Adult Attachment, Depressive Symptoms, and Validation From Self Versus Others.

Attachment working models of self and others may govern adults' preferences for internal vs. external sources of reassurance, which, if unavailable, lead to depressive symptoms. This study examined a model in which the link between depressive symptoms and attachment anxiety is mediated by (a) capacity for self-reinforcement and (b) need for reassurance from others, whereas the link between depressive symptoms and attachment avoidance is mediated only by the capacity for self-reinforcement. Analysis of survey data from 425 undergraduates indicated that both capacity for self-reinforcement and need for reassurance from others partially mediated the link between attachment anxiety and depression. Capacity for self-reinforcement fully mediated the link between attachment avoidance and depression. Moreover, 54% of the variance in depressive symptoms was explained by attachment anxiety, self-reinforcement, and need for reassurance from others. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Alpha Project: a model system for systems biology research

One goal of systems biology is to understand how genome-encoded parts interact to produce quantitative phenotypes. The Alpha Project is a medium-scale, interdisciplinary systems biology effort that aims to achieve this goal by understanding fundamental quantitative behaviours of a prototypic signal transduction pathway, the yeast pheromone response system from Saccharomyces cerevisiae. The Alpha Project distinguishes itself from many other systems biology projects by studying a tightly bounded and well-characterised system that is easily modified by genetic means, and by focusing on deep understanding of a discrete number of important and accessible quantitative behaviours. During the project, the authors have developed tools to measure the appropriate data and develop models at appropriate levels of detail to study a number of these quantitative behaviours. The authors have also developed transportable experimental tools and conceptual frameworks for understanding other signalling systems. In particular, the authors have begun to interpret system behaviours and their underlying molecular mechanisms through the lens of information transmission, a principal function of signalling systems. The Alpha Project demonstrates that interdisciplinary studies that identify key quantitative behaviours and measure important quantities, in the context of well-articulated abstractions of system function and appropriate analytical frameworks, can lead to deeper biological understanding. The authors' experience may provide a productive template for systems biology investigations of other cellular systems.     

The National Effective Teaching Institute: Assessment of Impact and Implications for Faculty Development

Background The National Effective Teaching Institute (NETI) is a three‐day teaching workshop that has been given annually since 1991 in conjunction with the Annual ASEE Conference. Its goals are to improve the participants' teaching effectiveness, promote their engagement in scholarly teaching and educational scholarship, and motivate them to engage in instructional development on their campuses. To evaluate the impact of the NETI on its participants, a Web‐based survey was administered to alumni of NETI offerings from 1993 to 2006. Purpose (Hypothesis ) The study was designed to test the hypothesis that the NETI met its stated goals, and to the extent that it did, to identify factors in the workshop's structure and delivery that might have contributed to its success. Design /Method An online survey collected information regarding the participants' awareness and use of selected teaching strategies, their students' and their own ratings of their teaching, and their engagement in scholarly teaching, educational research, and giving their own teaching workshops and seminars. The validity of the survey structure is supported by several published studies that compared self‐assessments of teaching with external evaluations by trained observers. Results The NETI has motivated many of its participants to adopt or increase their use of proven teaching strategies known to correlate with improved student learning; made them more student‐centered, scholarly, and reflective in their teaching practice; and induced many of them to engage in instructional development and educational scholarship. Conclusions The NETI has satisfactorily met its goals. When interpreted in the light of a theory of adult motivation, the results support the effectiveness of discipline‐specific faculty development for engineering educators.     

Building Knowledge Management Systems

Why do some organizations prosper and grow while others struggle? There are a variety of interrelated factors that determine the answer to such a complex question, and these factors differ for organizations in different places and at different times. However, one key ability that is common to all successful organizations is effective creation of relevant business knowledge and the timely dissemination of that knowledge to those members of the organization who need it.     

2D Layered Graphene Oxide Films Integrated with Micro‐Ring Resonators for Enhanced Nonlinear Optics

Layered 2D graphene oxide (GO) films are integrated with micro‐ring resonators (MRRs) to experimentally demonstrate enhanced nonlinear optics. Both uniformly coated (1?5 layers) and patterned (10?50 layers) GO films are integrated on complementary‐metal‐oxide‐semiconductor (CMOS)‐compatible doped silica MRRs using a large‐area, transfer‐free, layer‐by‐layer GO coating method with precise control of the film thickness. The patterned devices further employ photolithography and lift‐off processes to enable precise control of the film placement and coating length. Four‐wave‐mixing (FWM) measurements for different pump powers and resonant wavelengths show a significant improvement in efficiency of ≈7.6 dB for a uniformly coated device with 1 GO layer and ≈10.3 dB for a patterned device with 50 GO layers. The measurements agree well with theory, with the enhancement in FWM efficiency resulting from the high Kerr nonlinearity and low loss of the GO films combined with the strong light–matter interaction within the MRRs. The dependence of GO's third‐order nonlinearity on layer number and pump power is also extracted from the FWM measurements, revealing interesting physical insights about the evolution of the GO films from 2D monolayers to quasi bulk‐like behavior. These results confirm the high nonlinear optical performance of integrated photonic resonators incorporated with 2D layered GO films.     

