Application of Common Sense Computing for the Development of a Novel Knowledge-Based Opinion Mining Engine

The ways people express their opinions and sentiments have radically changed in the past few years thanks to the advent of social networks, web communities, blogs, wikis and other online collaborative media. The distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand, or organisation. These online social data, however, remain hardly accessible to computers, as they are specifically meant for human consumption. The automatic analysis of online opinions, in fact, involves a deep understanding of natural language text by machines, from which we are still very far. Hitherto, online information retrieval has been mainly based on algorithms relying on the textual representation of web-pages. Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling and counting their words. But when it comes to interpreting sentences and extracting meaningful information, their capabilities are known to be very limited. Existing approaches to opinion mining and sentiment analysis, in particular, can be grouped into three main categories: keyword spotting, in which text is classified into categories based on the presence of fairly unambiguous affect words; lexical affinity, which assigns arbitrary words a probabilistic affinity for a particular emotion; statistical methods, which calculate the valence of affective keywords and word co-occurrence frequencies on the base of a large training corpus. Early works aimed to classify entire documents as containing overall positive or negative polarity, or rating scores of reviews. Such systems were mainly based on supervised approaches relying on manually labelled samples, such as movie or product reviews where the opinionist’s overall positive or negative attitude was explicitly indicated. However, opinions and sentiments do not occur only at document level, nor they are limited to a single valence or target. Contrary or complementary attitudes toward the same topic or multiple topics can be present across the span of a document. In more recent works, text analysis granularity has been taken down to segment and sentence level, e.g., by using presence of opinion-bearing lexical items (single words or n-grams) to detect subjective sentences, or by exploiting association rule mining for a feature-based analysis of product reviews. These approaches, however, are still far from being able to infer the cognitive and affective information associated with natural language as they mainly rely on knowledge bases that are still too limited to efficiently process text at sentence level. In this thesis, common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques on two common sense knowledge bases was exploited to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data. The engine was tested on three different resources, namely a Twitter hashtag repository, a LiveJournal database and a PatientOpinion dataset, and its performance compared both with results obtained using standard sentiment analysis techniques and using different state-of-the-art knowledge bases such as Princeton’s WordNet, MIT’s ConceptNet and Microsoft’s Probase. Differently from most currently available opinion mining services, the developed engine does not base its analysis on a limited set of affect words and their co-occurrence frequencies, but rather on common sense concepts and the cognitive and affective valence conveyed by these. This allows the engine to be domain-independent and, hence, to be embedded in any opinion mining system for the development of intelligent applications in multiple fields such as Social Web, HCI and e-health. Looking ahead, the combined novel use of different knowledge bases and of common sense reasoning techniques for opinion mining proposed in this work, will, eventually, pave the way for development of more bio-inspired approaches to the design of natural language processing systems capable of handling knowledge, retrieving it when necessary, making analogies and learning from experience

A Cytochrome-b Perspective on Passerina Bunting Relationships

We sequenced the complete mitochondrial cytochrome-b gene (1,143 nucleotides) for representatives of each species in the cardinalid genera Passerina (6 species), Guiraca (1 species), and Cyanocompsa (3 species), and used a variety of phylogenetic methods to address relationships within and among genera. We determined that Passerina, as presently recognized, is paraphyletic. Lazuli Bunting (P. amoena) is sister to the much larger Blue Grosbeak (Guiraca caerulea). Indigo Bunting (P. cyanea) and Lazuli Bunting are not sister taxa as generally thought. In all weighted parsimony trees and for the gamma-corrected HKY tree, Indigo Bunting is the sister of two sister groups, a “blue” (Lazuli Bunting and Blue Grosbeak) and a “painted” (Rosita\u27s Bunting [P. rositae], Orange-breasted Bunting [P. leclancherii], Varied Bunting [P. versicolor], and Painted Bunting [P. ciris]) clade. The latter two species form a highly supported sister pair of relatively more recent origin. Uncorrected (p) distances for ingroup (Passerina and Guiraca) taxa range from 3.0% (P. versicolor–P. ciris) to 7.6% (P. cyanea–P. leclancherii) and average 6.5% overall. Assuming a molecular clock, a bunting “radiation” between 4.1 and 7.3 Mya yielded four lineages. This timing is consistent with fossil evidence and coincides with a late-Miocene cooling during which a variety of western grassland habitats evolved. A reduction in size at that time may have allowed buntings to exploit that new food resource (grass seeds). We speculate that the Blue Grosbeak subsequently gained large size and widespread distribution as a result of ecological character displacement

