This paper aims to reveal the rhetorical structure and the linguistic features of persuasive language in online advertisements of electronic products. Nowadays, the bulk of e-commerce is carried out in English, and it is often the case that non-native speakers are required to write different text types for various professional purposes, including promotional texts. This need has prompted the present study and the results have been used to build software to help native speakers of Spanish when writing promotional texts in English. The analysis reveals that these texts typically have two main rhetorical moves: one for identifying the product and another one for describing it. The latter move is further divided into two steps: one including objective features (size, weight, etc.) and the other focusing on persuading the potential customer. This is mainly achieved with the use of a relatively informal style (imperatives, contractions, clipping, subject/auxiliary omissions, etc.) and lexico-grammatical elements conveying positive evaluation (multiple modification, multal quantifying expressions, etc.). The findings show that online advertisements of electronic products may be regarded as a specific subgenre with particular macro-and microlinguistic characteristics, which have been identified in this paper for technical writing assistance.
The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of chronic diseases, 75 of non-chronic diseases and only 35 of healthy individuals. As more than 88% of the samples of the dataset are from the same class (Chronic), the use of a Variational Convolutional Autoencoder was proposed to generate new labeled data and other well known oversampling techniques after determining that the dataset classes are unbalanced. Once the preprocessing step was carried out, a Convolutional Neural Network (CNN) was used to classify the respiratory sounds into healthy, chronic, and non-chronic disease. In addition, we carried out a more challenging classification trying to distinguish between the different types of pathologies or healthy: URTI, COPD, Bronchiectasis, Pneumonia, and Bronchiolitis. We achieved results up to 0.993 F-Score in the three-label classification and 0.990 F-Score in the more challenging six-class classification.
The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems (IDS) are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems (IDS) can be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results.
Simple SummaryAgro-industrial by-products are the waste from either agricultural crops or vegetable processing industries, and their disposal represents an environmental problem since they are potential pollutants. One of their most promising alternative uses is as feedstuffs in ruminant diets. The aim of this study was to assess the nutritive value of different by-products by analysing their chemical composition, in vitro digestibility and gas production kinetics. The results showed a high variability in chemical composition, in vitro digestibility and rumen fermentation kinetics among different by-products. In addition, samples of the same by-product from a different origin or subjected to different conservation processes showed a certain variability in the evaluated parameters. The variability among by-products was reflected in the results of the cluster analysis, which divided the materials in four groups based on the multivariate analysis. Most by-products showed the potential to be included as alternative ingredients in ruminant rations. They could be used as a source of energy, fibre or protein, replacing part of the ingredients in a conventional diet and therefore, reducing the risk of environmental pollution and contributing to develop a circular economy by recycling these wastes. In addition, their use as feedstuffs might reduce competition between ruminants and humans for food or land.AbstractThe nutritive value of 26 agro-industrial by-products was assessed from their chemical composition, in vitro digestibility and rumen fermentation kinetics. By-products from sugar beet, grape, olive tree, almond, broccoli, lettuce, asparagus, green bean, artichoke, peas, broad beans, tomato, pepper, apple pomace and citrus were evaluated. Chemical composition, in vitro digestibility and fermentation kinetics varied largely across the by-products. Data were subjected to multivariate and principal component analyses (PCA). According to a multivariate cluster analysis chart, samples formed four distinctive groups (A–D). Less degradable by-products were olive tree leaves, pepper skins and grape seeds (group A); whereas the more degradable ones were sugar beet, orange, lemon and clementine pulps (group D). In the PCA plot, component 1 segregated samples of groups A and B from those of groups C and D. Considering the large variability among by-products, most of them can be regarded as potential ingredients in ruminant rations. Depending on the characteristic nutritive value of each by-product, these feedstuffs can provide alternative sources of energy (e.g., citrus pulps), protein (e.g., asparagus rinds), soluble fibre (e.g., sugar beet pulp) or less digestible roughage (e.g., grape seeds or pepper skin).
The energy supplied by the high-forage diets used in organic farming may be insufficient to meet the requirements of dairy cattle. However, few studies have considered this problem. The present study aimed to analyze the composition of the diets and the nutritional status (focusing on the energy–protein balance of the diets) of dairy cattle reared on organic farms in northern Spain, which are similar to other organic farming systems in temperate regions. Exhaustive information about diets was obtained from organic (ORG) and representative conventional grazing (GRZ) and conventional no-grazing (CNG) farms. Samples of feed from the respective farms were analyzed to determine the composition. Overall, the diets used on the ORG farms were very different from those used on the CNG farms, although the difference was not as evident for GRZ. The CNG farms were characterized by a higher total dry matter intake with a high proportion of concentrate feed, maize silage and forage silage. By contrast, on ORG and GRZ farms, the forage, pasture and fibre intake were the most important variables. The ration used on ORG farms contained a significantly higher percentage of ADF and lower organic matter (OM) content than the rations used in both of the conventional farming systems, indicating that the diets in the former were less digestible. Although the protein concentration in the diets used on the grazing farms (ORG and GRZ) was higher than those used on CNG farms, the protein intake was similar. The results indicated an imbalance between energy and protein due to the low level of energy provided by the ORG diets, suggesting that more microbial protein could be synthesized from the available rumen-degraded dietary nitrogen if rumen-fermentable OM was not limiting. The imbalance between energy and protein led to a reduced amount of total digestible protein reaching the intestine and a lower milk yield per kilogram of CP intake on the ORG farms. In order to improve the protein use efficiency and consequently to reduce the loss of nitrogen to the environment, organic farming should aim to increase the energy content of cattle diets by improving forage quality and formulating rations with more balanced combinations of forage and grain.
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