Pensando la supervisión docente como un modo de interpelar a la intenvención social : Modelo Operativo de Supervisión Docente

En este artículo se presenta una serie de reflexiones que el equipo de cátedra ha realizado en base a un análisis llevado a cabo en el marco del Programa La Cátedra Investiga, con el fin de pensar críticamente el proceso de supervisión docente que se lleva a cabo en la Carrera de Trabajo Social. La Supervisión Docente es una instancia de aprendizaje fundamental que, a partir de la práctica particular de los alumnos, intenta una articulación teórica-práctica, consolidar el yo profesional, develar e interpelar la complejidad de la intervención profesional en la actualidad. En consecuencia se presenta un modelo operativo de supervisión docente.In this article is presented a series of reflections that the team of chair has done in based on analysis carried out in the framework of the Program The Chair Investigates, in order to think critically the process of monitoring teacher to be carried out in the Career of Social Work. The monitoring teacher is an instance of basic learning that, from the particular practice of pupils tries a joint theory practice, consolidate the I professional, uncover and compel the complexity of the professional intervention in the presents. As a result is a business model of monitoring teacher.Fil: Blanco, María Teresita. Universidad Nacional de Cuyo. Facultad de Ciencias Políticas y SocialesFil: Parola, Ruth Noemí. Universidad Nacional de Cuyo. Facultad de Ciencias Políticas y SocialesFil: Avallone, Adela. Universidad Nacional de Cuyo. Facultad de Ciencias Políticas y SocialesFil: Mejías, Soledad. Universidad Nacional de Cuyo. Facultad de Ciencias Políticas y SocialesFil: Klimisch, María Laura. Universidad Nacional de Cuyo. Facultad de Ciencias Políticas y Sociale

Quantitative Determination of Carbon Monoxide in Blood by Gaschromatography

Peer Reviewe

Análisis del Comportamiento de la Vegetación a partir de Índices del Sensor MODIS en Santa Cruz, Argentina

The use of remote sensing allows the evaluation and management of vegetation, in large extensions and at low cost. Some attributes of vegetation cover, such as Net Primary Productivity and growing season, are obtained from the vegetation indices generated with this technology. The objective of this work was to analyse four vegetation indices (NDVI, EVI, SAVI and ARVI) in ecological areas of the province of Santa Cruz, with data from the MOD13Q1 sensor, from February 2000 to March 2021. The data, averaged by area, were obtained using Google Earth Engine and statistically analysed with the R-Studio program. Descriptive measures and the attributes of the annual mean curve attributes were obtained for each index. The correlation between indices was analysed. The four indices identified the moments of maximum productivity and were correlated. The NDVI was the index with the best correlation, showing a more homogeneous behaviuor with respect to the vegetation. In relation to the attributes of the NDVI, Andean Complex and Humid Magellanic Steppe showed a maximum in October, Dry Magellanic Steppe had a bimodal behaviour (October and April) and the other areas did not show clear patterns. The differences found are possibly due to the heterogeneity of each region. This could be verified by studying representative sites within each area.El uso de sensores remotos permite la evaluación y manejo de la vegetación, en grandes extensiones y a bajo costo. Algunos atributos de la cobertura vegetal, como Productividad Primaria Neta y temporada de crecimiento, son obtenidos a partir de los índices de vegetación generados con esta tecnología. El objetivo de este trabajo fue analizar cuatro índices de vegetación (NDVI, EVI, SAVI y ARVI) en las áreas ecológicas de la provincia de Santa Cruz, con datos del sensor MOD13Q1, desde febrero 2000 a marzo 2021. Los datos, promedios por área, fueron obtenidos utilizando Google Earth Engine y analizados estadísticamente con el programa R-Studio. Para cada índice se obtuvieron medidas descriptivas y los atributos de la curva media anual. Se analizó la correlación entre índices. Los cuatro índices identificaron los momentos de máxima productividad y resultaron correlacionados. El NDVI resultó ser el índice con mejor correlación, mostrando un comportamiento más homogéneo respecto de la vegetación. En relación a los atributos del NDVI, el Complejo Andino y Estepa Magallánica Húmeda, presentaron un máximo en octubre, Estepa Magallánica Seca tuvo un comportamiento bimodal (octubre y abril) y las demás áreas no presentaron patrones claros. Las diferencias encontradas posiblemente se deban a la heterogeneidad propia de cada región Esto podría comprobarse estudiando sitios representativos dentro de cada área

An improved method for calculating toxicity-based pollutant loads:Part 1. Method development

