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In distributional semantics words are represented by aggregated context features. The similarity of words can be computed by comparing their feature vectors. Thus, we can predict whether two words are synonymous or similar with respect to some other semantic relation. We will show on six different datasets of pairs of similar and non-similar words that a supervised learning algorithm on feature vectors representing pairs of words outperforms cosine similarity between vectors representing single words. We compared different methods to construct a feature vector representing a pair of words. We show that simple methods like pairwise addition or multiplication give better results than a recently proposed method that combines different types of features. The semantic relation we consider is relatedness of terms in thesauri for intellectual document classification. Thus our findings can directly be applied for the maintenance and extension of such thesauri. To the best of our knowledge this relation was not considered before in the field of distributional semantics.
Background: Foodstuff traders operating from warehouses (FTFW) are potentially exposed to dangerous rodenticides/pesticides that may have adverse effects on cardiopulmonary function. Methods: 50 consenting male foodstuff traders, comprising 15 traders (21–63 years) operating outside warehouses and 35 FTFW (20–64 years), were randomly recruited at Ogbete Market, Enugu, in a cross-sectional observational study of spirometric and electrocardiographic parameters. 17 FTFW (21–57 years) participated in focus group discussions. Qualitative and quantitative data were analysed thematically and with independent t-test and Pearson correlation coefficient at p < 0.05, respectively. Results: Most FTFW experienced respiratory symptoms, especially dry cough (97,1%) and wheezing (31.4%) with significant reductions in forced vital capacity (FVC) (t = -2.654; p = 0.011), forced expiratory volume in one second (FEV1) (t = -2.240; p = 0.030), maximum expiratory flow rate (FEF200-1200) (t = -1.148; p = -0.047), and forced end-expiratory flow (FEF25-75) (t = -1.11; p = 0.007). The maximum mid-expiratory flow (FEF25-75) was marginally decreased (p > 0.05) with a significantly prolonged (p < 0.05) QTc interval. Conclusion: Allergic response was evident in the FTFW. Significant decrease in FVC may negatively impact lung flow rates and explains the marginal decrease in FEF25-75, which implies a relative limitation in airflow of peripheral/distal airways and elastic recoil of the lungs. This is consistent with obstructive pulmonary disease; a significant decrease in FEF75-85/FEV1 supports this conclusion. Significant decrease in FEF200-1200 indicates abnormalities in the large airways/larynx just as significantly prolonged ventricular repolarization suggests cardiac arrhythmias.
Background: Physician-rating websites have become a popular tool to create more transparency about the quality of health care providers. So far, it remains unknown whether online-based rating websites have the potential to contribute to a better standard of care. Objective: Our goal was to examine which health care providers use online rating websites and for what purposes, and whether health care providers use online patient ratings to improve patient care. Methods: We conducted an online-based cross-sectional study by surveying 2360 physicians and other health care providers (September 2015). In addition to descriptive statistics, we performed multilevel logistic regression models to ascertain the effects of providers' demographics as well as report card-related variables on the likelihood that providers implement measures to improve patient care. Results: Overall, more than half of the responding providers surveyed (54.66%, 1290/2360) used online ratings to derive measures to improve patient care (implemented measures: mean 3.06, SD 2.29). Ophthalmologists (68%, 40/59) and gynecologists (65.4%, 123/188) were most likely to implement any measures. The most widely implemented quality measures were related to communication with patients (28.77%, 679/2360), the appointment scheduling process (23.60%, 557/2360), and office workflow (21.23%, 501/2360). Scaled-survey results had a greater impact on deriving measures than narrative comments. Multilevel logistic regression models revealed medical specialty, the frequency of report card use, and the appraisal of the trustworthiness of scaled-survey ratings to be significantly associated predictors for implementing measures to improve patient care because of online ratings. Conclusions: Our results suggest that online ratings displayed on physician-rating websites have an impact on patient care. Despite the limitations of our study and unintended consequences of physician-rating websites, they still may have the potential to improve patient care.
Editorial for the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016)
(2016)
Knowledge Organization Systems (KOS), in the form of classification systems, thesauri, lexical databases, ontologies, and taxonomies, play a crucial role in digital information management and applications generally. Carrying semantics in a well-controlled and documented way, Knowledge Organisation Systems serve a variety of important functions: tools for representation and indexing of information and documents, knowledge-based support to information searchers, semantic road maps to domains and disciplines, communication tool by providing conceptual framework, and conceptual basis for knowledge based systems, e.g. automated classification systems. New networked KOS (NKOS) services and applications are emerging, and we have reached a stage where many KOS standards exist and the integration of linked services is no longer just a future scenario. This editorial describes the workshop outline and overview of presented papers at the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) in Hannover, Germany.
