Reporting on social marketing issues - a news media analysis

This paper explores online news media reporting through automated web content analysis to determine the prevalence and attitudes of social marketing issues across various countries. Results showed that Education and Work was the most commonly reported on category followed by Health Services, Family Planning, Environment, Crime and Justice and Road Safety. News media reporting in South Africa was particularly strong across Education and Work as well as Health Services. Canada recorded the highest reporting for Family Planning. New Zealand was the most prevalent reporter for the Environmental category. Crime and Justice and Road Safety only contributed a negligible amount to the overall term frequency counts across all categories. Social marketing stakeholders must continue to rally supportfrom the media in order to increase awareness of specific issues facing countries and society

An Evaluation Framework and Adaptive Architecture for Automated Sentiment Detection

Analysts are often interested in how sentiment towards an organization, a product or a particular technology changes over time. Popular methods that process unstructured textual material to automatically detect sentiment based on tagged dictionaries are not capable of fulfilling this task, even when coupled with part-of-speech tagging, a standard component of most text processing toolkits that distinguishes grammatical categories such as article, noun, verb, and adverb. Small corpus size, ambiguity and subtle incremental change of tonal expressions between different versions of a document complicate sentiment detection. Parsing grammatical structures, by contrast, outperforms dictionary-based approaches in terms of reliability, but usually suffers from poor scalability due to its computational complexity. This work provides an overview of different dictionary- and machine-learning-based sentiment detection methods and evaluates them on several Web corpora. After identifying the shortcomings of these methods, the paper proposes an approach based on automatically building Tagged Linguistic Unit (TLU) databases to overcome the restrictions of dictionaries with a limited set of tagged tokens

Gemcitabine and carboplatin in intensively pretreated patients with metastatic breast cancer

Background: Patients with metastatic breast cancer (MBC) are increasingly exposed to anthracyclines and taxanes either during treatment of primary breast cancer or during initial therapy of metastatic disease. The combination of gemcitabine and carboplatin was therefore investigated as an anthracycline- and taxane-free treatment option. Patients and Methods: MBC patients previously treated with chemotherapy were enrolled in a multicenter phase II study. Treatment consisted of gemcitabine (1,000 mg/m(2) i.v. on days 1 and 8) and carboplatin (AUC 4 i.v. on day 1) applied every 3 weeks. Results: Thirty-nine patients were recruited, and a total of 207 treatment cycles were applied with a median of 5 cycles per patient. One complete response and 11 partial responses were observed for an overall response rate of 31% (95% CI: 17-48%). Twelve patients (31%) had stable disease. Median time to progression was 5.3 months (95% CI: 2.6-6.7 months) and median overall survival from start of treatment was 13.2 months (95% CI: 8.7-16.7 months). Grade 3/4 hematological toxicity included leukopenia (59%/5%), thrombo-cytopenia (26%/23%) and anemia (10%/0%). Nonhematological toxicity was rarely severe. Conclusion: Combination chemotherapy with gemcitabine and carboplatin is an effective and generally well-tolerated treatment option for intensively pretreated patients with MBC. Due to a considerable incidence of severe thrombocytopenia it would be reasonable to consider starting gemcitabine at the lower dose level of 800 mg/m(2). Copyright (c) 2008 S. Karger AG, Basel

Enriching Semantic Knowledge Bases for Opinion Mining in Big Data Applications

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process

Variational approximation for mixtures of linear mixed models

Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm. The conventional approach to determining a suitable number of components is to compare different mixture models using penalized log-likelihood criteria such as BIC.We propose fitting MLMMs with variational methods which can perform parameter estimation and model selection simultaneously. A variational approximation is described where the variational lower bound and parameter updates are in closed form, allowing fast evaluation. A new variational greedy algorithm is developed for model selection and learning of the mixture components. This approach allows an automatic initialization of the algorithm and returns a plausible number of mixture components automatically. In cases of weak identifiability of certain model parameters, we use hierarchical centering to reparametrize the model and show empirically that there is a gain in efficiency by variational algorithms similar to that in MCMC algorithms. Related to this, we prove that the approximate rate of convergence of variational algorithms by Gaussian approximation is equal to that of the corresponding Gibbs sampler which suggests that reparametrizations can lead to improved convergence in variational algorithms as well.Comment: 36 pages, 5 figures, 2 tables, submitted to JCG

Novel transcriptomic panel identifies histologically active eosinophilic oesophagitis.

