, but they are also becoming larger and more complex to manage. Toward this end, a growing body of work is emerging in the area of modular ontologies where the emphasis is on either extracting and managing "modules" of an ontology relevant to a particular application scenario (ontology decomposition) or developing them independently and integrating into a larger ontology (ontology composition). In this paper, we investigate state-of-the-art approaches in modular ontologies focusing on techniques that are based on rigorous logical formalisms as well as well-studied graph theories. We analyze and compare how such approaches can be leveraged in developing tools and applications in the biomedical domain. We conclude by highlighting some of the limitations of the modular ontology formalisms and put forward additional requirements to steer their future development.     

Distribution-Driven Visualization of Volume Data

Feature detection and display are the essential goals of the visualization process. Most visualization software achieves these goals by mapping properties of sampled intensity values and their derivatives to color and opacity. In this work, we propose to explicitly study the local frequency distribution of intensity values in broader neighborhoods centered around each voxel. We have found frequency distributions to contain meaningful and quantitative information that is relevant for many kinds of feature queries. Our approach allows users to enter predicate-based hypotheses about relational patterns in local distributions and render visualizations that show how neighborhoods match the predicates. Distributions are a familiar concept to nonexpert users, and we have built a simple graphical user interface for forming and testing queries interactively. The query framework readily applies to arbitrary spatial data sets and supports queries on time variant and multifield data. Users can directly query for classes of features previously inaccessible in general feature detection tools. Using several well-known data sets, we show new quantitative features that enhance our understanding of familiar visualization results.     

A Y-channel design for improving zeta potential and surface conductivity measurements using the current monitoring method

This study presents a new Y-channel design for measuring the zeta potential and surface conductance of a solid-liquid pairing using the current monitoring technique. The new design improves the throughput and reliability of the testing apparatus since the displacement between two solutions can be repeated many times without interfering with the experiments. It also increases the accuracy of the measurement by producing sharper start and end transitions for the current–time plot of the solution displacement process. In this design, efforts have been made to minimize the effects of electrolysis, Joule heating and undesired pressure driven flow on the measurements. An improvement on the current–time slope analysis is also presented. The Y-channel design was validated by comparing zeta potential measurements to published results. The zeta potential of several biological buffers relevant to the microfluidic community in plasma treated PDMS/PDMS and PDMS/Glass microchannels are presented. Preliminary studies of surface conductivity measurements using the Y-channel design were also conducted and are briefly discussed.     

The role of anergy in peripheral T cell unresponsiveness

When a T cell's encounter with specific antigen results in good signaling through the T cell antigen receptor yet does not lead to a proliferative response, the T cell enters a state of nonresponsiveness, or anergy. Anergy induction can result from a number of different situations, including antigen presentation by costimulation-deficient or "non-professional" antigen presenting cells, pharmacological blocking of T cell proliferation, or chronic stimulation of the T cell receptor by antigen. Anergy is a long-lived but temporary state characterized by a profound inability of the T cell to produce IL-2. Other effector functions may be affected to variable degrees. Anergy has been characterized most carefully under in vitro conditions, but several experimental models have demonstrated that T cells can also become anergic in vivo. This mechanism for tolerance induction may help to ensure that any mature autoreactive T cells which escape thymic deletion are unable to respond to host tissues. Furthermore, an understanding of the mechanism of anergy induction will most certainly lead to beneficial clinical applications, including improving graft acceptance and avoiding such deleterious immune responses as autoimmunity and allergy.     

Renal proliferative and phenotypic changes in rats with two-kidney, one-clip Goldblatt hypertension

Previous research in this laboratory has shown that preweaning and postweaning juvenile meadow voles, Microtus pennsylvanicus, can acquire a spatial task, the Morris water-maze task. The present study examined the influence of age of juvenile acquisition ("before weaning" (BW; Day 10 and 15 after birth) and "after weaning" (AW; Day 20 and 25 after birth)) of a spatial task on subsequent re-acquisition of the same hidden-platform spatial water-maze task. This study also compared sex differences and litter sex-ratio effects on reacquisition performance. Fifteen litters of adults were re-tested in the same water maze 6 weeks after being initially tested as juveniles. All analyses were conducted using a covariate that removed the group differences in the original task performance. Adult voles from female-biased litters, that had previously learned the task at an older juvenile age (AW), reacquired the same task faster than adults that had previously learned the task at a younger juvenile age (BW). In the adult BW group there was also a significant litter sex-ratio effect such that voles born into a female-biased litter re-acquired the task more slowly than did voles born into a male-biased litter. There were no significant sex or litter sex-ratio effects on spatial learning in the AW group. These results show that adult meadow voles can require a spatial task more quickly if they initially learned the task at an older juvenile age, suggestive of a period of infantile amnesia. In addition, these results indicate that the litter sex-ratio can affect adult spatial performance, suggesting that the relative amount of androgens in utero may influence the development of sexually-dimorphic spatial ability in adulthood.     

Development and field demonstration of a hardware-compressive fiber-optic true-time-delay steering system for phased-array antennas

We describe the design, fabrication, testing, and antenna-range demonstration of a photonic wavelengthmultiplexed true-time-delay steering system for use with broadband phased-array antennas. The prototype system is based on a unique hardware-compressive architecture and can drive 16 antenna elements over the 0.35-2.1-GHz band with 6-bit angular resolution over a ±45° scan angle.     

Case-Based Learning: Predictive Features in Indexing

Interest in psychological experimentation from the Artificial Intelligence community often takes the form of rigorous post-hoc evaluation of completed computer models. Through an example of our own collaborative research, we advocate a different view of how psychology and AI may be mutually relevant, and propose an integrated approach to the study of learning in humans and machines. We begin with the problem of learning appropriate indices for storing and retrieving information from memory. From a planning task perspective, the most useful indices may be those that predict potential problems and access relevant plans in memory, improving the planner's ability to predict and avoid planning failures. This predictive features hypothesis is then supported as a psychological claim, with results showing that such features offer an advantage in terms of the selectivity of reminding because they more distinctively characterize planning situations where differing plans are appropriate.We present a specific case-based model of plan execution, RUNNER, along with its indices for recognizing when to select particular plans—appropriateness conditions—and how these predictive indices serve to enhance learning. We then discuss how this predictive features claim as implemented in the RUNNER model is then tested in a second set of psychological studies. The results show that learning appropriateness conditions results in greater success in recognizing when a past plan is in fact relevant in current processing, and produces more reliable recall of the related information. This form of collaboration has resulted in a unique integration of computational and empirical efforts to create a model of case-based learning.