Geodatabase Development to Support Hyperspectral Imagery Exploitation

Geodatabase development for coastal studies conducted by the Naval Research Laboratory (NRL) is essential to support the exploitation of hyperspectral imagery (HSI). NRL has found that the remote sensing and mapping science community benefits from coastal classifications that group coastal types based on similar features. Selected features in project geodatabases relate to significant biological and physical forces that shape the coast. The project geodatabases help researchers understand factors that are necessary for imagery post processing, especially those features having a high degree of temporal and spatial variability. NRL project geodatabases include a hierarchy of environmental factors that extend from shallow water bottom types and beach composition to inland soil and vegetation characteristics. These geodatabases developed by NRL allow researchers to compare features among coast types. The project geodatabases may also be used to enhance littoral data archives that are sparse. This paper highlights geodatabase development for recent remote sensing experiments in barrier island, coral, and mangrove coast types

Changing the Custody of Children Whose Parents Have Been Divorced: A General View of the Process

The purpose of this project was to obtain a preliminary description, through study of the legal files, of that group of persons who appear before the Court of Domestic Relations for a reconsideration of the custody decision made initially, at the time of divorce. A sample of 92 cases heard in Multnomah County in 1965 was obtained. A survey of the literature revealed that much of what has been written on the subject of divorce and custody is primarily from a statistical or legalistic standpoint and very little bears directly on the granting or obtaining of custody or the problems encountered by the custodial or non-custodial parents and the children. A reading schedule was developed for the purpose of recording the information in the legal files maintained by the court. The characteristics of the sample group were tallied in an effort to obtain a statistical profile of that group requiring additional court appearances to settle the matter of custody. A number of hypotheses were developed and tested by means of Chi Square. Though this study was limited by the fact that no control group was used and no personal interviews were obtained, it clearly indicates the need for additional research in the area of divorce and custody and suggestions are made for future projects

Genomic biomarkers of prenatal intrauterine inflammation in umbilical cord tissue predict later life neurological outcomes

Preterm birth is a major risk factor for neurodevelopmental delays and disorders. This study aimed to identify genomic biomarkers of intrauterine inflammation in umbilical cord tissue in preterm neonates that predict cognitive impairment at 10 years of age

Estimating the Disease Burden of Pandemic (H1N1) 2009 Virus Infection in Hunter New England, Northern New South Wales, Australia, 2009

Introduction: On May 26, 2009, the first confirmed case of Pandemic (H1N1) 2009 virus (pH1N1) infection in Hunter New England (HNE), New South Wales (NSW), Australia (population 866,000) was identified. We used local surveillance data to estimate pH1N1-associated disease burden during the first wave of pH1N1 circulation in HNE. Methods: Surveillance was established during June 1-August 30, 2009, for: 1) laboratory detection of pH1N1 at HNE and NSW laboratories, 2) pH1N1 community influenza-like illness (ILI) using an internet survey of HNE residents, and 3) pH1N1-associated hospitalizations and deaths using respiratory illness International Classification of Diseases 10 codes at 35 HNE hospitals and mandatory reporting of confirmed pH1N1-associated hospitalizations and deaths to the public health service. The proportion of pH1N1 positive specimens was applied to estimates of ILI, hospitalizations, and deaths to estimate disease burden. Results: Of 34,177 specimens tested at NSW laboratories, 4,094 (12%) were pH1N1 positive. Of 1,881 specimens from patients evaluated in emergency departments and/or hospitalized, 524 (26%) were pH1N1 positive. The estimated number of persons with pH1N1-associated ILI in the HNE region was 53,383 (range 37,828–70,597) suggesting a 6.2% attack rate (range 4.4–8.2%). An estimated 509 pH1N1-associated hospitalizations (range 388–630) occurred (reported: 184), and up to 10 pH1N1-associated deaths (range 8–13) occurred (reported: 5). The estimated case hospitalization ratio was 1% and case fatality ratio was 0.02%. Discussion: The first wave of pH1N1 activity in HNE resulted in symptomatic infection in a small proportion of the population, and the number of HNE pH1N1-associated hospitalizations and deaths is likely higher than officially reported

