An improved deep learning-based approach for sentiment mining

The sentiment mining approaches can typically be divided into lexicon and machine learning approaches. Recently there are an increasing number of approaches which combine both to improve the performance when used separately. However, this still lacks contextual understanding which led to the introduction of deep learning approaches which allows for semantic compositionality over a sentiment treebank. This paper enhances the deep learning approach with semantic lexicon so that scores can be computed in-stead merely nominal classification. Besides, neutral classification is also improved. Results suggest that the approach outperforms its original

Arch dimensional changes following orthodontic treatment with extraction of four first premolars

BACKGROUND AND AIM: Tooth extraction as a part of orthodontic treatment plan to create space for leveling and aligning teeth or causing tooth movement leads to changes in arch width and length. The outcome of these changes is important for the clinicians and affects the treatment and retention plans. Despite some previous studies, data in this regard are still scarce and further investigation is required on this subject. The purpose of this study was to evaluate dental arch dimensional changes following four first premolars extraction orthodontic treatment. METHODS: In this study, 100 pairs of dental casts and respective patient records that fulfilled the inclusion criteria were randomly selected from the archives of the Department of Orthodontics, School of Dentistry in Shahid Beheshti University of Medical Sciences, Tehran, Iran. Length and width of dental arch were measured on the initial and final casts of patients using a digital caliper with 0.1 mm precision. The mean, standard deviation (SD) and standard error of variables were determined, and the data were analyzed using SPSS software. Paired t-test was applied to compare changes before and after treatment. RESULTS: The obtained results showed that the maxillary and mandibular inter-canine widths significantly increased as the result of fixed appliance therapy with the extraction of four first premolars. The arch width at the second premolar and molar at mesiobuccal cusp tip and distobuccal cusp tip regions in the maxilla and mandible showed a significant reduction (P < 0.001). In this study, arch length at different points was measured. In the maxilla, the incisor-canine distance in both quadrants experienced a significant increase (P < 0.001). Furthermore, the canine-molar distance and the incisor-molar distance in both quadrants and the total arch length showed a significant reduction (P < 0.001). In the mandible, the incisor-canine distance in the right quadrant significantly increased (P < 0.050), but the reduction in the incisor-canine distance in the left quadrant was not statistically significant. Moreover, the canine-molar and the incisormolar distance in both quadrants and the total arch length all decreased significantly (P < 0.001). CONCLUSION: Orthodontic treatment with extraction of four first premolars significantly increased the inter-canine width and incisor-canine distance in both jaws; but, the inter-premolar and inter-molar widths, canine-molar distance, incisor-molar distance, and total arch length significantly decreased. KEYWORDS: Dental Arch Length; Dental Arch Width; Extraction Orthodontic Treatmen

A knowledge audit model for requirement elicitation: a case study to assess knowledge in requirement elicitation

This paper aims to develop a knowledge audit (KA) model with the focus on knowledge assessment in the requirements elicitation process (REP) to allay the problems of REP regarding knowledge communication. The principal problems with REP are knowledge conflict and the failure to mention a variety of knowledge and requirements changes. Despite of many existing studies relating to KA, inadequate effort has been directed towards investigating the full part played by the KA process in REP. The purpose of this paper is to bridge this gap using a software prototype that uses the KA model in the REP. This study proposes a KA model using an iterative triangulation method. The proposed model is validated through a case study by using a software prototype developed based on the proposed KA model to see if this KA model is effective for software developers in REP by improving the completeness, correctness, and understandability of the elicited requirements knowledge. Research findings are based on responses of 40 respondents from software development organizations. The results of case study confirmed the effectiveness of KA model for REP with respect to completeness, correctness, and understandability. This research answers the call to assess knowledge in REP by developing a KA model and prototype to fill the existing gap in this area. Overall, a KA model for REP is introduced and validated to identify and assess knowledge that supports knowledge communication in REP

Self-adaptive Based Model for Ambiguity Resolution of The Linked Data Query for Big Data Analytics

Integration of heterogeneous data sources is a crucial step in big data analytics, although it creates ambiguity issues during mapping between the sources due to the variation in the query terms, data structure and granularity conflicts. However, there are limited researches on effective big data integration to address the ambiguity issue for big data analytics. This paper introduces a self-adaptive model for big data integration by exploiting the data structure during querying in order to mitigate and resolve ambiguities. An assessment of a preliminary work on the Geography and Quran dataset is reported to illustrate the feasibility of the proposed model that motivates future work such as solving complex query

Kansei design customization based on personality modelling

Product designers are obliged to meet the user’s desires; both implicit and explicit ones. Identifying the implicit needs is a complicated task. The methods of Kansei Engineering (KE) have aided in this process by using analysis of human emotions. KE starts by detecting the feelings and emotions towards a developing product and ends in giving product designs that satisfy users. However, can a single design satisfy all users? How can customization be done without losing any Kansei? Knowing the different needs and types of emotional expression between human personalities, this paper explores how modifications in the KE Framework can capture these differences and apply them to the final designs. The results of this process will be a set of customized designs for groups of similar personalities, knowing each design has captured the different interests of those groups

