A Personalized Travel Recommendation System Using Social Media Analysis

Personalization of recommender systems enables customized services to users. Social media is one resource that aids personalization. This study explores the use of twitter data to personalize travel recommendations. A machine learning classification model is used to identify travel related tweets. The travel tweets are then used to personalize recommendations regarding places of interest for the user. Places of interest are categorized as: historical buildings, museums, parks, and restaurants. To better personalize the model, travel tweets of the user\u27s friends and followers are also mined. Volunteer twitter users were asked to provide their twitter handle as well as rank their travel category preferences in a survey. We evaluated our model by comparing the predictions made by our model with the users choices in the survey. The evaluations show 68% prediction accuracy. The accuracy can be improved with a better travel-tweet training dataset as well as a better travel category identification technique using machine learning. The travel categories can be increased to include items like sports venues, musical events, entertainment, etc. and thereby fine-tune the recommendations. The proposed model lists \u27n\u27 places of interest from each category in proportion to the travel category score generated by the model

Social Media and Forecasting Stock Price Change

The Stock Market is a big influence on both national and international economies. Stock prices are driven by a number of factors: industry performance, company news and performance, investor confidence, micro and macro economic factors like employment rates, wage rates, etc. Stock pricing trends can be gauged from the factors that drive it as well as from the stock\u27s historical performance. As fluctuations in stock prices become more volatile and unpredictable, forecasting models help reduce some of the randomness involved in investing and financial decision making. Users on social media platforms like twitter, StockTwits, and eToro discuss issues related to the stock market. Can the analysis of posts on StockTwits add value to the existing features of stock price predicting models? An existing model that uses twits as features was extended to include sentiment analysis of the text referenced by the URL in the twits to see if the model accuracy did improve. Initial results indicate that the addition of sentiment analysis of the text referenced by the URL does not improve the performance of the model when all twits for a given day are taken into account since the model only identifies the direction of change and not the degree of change. The stock prediction model achieves 65% accuracy compared to the base case accuracy of 44% and augmenting the model with sentiment analysis did not change the accuracy. The study highlights some interesting observations regarding users on the StockTwits social media platform and proposes the need for a domain specific sentiment analyzer in future work

Double power laws in income and wealth distributions

Close examination of wealth distributions reveal the existence of two distinct power law regimes. The Pareto exponents of the super-rich, identified for example in rich lists such as provided by Forbes are smaller than the Pareto exponents obtained for top earners in income data sets. Our extension of the Slanina model of wealth is able to reproduce these double power law features.Comment: 10 pages, 4 figures, conference APFA6, Lisboa, July 200

Is sex necessary?

Fungal sexual reproductive modes have markedly high diversity and plasticity, and asexual species have been hypothesized to arise frequently from sexual fungal species. A recent study on the red yeasts provides further support for the notion that sexual ancestors may give rise to shorter-lived asexual species. However, presumed asexual species may also be cryptically sexual, as revealed by other recent studies

The untapped Australasian diversity of astaxanthin-producing yeasts with biotechnological potential—Phaffia Australis sp. nov. and Phaffia tasmanica sp. nov.

PTDC/BIA-MIC/30785/2017 UIDB/04378/2020 NIH/NIAID R37 MERIT Award AI39115-23 NIH/NIAID R01 AI50113-16Phaffia is an orange-colored basidiomycetous yeast genus of the order Cystofilobasidiales that contains a single species, P. rhodozyma. This species is the only fungus known to produce the economically relevant carotenoid astaxanthin. Although Phaffia was originally found in the Northern hemisphere, its diversity in the southern part of the globe has been shown to be much greater. Here we analyze the genomes of two Australasian lineages that are markedly distinct from P. rhodozyma. The two divergent lineages were investigated within a comprehensive phylogenomic study of representatives of the Cystofilobasidiales that supported the recognition of two novel Phaffia species, for which we propose the names of P. australis sp. nov. and P. tasmanica sp. nov. Comparative genomics and other analyses confirmed that the two new species have the typical Phaffia hallmark—the six genes necessary for the biosynthesis of astaxanthin could be retrieved from the draft genome sequences, and this carotenoid was detected in culture extracts. In addition, the organization of the mating-type (MAT) loci is similar to that of P. rhodozyma, with synteny throughout most regions. Moreover, cases of trans-specific polymorphism involving pheromone receptor genes and pheromone precursor proteins in the three Phaffia species, together with their shared homothallism, provide additional support for their classification in a single genus.publishersversionpublishe

A novel interleukin-10 DNA mucosal delivery system attenuates intestinal inflammation in a mouse model

