Suchergebnisse

Distintos organismos internacionales establecen que el turismo con base en el patrimonio cultural puede constituirse en un instrumento de inclusión y dinamización socioeconómica de un territorio. En este sentido, las áreas rurales como lugar de vida y de producción se ven como nuevos espacios a descubrir a través de sus tradiciones, sus paisajes, su gastronomía, su artesanía y/o su cultura. Sin embargo, para que pueda efectivizarse un proceso de desarrollo local‑rural basado en la actividad turística, el primer paso consiste en contar con información previa y, en particular, conocer los recursos/atractivos disponibles. En esta línea, a partir de distintas investigaciones previas sobre turismo y patrimonio realizadas en las aldeas San Antonio, San Juan y Santa Celia, provincia de Entre Ríos (Argentina), se consideró tomar estas localidades como estudio de caso. En ellas predominan descendientes de alemanes provenientes de la región del Volga (Rusia) arribados a fines del siglo XIX, y tienen la particularidad de haber preservado hasta el presente valiosas tradiciones y costumbres. De esta manera, el objetivo del trabajo fue realizar una evaluación del potencial turístico‑cultural de dichas aldeas. El trabajo forma parte de un proceso de investigación de tipo exploratorio, en el cual se realizaron consultas de fuentes primarias y secundarias, la elaboración de una ficha relevamiento y de una matriz de evaluación del potencial turístico de las aldeas. Dentro de los principales hallazgos se detectó, que a pesar del valioso patrimonio cultural tanto tangible como intangible existente, no hay un registro oficial de estos bienes. Por lo tanto, disponer de una información integral al respecto, permitiría impulsar acciones, tales como: promover una mayor difusión entre la propia comunidad; gestionar determinada normativa y/o financiamiento que permita preservar sitios relevantes; identificar atractivos que puedan integrarse a una posible oferta turística‑cultural, y analizar junto a la comunidad, futuros emprendimientos en base al patrimonio cultural. ; Many international organizations have posited tourism based on cultural heritage as a tool to be deployed toward greater inclusion and socio‑economic development. Rural areas, in this context, can be seen as places to be re‑discovered their traditions, their landscapes, their gastronomy, their handicraft, that is to say, their their culture. However, in order to begin a process of local‑rural development based on tourist activity, there is a need first to establish an inventory of the potential resources. Case studies were pursued in the country towns of San Antonio, San Juan and Santa Celia, in the province of Entre Rios (Argentina),. The locals are descendents of the Germans from the Volga Region (Russia) who came to Argentina in the late nineteenth century. They have maintained traditions and typical folklore through to the present day and therefore present cultural tourism potential. The work is part of an exploratory research process, using primary and secondary resources. A survey and evaluation matrix of the tourist potential were produced as part of the fieldwork. Any further work (community awareness, management financing and promotion/ legislation) requires the previous elaboration of an inventory.

<p style="margin: 0cm 0cm 0pt; text-align: justify;"><span style="font-family: 'Times New Roman',serif;"><span style="font-size: medium;">La finalidad de este artículo es presentar algunos resultados que surgen en el marco del proyecto de investigación "La planificación estratégica como instrumento para el desarrollo local. Su aplicación en el campo del turismo en Argentina (periodo 2003-2013)". El recorte del periodo de estudio se ha seleccionado a partir del año en que se iniciaron en el país una serie de políticas públicas que promueven el turismo como un sector dinamizador de la economía, generador de riqueza y de bienestar individual y colectivo. En la primera parte del trabajo se profundiza en la importancia de la planificación estratégica como instrumento para el desarrollo del turismo. Luego se realiza un recuento sobre algunos hitos que han incidido en el planeamiento del turismo en el ámbito nacional, y sobre esta base se procede a realizar un relevamiento de los planes de turismo provinciales desarrollados en el periodo de estudio. Dicho relevamiento se basó en una revisión de fuentes primarias y secundarias. Finalmente, se presenta un análisis de dichos planes a partir del método de los "interrogantes fundamentales" (Fundación DEMUCA, 2009), en el que, siguiendo una serie de preguntas, se realiza un estudio comparativo de estos.</span></span></p>

