Caracterización de personajes en la traducción audiovisual: análisis comparativo de las intervenciones del Genio en Aladdín (2019)

Treball de Final de Grau en Traducció i Interpretació. Codi: TI0983. Curs acadèmic 2020/2021En el presente trabajo se lleva a cabo un análisis comparativo de las intervenciones del personaje del Genio, interpretado por Will Smith, en la película Aladdín (2019). El objetivo principal es determinar qué aspectos moldean la caracterización del personaje y comparar la versión original de la película con la versión doblada para comprobar si dichos aspectos se han mantenido en la versión en español. Así, tras presentar el marco teórico, en el que se trata el doblaje como una de las modalidades de traducción audiovisual y algunos aspectos que cabe tener en cuenta a la hora de traducir y que moldean la caracterización de un personaje, como son el humor y el lenguaje coloquial; se analizarán qué estrategias se han utilizado en la versión doblada, si se han mantenido, si se han reforzado o si se han eliminado estos aspectos. Por otra parte, al tratarse Aladdín de una película musical, también se analizarán las canciones que están interpretadas por el personaje en cuestión. Para ello, se utilizará un modelo de análisis en el que se tengan en cuenta diferentes criterios que son importantes a la hora de traducir canciones. Mediante el análisis, se presentarán estadísticas de las estrategias utilizadas a lo largo de la película para solventar los problemas de traducción que puedan surgir al mantener o no los aspectos comentados con anterioridad

Development and Genome-Wide Analysis of a Blast-Resistant japonica Rice Variety

Rice is one of the most important crops in the world, and its production is severely affected by the rice blast disease caused by the fungus Magnaporthe oryzae. Several major blast resistance genes and QTLs associated with blast resistance have been described and mostly identified in indica rice varieties. In this work, we report the obtention of a blast-resistant rice breeding line derived from crosses between the resistant indica variety CT13432 and the japonica elite cultivar JSendra (highly susceptible to blast). The breeding line, named COPSEMAR9, was found to exhibit resistance to leaf blast and panicle blast, as demonstrated by disease assays under controlled and field conditions. Furthermore, a high-quality genome sequence of the blast-resistant breeding line was obtained using a strategy that combines short-read sequencing (Illumina sequencing) and long-read sequencing (Pacbio sequencing). The use of a whole-genome approach allowed the fine mapping of DNA regions of indica and japonica origin present in the COPSEMAR9 genome and the identification of parental gene regions potentially contributing to blast resistance in the breeding line. Rice blast resistance genes (including Pi33 derived from the resistant parent) and defense-related genes in the genome of COPSEMAR9 were identified. Whole-genome analyses also revealed the presence of microRNAs (miRNAs) with a known function in the rice response to M. oryzae infection in COPSEMAR9, which might also contribute to its phenotype of blast resistance. From this study, the genomic information and analysis methods provide valuable knowledge that will be useful in breeding programs for blast resistance in japonica rice cultivars.This research was supported by Projects RTI2018-101275-B-I00 and PID2021-128825OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” to B.SS, and PID2019-104099RR-I00 to C.D. We acknowledge financial support from the MCIN/AEI/10.13039/501100011033 through the “Severo Ochoa Programme for Centres of Excellence in R&D” (SEV-2015-0533 and CEX2019-000902-S) and the CERCA Programe/“Generalitat de Catalunya”. We also thank support from the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). G.E. was the recipient of Grant PEJ2018-002245-P funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”.info:eu-repo/semantics/publishedVersio

Effect of root colonization by arbuscular mycorrhizal fungi on growth, productivity and blast resistance in rice

