Towards measuring the complexity of introducing semantics into a company

The Semantics Difficulty Model (SDM) is a model that measures the difficult of introducing semantics technology into a company. SDM manages three descriptions of stages, which we will refer to as ?snapshots?: a company semantic snapshot, data snapshot and semantic application snapshot. Understanding a priory the complexity of introducing semantics into a company is important because it allows the organization to take early decisions, thus saving time and money, mitigating risks and improving innovation, time to market and productivity. SDM works by measuring the distance between each initial snapshot and its reference models (the company semantic snapshots reference model, data snapshots reference model, and the semantic application snapshots reference model) with Euclidian distances. The difficulty level will be "not at all difficult" when the distance is small, and becomes "extremely difficult" when the the distance is large. SDM has been tested experimentally with 2000 simulated companies with arrangements and several initial stages. The output is measured by five linguistic values: "not at all difficult, slightly difficult, averagely difficult, very difficult and extremely difficult". As the preliminary results of our SDM simulation model indicate, transforming a search application into integrated data from different sources with semantics is a "slightly difficult", in contrast with data and opinion extraction applications for which it is "very difficult"

Is the polarity of content producers strongly influenced by the results of the event?

This paper presents an approach to compare two types of data, subjective data (Polarity of Pan American Games 2011 event by country) and objective data (the number of medals won by each participating country), based on the Pearson corre- lation. When dealing with events described by people, knowledge acquisition is difficult because their structure is heterogeneous and subjective. A first step towards knowing the polarity of the information provided by people consists in automatically classifying the posts into clusters according to their polarity. The authors carried out a set of experiments using a corpus that consists of 5600 posts extracted from 168 Internet resources related to a specific event: the 2011 Pan American games. The approach is based on four components: a crawler, a filter, a synthesizer and a polarity analyzer. The PanAmerican approach automatically classifies the polarity of the event into clusters with the following results: 588 positive, 336 neutral, and 76 negative. Our work found out that the polarity of the content produced was strongly influenced by the results of the event with a correlation of .74. Thus, it is possible to conclude that the polarity of content is strongly affected by the results of the event. Finally, the accuracy of the PanAmerican approach is: .87, .90, and .80 according to the precision of the three classes of polarity evaluated

The unified sentiment lexicon using GPUs

This approach aims at aligning, unifying and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. A sentiment lexicon is a critical and essential resource for tagging subjective corpora on the web or elsewhere. In many situations, the multilingual property of the sentiment lexicon is important because the writer is using two languages alternately in the same text, message or post. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and the UnifiedMetrics procedure for CPU and GPU, respectively

Towards a unified sentiment lexicon based on graphics processing units

This paper presents an approach to create what we have called a Unified Sentiment Lexicon (USL). This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral {P, Z, N} depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95.430 lexical entries, out of which there are 35.201 considered to be positive, 22.029 negative, and 38.200 neutral. Finally, the runtime was 10 minutes for 95.430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times

Proyecto de repoblacion del termino municipal de La Mierla y coreccion de la rambla de Valdemierla

El término municipal de La Mierla que se propone repoblar, pertenece al partido judicial de Cogolludo, provincia de Guadalajara, y está limitado al Norte por los términos de Sacedoncillo y por el de Muriel, al Este por este mismo y por el de Beleña y al Oeste por éste último y por los de Puebla de Valles y Retiendas, marcando la separación del término que nos ocupa con el citado de Puebla de Valles, la carretera de Tamajón a Guadalajara y parcialmente también con los de Puebla de Belefta y Retiendas

The Spanish Travel Subjective Lexicon (STSL).

This paper presents a proposal for a recognition model for the appraisal value of sentences. It is based on splitting the text into independent sentences (full stops) and then analysing the appraisal elements contained in each sentence according to the previous value in the appraisal lexicon. In this lexicon, positive words are assigned a positive coefficient (+1) and negative words a negative coefficient (-1). We take into account word such as ?too?, ?little? (when it is not ?a bit?), ?less?, and ?nothing? than can modify the polarity degree of lexical unit when appear in the nearby environment. If any of these elements are present, then the previous coefficient will be multiplied by (-1), that is, they will change their sign. Our results show a nearly theoretical effectiveness of 90%, despite not achieving the recognition (or misrecognition) of implicit elements. These elements represent approximately 4% of the total of sentences analysed for appraisal and include the errors in the recognition of coordinated sentences. On the one hand, we found that 3.6 % of the sentences could not be recognized because they use different connectors than those included in the model; on the other hand, we found that in 8.6% of the sentences despite using some of the described connectors could not be applied the rules we have developed. The percentage relative to the whole group of appraisal sentences in the corpus was approximately of 5%