Inflammatory bowel diseases (IBD) describe a group of complex intestinal disorders characterized by inflammation in the gastrointestinal tract. Current treatments for IBD include the use of anti-inflammatory drugs; furthermore, recombinant lactic acid bacteria have been used as a therapeutic vehicle for anti-inflammatory agents in IBD models. Interleukin-10 (IL-10) is one of the most important anti-inflammatory cytokines; however, its oral administration is limited because it is quickly degraded in the gastrointestinal tract and systemic treatments have led to undesirable side effects. In this study, an engineered invasive strain of Lactococcus (L.) lactis producing Fibronectin Binding Protein A (FnBPA+), from Staphylococcus aureus capable of delivering, directly inside eukaryotic cells, an eukaryotic DNA expression vector containing the ORF coding for IL-10 of Mus musculus (pValac:il-10) was developed and its functionality was evaluated using in vitro and in vivo assays. Functionality of the plasmid and the invasive strain was demonstrated by transfection and invasiveness assays using cell cultures and in vivo in mice by fluorescence microscopy. TNBS inoculated mice that received this novel strain showed lower damage scores in their large intestines (at both macroscopic and microscopic levels), lower microbial translocation to liver, and increased anti-inflammatory/pro-inflammatory cytokine ratios compared to mice that received L. lactis FnBPA+ without the pValac:il-10 plasmid. The effectiveness was demonstrated of this novel DNA delivery therapeutic strategy in the prevention of inflammation using a murine model of colitis.Fil: del Carmen, Silvina Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán. Centro de Referencia para Lactobacilos (i); ArgentinaFil: Zurita-Turk, Meritxell. Universidade Federal Do Minas Gerais; Brasil;Fil: Alvarenga Lima, Fernanda. Universidade Federal Do Minas Gerais; Brasil;Fil: Coelho Dos Santos, Janete. No especifíca;Fil: Leclercq, Sophie Yvette. No especifíca;Fil: Chatel, Jean-Marc. Institut National de la Recherche Agronomique; Francia;Fil: Azevedo, Vasco. Universidade Federal Do Minas Gerais; Brasil;Fil: de Moreno, Maria Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán. Centro de Referencia para Lactobacilos (i); ArgentinaFil: Miyoshi, Anderson. Universidade Federal Do Minas Gerais; Brasil;Fil: Leblanc, Jean Guy Joseph. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán. Centro de Referencia para Lactobacilos (i); Argentina. Universidad Nacional de Tucuman. Facultad de Medicina. Departamento de Investigacion. Catedra de Metodologia de la Invest.cientifica; Argentin

Ancient bears provide insights into Pleistocene ice age refugia in Southeast Alaska

During the Late Pleistocene, major parts of North America were periodically covered by ice sheets. However, there are still questions about whether ice-free refugia were present in the Alexander Archipelago along the Southeast (SE) Alaska coast during the last glacial maximum (LGM). Numerous subfossils have been recovered from caves in SE Alaska, including American black (Ursus americanus) and brown (U. arctos) bears, which today are found in the Alexander Archipelago but are genetically distinct from mainland bear populations. Hence, these bear species offer an ideal system to investigate long-term occupation, potential refugial survival and lineage turnover. Here, we present genetic analyses based on 99 new complete mitochondrial genomes from ancient and modern brown and black bears spanning the last ~45,000 years. Black bears form two SE Alaskan subclades, one preglacial and another postglacial, that diverged \u3e100,000 years ago. All postglacial ancient brown bears are closely related to modern brown bears in the archipelago, while a single preglacial brown bear is found in a distantly related clade. A hiatus in the bear subfossil record around the LGM and the deep split of their pre-and postglacial subclades fail to support a hypothesis of continuous occupancy in SE Alaska throughout the LGM for either species. Our results are consistent with an absence of refugia along the SE Alaska coast, but indicate that vegetation quickly expanded after deglaciation, allowing bears to recolonize the area after a short-lived LGM peak

Statistical and semi-dynamical road traffic noise models comparison with field measurements

The need for road traffic noise monitoring is growing in urban areas due to the growth of vehicles number and to the consequent increase of risk for human health. Noise measurements cannot be performed everywhere, or even in a large number of sites, because of high costs and time consumption. For this reasons, Road Traffic Noise predictive Models (RTNMs) can be implemented to estimate the noise levels at any distance, knowing certain parameters needed as input of the RTNM. In this paper, the main statistical RTNMs are presented, together with the implementation of two innovative and advanced models: the EU suggested model (CNOSSOS-EU) and a research model presented by Quartieri et al. (2010). These models will be compared with noise measurements performed in different sites and with different traffic conditions, in order to avoid bias from geometry or other features of the area under study. The main conclusion is that the application of innovative models and the inclusion of dynamical information about traffic flow, will lead to better results with respect to statistical models

Was There a National Labor Market at the End of the Nineteenth Century? New Evidence on Earnings in Manufacturing

DOI:10.1017/S002205070001696XAverage annual earnings calculated from the census of manufactures are used to extend previous research on labor market integration in the United States. In contrast to earlier research examining occupational wage rates, census average earnings indicate that a well-integrated labor market had emerged in the Northeast and North Central regions as early as 1879. They also reveal substantial convergence within the South Atlantic and South Central regions, suggesting the emergence of a unified southern labor market. Large and persistent North-South differentials indicate, however, that a unified national labor market did not develop before World War I