Altres ajuts: CERCA Programme/Generalitat de CatalunyaBackground: Arbuscular mycorrhizal (AM) fungi form symbiotic associations with roots in most land plants. AM symbiosis provides benefits to host plants by improving nutrition and fitness. AM symbiosis has also beenassociated with increased resistance to pathogen infection in several plant species. In rice, the effects of AM symbiosis is less studied, probably because rice is mostly cultivated in wetland areas, and plants in such ecosystems have traditionally been considered as non-mycorrhizal. In this study, we investigated the effect of AM inoculation on performance of elite rice cultivars (Oryza sativa, japonica subspecies) under greenhouse and field conditions, focusing on growth, resistance to the rice blast fungus Magnaporthe oryzae and productivity. Results: The response to inoculation with either Funneliformis mosseae or Rhizophagus irregularis was evaluated in a panel of 12 rice cultivars. Root colonization was confirmed in all rice varieties. Under controlled greenhouse conditions, R. irregularis showed higher levels of root colonization than F. mosseae. Compared to non-inoculated plants, the AM-inoculated plants had higher Pi content in leaves. Varietal differences were observed in the growth response of rice cultivars to inoculation with an AM fungus, which were also dependent on the identity of the fungus. Thus, positive, negligible, and negative responses to AM inoculation were observed among rice varieties. Inoculation with F. mosseae or R. irregularis also conferred protection to the rice blast fungus, but the level of mycorrhiza-induced blast resistance varied among host genotypes. Rice seedlings (Loto and Gines varieties) were pre-inoculated with R. irregularis, transplanted into flooded fields, and grown until maturity. A significant increase in grain yield was observed in mycorrhizal plants compared with non-mycorrhizal plants, which was related to an increase in the number of panicles. Conclusion: Results here presented support that rice plants benefit from the AM symbiosis while illustrating the potential of using AM fungi to improve productivity and blast resistance in cultivated rice. Differences observed in the mycorrhizal responsiveness among the different rice cultivars in terms of growth promotion and blast resistance indicate that evaluation of benefits received by the AM symbiosis needs to be carefully evaluated on a case-by-case basis for efficient exploitation of AM fungi in rice cultivation

Agronomic performance and remote sensing assessment of organic and mineral fertilization in rice fields

Introduction: Rice heavily relies on nitrogen fertilizers, posing environmental, resource, and geopolitical challenges. This study explores sustainable alternatives like animal manure and remote sensing for resource-efficient rice cultivation. It aims to assess the long-term impact of organic fertilization and remote sensing monitoring on agronomic traits, yield, and nutrition. Methods: A six-year experiment in rice fields evaluated fertilization strategies, including pig slurry (PS) and chicken manure (CM) with mineral fertilizers (MIN), MIN-only, and zero-fertilization. Traits, yield, spectral responses, and nutrient content were measured. Sentinel-2 remote sensing tracked crop development. Results: Cost-effective organic fertilizers (PS and CM) caused a 13% and 15% yield reduction but still doubled zero-fertilization yield. PS reduced nitrogen leaching. Heavy metals in rice grains were present at safe amounts. Organic-fertilized crops showed nitrogen deficiency at the late vegetative stages, affecting yield. Sentinel-2 detected nutrient deficiencies through NDVI. Discussion: Organic fertilizers, especially PS, reduce nitrogen loss, benefiting the environment. However, they come with yield trade-offs and nutrient management challenges that can be managed and balanced with reduced additional mineral applications. Sentinel-2 remote sensing helps manage nutrient deficiencies. In summary, this research favors cost-effective organic fertilizers with improved nutrient management for sustainable rice production.This work was commissioned and funded by the Catalan Ministry of Climate Action, Food and Rural Agenda, by the projects TED2021-131606B-C21 and PLEC2021-007786 of the Spanish Ministry of Economy and Competitiveness and by the CROPDIVA (Climate Resilient Orphan croPs for increased DIVersity in Agriculture) project through the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101000847. The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.info:eu-repo/semantics/publishedVersio

Agricultural policies against invasive species generate contrasting outcomes for climate change mitigation and biodiversity conservation