Association of pol Diversity with Antiretroviral Treatment Outcomes among HIV-Infected African Children

Background: In HIV-infected children, viral diversity tends to increase with age in the absence of antiretroviral treatment (ART). We measured HIV diversity in African children (ages 6–36 months) enrolled in a randomized clinical trial comparing two ART regimens (Cohort I of the P1060 trial). Children in this cohort were exposed to single dose nevirapine (sdNVP) at birth. Methods: HIV diversity was measured retrospectively using a high resolution melting (HRM) diversity assay. Samples were obtained from 139 children at the enrollment visit prior to ART initiation. Six regions of the HIV genome were analyzed: two in gag, one in pol, and three in env. A single numeric HRM score that reflects HIV diversity was generated for each region; composite HRM scores were also calculated (mean and median for all six regions). Results: In multivariable median regression models using backwards selection that started with demographic and clinical variables, older age was associated with higher HRM scores (higher HIV diversity) in pol (P = 0.005) and with higher mean (P = 0.014) and median (P<0.001) HRM scores. In multivariable models adjusted for age, pre-treatment HIV viral load, pre-treatment CD4%, and randomized treatment regimen, higher HRM scores in pol were associated with shorter time to virologic suppression (P = 0.016) and longer time to study endpoints (virologic failure [VF], VF/death, and VF/off study treatment; P<0.001 for all measures). Conclusions: In this cohort of sdNVP-exposed, ART-naïve African children, higher levels of HIV diversity in the HIV pol region prior to ART initiation were associated with better treatment outcomes

Correction: Association of pol Diversity with Antiretroviral Atment Outcomes among HIV-Infected African Children

Background: In HIV-infected children, viral diversity tends to increase with age in the absence of antiretroviral treatment (ART). We measured HIV diversity in African children (ages 6–36 months) enrolled in a randomized clinical trial comparing two ART regimens (Cohort I of the P1060 trial). Children in this cohort were exposed to single dose nevirapine (sdNVP) at birth. Methods: HIV diversity was measured retrospectively using a high resolution melting (HRM) diversity assay. Samples were obtained from 139 children at the enrollment visit prior to ART initiation. Six regions of the HIV genome were analyzed: two in gag , one in pol , and three in env . A single numeric HRM score that reflects HIV diversity was generated for each region; composite HRM scores were also calculated (mean and median for all six regions). Results: In multivariable median regression models using backwards selection that started with demographic and clinical variables, older age was associated with higher HRM scores (higher HIV diversity) in pol (P = 0.005) and with higher mean (P = 0.014) and median (P , 0.001) HRM scores. In multivariable models adjusted for age, pre-treatment HIV viral load, pre- treatment CD4%, and randomized treatment regimen, higher HRM scores in pol were associated with shorter time to virologic suppression (P = 0.016) and longer time to study endpoints (virologic failure [VF], VF/death, and VF/off study treatment; P , 0.001 for all measures). Conclusions:In this cohort of sdNVP-exposed, ART-naı ̈ ve African children, higher levels of HIV diversity in the HIV pol region prior to ART initiation were associated with better treatment outcome

New Approaches In Medicaid: Work Requirements, Health Savings Accounts, And Health Care Access

Alternative approaches in Medicaid are proliferating under the Trump Administration. Using a novel telephone survey, we assessed views on health savings accounts, work requirements, and private vs. public coverage. Our sample included low-income non-elderly adults (N=2739) in three Midwestern states with different policies: 1) Ohio, which expanded traditional Medicaid; 2) Indiana, which expanded using health savings accounts (“POWER” Accounts); and 3) Kansas, which has not expanded. We found that coverage and access to care in 2017 were significantly higher in expansion states than in Kansas. However, compared to Ohio’s traditional expansion, cost-related barriers were more common in Indiana. Among beneficiaries eligible for Indiana’s program, 39% had not heard of POWER Accounts, and only 36% were making their required payments, meaning that nearly two-thirds were potentially subject to loss of benefits or coverage. Meanwhile, in Kansas, 77% supported expanding Medicaid, with similar attitudes towards Medicaid or private insurance. 49% of potential Medicaid enrollees in Kansas were already working, 34% were disabled, and only 11% were unemployed and would seek work if required by Medicaid. These findings suggest that curren