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.

Safe oxygen saturation targeting and monitoring in preterm infants: can we avoid hypoxia and hyperoxia?

Abstract: Oxygen is a neonatal health hazard that should be avoided in clinical practice. In this review, an international team of neonatologists and nurses assessed oxygen saturation (SpO2) targeting in preterm infants and evaluated the potential weaknesses of randomised clinical trials. Conclusion SpO2 of 85–89% can increase mortality and 91–95% can cause hyperoxia and ill effects. Neither of these ranges can be recommended, and wider intermediate targets, such as 87–94% or 88–94%, may be safer.

Two-Dimensional Disorder in Black Phosphorus and Monochalcogenide Monolayers

Abstract: Ridged, orthorhombic two-dimensional atomic crystals with a bulk Pnma structure such as black phosphorus and monochalcogenide monolayers are an exciting and novel material platform for a host of applications. Key to their crystallinity, monolayers of these materials have a 4-fold degenerate structural ground state, and a single energy scale EC (representing the elastic energy required to switch the longer lattice vector along the x- or y-direction) determines how disordered these monolayers are at finite temperature. Disorder arises when nearest neighboring atoms become gently reassigned as the system is thermally excited beyond a critical temperature Tc that is proportional to EC/kB. EC is tunable by chemical composition and it leads to a classification of these materials into two categories: (i) Those for which EC ≥ kBTm, and (ii) those having kBTm > EC ≥ 0, where Tm is a given material’s melting temperature. Black phosphorus and SiS monolayers belong to category (i): these materials do not display an i...

Gender and Corruption: Lessons from Laboratory Corruption Experiments

Abstract: Reliable microdata on corrupt behavior are hard to obtain in the field, and available field data are hard to interpret. Laboratory corruption experiments have therefore recently gained in popularity, and those that shed light on gender effects are surveyed in this article. The tentative main result is this: if women are involved in a potentially corrupt transaction, it is more likely to fail. The reason is not that women are intrinsically more honest, but that they are more opportunistic when they have the chance to break an implicitly corrupt contract and less engaged in retaliating nonperformance. The survey closes with tentative implications for development policy. Les micro-donnees fiables sur les comportements de corruption sont difficiles a recueillir sur le terrain, et les donnees de terrain disponibles sont difficilement interpretables. Les experiences en laboratoire sur la corruption gagnent donc, depuis quelques temps, en popularite. Celles qui mettent en lumiere les effets de genre sont examinees dans cet article. Un premier constat provisoire est celui ci: Si des femmes sont impliquees dans une transaction potentiellement frauduleuse, la probabilite d’echec de cette derniere est plus elevee. La raison n’en n’est pas que les femmes sont intrinsequement plus honnetes, mais plutot qu’elles sont plus opportunistes lorsqu’il s’agit de rompre un contrat teinte de corruption et moins enclines a reagir face a des performances insatisfaisantes. L’etude conclut en decrivant des implications possibles pour les politiques de developpement.’

On the relationship between visual attributes and convolutional networks

Abstract: One of the cornerstone principles of deep models is their abstraction capacity, i.e. their ability to learn abstract concepts from ‘simpler’ ones. Through extensive experiments, we characterize the nature of the relationship between abstract concepts (specifically objects in images) learned by popular and high performing convolutional networks (conv-nets) and established mid-level representations used in computer vision (specifically semantic visual attributes). We focus on attributes due to their impact on several applications, such as object description, retrieval and mining, and active (and zero-shot) learning. Among the findings we uncover, we show empirical evidence of the existence of Attribute Centric Nodes (ACNs) within a conv-net, which is trained to recognize objects (not attributes) in images. These special conv-net nodes (1) collectively encode information pertinent to visual attribute representation and discrimination, (2) are unevenly and sparsely distribution across all layers of the conv-net, and (3) play an important role in conv-net based object recognition.

Synthesis of Biologically Active Molecules through Multicomponent Reactions

Abstract: Focusing on the literature progress since 2002, the present review explores the highly significant role that multicomponent reactions (MCRs) have played as a very important tool for expedite synthesis of a vast number of organic molecules, but also, highlights the fact that many of such molecules are biologically active or at least have been submitted to any biological screen. The selected papers covered in this review must meet two mandatory requirements: (1) the reported products should be obtained via a multicomponent reaction; (2) the reported products should be biologically actives or at least tested for any biological property. Given the diversity of synthetic approaches utilized in MCRs, the highly diverse nature of the biological activities evaluated for the synthesized compounds, and considering their huge structural variability, much of the reported data are organized into concise schemes and tables to facilitate comparison, and to underscore the key points of this review.