Hierarchical linear models in Psychiatry: A bibliometric study

Development of research methods requires a systematic review of their status. This study focuses on the use of Hierarchical Linear Modeling methods in psychiatric research. Evaluation includes 207 documents published until 2007, included and indexed in the ISI Web of Knowledge databases; analyses focuses on the 194 articles in the sample. Bibliometric methods are used to describe the publications patterns. Results indicate a growing interest in applying the models and an establishment of methods after 2000. Both Lotka"s and Bradford"s distributions are adjusted to the data.

Flocking behaviour: Agent-based simulation and hierarchical leadership.

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Anonymizing Graphs: Measuring Quality for Clustering

Peer-reviewed

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

A new approach to segmentation based on fusing circumscribed contours, region growing and clustering

One of the major problems in machine vision is the segmentation of images of natural scenes. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. The main contours of the scene are detected and used to guide the posterior region growing process. The algorithm places a number of seeds at both sides of a contour allowing stating a set of concurrent growing processes. A previous analysis of the seeds permits to adjust the homogeneity criterion to the regions's characteristics. A new homogeneity criterion based on clustering analysis and convex hull construction is proposed

Solubilization of decane into gemini surfactant with a modified Jeffamine backbone: Design of hierarchical porous silica

Herein, we have investigated the solubilization of decane into a novel nonionic gemini surfactant, myristoyl-end capped Jeffamine, synthesized from a polyoxyalkyleneamine (ED900). Starting from this system, porous silica materials have been prepared. Performing the hydrothermal treatment at low temperature, a slight increase of the mesopore diameter is observed in the presence of decane. Increasing the temperature of the hydrothermal treatment, no swelling effect of decane is detected. By contrast, the pore diameter decreases but better mesopore homogeneity and a larger wall thickness are obtained. At high decane concentration the new myristoyl-end capped Jeffamine/decane/water system forms oil-in-water emulsions, which are used as template for the formation of hierarchical porous silica materials.