A model for client recommendation to a desktop grid server

A vast amount of idle computational power of desktop computers could be utilized throughout desktop grids. For an appropriate utilization, the scheduler, needs to determine clients which are best suited to deliver assigned jobs in time. Diversity of hosts (i.e. OS, hardware and network specifications) and intermittent availability of resources are known issues which complicate the schedulers work. As a solution to this problem, a client–server model consisting two modules for a desktop grid middleware is discussed: a module to forecast machine resource availability in the client side and a module in the server side that recommends clients to the scheduler that are the nearest to job expectations. Historic data, time-series analyses and machine learning are used for this purpose in the modules

Sleep-Related Falling Out of Bed in Parkinson's Disease

Background and purposeSleep-related falling out of bed (SFOB), with its potential for significant injury, has not been a strong focus of investigation in Parkinson's disease (PD) to date. We describe the demographic and clinical characteristics of PD patients with and without SFOB.MethodsWe performed a retrospective analysis of 50 consecutive PD patients, who completed an REM sleep behavior disorder screening questionnaire (RBDSQ), questionnaires to assess for RBD clinical mimickers and questions about SFOB and resulting injuries. Determination of high risk for RBD was based on an RBDSQ score of 5 or greater.ResultsThirteen patients reported history of SFOB (26%). Visual hallucinations, sleep-related injury, quetiapine and amantadine use were more common in those patients reporting SFOB. Twenty-two patients (44%) fulfilled criteria for high risk for RBD, 12 of which (55%) reported SFOB. Five patients reported injuries related to SFOB. SFOB patients had higher RBDSQ scores than non-SFOB patients (8.2±3.0 vs. 3.3±2.0, p&lt;0.01). For every one unit increase in RBDSQ score, the likelihood of SFOB increased two-fold (OR 2.4, 95% CI 1.3-4.2, p&lt;0.003).ConclusionsSFOB may be a clinical marker of RBD in PD and should prompt confirmatory polysomnography and pharmacologic treatment to avoid imminent injury. Larger prospective studies are needed to identify risk factors for initial and recurrent SFOB in PD

Pathogenic Bacillus anthracis in the progressive gene losses and gains in adaptive evolution

Background: Sequence mutations represent a driving force of adaptive evolution in bacterial pathogens. It is especially evident in reductive genome evolution where bacteria underwent lifestyles shifting from a free-living to a strictly intracellular or host-depending life. It resulted in loss of function mutations and/or the acquisition of virulence gene clusters. Bacillus anthracis shares a common soil bacterial ancestor with its closely related bacillus species but is the only obligate, causative agent of inhalation anthrax within the genus Bacillus. The anthrax-causing Bacillus anthracis experienced the similar lifestyle changes. We thus hypothesized that the bacterial pathogen would follow a compatible evolution path. Results: In this study, a cluster-based evolution scheme was devised to analyze genes that are gained by or lost from B. anthracis. The study detected gene losses/gains at two separate evolutionary stages. The stage I is when B. anthracis and its sister species within the Bacillus cereus group diverged from other species in genus Bacillus. The stage II is when B. anthracis differentiated from its two closest relatives: B. cereus and B. thuringiensis. Many genes gained at these stages are homologues of known pathogenic factors such those for internalin, B. anthracis-specific toxins and large groups of surface proteins and lipoproteins. Conclusion: The analysis presented here allowed us to portray a progressive evolutionary process during the lifestyle shift of B. anthracis, thus providing new insights into how B. anthracis had evolved and bore a promise of finding drug and vaccine targets for this strategically important pathogen

Age- and gender-specific risk of death after first hospitalization for heart failure

<p>Abstract</p> <p>Background</p> <p>Hospitalization for heart failure (HF) is associated with high-in-hospital and short- and long-term post discharge mortality. Age and gender are important predictors of mortality in hospitalized HF patients. However, studies assessing short- and long-term risk of death stratified by age and gender are scarce.</p> <p>Methods</p> <p>A nationwide cohort was identified (ICD-9 codes 402, 428) and followed through linkage of national registries. The crude 28-day, 1-year and 5-year mortality was computed by age and gender. Cox regression models were used for each period to study sex differences adjusting for potential confounders (age and comorbidities).</p> <p>Results</p> <p>14,529 men, mean age 74 ± 11 years and 14,524 women, mean age 78 ± 11 years were identified. Mortality risk after admission for HF increased with age and the risk of death was higher among men than women. Hazard ratio's (men versus women and adjusted for age and co-morbidity) were 1.21 (95%CI 1.14 to 1.28), 1.26 (95% CI 1.21 to 1.31), and 1.28 (95%CI 1.24 to 1.31) for 28 days, 1 year and 5 years mortality, respectively.</p> <p>Conclusions</p> <p>This study clearly shows age- and gender differences in short- and long-term risk of death after first hospitalization for HF with men having higher short- and long-term risk of death than women. As our study population includes both men and women from all ages, the estimates we provide maybe a good reflection of 'daily practice' risk of death and therefore be valuable for clinicians and policymakers.</p