Experiencias de intervención institucional en escuelas vulnerables en Latinoamérica

En el presente artículo, se revisaron experiencias de diversa índole de intervención institucional enfocadas a escuelas que atienden a población de nivel socioeconómico bajo cuyo fin es generar procesos de cambios que redunden en una mejora de la calidad de la educación. Posteriormente se discuten los alcances y proyecciones que tienen este tipo de intervenciones en un contexto que trascienda a la escuela en si mism

Organization of Research Activities as a Factor in Increasing the Efficiency of Training International Students in Host Russian Universities

This article summarizes the practices of organizing research activities that can improve the training of international students in Russian universities. The authors analyzed and identified the correlation between the internal costs of research and development (R&D), the equipment in university research laboratories, and the number of foreigners studying at Russian universities. The authors used the methods of analysis and synthesis and a systematic approach to explore the experience of Russian universities in the training of international students. To identify the impact of internal R&D costs and the equipment of university research laboratories on the number of foreigners studying in Russian universities, the authors applied correlation and regression analysis, which included building a regression equation, calculating the correlation coefficient, the t-test, the coefficient of elasticity, and the coefficient of determination. This research paper revealed a strong correlation between the number of international students in the Russian Federation on the internal R&D costs and the cost of fixed assets and the equipment of Russian universities, which was proven by the calculated correlation coefficients, elasticity coefficients, and determination coefficients. The authors concluded that universities could influence the number of international students. This article proposes some methods for organizing the research activities of international students that increase their academic mobility and form the most relevant scientific and professional competencies. Higher educational institutions of any major can implement these recommendations for managing the research activities of international students. The novelty of this study lies in the fact that the authors performed the correlation and regression analysis and revealed the dependence of the number of international students in the Russian Federation on internal R&D costs, the cost of fixed assets, and the equipment of Russian universities. The authors illustrated the analysis results with the trend predictive values of factorial features and the value of the effective feature estimated according to the regression equations built. Using the calculated MAPE and Forecast Accuracy indicators for these predicted values, the authors concluded that the level of factorial features and the effective feature were predicted with high accuracy. Thus, host Russian universities can increase the number of international students through effective organization of research activities

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Open kitchens: customers' influence on chefs' working practices

The open kitchen as a customer restaurant vista is an emerging phenomenon. The existing research on chefs has primarily focused on the dark side of professional kitchen work which is often facilitated by being closed production spaces. To date, limited research has explored the transformation of chefs' experience through the re-orientation of their work environment from closed to open kitchens which now necessitate customer engagement. We build on the research gap, by investigating chefs’ perceptions of this transition, through a Goffmanian lens to theorise the impact of customer interactions. Purposive and snowball sampling strategies were employed to identify and interview twenty-eight chefs located in different cities in the UK. Chefs spoke passionately about how their social reality and shared perceptions of kitchen work are shifting due to exposure to customers. Fundamental, positive changes are occurring for chefs' working practices and the skills required in meeting the demands of the experience economy. Theoretically, our novel findings offer a fresh perspective of the modern chef and advance the conversation beyond the negative connotations portrayed of kitchen life

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types

Flow topology and secondary separation modelling at crossing shock wave/turbulent boundary layer interaction conditions

Steady RANS modelling has been carried out for a symmetrical double-sharp-fin configuration with an inclination angle 15°, Mach 3.92 and Reynolds number Reδ = 3.08 x 105. Grid refinement and turbulence model influences using ω-based Reynolds Stress model (RSM), one-equation Eddy Viscosity Transport and two-equation Shear Stress Transport, have been studied and predicted wall pressure distributions were in good agreement with experiment data. RSM model surface flow topology was found to be in better qualitatively agreement with experimental oil-flow visualization than those from other two models. The secondary separation phenomenon observed in the experiment was successfully reproduced by the RSM model, due to its ability to evaluate correct level of turbulence kinetic energy that is critical in determining pseudo-laminar state of an embedded reversed flow underneath the main cross-flow vortex. Three-dimensional flow structures demonstrated that the initially weak secondary separation has been further strengthened in span-wise direction towards the central separated zone

Surface Waves Prediction Based on Long-Range Acoustic Backscattering in a Mid-Frequency Range

Underwater acoustic echosounding for surface roughness parameters retrieval is studied in a frequency band that is relatively new for such purposes. During the described 2-weeks sea experiment, 1–3 kHz tonal pulses were emitted from an oceanographic platform, located on the northern Black Sea shelf. Doppler spectra of the resulting reverberation were studied. The frequency band of the acoustic system, selected for this study, is chosen due to the fact that the sound propagation range is large enough for remote sensing in a coastal zone, and the resolution cell size does not limit the research. Backscattering of acoustical signals was received for distances around two nautical miles. However, it turned to be quite difficult to interpret the obtained data since backscattering spectrum shape was influenced by a series of effects, resulting in a complicated link to wind waves and currents’ parameters. Significant wave height and dominant wave frequency were estimated as the result of such signals processed with the use of machine learning tools. A decision-tree-based mathematical regression model was trained to solve the inverse problem. Wind waves prediction is in a good agreement with direct measurements, made on the platform, and machine learning results allow physical interpretation

Surface Waves Prediction Based on Long-Range Acoustic Backscattering in a Mid-Frequency Range

Underwater acoustic echosounding for surface roughness parameters retrieval is studied in a frequency band that is relatively new for such purposes. During the described 2-weeks sea experiment, 1–3 kHz tonal pulses were emitted from an oceanographic platform, located on the northern Black Sea shelf. Doppler spectra of the resulting reverberation were studied. The frequency band of the acoustic system, selected for this study, is chosen due to the fact that the sound propagation range is large enough for remote sensing in a coastal zone, and the resolution cell size does not limit the research. Backscattering of acoustical signals was received for distances around two nautical miles. However, it turned to be quite difficult to interpret the obtained data since backscattering spectrum shape was influenced by a series of effects, resulting in a complicated link to wind waves and currents’ parameters. Significant wave height and dominant wave frequency were estimated as the result of such signals processed with the use of machine learning tools. A decision-tree-based mathematical regression model was trained to solve the inverse problem. Wind waves prediction is in a good agreement with direct measurements, made on the platform, and machine learning results allow physical interpretation