Eosinophilic oesophagitis (EoE) is characterised by symptoms of esophageal dysfunction and oesinophil tissue infiltration. The EoE Diagnostic Panel (EDP) can distinguish between active and non-active EoE using a set of 77 genes. Recently, the existence of distinct EoE variants featuring symptoms similar to EoE, such as oesophageal dysfunction but lacking eosinophil infiltration, had been determined. We used oesophageal biopsies from patients with histologically active (n=10) and non-active EoE (n=9) as well as from healthy oesophageal controls (n=5) participating in the Swiss Eosinophilic Esophagitis Cohort Study (SEECS) and analysed the gene expression profile in these biopsies by total RNA-sequencing (RNA-seq). Moreover, we employed the publicly accessible RNA-seq dataset (series GSE148381) as reported by Greuter et al, encompassing a comprehensive genomic profile of patients presenting with EoE variants. A novel, diagnostic gene expression panel that can effectively distinguish patients with histologically active conventional EoE from patients with EoE in histological remission and control individuals, and from three newly discovered EoE variants was identified. Histologically Active EoE Diagnostic Panel (HAEDP) consists of 53 genes that were identified based on differential expression between histologically active EoE, histological remission and controls (p≤0.05). By combining the HAEDP with EDP, we expanded our knowledge about factors that may contribute to the inflammation in EoE and improved our understanding of the underlying mechanisms of the disease. Conversely, we suggested a compact group of genes common to both HAEDP and EDP to create a reliable diagnostic tool that might enhance the accuracy of EoE diagnosis. We identified a novel set of 53 dysregulated genes that are closely associated with the histological inflammatory activity of EoE. In combination with EDP, our new panel might be a valuable tool for the accurate diagnosis of patients with EoE as well as for monitoring their disease course

Systematic evaluation of clinical predictors of aggressive ulcerative colitis

Background: Studies evaluating risk factors associated with an "aggressive" disease course in ulcerative colitis (UC) are scarce. A recent definition of "aggressive" UC incorporated the following characteristics: 1) high relapse rate, 2) need for surgery, 3) development of colorectal cancer, and 4) presence of extraintestinal manifestations (EIM). The following factors for an aggressive / disabling disease course in UC have been identified so far: age < 40 years at S140 Poster presentations UC diagnosis, pancolitis, concomitant primary sclerosing cholangitis, and deep ulcerations of the colonic mucosa. We aimed to evaluate risk factors for an "aggressive" disease course in UC patients. Methods: Data from the Swiss IBD cohort study were analyzed. Patients were recruited from university centers (80%), regional hospitals (19%), and private practices (1%). We applied the following definition for "aggressive" UC: 1) patients ever treated with TNFantagonists or calcineurin inhibitors (tacrolimus / cyclosporine), and 2) need for (procto)-colectomy. Non-normal data are presented as median and interquartile range [IQR]

Numerical and Experimental Investigation of Laminar One-Dimensional Counter-Flow Flames Using Product Gas From Pyrolysis and Gasification of Woody Biomass

