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Although the pour plate method is widely employed in microbiological quality control, it has certain drawbacks, including having to melt the culture medium before seeding. In this study, the preparation of the culture medium was modified by using a lower concentration of agar (10 g/L), which was separated from the nutrients during sterilization. The new protocol was assessed in media frequently used in microbiological quality control of food, cosmetics, and pharmaceutical products, with tryptic soy agar (TSA), Sabouraud 4% dextrose agar (SDA), and violet red bile glucose agar (VRBG). In comparison with the conventionally produced media, the modifications significantly improved the growth of Saccharomyces cerevisiae in SDA, Staphylococcus aureus, Salmonella enterica subsp. enterica serovar Typhimurium, and Candida albicans in TSA and Escherichia coli ATCC 8739 and ATCC 25922 and S. Typhimurium in VRBG. The modified VRBG was also more selective for Pseudomonas aeruginosa. Regarding physicochemical properties, a significantly lower pH was observed in TSA and VRBG and lower strength values in TSA. Sterilizing agar separately from the other components of the medium and reducing the agar concentration to 10 g/L can improve microorganism growth and enhance the selectivity of differential media in the pour plate method. These modifications could facilitate the automation of this culture technique, Postprint (published version)

The data were used to evaluate long-term (~10,000 y) changes in the functional composition of tree communities in Amazonian and Andean forests, and how these changes are explained by climate change, droughts, and disturbances. The dataset contains community-weighted means (CWM) over time of four traits: wood density, seed mass, leaf area and adult tree height. Traits were weighted by taxon abundances derived from fossil pollen records. The dataset also contains data on climate (d18O), temperature, droughts (El Niño frequency), fire disturbance (from charcoal abundance), and other general disturbances (from Cecropia abundance).

Robust spin injection and detection in antiferromagnetic thin films is a prerequisite for the exploration of antiferromagnetic spin dynamics and the development of nanoscale antiferromagnet-based spintronic applications. Previous studies have shown spin injection and detection in antiferromagnet/nonmagnetic metal bilayers; however, spin injection in these systems has been found effective at cryogenic temperatures only. Here, we experimentally demonstrate sizable interfacial spin transport in a hybrid antiferromagnet/ferromagnet system, consisting of Cr2O3 and permalloy, which remains robust up to the room temperature. We examine our experimental data within a spin diffusion model and find evidence for the important role of interfacial magnon pumping in the signal generation. The results bridge spin-orbitronic phenomena of ferromagnetic metals with antiferromagnetic spintronics and demonstrate an advancement toward antiferromagnetic spin-torque devices.

Digital Libraries will be one of the main ways to access structured information through the Internet. Information related to resources or objects is known as metadata. Several metadata models have been proposed; however, the model proposed by the Dublin Core Metadata Initiative (DCMI) [1] has demonstrated great utility in digital libraries. The simplicity and generality of DCMI has facilitated the deployment of digital libraries and their interoperability. This paper proposes DCMI as metadata model in our own Digital Library Architecture (Biblioteca Digital de Nueva Generación -BDNG). We have extended DCMI and used some elements of DC-Library application profile (DC-Lib) [2] in addition to new elements not previously considered. This paper presents the metadata models for the following applications: digital library of EAFIT University (BDEeafit), integration of digital or referential libraries (BDMetaLib) and digital library for E-Learning systems (BDEI). This paper also describes the general architecture of BDNG.

Information and Communication Technologies (ICT) can be used in order to motivate students to establish links between the classroom material and real life situations by modeling those situations through the course equations. This article describes the results of an experience involving a group of Multivariable Calculus at Eafit University. 3DUniversal is the program developed for the experience, which runs on Pocket PC. It allows students to interact and communicate inside the classroom. At each stage of the experience, students were asked to establish links between the classroom-covered material and real objects in their environment. © Springer Science+Business Media B.V. 2008.

Multicast plays an important role in supporting a new generation of applications. At present and for different reasons, technical and non-technical, multicast IP hasn't yet been totally adopted for Internet. During recent years, an active area of research is that of implementing this kind of traffic in the application layer where the multicast functionality isnt a responsibility of the routers but that of the hosts, which we know as Multicast Overlay Networks (MON). In this article, routing in an MON is put forward as a multiobjective optimization problem (MOP) where two functions are optimized: 1) the total end to end delay of the multicast tree and 2) the maximum link utilization. The simultaneous optimization of these two functions is an NP-Complete problem and to solve this we suggest using Multiobjective Evolutionary Algorithms (MOEA), specifically NSGA-II.

Information and Communication Technologies (ICT) can be used in order to motivate students to establish links between the classroom material and real life situations by modeling those situations through the course equations. This article describes the results of an experience involving a group of Multivariable Calculus at Eafit University. 3DUniversal is the program developed for the experience, which runs on Pocket PC. It allows students to interact and communicate inside the classroom. At each stage of the experience, students were asked to establish links between the classroom-covered material and real objects in their environment. © Springer Science+Business Media B.V. 2008.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture. © 2020 The Authors

This paper analyses the capabilities of different techniques to build a semantic representation of educational digital resources. Educational digital resources are modeled using the Learning Object Metadata (LOM) standard, and these semantic representations can be obtained from different LOM fields, like the title, description, among others, in order to extract the features/characteristics from the digital resources. The feature extraction methods used in this paper are the Best Matching 25 (BM25), the Latent Semantic Analysis (LSA), Doc2Vec, and the Latent Dirichlet allocation (LDA). The utilization of the features/descriptors generated by them are tested in three types of educational digital resources (scientific publications, learning objects, patents), a paraphrase corpus and two use cases: in an information retrieval context and in an educational recommendation system. For this analysis are used unsupervised metrics to determine the feature quality proposed by each one, which are two similarity functions and the entropy. In addition, the paper presents tests of the techniques for the classification of paraphrases. The experiments show that according to the type of content and metric, the performance of the feature extraction methods is very different; in some cases are better than the others, and in other cases is the inverse. © 2020 by the authors.