Stock price change prediction using news text mining

Along with the advent of the Internet as a new way of propagating news in a digital format, came the need to understand and transform this data into information. This work presents a computational framework that aims to predict the changes of stock prices along the day, given the occurrence of news articles related to the companies listed in the Down Jones Index. For this task, an automated process that gathers, cleans, labels, classifies, and simulates investments was developed. This process integrates the existing data mining and text algorithms, with the proposal of new techniques of alignment between news articles and stock prices, pre-processing, and classifier ensemble. The result of experiments in terms of classification measures and the Cumulative Return obtained through investment simulation outperformed the other results found after an extensive review in the related literature. This work also argues that the classification measure of Accuracy and incorrect use of cross validation technique have too few to contribute in terms of investment recommendation for financial market. Altogether, the developed methodology and results contribute with the state of art in this emerging research field, demonstrating that the correct use of text mining techniques is an applicable alternative to predict stock price movements in the financial market.Com o advento da Internet como um meio de propagação de notícias em formato digital, veio a necessidade de entender e transformar esses dados em informação. Este trabalho tem como objetivo apresentar um processo computacional para predição de preços de ações ao longo do dia, dada a ocorrência de notícias relacionadas às companhias listadas no índice Down Jones. Para esta tarefa, um processo automatizado que coleta, limpa, rotula, classifica e simula investimentos foi desenvolvido. Este processo integra algoritmos de mineração de dados e textos já existentes, com novas técnicas de alinhamento entre notícias e preços de ações, pré-processamento, e assembleia de classificadores. Os resultados dos experimentos em termos de medidas de classificação e o retorno acumulado obtido através de simulação de investimentos foram maiores do que outros resultados encontrados após uma extensa revisão da literatura. Este trabalho também discute que a acurácia como medida de classificação, e a incorreta utilização da técnica de validação cruzada, têm muito pouco a contribuir em termos de recomendação de investimentos no mercado financeiro. Ao todo, a metodologia desenvolvida e resultados contribuem com o estado da arte nesta área de pesquisa emergente, demonstrando que o uso correto de técnicas de mineração de dados e texto é uma alternativa aplicável para a predição de movimentos no mercado financeiro

Conditional discriminations following consistent matching-to-sample training of complex stimuli

The aim of this study was to verify the formation of conditional discriminations through a consistent matching training procedure with complex sample stimuli. Four university students were trained in the formation of AF, BE e DC conditional relations using simple stimuli and explicit differential reinforcement (Phase 1). They were subjected to consistent matching-to-sample training on the AB-E/F and AD-C/F relations involving complex sample stimuli (Phase 2). These participants were given the transitive and equivalent tests. Training trials were then "dismembered" (simplified) from AB-E/F, and AD-C/F sequences to AB-E; AB-F; AD-C; AD-F sequences, and the students were again tested for transitivity and equivalence (Phase 3). All participants reached the learning criterion. Two of them demonstrated the emergent relations tested before and after simplified training, and demonstrated response stability. These results indicated that the dismembered procedure was appropriate for reversing the restricted stimulus control.O objetivo do presente estudo foi verificar a formação de discriminações condicionais através de um procedimento de treino por pareamento consistente de estímulos complexos. Na Fase 1, com quatro universitários, foi realizado o treino AF, BE e DC envolvendo estímulos modelos e de comparação simples e reforçamento diferencial explícito. Na Fase 2, houve o treino AB-E/F e AD-C/F, com modelos complexos e estímulos de comparação simples num formato de pareamento consistente. Após isso, os participantes foram expostos aos testes de transitividade e de equivalência. Na Fase 3, os treinos AB-E/F e AD-C/F foram desmembrados (simplificados) em AB-E; AB-F; AD-C; AD-F, e reaplicados os mesmos testes. Todos os participantes formaram as relações condicionais e dois deles formaram as relações emergentes, anterior e posterior ao desmembramento dos treinos. Os resultados sugerem que esse desmembramento foi um procedimento adequado para reverter o controle restrito de estímulo

Encephalic Meningioma in Dogs

Background: Meningioma is the most common brain tumor in dogs. These extra-axial tumors originate in one of the meninges, and arachnoid is the most common. Several retrospective studies of brain tumors are found in the international literature. However there are few researches in the national literature. The purpose of this study is to report twelve dogswith brain meningioma. The breed, gender, age, neurological signs, the brain location, the clinical evolution, the tumor classifcation and diagnostics tests were investigated.Cases: Twelve dogs were attended at Veterinary Hospital of Santa Maria University: six mixed-breeds; four Boxer; a Dachs hund; and a Poodle. The age ranged from eight to 14 years, with average of ten years and nine months old. The clinical signs observed were generalized seizures (9/12); behavioral changes (6/12); walk in circle (5/12); swallowing diffculty (2/12 [16%]); hypermetria (2/12); central vestibular syndrome (1/12); and amaurosis (1/12). The presumptive diagnosis was brain neoplasm in all dogs. Six dogs were underwent symptomatic treatment with corticosteroids and anticonvulsants; two dogs were underwent corticosteroids; and four were euthanized without performing treatment. After starting treatment,four dogs (50%) showed clinical improvement in the frst week, however, the clinical signs worsened after two weeks. The thalamus-cortex region was affected in seven cases (59%), followed by cerebellar-pontine region (25%), brainstem (8%) and cerebellum (8%). In the histological classifcation of meningiomas, the meningothelial variant was observed in six dogs, three psammomatous, two transitional and a fbroblast.Discussion: The average age of initiation of clinical signs was ten years and nine months, similar result found in a large study about brain tumor. Female dogs were most affected (n = 8), although some authors did not report sexual predis position. The neurological signs of dogs with brain meningiomas occur through adjacent structures compression, directinvasion of tissues, interruption of circulation, edema, inflammation and necrosis. The thalamus-cortex region was the most affected and the seizures were the most common clinical signs observed in dogs, according to the international literature. The meningiomas canine are histologically classifed into two groups: benign tumors (meningothelial, fbroblast,transitional, psammomatous, angiomatous, papillary, myxoid and granular cells); and malignant tumors (anaplastic). The meningothelial variant was found most frequently in this stud (50%), according to the others authors. The clinical course of time was determined from the onset of signs found in neurological examination until the time of death or euthanasia of dogs, being progressive in all patients. In this study, encephalic neoplasms showed slow evolution of signals between fve to 180 days (mean 58 days). This time is longer compared to other study in which the mean survival of 86 dogs was 30 days. In the present study, there was only symptomatic treatment with corticosteroids and/or anticonvulsant. The conclusion of this study is that brain meningioma is a common tumor; occur in adult and older dogs of different breeds; the clinical signs more frequent were seizures, behavioral changes and walk in circle to the side of the lesion. The palliative treatment with corticosteroids and anticonvulsants may be effcient in controlling the clinical signs, however the long-term prognosis is adverse.Keywords: neoplasm, brain, neurology, dog

