Liberacion comercial y crecimiento economico en Mercosur 1994-2000

El presente trabajo es un estudio del desarrollo del Mercado Comun del Sur, desde sus antecedentes juridicos y su creacion en 1991 hasta la actualidad, señalando una fecha de referencia (1995), con objeto de analizar los efectos de la entrada en vigor del arancel externo comun en el crecimiento economico del Mercosur, contrastando el "shock" producido por la apertura de sus mercados al exterior, si bien la liberalizacion comercial venia siendo progresiva, de acuerdo al programa de desgravacion arancelaria. This paper studies the evolution of Mercosur, from its regulatory commences and its birth in 1991 to the present day. In order to analyse the effects of the implementation of a common external tariff in 1995 over the economic growth of Mercosur, we tested the shock caused for this policy measure. However, we should take into account that a policy addressed to achieve more international openness of these economies had been being progressively implemented before this date.

Fast Hardware Implementations of Static P Systems

In this article we present a simulator of non-deterministic static P systems using Field Programmable Gate Array (FPGA) technology. Its major feature is a high performance, achieving a constant processing time for each transition. Our approach is based on representing all possible applications as words of some regular context-free language. Then, using formal power series it is possible to obtain the number of possibilities and select one of them following a uniform distribution, in a fair and non-deterministic way. According to these ideas, we yield an implementation whose results show an important speed-up, with a strong independence from the size of the P system

Arquitectura de PLN aplicada al contexto de la salud mental

At a global level, the situation caused by COVID-19 has created a worrying and discouraging reality, especially for governments, especially for the most vulnerable populations due to the fact that they do not know how to eradicate the pandemic, many have not been able to overcome the challenges mainly emerging from an infectious disease with implications for physical health and which has also profoundly affected people's mental health and well-being. Mental health affectations are problems that affect all of us at some point in our lives, either due to experiences we have experienced or even biological factors. Paying attention and providing the necessary support at an early stage is the key to preventing more severe effects. The discipline of natural language processing (NLP) is a sub-area of artificial intelligence (AI) that studies the interactions between computers and the language that humans speak. This research proposes the design and implementation of a comprehensive architecture based on AI, machine learning (ML) and PLN components, which will allow us to detect and analyze behavior patterns in people and generate possible early diagnoses of mental health diseases.A nivel global la situación acarreada por COVID-19, ha creado una realidad preocupante y desalentadora especialmente a los gobiernos en especialmente a las poblaciones más vulnerables por el hecho de desconocer como erradicar la pandemia, muchos no han podido superar los desafíos principalmente emergentes de una enfermedad infecciosa con implicaciones para la salud física y que también ha afectado profundamente la salud mental y el bienestar de las personas. Las afectaciones de salud mental son problemas que nos afectan a todos en algún momento de nuestras vidas, ya sea por experiencias que hemos vivido o incluso factores biológicos. Prestarle la atención y brindar el apoyo necesario en una etapa temprana es la clave para prevenir afectaciones más severas. La disciplina del procesamiento de lenguaje natural (PLN), es una sub área inteligencia artificial (IA) que estudia las interacciones entre las computadoras y el lenguaje que hablamos los humanos. En esta investigación se propone el diseño e implementación de una arquitectura integral basada en componentes de IA, aprendizaje automático (ML) y PLN, la cual nos permitirá detectar y analizar patrones de comportamiento en las personas y generar posibles diagnósticos tempranos a enfermedades de salud mental