Pollutant loads are a means for assessing regulatory compliance and setting targets to reduce pollution entering receiving waterbodies. However, a pollutant load is often comprised of multiple chemicals, which may exert joint toxicity on biota. When the ultimate goal for assessing pollutant loads is to protect ecosystems from adverse effects of toxicants, then the total pollutant load needs to be calculated based on the principles of mixture toxicology. In this article, an improved method is proposed to convert a pollutant load to a toxicity-based load (toxic load) using a modified toxic equivalency factor (TEF) derivation method. The method uses the relative potencies (RePs) of multiple species to represent the response of the ecological community. The TEF is calculated from a percentile of a cumulative distribution function (CDF) fitted to the RePs. The improvements permit the determination of which percentile of the CDF generates the most environmentally relevant and robust toxic loads. That is, environmental relevance ensures that a reduction in the toxic load is likely to result in a corresponding improvement in ecosystem health and robustness ensures that the calculation of the toxic loads is not biased by the reference chemical used. The improved methodology will therefore ensure that correct management decisions will be made and ultimately, a reduction in the toxic load will lead to a commensurate improvement in water quality

Fotosíntesis neta del sensor modis y su relación con variables climáticas y espectrales en la Estepa Magallánica Seca (Patagonia)

Conocer la productividad en pastizales es de importancia por ser la base principal del alimento de la ganadería. Estimarla es dificultoso debido a que requiere cortes de biomasa a campo, lo que demanda tiempo y dinero. Una alternativa es utilizar datos de Fotosíntesis Neta desde sensores remotos como estimador de la productividad, esta última depende de variables ambientales tales como precipitación y temperatura. El objetivo de este trabajo fue modelar la relación entre Fotosíntesis Neta obtenida del sensor MODIS con series temporales de variables ambientales y satelitales, en cuatro estaciones meteorológicas para el área de la Estepa Magallánica Seca al sur de la Patagonia en el periodo 2000-2019. Desde polígonos adyacentes a las estaciones meteorológicas con vegetación representativa y al menos 5 pixeles de imágenes, se extrajeron la información de diferentes productos: índices de vegetación (MOD13Q1), temperatura superficial (MOD11A2) y Fotosíntesis Neta (MOD17A2) utilizando la plataforma Google Earth Engine (GEE). A partir de estas variables y de las series meteorológicas se calcularon algunos índices de anomalía para la precipitación, temperatura y para la vegetación. Se compararon las medias de la variable Fotosíntesis Neta y se propusieron modelos lineales considerando una estructura autorregresiva para los errores en cada una de las ubicaciones bajo estudio. Los resultados indican que existen diferencias entre las estaciones en relación a la cantidad media de Fotosíntesis Neta. Además, las variables que más influyen son la temperatura superficial (o la temperatura), el índice de vegetación normalizado, las anomalías de este índice en relación a las medias en el periodo considerado y la precipitación. En los sitios que presentan menores valores medios de Fotosíntesis Neta la precipitación incide de manera significativa.Fil: Maglione, Dora. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Paredes, Paula. Universidad Nacional de la Patagonia Austral; Argentina. Instituto Nacional de Tecnología Agropecuaria. Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Luna, Silvia. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Klimisch, Bárbara. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Saenz, José Luis. Universidad Nacional de la Patagonia Austral; Argentina

A Strategy for Structuring and Reporting a Read-Across Prediction of Toxicity

Category formation, grouping and read across methods are broadly applicable in toxicological assessments and may be used to fill data gaps for chemical safety assessment and regulatory decisions. In order to facilitate a transparent and systematic approach to aid regulatory acceptance, a strategy to evaluate chemical category membership, to support the use of read-across predictions that may be used to fill data gaps for regulatory decisions is proposed. There are two major aspects of any read-across exercise, namely assessing similarity and uncertainty. While there can be an over-arching rationale for grouping organic substances based on molecular structure and chemical properties, these similarities alone are generally not sufficient to justify a read-across prediction. Further scientific justification is normally required to justify the chemical grouping, typically including considerations of bioavailability, metabolism and biological/mechanistic plausibility. Sources of uncertainty include a variety of elements which are typically divided into two main issues: the uncertainty associated firstly with the similarity justification and secondly the completeness of the read-across argument. This article focuses on chronic toxicity, whilst acknowledging the approaches are applicable to all endpoints. Templates, developed from work to prepare for the application of new toxicological data to read-across assessment, are presented. These templates act as proposals to assist in assessing similarity in the 50 context of chemistry, toxicokinetics and toxicodynamics as well as to guide the systematic characterisation of uncertainty both in the context of the similarity rationale, the read across data and overall approach and conclusion. Lastly, a workflow for reporting a read-across prediction is suggested

Ecotoxicity Thresholds for Ametryn, Diuron, Hexazinone and Simazine in Fresh and Marine Waters

