The Parameterized Complexity of Centrality Improvement in Networks

The centrality of a vertex v in a network intuitively captures how important v is for communication in the network. The task of improving the centrality of a vertex has many applications, as a higher centrality often implies a larger impact on the network or less transportation or administration cost. In this work we study the parameterized complexity of the NP-complete problems Closeness Improvement and Betweenness Improvement in which we ask to improve a given vertex' closeness or betweenness centrality by a given amount through adding a given number of edges to the network. Herein, the closeness of a vertex v sums the multiplicative inverses of distances of other vertices to v and the betweenness sums for each pair of vertices the fraction of shortest paths going through v. Unfortunately, for the natural parameter "number of edges to add" we obtain hardness results, even in rather restricted cases. On the positive side, we also give an island of tractability for the parameter measuring the vertex deletion distance to cluster graphs

Outlier Edge Detection Using Random Graph Generation Models and Applications

Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or mistakenly by normal users. Detecting outlier nodes and edges is important for data mining and graph analytics. However, previous research in the field has merely focused on detecting outlier nodes. In this article, we study the properties of edges and propose outlier edge detection algorithms using two random graph generation models. We found that the edge-ego-network, which can be defined as the induced graph that contains two end nodes of an edge, their neighboring nodes and the edges that link these nodes, contains critical information to detect outlier edges. We evaluated the proposed algorithms by injecting outlier edges into some real-world graph data. Experiment results show that the proposed algorithms can effectively detect outlier edges. In particular, the algorithm based on the Preferential Attachment Random Graph Generation model consistently gives good performance regardless of the test graph data. Further more, the proposed algorithms are not limited in the area of outlier edge detection. We demonstrate three different applications that benefit from the proposed algorithms: 1) a preprocessing tool that improves the performance of graph clustering algorithms; 2) an outlier node detection algorithm; and 3) a novel noisy data clustering algorithm. These applications show the great potential of the proposed outlier edge detection techniques.Comment: 14 pages, 5 figures, journal pape

Eyeblink conditioning in the infant rat: an animal model of learning in developmental neurotoxicology.

Classical conditioning of the eyeblink reflex is a relatively simple procedure for studying associative learning that was first developed for use with human subjects more than half a century ago. The use of this procedure in laboratory animals by psychologists and neuroscientists over the past 30 years has produced a powerful animal model for studying the behavioral and biological mechanisms of learning. As a result, eyeblink conditioning is beginning to be pursued as a very promising model for predicting and understanding human learning and memory disorders. Among the many advantages of this procedure are (a) the fact that it can be carried out in the same manner in both humans and laboratory animals; (b) the many ways in which it permits one to characterize changes in learning at the behavioral level; (c) the readiness with which hypotheses regarding the neurological basis of behavioral disorders can be formulated and tested; (d) the fact that it can be used in the same way across the life-span; and (e) its ability to distinguish, from normative groups, populations suffering from neurological conditions associated with impaired learning and memory, including those produced by exposure to neurotoxicants. In this article, we argue that these properties of eyeblink conditioning make it an excellent model system for studying early impairments of learning and memory in developmental neurotoxicology. We also review progress that has been made in our laboratory in developing a rodent model of infant eyeblink conditioning for this purpose

Edge centrality via the Holevo quantity

In the study of complex networks, vertex centrality measures are used to identify the most important vertices within a graph. A related problem is that of measuring the centrality of an edge. In this paper, we propose a novel edge centrality index rooted in quantum information. More specifically, we measure the importance of an edge in terms of the contribution that it gives to the Von Neumann entropy of the graph. We show that this can be computed in terms of the Holevo quantity, a well known quantum information theoretical measure. While computing the Von Neumann entropy and hence the Holevo quantity requires computing the spectrum of the graph Laplacian, we show how to obtain a simplified measure through a quadratic approximation of the Shannon entropy. This in turns shows that the proposed centrality measure is strongly correlated with the negative degree centrality on the line graph. We evaluate our centrality measure through an extensive set of experiments on real-world as well as synthetic networks, and we compare it against commonly used alternative measures

Isolation and detection of circulating tumour cells from metastatic melanoma patients using a slanted spiral microfluidic device.