On the new metrics for IMRT QA verification

Purpose: the aim of this work is to search for new metrics that could give more reliable acceptance/ rejection criteria on the IMRT verification process and to offer solutions to the discrepancies found among different conventional metrics. Therefore, besides conventional metrics, new ones are proposed and evaluated with new tools to find correlations among them. These new metrics are based on the processing of the dosevolume histogram information, evaluating the absorbed dose differences, the dose constraint fulfillment, or modified biomathematical treatment outcome models such as tumor control probability (TCP) and normal tissue complication probability (NTCP). An additional purpose is to establish whether the new metrics yield the same acceptance/rejection plan distribution as the conventional ones. Methods: Fifty eight treatment plans concerning several patient locations are analyzed. All of them were verified prior to the treatment, using conventional metrics, and retrospectively after the treatment with the new metrics. These new metrics include the definition of three continuous functions, based on dosevolume histograms resulting from measurements evaluated with a reconstructed dose system and also with a Monte Carlo redundant calculation. The 3D gamma function for every volume of interest is also calculated. The information is also processed to obtain dTCP or dNTCP for the considered volumes of interest. These biomathematical treatment outcome models have been modified to increase their sensitivity to dose changes. A robustness index from a radiobiological point of view is defined to classify plans in robustness against dose changes. Results: Dose difference metrics can be condensed in a single parameter: the dose difference global function, with an optimal cutoff that can be determined from a receiver operating characteristics (ROC) analysis of the metric. It is not always possible to correlate differences in biomathematical treatment outcome models with dose difference metrics. This is due to the fact that the dose constraint is often far from the dose that has an actual impact on the radiobiological model, and therefore, biomathematical treatment outcome models are insensitive to big dose differences between the verification system and the treatment planning system. As an alternative, the use of modified radiobiological models which provides a better correlation is proposed. In any case, it is better to choose robust plans from a radiobiological point of view. The robustness index defined in this work is a good predictor of the plan rejection probability according to metrics derived from modified radiobiological models. The global 3D gamma-based metric calculated for each plan volume shows a good correlation with the dose difference metrics and presents a good performance in the acceptance/rejection process. Some discrepancies have been found in dose reconstruction depending on the algorithm employed. Significant and unavoidable discrepancies were found between the conventional metrics and the new ones. Conclusions: The dose difference global function and the 3D gamma for each plan volume a e good classifiers regarding dose difference metrics. ROC analysis is useful to evaluate the predictive power of the new metrics. The correlation between biomathematical treatment outcome models and the dose difference-based metrics is enhanced by using modified TCP and NTCP functions that take into account the dose constraints for each plan. The robustness index is useful to evaluate if a plan is likely to be rejected. Conventional verification should be replaced by the new metrics, which are clinically more relevant

Image augmentation for object detection of grapevines

Machine Learning methods are widely used for data analysis in various areas. In this work we use Neural Networks for image analysis in order to detect grape fruit clusters. A set of manually tagged images is built and a comparison is made between different data augmentation techniques in order to analyse the best way to expand the image set. The technique presented here obtained up to 13% better detection performance starting with only 100 images for training. The types of transformations and filters that worked the best for these images are discussed. In addition, training and detection times in five different hardware infrastructures, both CPU and GPUs, are briefly discussed.Workshop: WASI – Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informátic

Four haplotype blocks linked to Ascochyta blight disease resistance in chickpea under Mediterranean conditions

Ascochyta blight, caused by the fungal pathogen Ascochyta blight, caused by the fungal pathogen Ascochyta rabiei, is a devastating biotic stress that poses a significant threat to chickpea cultivation worldwide. To combat this disease, breeding programs have focused on developing cultivars with resistance to Ascochyta blight. However, a comprehensive understanding of the underlying plant defense mechanism is still lacking. To identify genomic regions associated with resistance, a recombinant inbred line (RIL) population was created by crossing ILC3279 (kabuli, resistant) and WR315 (desi, susceptible), which was then phenotyped and sequenced using a tuneable genotyping-by-sequencing (tGBS) protocol to obtain single nucleotide polymorphisms (SNPs). We further validated the association of genomic regions with Ascochyta blight resistance in a second recombinant inbred line\population derived from the cross between JG62 (desi, susceptible) and ILC72 (kabuli, resistant). Our analysis identified four genomic regions associated with Ascochyta blight resistance in chromosomes 2 and 4, among which a region spanning from 3.52 to 8.20 Mb in chromosome 4 was the most robust candidate for resistance, being associated with resistance in both years and populations. A total of 30 genes from the identified regions were selected as robust candidates, and LOC101507066, which encodes a leucine-rich repeat receptor-like protein kinase, was the most robust candidate gene, as it plays critical roles in plant stress responses and immunity. Our findings have potential to accelerate marker-assisted genetic improvement and facilitate the development of integrated strategies for crop protection

