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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.

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.

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.

Abstract The transformation of an hydrogenated amorphous silicon solar cell (aSiH) into an optoelectronic refratometric sensor has been possible through the addition of dielectric bow-tie resonant structures. The indium transparent oxide top electrode is replaced by a thin metallic layer to selectively prevent the direct transmission of light to the active layer of the cell. Then, an array of dielectric bow-tie structures is placed on top of this electrode, to activate the optical absorption through surface plasmon resonance (SPR). The whole device is exposed to the analyte under measure, which is the surrounding medium. Three different dielectric materials with low, medium, and high refractive index were selected for the bow-ties, namely magnesium fluoride (MgF $$_2$$ 2 ), silicon dioxide (SiO $$_2$$ 2 ), and aluminum nitride (AlN) have been tested as coupling structure for SPR excitation. The maximization of the readout/short circuit current has been achieved through the geometrical parameters of such structure. We have selected the geometrical parameters to maximize the short circuit current delivered by the a-Si cell at a given selected wavelength. The design has been customized to gas measurements application, where the index of refraction is slightly above 1 around 10 $$^{-4}$$ - 4 . Our analysis reveals ultra-high sensitivity of $$2.4 \times 10^4$$ 2.4 × 10 4 (mA/W)/RIU, and a figure of merit FOM= 107 RIU $$^{-1}$$ - 1 , when the bow-tie is made of SiO $$_2$$ 2 . A performance rally competitive with those previously reported in literature, with the additional advantage of circunventing both moving parts and spectral interrogation elements.