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We present an approach for the development of Language Understanding systems from a Transduction point of view. We describe the use of two types of automatically inferred transducers as the appropriate models for the understanding phase in dialog systems.

Gaseous and particulate emission profiles during controlled rice straw burningSanchis, E 1 ., Ferrer, M 1 ., Calvet, S 1 ., Coscollà, C 2 ., Yusà, V 2 ., Cambra-López, M 1 . AbstractBurning of rice straw can emit considerable amounts of atmospheric pollutants. We evaluated the effect of rice straw moisture content (5%, 10% and 20%) on the emission of carbon dioxide (CO 2 ) and on the organic and inorganic constituents of released particulate matter (PM): dioxins, heavy metals, and polycyclic aromatic hydrocarbons (PAHs). Four burning tests were conducted per moisture treatment using the open chamber method. Gaseous emission profiles of carbon monoxide (CO), sulfur dioxide (SO 2 ), nitrogen monoxide (NO), and nitrogen dioxide (NO 2 ) were also measured. Additionally, combustion characteristics, including burning stages, durations, combustion efficiency, temperature, and relative humidity, were recorded. Burning tests showed flaming and smoldering stages were significantly longer in 20% moisture treatment (P<0.05) compared with the rest. The amount of burned straw and ashes decreased with increasing straw moisture content (P<0.001). Carbon dioxide was the main product obtained during combustion with emission values ranging from 692 g CO 2 kg dry straw -1 (10% moisture content) to 835 g CO 2 kg dry straw -1 (20% moisture content). Emission factors for PM were the highest in 20% moisture treatment (P<0.005). Fine PM (PM2.5) accounted to more than 60% of total PM mass. Emission factors for dioxins increased with straw moisture content, being the highest in 20% moisture treatment, although showing a wide variability among burning tests (P>0.05). Emissions factors for heavy metals were low and similar among moisture treatments (P>0.05). Emission factors for individual PAHs were generally higher in 20% moisture treatment. Average SO 2 and NO emissions decreased with moisture content. In contrast, CO emissions increased with moisture content.Overall, emission factors of atmospheric pollutants measured in our study were higher in the 20% moisture content. This difference could be attributed to the incomplete combustion at higher levels *Manuscript Click here to download Manuscript: Quema_sin tablas ni figuras_cor.docx Click here to view linked References 2 of rice straw moisture content. According to our results, rice straw burning should be done after straw drying and under minimal moisture conditions to lower pollutant emission levels.

In this paper, we present an extractive approach to document summarization based on Siamese Neural Networks. Specifically, we propose the use of Hierarchical Attention Networks to select the most relevant sentences of a text to make its summary. We train Siamese Neural Networks using document-summary pairs to determine whether the summary is appropriated for the document or not. By means of a sentence-level attention mechanism the most relevant sentences in the document can be identified. Hence, once the network is trained, it can be used to generate extractive summaries. The experimentation carried out using the CNN/DailyMail summarization corpus shows the adequacy of the proposal. In summary, we propose a novel endto-end neural network to address extractive summarization as a binary classification problem which obtains promising results in-line with the state-of-the-art on the CNN/DailyMail corpus.

Livestock housing is one of the main sources of ammonia (NH3) emissions from agriculture. Different management and environmental factors are known to affect NH3 emissions from housing systems. The aim of this study was to quantitatively define the effect of temperature, wind speed, relative humidity, and ventilation rate in NH3 release rates from dairy cattle housing by conducting a meta-analysis of published scientific results. A literature survey was performed to review studies published before January 2018 that have identified statistical relationships between NH3 emissions and environmental factors such as air temperature, wind speed, relative humidity, or ventilation rate in dairy cattle housing. Experimental values were related using a mixed model analysis in order to analyze the effect of environmental factors on NH3 emissions. For this exercise, a total of 19 peer-reviewed papers were considered and 27 different relations between air temperature and NH3 emissions were used for the analysis.

Running titleRice management practices and methane emissions 2 AbstractRice fields contribute substantially to global warming of the atmosphere through the emission of methane (CH4). This paper reviews the state-of-the-art of factors affecting CH4 emissions in rice fields, focusing on soil organic matter content and water management practices. It establishes a quantitative relationship between these factors based on a literature survey through a meta-analysis, useful to update the emission factors used to estimate CH4 in National Emission Inventories. Methane emissions in rice fields can be as much as 90% higher in continuously flooded rice fields compared with other water management systems, independent from straw addition. Water management systems which involve absence of flooding in total or part of the growing period such as midseason drainages, intermittent flooding and percolation control can reduce CH4 emissions substantially. Moreover, CH4 emissions increase with the amount of straw added until 7.7 t/ha for continuously flooded soils and until 5.1 t/ha for other water regimes. Above these levels, no further increase is produced with further addition of straw. As regards to rice straw management mitigation strategies, recommended practices are: composting rice straw, straw burning under controlled conditions, recollecting rice straw for biochar production, generation of energy, to be used as a substrate, or to obtain other by-products with added value. This review improves the understanding of the relationship between straw application rate, water regimes and CH4 emissions from rice fields to date. This relationship can help to select the most appropriate management practices to improve current mitigation strategies to reduce atmospheric CH4.

Abstract. This paper presents an indexing technique based on WordNet synonyms and holonyms. This technique has been developed for the Geographical Information Retrieval task. It may help in finding implicit geographic information contained in texts, particularly if the indication of the containing geographical entity is omitted. Our experiments were carried out with the Lucene search engine over the GeoCLEF 2006 set of topics. Results show that expansion can improve recall in some cases, although a specific ranking function is needed in order to obtain better results in terms of precision.