Increased expression of cytokines, soluble cytokine receptors, soluble apoptosis ligand and apoptosis in dengue

AbstractSeveral studies have been performed to determine biomarkers that define the risk factors to developing severe forms of dengue. In this study, the levels of TNF-α, IL-6, IL-1, IL-17, soluble interleukin-1 receptor like 1 protein (sST2), soluble TNF-related apoptosis-inducing ligand (sTRAIL), IL-12 and soluble receptors for TNF (sTNF-RI and sTNF-RII) were determined by ELISA in dengue patients and monocyte/macrophage cultures. Dengue was classified as dengue without warning symptoms (DNWS), with warning symptoms (DWWS) and severe dengue (SD). High values of IL-6, sTNFRI, sTNFRII and sST2 were observed in DWWS and/or SD and IL-12 and sTRAIL in DNWS. TNF-α and IL-17 were increased not associated to the disease severity. High production of TNF-α, IL-1β, IL-12, IL-17, sST2 and sTRAIL and apoptosis expression were observed in dengue monocyte/macrophage cultures. This study shows that beneficial or deleterious biomarkers can be present in dengue regardless the disease severity and that monocytes may be in part the source of studied molecules

Dysfunctional Immune Response in Acute-on-Chronic Liver Failure: It Takes Two to Tango

Acute-on-chronic liver failure (ACLF) is characterized by the acute decompensation of cirrhosis associated with organ failure and high short-term mortality. The key event in the pathogenesis is a dysfunctional immune response arising from exacerbation of the two main immunological alterations already present in cirrhosis: systemic inflammation and immune cell paralysis. High-grade systemic inflammation due to predominant activation and dysregulation of the innate immune response leads to the massive release of cytokines. Recognition of acutely increased pathogen and damage-associated molecular patterns by specific receptors underlies its pathogenesis and contributes to tissue damage and organ failure. In addition, an inappropriate compensatory anti-inflammatory response over the course of ACLF, along with the exhaustion and dysfunction of both the innate and adaptive immune systems, leads to functional immune cell paralysis. This entails a high risk of infection and contributes to a poor prognosis. Therapeutic approaches seeking to counteract the immune alterations present in ACLF are currently under investigation

Histopathological study of JNK in venous wall of patients with chronic venous insufficiency related to osteogenesis process

Chronic venous insufficiency (CVI) is one of the most common vascular pathologies worldwide. One of the risk factors for the development of CVI is aging, which is why it is related to senile changes. The main trigger of the changes that occur in the venous walls in CVI is blood flow reflux, which produces increased hydrostatic pressure, leading to valve incompetence. The cellular response is one of the fundamental processes in vascular diseases, causing the activation of cell signalling pathways such as c-Jun N-terminal kinase (JNK). Metabolic changes and calcifications occur in vascular pathology as a result of pathophysiological processes. The aim of this study was to determine the expression of JNK in venous disease and its relationship with the role played by the molecules involved in the osteogenic processes in venous tissue calcification. This was a cross-sectional study that analyzed the greater saphenous vein wall in 110 patients with (R) and without venous reflux (NR), classified according to age. Histopathological techniques were used and protein expression was analysed using immunohistochemistry techniques for JNK and markers of osteogenesis (RUNX2, osteocalcin (OCN), osteopontin (OPN)). Significantly increased JNK, RUNX2, OCN, OPN and pigment epithelium-derived factor (PEDF) protein expression and the presence of osseous metaplasia and amorphous calcification were observed in younger patients (<50 years) with venous reflux. This study shows for the first time the existence of an osteogenesis process related to the expression of JNK in the venous wall.This study (FIS-PI18/00912) was supported by the Instituto de Salud Carlos III (Plan Estatal de I+D+i 2013-2016) and cofinanced by the European Development Regional Fund ‘‘A way to achieve Europe’’ (ERDF) and B2017/BMD-3804 MITIC-C