Direct consequences of biological invasions on biodiversity and the environment have been largely documented. Yet collateral indirect effects mediated by changes in agri-environmental policies aimed at combating invasions remain little explored. Here we assessed the effects of recent changes in water management in rice farming, which are aimed at buffering the impact of the invasive apple snail (Pomacea maculata, Lamarck) on greenhouse gas emissions and diversity of waterbird communities. We used observational data from a 2-year field monitoring (2015–2016) performed at the Ebro Delta regional scale. We found that drying rice fields reduced methane emission rates by 82% (2015) and 51% (2016), thereby reducing the contribution of rice farming to climate change. However, there was a marked reduction (75% in 2015 and 57% in 2016) in waterbird diversity in dry fields compared with flooded fields, thus suggesting that post-invasion policies might hinder biodiversity conservation. Our results highlight the need for accounting for potential collateral effects during the policy decision-making process to design efficient agricultural management plans that lessen undesirable agri-environmental outcomes.info:eu-repo/semantics/acceptedVersio

The main drivers of methane emissions differ in the growing and flooded fallow seasons in Mediterranean rice fields

Purpose To assess 1) the cumulative greenhouse gas emissions –GHG- and global warming potential (methane – CH4- and nitrous oxide) from rice fields in the growing and fallow seasons, and 2) the environmental and agronomic drivers of CH4 emissions, and their relative capacity to explain CH4 variation. Methods A two-year multisite field experiment covering the agronomic and environmental variability of a rice growing area in NE Iberian Peninsula was conducted with monthly samplings of GHG and monitoring of both environmental and agronomic factors. Information-theoretic framework analysis was used to assess the relative contribution of the environmental and agronomic variables on methane emissions. Results Two thirds of the CH4 is emitted in the fallow season. Edaphic factors exert more influence during the growing season whereas agronomic factors have a higher impact in the fallow. The implications of these findings on the design of improved mitigation options rice are discussed. Conclusions Soils with higher soil sulphate concentration, bulk density and clay content emit less CH4 in growing season. In the fallow season, the rates of both straw input and nitrogen fertilization stimulate CH4 emissions.info:eu-repo/semantics/publishedVersio

Multiple environmental benefits of alternate wetting and drying irrigation system with limited yield impact on European rice cultivation : the Ebre Delta case

Acknowledgements This research was supported by the FACCE-JPI NET project GreenRice (Sustainable and environmentally friendly rice cultivation systems in Europe, ref. 618105), which for M.M-E and M.C-F. was awarded through the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA); and for AHP, YAT, VO and NC was awarded through BBSRC grant BB/M018415/1. The support of the CERCA Programme / Generalitat de Catalunya is also acknowledged. The authors also wish to thank Dr. Esperança Gacia (Blanes Centre for Advanced Studies - Higher Council of Scientific Investigations -CEAB-CSIC) for her revision of the manuscript prior to submission. The authors would like to thank Lluís Jornet, Pep Cabanes and David Mateu (IRTA-Marine and continental waters) and, Oriol Navarro (IRTA- Extensive crops) for their technical assistance in field.Peer reviewedPostprin

An Overview of Rice Cultivation in Spain and the Management of Herbicide-Resistant Weeds

