Are the States United? An analysis of US hotels’ offers through TripAdvisor’s eyes

This empirical data-driven research aims to unveil thought-provoking insights on the U.S. hotel offer across its 50 states. Information of more than 30,000 hotels was collected through web scraping from TripAdvisor. Using such data, 50 support vector machine models were trained to model the TripAdvisor score, one per state, to assess the convergent and divergent factors in customer satisfaction across all the U.S. states. A conceptual model is proposed and validated through the data-driven support vector machine models developed for each state to identify convergent features across the states to explain customer satisfaction (here represented by TripAdvisor score). Hotel size, price, and stars are not moderated by the location, expressed by the corresponding state, although these highly influence satisfaction, whereas both hotel number of published photos and the amenities are affected by the location. Thus, adaptation issues were found regarding amenities and published photos within each state’s offer.info:eu-repo/semantics/acceptedVersio

Leveraging national tourist offices through data analytics

Purpose This study aims to propose a data-driven approach, based on open-source tools, that makes it possible to understand customer satisfaction of the accommodation offer of a whole country. Design/methodology/approach The method starts by extracting information from all hotels of Portugal available at TripAdvisor through Web scraping. Then, a support vector machine is adopted for modeling the TripAdvisor score, which is considered a proxy of customer satisfaction. Finally, knowledge extraction from the model is achieved using sensitivity analysis to unveil the influence of features on the score. Findings The model of the TripAdvisor score achieved a mean absolute percentage error of around 5 per cent, proving the value of modeling the extracted data. The number of rooms of the unit and the minimum price are the two most relevant features, showing that customers appreciate smaller and more expensive units, whereas the location of the hotel does not hold significant relevance. Originality/value National tourist offices can use the proposed approach to understand what drives tourists’ satisfaction, helping to shape a country’s strategy. For example, licensing new hotels may take into account the unit size and other characteristics that make it more attractive to tourists. Furthermore, the procedure can be replicated at any time and in any country, making it a valuable tool for data-driven decision support on a national scale.info:eu-repo/semantics/acceptedVersio

Bradykinin B2 receptor is essential to running-induced cell proliferation in the adult mouse hippocampus

Physical exercise is a strong external effector that induces precursor cell proliferation in the adult mouse hippocampus. Research into mechanisms has focused on central changes within the hippocampus and we have established that serotonin is the signaling factor that transduces physical activity into adult neurogenesis. Less focus has been given on potential peripheral signals that may cause pro-mitotic running effects. Vasoactive kinin peptides are important for blood pressure regulation and inflammatory processes to maintain cardiovascular homeostasis. Acting via the two receptors termed B1 (B1R) and B2R, the peptides also function in the brain. In particular, studies attribute B2R a role in cell proliferation and differentiation into neurons in vitro. Here, we determined B1R and B2R mRNA expression levels in the adult mouse hippocampus and prefrontal cortex in vivo, and in response to running exercise. Using mice depleted in either or both receptors, B1-knockout (KO), B2KO and B1/2KO we observed changes in running performance overnight and in running distances. However, voluntary exercise led to the known pro-mitotic effect in the dentate gyrus of B1KO mice while it was attenuated in B2KO accompanied by an increase in microglia cells. Our data identify B2R as an important factor in running-induced precursor cell proliferation

A proteomic study to identify soya allergens - the human response to transgenic versus non-transgenic soya samples

BACKGROUND: In spite of being among the main foods responsible for allergic reactions worldwide, soybean (Glycine max)-derived products continue to be increasingly widespread in a variety of food products due to their well-documented health benefits. Soybean also continues to be one of the elected target crops for genetic modification. The aim of this study was to characterize the soya proteome and, specifically, IgE-reactive proteins as well as to compare the IgE response in soya-allergic individuals to genetically modified Roundup Ready soya versus its non-transgenic control. METHODS: We performed two-dimensional gel electrophoresis of protein extracts from a 5% genetically modified Roundup Ready flour sample and its non-transgenic control followed by Western blotting with plasma from 5 soya-sensitive individuals. We used peptide tandem mass spectrometry to identify soya proteins (55 protein matches), specifically IgE-binding ones, and to evaluate differences between transgenic and non-transgenic samples. RESULTS: We identified 2 new potential soybean allergens--one is maturation associated and seems to be part of the late embryogenesis abundant proteins group and the other is a cysteine proteinase inhibitor. None of the individuals tested reacted differentially to the transgenic versus non-transgenic samples under study. CONCLUSION: Soybean endogenous allergen expression does not seem to be altered after genetic modification. Proteomics should be considered a powerful tool for functional characterization of plants and for food safety assessment

Caracterização fisico-quimica da polpa de tucumãs do BAG da Embrapa Amazônia Oriental (Astrocaryum vulgare Mart.).

Editores técnicos: Nádia Elígia Pinto Paracampo, Laura Figueiredo Abreu. XIII MET

Surface laser-glazing of plasma-sprayed thermal barrier coatings

Atmospheric plasma-sprayed (APS) ZrO2–8%WtY2O3 thermal barrier coatings (TBCs) were subjected to a CO2 continuous wave laser-glazing process in order to generate an external dense layer produced by different processing parameters. For that purpose, different beam scanning speeds and track overlapping were chosen. Surface roughness has been reduced significantly after laser-glazing. Despite the surface crack network, all laser-glazed specimens presented a fully dense and porous free external layer with a columnar microstructure. Surface cracks along the densified layer were found to have tendency to be oriented in two perpendicular directions, one in the direction of the laser beam travel, the other perpendicular to it. Moreover, the cracks parallel to the beam moving direction are found to be on the overlapping zone, coinciding with the edge of the subsequent track. The cracks along the densified layer are vertical and tend to branch and deviate from the vertical direction within the porous PS coating. The largest overlapping allied to the smallest amount of irradiated energy generated the most uniform layer with the shortest crack branches within the PS coating. For the as-sprayed coating, the XRD results revealed mainly t0 non-transformable tetragonal zirconia with a small percentage of residual monoclinic zirconia. All glazed coatings presented only t0 non-transformable tetragonal zirconia with some variations on preferable crystal orientation.União Europeia (UE). Fundo Europeu de Desenvolvimento Regional (FEDER).Fundação para a Ciência e a Tecnologia (FCT) - Project POCTI/CTM44590/2002

Transformer-based language models for semantic search and mobile applications retrieval

Search engines are being extensively used by Mobile App Stores, where millions of users world-wide use them every day. However, some stores still resort to simple lexical-based search engines, despite the recent advances in Machine Learning, Information Retrieval, and Natural Language Processing, which allow for richer semantic strategies. This work proposes an approach for semantic search of mobile applications that relies on transformer-based language models, fine-tuned with the existing textual information about known mobile applications. Our approach relies solely on the application name and on the unstructured textual information contained in its description. A dataset of about 500 thousand mobile apps was extended in the scope of this work with a test set, and all the available textual data was used to fine-tune our neural language models. We have evaluated our models using a public dataset that includes information about 43 thousand applications, and 56 manually annotated non- exact queries. The results show that our model surpasses the performance of all the other retrieval strategies reported in the literature. Tests with users have confirmed the performance of our semantic search approach, when compared with an existing deployed solution.info:eu-repo/semantics/acceptedVersio

Determinação do teor de lipídios das amêndoas do tucumã-do-amazonas (Astrocaryum aculeatum) e do tucumã-do-pará (Astrocaryum vulgare).

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