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Twitter is a microblog on which users can post updates (tweets) to friends (followers). Sentiment Analysis has become an important field of study in this environment due to the sheer number of tweets available, which allows several applications such as monitoring of brands and products, forecasting political campaigns and even applications in the financial market. One of the great challenges in analyzing feelings is in the creation of predictive models that are able to classify tweets as positive, negative or neutral. The main models are based on natural language processing and machine learning. Given this context, this article aims to compare the performance of the following methods of sentiment analysis: machine learning, lexical dictionaries, emoticons, part-of-speech, ensembles and word embeddings. The objective is to indicate to the reader, among such approaches, which best suits the particularities of the tweets. The experiments were applied to two databases, Sanders and HCR. In both datasets, the procedures that obtained the best results were based on lexical dictionary and word embeddings with 79.09% and 79.36% of accuracy, respectively, for Sanders. While for HCR the result was 69.11% and 68.22% accuracy, respectively.

Machine learning techniques can be used to automatically infer information that is not available from large volumes of data. Social networks have been gaining popularity and turning into an important sources of data for an application of computer techniques. The goal of this work is to study how well preprocessing techniques, feature sets and classifiers work on the task of automatic bullying trace detection, as well as the role of the author of the text on the reported episode.We focused on social networks texts written in Brazilian Portuguese. Several different classifiers and attribute sets were studied and compared, in order to identify which one is the most appropriate for this task. Among all tested configurations, the best results was found when using the largest trainning set transformed into a feature set made of unigrams and bigrams in conjunction with SVM with an RBF kernel

We consider the problem of estimating vector-valued variables from noisy “relative” measurements. The measurement model can be expressed in terms of a graph, whose nodes correspond to the variables being estimated and the edges to noisy measurements of the difference between the two variables. This type of measurement model appears in several sensor network problems, such as sensor localization and time synchronization. We consider the optimal estimate for the unknown variables obtained by applying the classical Best Linear Unbiased Estimator, which achieves the minimum variance among all linear unbiased estimators.We propose a new algorithm to compute the optimal estimate in an iterative manner, the Overlapping Subgraph Estimator algorithm. The algorithm is distributed, asynchronous, robust to temporary communication failures, and is guaranteed to converges to the optimal estimate even with temporary communication failures. Simulations for a realistic example show that the algorithm can reduce energy consumption by a factor of two compared to previous algorithms, while achieving the same accuracy.

Mário M Oliveira, Luisa M Branco, Ana Galrinho, Nogueira da Silva, Pedro S Cunha, Bruno Valente, Joana Feliciano, Ricardo Pimenta, Ana Sofia Delgado, Rui Cruz Ferreira Santa Marta Hospital, Lisbon, Portugal Background: Inappropriate settings of atrioventricular (AV) and ventriculo-ventricular (VV) intervals can be one of the factors impacting response to cardiac resynchronization therapy (CRT). Optimal concordance of AV and VV intervals between echocardiographic-based assessment and a device-based automatic programming with a hemodynamic sensor was investigated, together with left ventricle (LV) reverse remodeling after 6 months of regular automatic device-based optimization.Methods: We evaluated blindly 30 systematic echocardiographic examinations during 6 months in 17 patients (12 men, 64±10 years, in sinus rhythm and New York Heart Association class III; 76% with non-ischemic dilated cardiomyopathy, LV ejection fraction [LVEF] 40%). A statistically significant increase in LVEF was observed between baseline and 6 months post implant (P

A teacher, warned not to put anything in the individualized education program that will cost the school district money, is urged to go to the supervisor, file a noncompliance charge with the state education agency, or alert a third party to take that action. (CL)

The author discusses the implications of the Rowley case in which an 8-year-old deaf child requested the school district to provide her with a sign language interpreter. (SW)

The author addresses proposals submitted by the Department of Education to change the regulations of P.L. 94-142, the Education for All Handicapped Children Act. Possible consequences of the proposed changes are cited. The author concludes that the regulation changes will not pass scrutiny of Congress, the courts, or the public. (CL)

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The article discusses a study which described the main strengths and weaknesses of the French surveillance system for Salmonella based on a national system for human cases and animal reservoirs. Different approaches were compared using grid analysis. The study showed that passive systems are useful for detecting emerging or unusual events and for early warning of outbreaks, and for producing time series of cases. It is stated that active surveillance data are key elements in the application of risk analysis.

The New Zealand Black X New Zealand White F1 [(NZB/NZW) F1] mouse develops an autoimmune condition resembling aspects of human systemic lupus erythematosus (SLE). We investigated the effects of a novel prophylactic thoraco-abdominal gamma irradiation protocol on the onset and evolution of lupus in these animals. Survival of irradiated mice was higher when compared with nonirradiated mice. Kidney lesions were milder and autoantibody levels were lower in irradiated mice. To identify possible mechanisms involved in the radiation-induced improvement of disease, distinct components of humoral and cellular immune responses were evaluated. Because B-1 cells are known to be involved in various autoimmune diseases, we investigated the participation of these cells in SLE progression. Unexpectedly, B-1 cells were not depleted in (NZB/NZW) F1, even after several rounds of irradiation. No alterations were found in viability and physiology of B-1 cells in SLE animals with the exception of constitutive overexpression of the anti-apoptotic molecule Bcl-2, which may account for the observed radioresistance. Thus, a role for B-1 cells in murine SLE cannot be excluded, since the irradiation protocol did not effectively eliminate these cells. Additionally, we demonstrate a marked delay in the ability of splenocytes to repopulate the spleen after irradiation in (NZB/NZW) F1, in contrast to leucocytes in other cellular compartments. The implications of these findings for the fate of SLE in this model are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Medical Mycology / Journal de Mycologie Médicale is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)