Empirical Wavelet Transform-based Detection of Anomalies in ULF Geomagnetic Signals Associated to Seismic Events with a Fuzzy Logic-based System for Automatic Diagnosis

Owing to the relevance and severity of damages caused by earthquakes (EQs), the development and application of new methods for seismic activity detection that offer an efficient and reliable diagnosis in terms of processing and performance are still demanding tasks. In this work, the application of the Empirical Wavelet Transform (EWT) for seismic detection in ultra-low-frequency (ULF) geomagnetic signals is presented. For this, several ULF signals associated to seismic activities and random calm periods are analysed. These signals have been obtained through a tri-axial fluxgate magnetometer at the Juriquilla station localized in Queretaro, Mexico, longitude -100.45° N and latitude 20.70°E. In order to show the advantages of the proposal, a comparison with the discrete wavelet transform (DWT) is presented. The results shown a better detection capability of seismic signals before, during, and after the main shock than the ones obtained by the DWT, which makes the proposal a more suitable and reliable tool for this task. Finally, a fuzzy logic (FL)-based system for automatic diagnosis using the variance of the EWT outputs for the tri-axial fluxgate magnetometer signals is also proposed

Sexual estimation in bone remains of hunter gatherers from Central Patagonia, Argentina: contrasting of morphometric methods with paleogenetic analysis

En el presente trabajo se comparan los resultados de la estimación de sexo en restos óseos humanos antiguos de individuos adultos de la Patagonia central argentina (N=42) a partir de dos métodos: por una parte, el estudio de estructuras de la pelvis, el cráneo, el húmero, el fémur y la tibia; por otra, el análisis molecular de secuenciación masiva (Next Generation Sequencing), mediante herramientas bioinformáticas validadas para ADN antiguo. Los resultados mostraron que la concavidad subpúbica y el arco ventral de la pelvis, el proceso mastoides del cráneo y las fórmulas propuestas por Béguelin para fémur y húmero ofrecen las estimaciones del sexo más confiables en esta muestra de restos humanos arqueológicos de Patagonia central. Por el contrario, las estructuras de la tibia y el ancho bicondilar del humero y el fémur ofrecen resultados significativamente diferentes o con bajas asociaciones a los obtenidos por métodos moleculares. Futuros análisis deberán enfocarse en estudios similares en esqueletos de subadultos.The present study compares the results of sex estimation in ancient human bone remains of adult individuals from Argentine central Patagonia (N=42) using two methods. On the one hand, the study of structures of the pelvis, skull, humerus, femur, and tibia. On the other hand, the biological sex estimated by means of molecular analysis (Next Generation Sequencing), using bioinformatic tools validated for ancient DNA. The results showed that sex estimations based on features of the pelvis (subpubic concavity and ventral arc), the mastoid process of the skull and the formulas proposed by Béguelin for humerus and femur were statistically similar to molecular results in this particular sample from Patagonia. In contrast, the estimations based on structures of the tibia and bicondylar width of humerus and femur were significantly different from molecular sex estimations. Further research needs to be conducted in order to test sex-estimation methods on subadult skeletons.Fil: Millan, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Tamburrini, Camila. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Parolin, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Dahinten, Silvia Lucrecia V.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Gomez Otero, Julieta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Suby, Jorge Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Arqueológicas y Paleontológicas del Cuaternario Pampeano. Grupo de Investigación en Bioarqueología (GIB). Unidad de Enseñanza Universitaria Quequén. Departamento de Arqueología. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentin