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Este artículo estudia la teoría económica que se encuentra detrás de los análisis y la política pública sobre la informalidad. Para esto se realizará un repaso por la teoría hegemónica (marginalista-neoclásica) buscando comprender dicho marco teórico y su relación con la política económica. De esta manera, se presentará la principal corriente del pensamiento económico, con sus implicaciones sobre la política pública y el tratamiento de la informalidad, y se le criticará de manera profunda y concisa, hallando sus principales falencias teóricas y pretendiendo demostrar su incapacidad para describir cualquier sistema económico de forma lógica y coherente. Con esto en mente, se discutirán nociones alternativas para comprender el fenómeno de la informalidad y el desempleo, partiendo de la propuesta de la economía popular del profesor César Giraldo y continuando con la teoría de la demanda efectiva de Keynes. De aquí se desprenderán condicionantes para una política pública que pretenda, por un lado, la reducción del desempleo y, por el otro, el reconocimiento del sujeto social de la economía popular.

En este artículo se pretende desarrollar la idea del Supermultiplicador Sraffiano, presentándolo como una alternativa al pensamiento neoclásico tradicional sobre el crecimiento económico y la política económica, De esta forma, se hace una breve introducción acerca de la importancia del crecimiento económico para los economistas clásicos, seguido del desarrollo del modelo de Harrod y las diferentes soluciones que se han planteado al problema de inestabilidad. Finalmente, se presenta el modelo de supermultiplicador de Serrano junto a la evidencia empírica internacional que le respalda; por último se desarrollan propuestas de política económica.

The implementation of adequate quality assessment (QA) and quality control (QC) protocols within the magnetic resonance imaging (MRI) research workflow is resource- and time-consuming and even more so is their execution. As a result, QA/QC practices highly vary across laboratories and “MRI schools”, ranging from highly specialized knowledge spots to environments where QA/QC is considered overly onerous and costly despite evidence showing that below-standard data increase the false positive and false negative rates of the final results. Here, we demonstrate a protocol based on the visual assessment of images one-by-one with reports generated by MRIQC and fMRIPrep, for the QC of data in functional (blood-oxygen dependent-level; BOLD) MRI analyses. We particularize the proposed, open-ended scope of application to whole-brain voxel-wise analyses of BOLD to correspondingly enumerate and define the exclusion criteria applied at the QC checkpoints. We apply our protocol on a composite dataset (n = 181 subjects) drawn from open fMRI studies, resulting in the exclusion of 97% of the data (176 subjects). This high exclusion rate was expected because subjects were selected to showcase artifacts. We describe the artifacts and defects more commonly found in the dataset that justified exclusion. We moreover release all the materials we generated in this assessment and document all the QC decisions with the expectation of contributing to the standardization of these procedures and engaging in the discussion of QA/QC by the community.

Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.

La diabetes es una enfermedad grave y muy extendida en todo el mundo hoy en día. Muchos investigadores están trabajando en métodos para su diagnóstico y tratamiento. Una herramienta utilizada para ello son los modelos matemáticos que describen la cinética en sangre de las concentraciones de glucosa e insulina. Existen en la literatura especializada muchos intentos para construir modelos satisfactorios para este sistema glucosa-insulina. En el presente trabajo se estudian algunos sistemas de ecuaciones diferenciales ordinarias que sirven para modelizar los procesos fisiológicos que ocurren durante la metabolización de la glucosa en el cuerpo humano. Nos centraremos en el trabajo de Ackerman et al (1964), por ser su equipo pionero en modelizar este proceso biológico, y porque además su modelo sigue mostrando unos resultados aceptables en la práctica.

Age-specific resources in human MRI mitigate processing biases that arise from structural changes across the lifespan. There are fewer age-specific resources for preclinical imaging, and they only represent developmental periods rather than adulthood. Since rats recapitulate many facets of human aging, it was hypothesized that brain volume and each tissue's relative contribution to total brain volume would change with age in the adult rat. Data from a longitudinal study of rats at 3, 5, 11, and 17 months old were used to test this hypothesis. Tissue volume was estimated from high resolution structural images using a priori information from tissue probability maps. However, existing tissue probability maps generated inaccurate gray matter probabilities in subcortical structures, particularly the thalamus. To address this issue, gray matter, white matter, and CSF tissue probability maps were generated by combining anatomical and signal intensity information. The effects of age on volumetric estimations were then assessed with mixed-effects models. Results showed that herein estimation of gray matter volumes better matched histological evidence, as compared to existing resources. All tissue volumes increased with age, and the tissue proportions relative to total brain volume varied across adulthood. Consequently, a set of rat brain templates and tissue probability maps from across the adult lifespan is released to expand the preclinical MRI community's fundamental resources.

El desarrollo en América Latina y el Caribe debe pensarse como un problema de restricción externa, donde se han impuesto discursos que impiden cualquier proceso de convergencia con las economías desarrolladas. Por esto, se hace necesario cuestionar los fundamentos teóricos de tales discursos, demostrando que, en su mayoría, han sido controvertidos y declarados inconsistentes; transformando tales posturas en ideológicas y nunca coherentes. Así pues, en este artículo se busca afrontar los desafíos del desarrollo que enfrenta la región a partir de un análisis teórico alternativo que nos acerque a una concepción global de los conflictos socio-económicos del desarrollo y nos permita sostener postulados normativos para contribuir al debate por el desarrollo de nuestras naciones, abogando siempre por políticas de industrialización y de crecimiento vía demanda efectiva.

The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here, we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlight the importance of the Brain Imaging Data Structure standard for enabling effective curation, sharing, and reuse of data. The archive presently shares more than 600 datasets including data from more than 20,000 participants, comprising multiple species and measurement modalities and a broad range of phenotypes. The impact of the shared data is evident in a growing number of published reuses, currently totalling more than 150 publications. We conclude by describing plans for future development and integration with other ongoing open science efforts.

In the competition of solar cell efficiency, besides top-performance multijunction cells, tandem cells based on perovskites are also breaking efficiency records to enter into the 30% range. Their design takes advantage of the rapid development of perovskite cells, and the good sharing of the available spectrum between the perovskite, absorbing at short wavelengths, and the c-Si or similar lower band gap material, working at longer wavelengths. In this paper, we present a novel tandem solar cell that combines crystalline silicon (c-Si) and perovskites cells. We analyzed the device with computational electromagnetism based on the finite element method. Our design arranges the perovskite solar cell as a multilayer 1D grating, which is terminated with a gold thin film (top metallic contact). This multilayer nanostructure is placed on top of the c-Si cell and a thin protective dielectric layer of aluminum nitride covers the whole device. The short-circuit current of the perovskite cell is maximized by maintaining the current-matching conditions with the output from the c-Si cell. This optimization considers the geometrical parameters of the grating: period and thickness of the active layer of the perovskite cell. We compared the simulated short-circuit current of this device to the planar tandem solar cell with indium tin oxide (top contact). The comparison shows a slight increment, around 3%, of our device’s performance. Moreover, it has the potential capability to circumvent postprocessing procedures used with transparent contact oxides, which can reduce the device’s final efficiency. Furthermore, our proposed design can take advantage of photolithographic and nanoimprint techniques, enabling large-scale production at a relatively low cost.

Though tractography is widely used, it has not been systematically validated. Here, authors report results from 20 groups showing that many tractography algorithms produce both valid and invalid bundles.

En este artículo cuestionamos la ortodoxia de la teoría del valor frente a posibles alternativas. Hay una teoría económica dominante a través de la cual se nos presenta un mundo sujeto a leyes económicas incuestionables: la teoría neoclásica. Se hace necesaria una teoría del valor alternativa que permita dar cuenta de los mecanismos que posibilitan la coordinación de agentes descentralizados. Presentamos dos posturas frente a las teorías del valor alternativas que nos abren caminos para responder a la cuestión de la coordinación en una sociedad capitalista.

The verification and validation of segmentation and registration methods is a necessary assessment in the development of new processing methods. However, verification and validation of diffusion MRI (dMRI) processing methods is challenging for the lack of gold-standard data. The data described here are related to the research article entitled “Surface-driven registration method for the structure-informed segmentation of diffusion MR images” [1], in which publicly available data are used to derive golden-standard reference-data to validate and evaluate segmentation and registration methods in dMRI. Keywords: Neuroimage, Image processing, MRI methods, Diffusion MRI

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

Quality control of MRI is essential for excluding problematic acquisitions and avoiding bias in subsequent image processing and analysis. Visual inspection is subjective and impractical for large scale datasets. Although automated quality assessments have been demonstrated on single-site datasets, it is unclear that solutions can generalize to unseen data acquired at new sites. Here, we introduce the MRI Quality Control tool (MRIQC), a tool for extracting quality measures and fitting a binary (accept/exclude) classifier. Our tool can be run both locally and as a free online service via the OpenNeuro.org portal. The classifier is trained on a publicly available, multi-site dataset (17 sites, N = 1102). We perform model selection evaluating different normalization and feature exclusion approaches aimed at maximizing across-site generalization and estimate an accuracy of 76%±13% on new sites, using leave-one-site-out cross-validation. We confirm that result on a held-out dataset (2 sites, N = 265) also obtaining a 76% accuracy. Even though the performance of the trained classifier is statistically above chance, we show that it is susceptible to site effects and unable to account for artifacts specific to new sites. MRIQC performs with high accuracy in intra-site prediction, but performance on unseen sites leaves space for improvement which might require more labeled data and new approaches to the between-site variability. Overcoming these limitations is crucial for a more objective quality assessment of neuroimaging data, and to enable the analysis of extremely large and multi-site samples.

The combustion of coal wastes resulting from mining is of particular environmental concern, and the importance of proper management involving real-time assessment of their status and identification of probable evolution scenarios is recognized. Continuous monitoring of the combustion temperature and emission levels of certain gases allows for the possibility of planning corrective actions to minimize their negative impact on the surroundings. Optical fiber technology is well suited to this purpose and here we describe the main attributes and results obtained from a fiber optic sensing system projected to gather data on distributed temperature and gas emissions in these harsh environments.