HIV Infection and Oral Manifestations: An Update

Human immunodeficiency virus (HIV) causes a complete depletion of the immune system; it has been a major health issue around the world since the 1980s, and due to the reduction of CD4+ T lymphocytes levels, it can trigger various opportunistic infections. Oral lesions are usually accurate indicators of immunosuppression because these oral manifestations may occur as a result of the compromised immune system caused by HIV infection; therefore, oral lesions might be initial and common clinical features in people living with HIV. So, it is necessary to evaluate and understand the mechanism, prevalence, and risk factors of oral lesions to avoid the increase morbidity among those with oral diseases

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus Kjøller, Tamir Klein, Michael Kleyer, Jitka Klimešová, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan Llusià, Madelon Lohbeck, Álvaro López-García, Gabriela Lopez-Gonzalez, Zdeňka Lososová, Frédérique Louault, Balázs A. Lukács, Petr Lukeš, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki Mäkelä, Harri Mäkinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina Martínez-Garza, Jordi Martínez-Vilalta, Tereza Mašková, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, Céline Meredieu, Julie Messier, Ilona Mészáros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila Molnár V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka Moravcová, Alvaro Moreno-Martínez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina Müller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis Pärtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, Valério D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr Pyšek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime Réjou-Méchain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja Rüger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-García, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun Siebenkäs, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, Grégory Sonnier, Mia Vedel Sørensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana Svitková, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, Rubén Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, Lubomír Tichý, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, Péter Török, Tonantzin Tarin, José M. Torres-Ruiz, Béla Tóthmérész, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim André Vanselow, Angelica Vårhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime Villacís, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, Kátia Janaina Zanini, Amy E. Zanne, David Zelený, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia Ziemińska, Chad R. Zirbel, Georg Zizka, Irié Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et Société'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Choquet integral parameter optimization for a fusion system devoted to image interpretation

International audienceParameter adjustment of a fusion system for 3D image interpretation is often a difficult task that is emphasized by the non-understandability of the parameters by the end-users. Moreover, such fusion systems are complex because they involve a complete information treatment chain (from the information extraction to the decision). The sub-parts of the system concern also different scientific areas which add some additional difficulties. Some parameters cannot be easily set empirically and their adjustments are made by trials and errors. This paper studies an optimization of a generalized Choquet Integral parameters by means of genetic algorithms. Fuzzy measures are first learnt thanks to the reference data given by experts and then the best importance coefficients are searched around the initial ones. The approach is illustrated on a cooperative fusion system based on Choquet Integral and devoted to 3D image interpretation

Estimación del consumo de combustible y las emisiones de un vehículo de servicio pesado con mezcla diésel - nano aditivo en condiciones reales de conducción.

En las ciudades del Ecuador la contaminación del aire producto de la combustión de hidrocarburos, en los últimos años ha alcanzado niveles alarmantes, entre las causas de este problema están su propio emplazamiento al estar situadas a alturas considerables como es el caso del Distrito Metropolitano de Quito que se encuentra a una altura promedio de 2850 m. En la presente investigación se realizan mediciones de consumo de combustible y emisiones contaminantes en un vehículo de servicio pesado bajo condiciones reales de conducción. El propósito es evaluar desempeño del motor Diesel en cuanto a sus emisiones de CO2 en % V, CO en % V, HC en ppm, NOx en ppm, material particulado (MP2.5) en % mg/m3 y el consumo de combustible en Km/galón al utilizar una mezcla de combustible diésel y nano aditivo a base a óxido de cerio. Para el desarrollo del experimento se estableció un ciclo de ruta de 27.41 Km considerando las características de circulación de este tipo de vehículos pesados en la ciudad, el punto más alto está ubicado a 3064 m y el punto a menor altura está a 2525 m, el vehículo es operado con una carga al 70% del máximo de su peso vehicular combinado permitido por las autoridades de regulación y control. Se realizan 5 repeticiones por cada combustible, diésel base y mezcla diésel – nano aditivo para una concentración de 250 ppm en el diésel. Las mediciones se realizan con equipos portátiles AXION y MPM-4 instalados en el vehículo de pruebas que permiten la obtención de datos segundo a segundo. Los resultados obtenidos fueron analizados estadísticamente mediante el empleo de gráficas de control, del experimento de obtienen los siguientes resultados preliminares una reducción del material particulado del 27,1% para la mezcla combustible, aumento de NOx de 24,9% y HC de 24,2% respectivamente en comparación con diésel base. En cuanto al consumo de combustible se obtiene una reducción del 1% para la mezcla combustible, en relación al diésel base