Spain is the second highest rice-producing country in the European Union, with approximately 105,000 ha used to grow this crop. The major rice-producing regions in Spain are Andalusia, Extremadura, Catalonia, and Valencia, followed by Aragon and Navarre. The main soil texture throughout Spanish rice areas is silty clay loam, with alkaline soils (pH > 7.5)—except in the Extremadura area (pH = 5.5–6)—and a low organic matter content. Water quality in terms of salinity is acceptable, although in some coastal rice areas salinity issues occasionally appear to be a determining factor for high yield achievement. According to a survey carried out on farmers and technicians, the most problematic weeds found in rice crops today in Spain are Echinochloa spp., Leptochloa spp., and Cyperus difformis. Most of the currently authorized herbicides can be classified according to two modes of action: ALS-inhibiting and ACCase-inhibiting. Repeated field applications of herbicides with the same mode of action have resulted in the selection of herbicide-resistant weeds. At present, resistance has been confirmed in different regions of Spain to ALS inhibitors in Echinochloa spp., Leptochloa spp., and Cyperus difformis, and to ACCase inhibitors in Echinochloa spp. and Leptochloa spp. The mechanism of resistance in these species is a mutation in the target site of these herbicides. Several mutations have been found in the ALS gene, both in Echinochloa spp. and Cyperus difformis, distributed in the different rice-growing regions considered in this work. ACCase gene mutations have been mainly found in Leptochloa spp. individuals from Extremadura and Valencia. These different mutations have resulted in different patterns of cross-resistance to ALS- and ACCase-inhibiting herbicides. It is likely that the repeated use of these two modes of action in rice will result in the evolution of more resistant weed populations. The possible availability of new herbicides with alternative modes of action in a short space of time seems very limited, suggesting the need for a more appropriate use of the available alternative strategies (crop rotation, dry sowing, manual weeding, etc.). This work presents a review of the main characteristics of rice cultivation in Spain, emphasizing the current problems in this crop and the management of herbicide-resistant weeds.info:eu-repo/semantics/publishedVersio

Chess Practice as a Protective Factor in Dementia

Background: dementia is one of the main causes of disability and dependency among the older population worldwide, producing physical, psychological, social and economic impact in those affected, caregivers, families and societies. However, little is known about dementia protective factors and their potential benefits against disease decline in the diagnosed population. Cognitive stimulating activities seem to be protective factors against dementia, though there is paucity in the scientific evidence confirming this, with most publications focusing on prevention in non-diagnosed people. A scoping review was conducted to explore whether chess practice could mitigate signs, deliver benefits, or improve cognitive capacities of individuals diagnosed with dementia through the available literature, and therefore act as a protective factor. Methods: twenty-one articles were selected after applying inclusion and exclusion criteria. Results: the overall findings stress that chess could lead to prevention in non-diagnosed populations, while little has been shown with respect to individuals already diagnosed. However, some authors suggest its capacity as a protective factor due to its benefits, and the evidence related to the cognitive functions associated with the game. Conclusion: although chess is indirectly assumed to be a protective factor due to its cognitive benefits, more studies are required to demonstrate, with strong evidence, whether chess could be a protective factor against dementia within the diagnosed population

Application of machine learning algorithms in thermal images for an automatic classification of lumbar sympathetic blocks

Purpose There are no previous studies developing machine learning algorithms in the classification of lumbar sympathetic blocks (LSBs) performance using infrared thermography data. The objective was to assess the performance of different machine learning algorithms to classify LSBs carried out in patients diagnosed with lower limbs Complex Regional Pain Syndrome as successful or failed based on the evaluation of thermal predictors. Methods 66 LSBs previously performed and classified by the medical team were evaluated in 24 patients. 11 regions of interest on each plantar foot were selected within the thermal images acquired in the clinical setting. From every region of interest, different thermal predictors were extracted and analysed in three different moments (minutes 4, 5, and 6) along with the baseline time (just after the injection of a local anaesthetic around the sympathetic ganglia). Among them, the thermal variation of the ipsilateral foot and the thermal asymmetry variation between feet at each minute assessed and the starting time for each region of interest, were fed into 4 different machine learning classifiers: an Artificial Neuronal Network, K-Nearest Neighbours, Random Forest, and a Support Vector Machine. Results All classifiers presented an accuracy and specificity higher than 70%, sensitivity higher than 67%, and AUC higher than 0.73, and the Artificial Neuronal Network classifier performed the best with a maximum accuracy of 88%, sensitivity of 100%, specificity of 84% and AUC of 0.92, using 3 predictors. Conclusion These results suggest thermal data retrieved from plantar feet combined with a machine learning-based methodology can be an effective tool to automatically classify LSBs performance