An image analysis algorithm for dendritic spines

The structure of neuronal dendrites and their spines underlie the connectivity of neural networks. Dendrites, spines, and their dynamics are shaped by genetic programs as well as sensory experience. Dendritic structures and dynamics may therefore be important predictors of the function of neural networks. Based on new imaging approaches and increases in the speed of computation, it has become possible to acquire large sets of high-resolution optical micrographs of neuron structure at length scales small enough to resolve spines. This advance in data acquisition has not been accompanied by comparable advances in data analysis techniques; the analysis of dendritic and spine morphology is still accomplished largely manually. In addition to being extremely time intensive, manual analysis also introduces systematic and hard-to-characterize biases. We present a geometric approach for automatically detecting and quantifying the three-dimensional structure of dendritic spines from stacks of image data acquired using laser scanning microscopy. We present results on the measurement of dendritic spine length, volume, density, and shape classification for both static and time-lapse images of dendrites of hippocampal pyramidal neurons. For spine length and density, the automated measurements in static images are compared with manual measurements. Comparisons are also made between automated and manual spine length measurements for a time-series data set. The algorithm performs well compared to a human analyzer, especially on time-series data. Automated analysis of dendritic spine morphology will enable objective analysis of large morphological data sets. The approaches presented here are generalizable to other aspects of neuronal morphology.     

Dynamic consistency of fuzzy conditional temporal problems

Conditional Temporal Problems (CTPs) can deal simultaneously with uncertainty and temporal constraints, allowing for the representation of temporal and conditional plans. CTPPs generalize CTPs by adding preferences to the temporal constraints and by allowing fuzzy thresholds for the occurrence of some events. Here we focus on dynamic consistency of CTPPs, the most useful notion of consistency in practice. We describe an algorithm which allows for testing if a CTPP is dynamically consistent and we study its complexity. Simple temporal problems with preferences and uncertainty (STPPUs) are another formalism to model temporal constraints where preference and uncertainty coexist. While uncertainty is CTPPs is modeled via conditions on the execution of variables, in STPPUs it is modelled by means of events whose occurrence time is not known. We consider the relation between CTPPs and STPPUs and we show that the former framework is at least as expressive as the second one. Such a result is obtained by providing a polynomial mapping from STPPUs to CTPPs.     

Elicitation strategies for soft constraint problems with missing preferences: Properties,algorithms and experimental studies

We consider soft constraint problems where some of the preferences may be unspecified. This models, for example, settings where agents are distributed and have privacy issues, or where there is an ongoing preference elicitation process. In this context, we study how to find an optimal solution without having to wait for all the preferences. In particular, we define algorithms, that interleave search and preference elicitation, to find a solution which is necessarily optimal, that is, optimal no matter what the missing data will be, with the aim to ask the user to reveal as few preferences as possible. We define a combined solving and preference elicitation scheme with a large number of different instantiations, each corresponding to a concrete algorithm, which we compare experimentally. We compute both the number of elicited preferences and the user effort, which may be larger, as it contains all the preference values the user has to compute to be able to respond to the elicitation requests. While the number of elicited preferences is important when the concern is to communicate as little information as possible, the user effort measures also the hidden work the user has to do to be able to communicate the elicited preferences. Our experimental results on classical, fuzzy, weighted and temporal incomplete CSPs show that some of our algorithms are very good at finding a necessarily optimal solution while asking the user for only a very small fraction of the missing preferences. The user effort is also very small for the best algorithms.     

Towards an evaluation framework for knowledge management systems

In this paper we develop an evaluation framework for Knowledge Management Systems (KMS). The framework builds on the theoretical foundations underlying organizational Knowledge Management (KM) to identify key KM activities and the KMS capabilities required to support each activity. These capabilities are then used to form a benchmark for evaluating KMS. Organizations selecting KMS can use the framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KMS portfolio meet the KM needs of the organization. Other applications of the framework are also discussed.

Fully dynamic maintenance of k-connectivity in parallel

Given a graph G=(V, E) with n vertices and m edges, the k-connectivity of G denotes either the k-edge connectivity or the k-vertex connectivity of G. In this paper, we deal with the fully dynamic maintenance of k-connectivity of G in the parallel setting for k=2, 3. We study the problem of maintaining k-edge/vertex connected components of a graph undergoing repeatedly dynamic updates, such as edge insertions and deletions, and answering the query of whether two vertices are included in the same k-edge/vertex connected component. Our major results are the following: (1) An NC algorithm for the 2-edge connectivity problem is proposed, which runs in O(log n log(m/n)) time using O(n^3/4) processors per update and query. (2) It is shown that the biconnectivity problem can be solved in O(log^{2 n} ) time using O(nα(2n, n)/logn) processors per update and O(1) time with a single processor per query or in O(log n log_n/^m) time using O(nα(2n, n)/log n) processors per update and O(logn) time using O(nα(2n, n)/logn) processors per query, where α(.,.) is the inverse of Ackermann's function. (3) An NC algorithm for the triconnectivity problem is also derived, which takes O(log n log_n/^m+logn log log n/α(3n, n)) time using O(nα(3n, n)/log n) processors per update and O(1) time with a single processor per query. (4) An NC algorithm for the 3-edge connectivity problem is obtained, which has the same time and processor complexities as the algorithm for the triconnectivity problem. To the best of our knowledge, the proposed algorithms are the first NC algorithms for the problems using O(n) processors in contrast to Ω(m) processors for solving them from scratch. In particular, the proposed NC algorithm for the 2-edge connectivity problem uses only O(n^3/4) processors. All the proposed algorithms run on a CRCW PRAM