Triazine and urea herbicides are two groups of photosystem II inhibiting herbicides frequently detected in surface, ground and marine waters. Yet, there are few water quality guidelines for herbicides. Ecotoxicity thresholds (ETs) for ametryn, hexazinone and simazine (triazine herbicides) and diuron (a urea herbicide) were calculated using the Australian and New Zealand method for deriving guideline values to protect fresh and marine ecosystems. Four ETs were derived for each chemical and ecosystem that should theoretically protect 99, 95, 90 and 80% of species (i.e. PC99, PC95, PC90 and PC80, respectively). For all four herbicides, the phototrophic species were significantly more sensitive than non-phototrophic species, and therefore, only the former data were used to calculate the ETs. Comparison of the ET values to measured concentrations in 2606 samples from 15 waterways that discharge to the Great Barrier Reef (2011–2015) found three exceedances of the simazine PC99, regular exceedances (up to 30%) of the PC99 in a limited number of rivers for ametryn and hexazinone and frequent (> 40%) exceedances of the PC99 and PC95 ETs in at least four waterways for diuron. There were no exceedances of the marine ETs in inshore reef areas. Further, ecotoxicity data are required for ametryn and hexazinone to fresh and marine phototrophic species, for simazine to marine phototrophic species, for tropical phototrophic species, repeated pulse exposures and long-term (2 to 12 months) exposures to environmentally relevant concentrations.Griffith Sciences, Griffith Institute for Drug DiscoveryNo Full Tex

Enhancing Credibility of Chemical Safety Studies: Emerging Consensus on Key Assessment Criteria

Objectives: We examined the extent to which consensus exists on the criteria that should be used for assessing the credibility of a scientific work, regardless of its funding source, and explored how these criteria might be implemented. Data sources: Three publications, all presented at a session of the 2009 annual meeting of the Society for Risk Analysis, have proposed a range of criteria for evaluating the credibility of scientific studies. At least two other similar sets of criteria have recently been proposed elsewhere. Data extraction/synthesis: In this article we review these criteria, highlight the commonalities among them, and integrate them into a list of 10 criteria. We also discuss issues inherent in any attempt to implement the criteria systematically. Con c l u s i o n s: Recommendations by many scientists and policy experts converge on a finite list of criteria for assessing the credibility of a scientific study without regard to funding source. These criteria should be formalized through a consensus process or a governmental initiative that includes discussion and pilot application of a system for reproducibly implementing them. Formal establishment of such a system should enable the debate regarding chemical studies to move beyond funding issues and focus on scientific merit

How should the completeness and quality of curated nanomaterial data be evaluated?

Nanotechnology is of increasing significance. Curation of nanomaterial data into electronic databases offers opportunities to better understand and predict nanomaterials' behaviour. This supports innovation in, and regulation of, nanotechnology. It is commonly understood that curated data need to be sufficiently complete and of sufficient quality to serve their intended purpose. However, assessing data completeness and quality is non-trivial in general and is arguably especially difficult in the nanoscience area, given its highly multidisciplinary nature. The current article, part of the Nanomaterial Data Curation Initiative series, addresses how to assess the completeness and quality of (curated) nanomaterial data. In order to address this key challenge, a variety of related issues are discussed: the meaning and importance of data completeness and quality, existing approaches to their assessment and the key challenges associated with evaluating the completeness and quality of curated nanomaterial data. Considerations which are specific to the nanoscience area and lessons which can be learned from other relevant scientific disciplines are considered. Hence, the scope of this discussion ranges from physicochemical characterisation requirements for nanomaterials and interference of nanomaterials with nanotoxicology assays to broader issues such as minimum information checklists, toxicology data quality schemes and computational approaches that facilitate evaluation of the completeness and quality of (curated) data. This discussion is informed by a literature review and a survey of key nanomaterial data curation stakeholders. Finally, drawing upon this discussion, recommendations are presented concerning the central question: how should the completeness and quality of curated nanomaterial data be evaluated

Identification and Description of the Uncertainty, Variability, Bias and Influence in Quantitative Structure-Activity Relationships (QSARs) for Toxicity Prediction

Improving regulatory confidence in, and acceptance of, a prediction of toxicity from a quantitative structure-activity relationship (QSAR) requires assessment of its uncertainty and determination of whether the uncertainty is acceptable. Thus, it is crucial to identify potential uncertainties fundamental to QSAR predictions. Based on expert review, sources of uncertainties, variabilities and biases, as well as areas of influence in QSARs for toxicity prediction were established. These were grouped into three thematic areas: uncertainties, variabilities, potential biases and influences associated with 1) the creation of the QSAR, 2) the description of the QSAR, and 3) the application of the QSAR, also showing barriers for their use. Each thematic area was divided into a total of 13 main areas of concern with 49 assessment criteria covering all aspects of QSAR development, documentation and use. Two case studies were undertaken on different types of QSARs that demonstrated the applicability of the assessment criteria to identify potential weaknesses in the use of a QSAR for a specific purpose such that they may be addressed and mitigation strategies can be proposed, as well as enabling an informed decision on the adequacy of the model in the considered context