Agricultural land abandonment is an emerging problem in European Union (EU), and about 11% of agricultural EU land is at high risk of abandonment in the coming 10 years. Land abandonment may have both positive and negative effects in ecosystems. Due to the potential for land abandonment to increase soil fertility, the study of vegetation succession effects on soil quality is of great importance. In this study, we investigated an abandoned vineyard where, after a period of 30 years, rows and alleys were characterized by two different forms of vegetation succession: natural recolonization by trees along the rows and by herbaceous vegetation in the alleys. No-tilled alleys covered by herbaceous vegetation of a neighboring conventionally cultivated vineyard were used as a comparison. Soil samples were chemically characterized (pH, extractable element, and available and total metals), and analyzed for the determination of carbon (C) and nitrogen (N) pools ; hydrolytic and phenol oxidizing (PO) enzyme activities involved in C, N, and phosphorus (P) cycles ; and the enzyme ratios. Results highlighted that natural recolonization by trees increased the organic C and N soil pools by 58% and 34%, respectively, compared to the natural recolonization by herbaceous vegetation. Moreover, natural recolonization by trees reduced β-glucosidase by 79%, urease by 100%, alkaline phosphastase by 98%, acid phosphatase specific hydrolytic activities by 50%, and catechol oxidase and laccase specific oxidative activities by 127% and 119%, respectively, compared to the renaturalization by herbaceous vegetation. In addition, the natural recolonization by trees reduced the C (βglu):C (PO) enzymes ratio by 16% compared to that of the conventional vineyard. Comparing the natural recolonization by herbaceous vegetation with that of the conventional vineyard revealed little significant difference (15% of the measured and calculated parameters) ; in particular, PO activities significantly decreased in the renaturalized vineyard with herbaceous vegetation by 49% (catechol oxidase) and 52% (laccase), and the C (βglu):C (PO) enzyme ratio showed a reduction (−11%) in the vineyard naturally recolonized by herbaceous vegetation compared to the conventional vineyard. This highlights that the type of vegetation succession that takes place after land abandonment may have a significant impact in terms of soil fertility and C accrual potential. These results help to focus attention on the practices used in agro-forestry that should be adopted in abandoned agro-ecosystems to increase their biodiversity, soil C stock, and soil quality, because these indicators are affected by the type of vegetative coverage.

[EN] Optical Music Recognition is the technology that allows computers to read music notation, which is also referred to as Handwritten Music Recognition when it is applied over handwritten notation. This technology aims at efficiently transcribing written music into a representation that can be further processed by a computer. This is of special interest to transcribe the large amount of music written in early notations, such as the Mensural notation, since they represent largely unexplored heritage for the musicological community. Traditional approaches to this problem are based on complex strategies with many explicit rules that only work for one particular type of manuscript. Machine learning approaches offer the promise of generalizable solutions, based on learning from just labelled examples. However, previous research has not achieved sufficiently acceptable results for handwritten Mensural notation. In this work we propose the use of deep neural networks, namely convolutional recurrent neural networks, which have proved effective in other similar domains such as handwritten text recognition. Our experimental results achieve, for the first time, recognition results that can be considered effective for transcribing handwritten Mensural notation, decreasing the symbol-level error rate of previous approaches from 25.7% to 7.0%. (C) 2019 Elsevier B.V. All rights reserved. ; First author thanks the support from the Spanish Ministry "HISPAMUS" project (TIN2017-86576-R), partially funded by the EU. The other authors were supported by the European Union's H2020 grant "Recognition and Enrichment of Archival Documents" (Ref. 674943), by the BBVA Foundacion through the 2017-2018 and 2018-2019 Digital Humanities research grants "Carabela" and "HistWeather - Dos Siglos de Datos Cilmaticos", and by EU JPICH project "HOME - History Of Medieval Europe"(Spanish PEICTI Ref. PCI2018-093122). ; Calvo-Zaragoza, J.; Toselli, AH.; Vidal, E. (2019). Handwritten Music Recognition for Mensural notation with convolutional recurrent ...

Optical Music Recognition is the technology that allows computers to read music notation, which is also referred to as Handwritten Music Recognition when it is applied over handwritten notation. This technology aims at efficiently transcribing written music into a representation that can be further processed by a computer. This is of special interest to transcribe the large amount of music written in early notations, such as the Mensural notation, since they represent largely unexplored heritage for the musicological community. Traditional approaches to this problem are based on complex strategies with many explicit rules that only work for one particular type of manuscript. Machine learning approaches offer the promise of generalizable solutions, based on learning from just labelled examples. However, previous research has not achieved sufficiently acceptable results for handwritten Mensural notation. In this work we propose the use of deep neural networks, namely convolutional recurrent neural networks, which have proved effective in other similar domains such as handwritten text recognition. Our experimental results achieve, for the first time, recognition results that can be considered effective for transcribing handwritten Mensural notation, decreasing the symbol-level error rate of previous approaches from 25.7% to 7.0%. ; First author thanks the support from the Spanish Ministry "HISPAMUS"project (TIN2017-86576-R), partially funded by the EU. The other authors were supported by the European Union 's H2020 grant "Recognition and Enrichment of Archival Documents"(Ref. 674943 ), by the BBVA Foundacion through the 2017–2018 and 2018–2019 Digital Humanities research grants "Carabela"and "HistWeather –Dos Siglos de Datos Cilmáticos", and by EU JPICH project "HOME - History Of Medieval Europe"(Spanish PEICTI Ref. PCI2018-093122).