Further advances in the utilization of biomass-based gaseous fuels in combustion systems require a deeper understanding of the combustion chemistry behind, as well as of the coupling of the chemistry with physical phenomena such as turbulence. The former is investigated in the present study combining both experiments with numerical simulations of different types of laminar non-premixed flames (sooting and non-sooting) in a counter-flow setup. The focus is put on synthetic gas mixtures, resembling, to different extents, typical compositions of the product gas obtained in biomass gasification consisting of CH4 (reference) and CH4 mixed with CO2, N2, O2, and/or H2, always. The oxidizer in all cases is air. A wide range of air-fuel ratios is considered. The influence of the product gas composition on the flame behaviour and flame structure with respect to the changes of the species profiles and peak temperatures with changing flow velocities is discussed. Laser-based spectroscopy techniques, in particular laser-induced Rayleigh scattering and laser-induced fluorescence (LIF), are applied as diagnostic tools. The former can provide an accurate understanding of temperature distributions, while the latter helps to identify the flame front through the tracking of intermediate species, such as CH2O (formaldehyde). Additionally, CH* chemiluminescence contributes to localize the flame front. Lastly, the influence of the N2-shroud flow velocities and diameters, as well as resulting buoyancy effects due to a raise in temperature, are taken into account. In correspondence to these experiments, the flames are numerically simulated by an in-house time-dependent implicit Fortran code

Flight Test Evaluation of the ATD-1 Interval Management Application

Interval Management (IM) is a concept designed to be used by air traffic controllers and flight crews to more efficiently and precisely manage inter-aircraft spacing. Both government and industry have been working together to develop the IM concept and standards for both ground automation and supporting avionics. NASA contracted with Boeing, Honeywell, and United Airlines to build and flight test an avionics prototype based on NASA's spacing algorithm and conduct a flight test. The flight test investigated four different types of IM operations over the course of nineteen days, and included en route, arrival, and final approach phases of flight. This paper examines the spacing accuracy achieved during the flight test and the rate of speed commands provided to the flight crew. Many of the time-based IM operations met or exceeded the operational design goals set out in the standards for the maintain operations and a subset of the achieve operations. Those operations which did not meet the goals were due to issues that are identified and will be further analyzed

Expression Patterns of TNFα, MAdCAM1, and STAT3 in Intestinal and Skin Manifestations of Inflammatory Bowel Disease.

Pathogenesis of cutaneous extraintestinal manifestations [EIM] in inflammatory bowel disease [IBD] remains elusive. Efficacy of anti-TNF agents suggests TNF-dependent mechanisms. The role of other biologics, such as anti-integrins or JAK-inhibitors, is not yet clear. We performed immunohistochemistry for TNFα, NFκB, STAT1/STAT3, MAdCAM1, CD20/68, caspase 3/9, IFNγ, and Hsp-27/70 on 240 intestinal [55 controls, 185 IBD] and 64 skin biopsies [11 controls, 18 erythema nodosum [EN], 13 pyoderma gangenosum [PG], 22 psoriasis]. A semiquantitative score [0-100%] was used for evaluation. TNFα was upregulated in intestinal biopsies from active Crohn`s disease [CD] vs controls [36.2 vs 12.1, p < 0.001], but not ulcerative colitis [UC: 17.9]. NFκB, however, was upregulated in intestinal biopsies from both active CD and UC [43.2 and 34.5 vs 21.8, p < 0.001 and p = 0.017, respectively]. TNFα and NFκB were overexpressed in skin biopsies from EN, PG, and psoriasis. No MAdCAM1 overexpression was seen in skin tissues, whereas it was upregulated in active UC vs controls [57.5 vs 35.4, p = 0.003]. STAT3 was overexpressed in the intestinal mucosa of active and non-active IBD, and a similar upregulation was seen in skin biopsies from EN [84.7 vs 22.3, p < 0.001] and PG [60.5 vs 22.3, p = 0.011], but not in psoriasis. Caspase 3 and CD68 overexpression in skin biopsies distinguished EN/PG from psoriasis and controls. Upregulation of TNFα/NFκB in EN and PG is compatible with the efficacy of anti-TNF in EIM management. Data on overexpressed STAT3, but not MAdCAM1, support a rationale for JAK-inhibitors in EN and PG, while questioning the role of vedolizumab