Universidad del Norte, Colombia

About: Universidad del Norte, Colombia is a education organization based out in Barranquilla, Colombia. It is known for research contribution in the topics: Population & Context (language use). The organization has 3562 authors who have published 4355 publications receiving 37861 citations. The organization is also known as: University of the North, Colombia & Uninorte.

Respiratory syncytial virus infection as a cause of hospitalization in population under 1 year in Colombia

Abstract: Objective: to determine the frequency, complications and seasonality at which respiratory syncytial virus (RSV) infection of the lower respiratory tract causes hospitalization in infants of age 1 year or less in 6 cities of Colombia. Methods: one-year prospective multicentric observational study that included 717 patients presenting to the emergency department with respiratory symptoms in 6 cities of Colombia. Hospitalized children were tested for RSV with an immunofluorescence rapid test in nasopharyngeal secretions. Descriptive and statistical analyses of the population were conducted. Results: the study population included 717 patients with a mean age of 3.6 months (SD 3.25), 4:3 male: female ratio and a positive RSV LRTI prevalence of 30.0% (216 infants/City, range 26.0 - 49.0%). Risk factors for RSV LRTI were found in 8.2% of the population, of which 28.8% were RSV positive. RSV positive and negative groups were compared using a two-tailed t test with 95.0%CI, p < 0.05. No statistically significant differences were found. All cities presented specific year trimesters in the occurrence of RSV LRTI. Conclusions: the RSV caused 1 in 3 LRTI hospitalizations in the population, with an incidence of 30.0%. This confirms a continuous circulation of RSV in Colombia varying by geographic location. © 2013 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Vanadium adsorption and incorporation at the GaN(0001) surface: A first-principles study

Abstract: We have carried out first-principles spin-polarized calculations in order to study the energetics and electronic structure of vanadium adsorption and incorporation on $\text{GaN}(0001)\text{\ensuremath{-}}2\ifmmode\times\else\texttimes\fi{}2$ surface using density-functional theory within a plane-wave ultrasoft pseudopotential scheme. It was found that V atoms preferentially adsorb at the T4 sites at low and high coverages (from 1/4 up to 1 monolayer). In addition, calculating the relative surface energy of several configurations and various V concentrations, we constructed a phase diagram showing the energetically most stable surfaces as a function of the Ga chemical potential. Based on these results, we found that incorporation of V adatoms in the Ga-substitutional site is energetically more favorable compared with the adsorption on the top layers. Our calculations show that the vanadium incorporation is most favorable under a nitrogen environment, in agreement with recent experimental results.

ADGRL3 (LPHN3) Variants Predict Substance Use Disorder

Abstract: Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.

Automated Visual Recognition of Construction Equipment Actions Using Spatio-Temporal Features and Multiple Binary Support Vector Machines

Abstract: Video recording of construction operations provides an understandable data that could be used to analyze and improve construction performance Despite the benefits, manual stopwatch study of previously recorded videos can be laborintensive, may suffer from biases of the observers, and impractical after substantial period of observations To address these limitations, this paper presents a new visionbased method for automated action recognition of construction equipment from different camera viewpoints This is particularly a challenging task as construction equipment can be partially occluded and they usually come in wide variety of sizes and appearances The scale and pose of the equipment action can also significantly vary based on the camera configurations In the proposed method, first a video is represented as a collection of spatio-temporal features by extracting space-time interest points and describing each feature with a histogram of oriented gradients (HOG) The algorithm automatically learns the probability distributions of the spatiotemporal features and action categories using a multiple binary Support Vector Machine (SVM) classifier This strategy handles noisy feature points arisen from typical dynamic backgrounds Given a novel video sequence, the multiple binary SVM classifier recognizes and localizes multiple equipment actions in long and dynamic video sequences containing multiple equipment actions We have exhaustively tested our algorithm on 1,200 videos from earthmoving operations Results with average accuracy of 85% across all categories of equipment actions reflect the promise of the proposed method for automated performance monitoring

Evaluating strategic freight transport corridors including external costs

Abstract: A relevant issue for the strategic modeling of interregional freight transport networks is to include external costs as part of a policy that supports the mechanisms for managing and pricing to achieve the social optimum. In this paper, a freight transport model, including external cost, is developed and applied to the Colombian intercity intermodal strategic network involving equilibrium between the phases of distribution and traffic assignment. Each link on the network includes internal costs: time and operation, and external costs: congestion, accidents, air pollution and CO2 emissions. Marginal costs on the freight transport network are calculated using two approaches. First, it is assumed that an additional unit of demand does not affect the equilibrium of the transport network, and then the marginal cost is estimated as the sum of marginal costs on the shortest path links. The second approach assumes that an additional unit of demand changes the network equilibrium and, consequently, the ma...