Circulating Tumour Cells (CTCs) are promising cancer biomarkers. Several methods have been developed to isolate CTCs from blood samples. However, the isolation of melanoma CTCs is very challenging as a result of their extraordinary heterogeneity, which has hindered their biological and clinical study. Thus, methods that isolate CTCs based on their physical properties, rather than surface marker expression, such as microfluidic devices, are greatly needed in melanoma. Here, we assessed the ability of the slanted spiral microfluidic device to isolate melanoma CTCs via label-free enrichment. We demonstrated that this device yields recovery rates of spiked melanoma cells of over 80% and 55%, after one or two rounds of enrichment, respectively. Concurrently, a two to three log reduction of white blood cells was achieved with one or two rounds of enrichment, respectively. We characterised the isolated CTCs using multimarker flow cytometry, immunocytochemistry and gene expression. The results demonstrated that CTCs from metastatic melanoma patients were highly heterogeneous and commonly expressed stem-like markers such as PAX3 and ABCB5. The implementation of the slanted microfluidic device for melanoma CTC isolation enables further understanding of the biology of melanoma metastasis for biomarker development and to inform future treatment approaches

Beyond the culture effect on credibility perception on microblogs

We investigated the credibility perception of tweet readers from the USA and by readers from eight Arabic countries; our aim was to understand if credibility was affected by country and/or by culture. Results from a crowd-sourcing experiment, showed a wide variety of factors affected credibility perception, including a tweet author's gender, profile image, username style, location, and social network overlap with the reader. We found that culture determines readers' credibility perception, but country has no effect. We discuss the implications of our findings for user interface design and social media systems

Behavior therapy for pediatric trichotillomania: Exploring the effects of age on treatment outcome

<p>Abstract</p> <p>Background</p> <p>A randomized controlled trial examining the efficacy of behavior therapy for pediatric trichotillomania was recently completed with 24 participants ranging in age from 7 - 17. The broad age range raised a question about whether young children, older children, and adolescents would respond similarly to intervention. In particular, it is unclear whether the younger children have the cognitive capacity to understand concepts like "urges" and whether they are able to introspect enough to be able to benefit from awareness training, which is a key aspect of behavior therapy for trichotillomania.</p> <p>Methods</p> <p>Participants were randomly assigned to receive either behavior therapy (N = 12) or minimal attention control (N = 12), which was included to control for repeated assessments and the passage of time. Primary outcome measures were the independent evaluator-rated NIMH-Trichotillomania Severity Scale, a semi-structured interview often used in trichotillomania treatment trials, and a post-treatment clinical global impression improvement rating (CGI-I).</p> <p>Results</p> <p>The correlation between age and change in symptom severity for all patients treated in the trial was small and not statistically significant. A 2 (group: behavioral therapy, minimal attention control) × 2 (time: week 0, 8) × 2 (children < 9 yrs., children > 10) ANOVA with independent evaluator-rated symptom severity scores as the continuous dependent variable also detected no main effects for age or for any interactions involving age. In light of the small sample size, the mean symptom severity scores at weeks 0 and 8 for younger and older patients randomized to behavioral therapy were also plotted. Visual inspection of these data indicated that although the groups appeared to have started at similar levels of severity for children ≤ 9 vs. children ≥ 10; the week 8 data show that the three younger children did at least as well as if not slightly better than the nine older children and adolescents.</p> <p>Conclusions</p> <p>Behavior therapy for pediatric trichotillomania appears to be efficacious even in young children. The developmental and clinical implications of these findings will be discussed.</p> <p>Trial Registration</p> <p>Clinicaltrials.gov NCT00043563.</p

Primary vs. Secondary Antibody Deficiency: Clinical Features and Infection Outcomes of Immunoglobulin Replacement

<div><p>Secondary antibody deficiency can occur as a result of haematological malignancies or certain medications, but not much is known about the clinical and immunological features of this group of patients as a whole. Here we describe a cohort of 167 patients with primary or secondary antibody deficiencies on immunoglobulin (Ig)-replacement treatment. The demographics, causes of immunodeficiency, diagnostic delay, clinical and laboratory features, and infection frequency were analysed retrospectively. Chemotherapy for B cell lymphoma and the use of Rituximab, corticosteroids or immunosuppressive medications were the most common causes of secondary antibody deficiency in this cohort. There was no difference in diagnostic delay or bronchiectasis between primary and secondary antibody deficiency patients, and both groups experienced disorders associated with immune dysregulation. Secondary antibody deficiency patients had similar baseline levels of serum IgG, but higher IgM and IgA, and a higher frequency of switched memory B cells than primary antibody deficiency patients. Serious and non-serious infections before and after Ig-replacement were also compared in both groups. Although secondary antibody deficiency patients had more serious infections before initiation of Ig-replacement, treatment resulted in a significant reduction of serious and non-serious infections in both primary and secondary antibody deficiency patients. Patients with secondary antibody deficiency experience similar delays in diagnosis as primary antibody deficiency patients and can also benefit from immunoglobulin-replacement treatment.</p></div