Integrating distributional and lexical information for semantic classification of words using MRMF
(2016)
Semantic classification of words using distributional features is usually based on the semantic similarity of words. We show on two different datasets that a trained classifier using the distributional features directly gives better results. We use Support Vector Machines (SVM) and Multirelational Matrix Factorization (MRMF) to train classifiers. Both give similar results. However, MRMF, that was not used for semantic classification with distributional features before, can easily be extended with more matrices containing more information from different sources on the same problem. We demonstrate the effectiveness of the novel approach by including information from WordNet. Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.
The CogALex-V Shared Task provides two datasets that consists of pairs of words along with a classification of their semantic relation. The dataset for the first task distinguishes only between related and unrelated, while the second data set distinguishes several types of semantic relations. A number of recent papers propose to construct a feature vector that represents a pair of words by applying a pairwise simple operation to all elements of the feature vector. Subsequently, the pairs can be classified by training any classification algorithm on these vectors. In the present paper we apply this method to the provided datasets. We see that the results are not better than from the given simple baseline. We conclude that the results of the investigated method are strongly depended on the type of data to which it is applied.
Background: Often preventive measures are not accessed by the people who were intended to be reached. Programs for older adults may target men and women, older adults, advanced old age groups and/or chronically ill patients with specific indications. The defined target groups rarely participate in the conception of programs or in the design of information materials, although this would increase accessibility and participation. In the German “Reaching the Elderly” study (2008–2011), an approach to motivating older adults to participate in a preventive home visit (PHV) program was modified with the participatory involvement of the target groups. The study examines how older men and women would prefer to be addressed for health and prevention programs.
Methods: Four focus groups (N = 42 participants) and 12 personal interviews were conducted (women and men in 2 age groups: 65–75 years and ≥ 76 years). Participants from two districts of a major German city were selected from a stratified random sample (N = 200) based on routine data from a local health insurance fund. The study focused on the participants’ knowledge about health and disease prevention and how they preferred to be approached and addressed. Videos of the focus groups were recorded and analysed using mind mapping techniques. Interviews were digitally recorded, transcribed verbatim and subjected to qualitative content analysis.
Results: A gender-specific approach profile was observed. Men were more likely to favor competitive and exerciseoriented activities, and they associated healthy aging with mobility and physical activity. Women, on the other hand, displayed a broader understanding of healthy aging, which included physical activity as only one aspect as well as a healthy diet, relaxation/wellness, memory training and independent living; they preferred holistic and socially oriented services that were not performance-oriented. The “older seniors” (76+) were ambivalent towards
certain wordings referring to aging.
Conclusions: Our results suggest that gender-specific needs must be considered in order to motivate older adults to participate in preventive services. Age-specific characteristics seem to be less relevant. It is more important to pay attention to factors that vary according to the individual state of health and life situation of
the potential participants.
Discovery and efficient reuse of technology pictures using Wikimedia infrastructures. A proposal
(2016)
Multimedia objects, especially images and figures, are essential for the visualization and interpretation of research findings. The distribution and reuse of these scientific objects is significantly improved under open access conditions, for instance in Wikipedia articles, in research literature, as well as in education and knowledge dissemination, where licensing of images often represents a serious barrier.
Whereas scientific publications are retrievable through library portals or other online search services due to standardized indices there is no targeted retrieval and access to the accompanying images and figures yet. Consequently there is a great demand to develop standardized indexing methods for these multimedia open access objects in order to improve the accessibility to this material.
With our proposal, we hope to serve a broad audience which looks up a scientific or technical term in a web search portal first. Until now, this audience has little chance to find an openly accessible and reusable image narrowly matching their search term on first try - frustratingly so, even if there is in fact such an image included in some open access article.
Purpose. To identify stroke survivors with symptoms of poststroke depression and the extent of psychiatry needs and care they have received while on physiotherapy rehabilitation. Participants. Fifty stroke survivors (22 females and 28 males) at the outpatient unit of Physiotherapy Department, University of Nigeria Teaching Hospital, Enugu, who gave their informed consent, were randomly selected. Their age range and mean age were 26–66 years and 54.76 ± 8.79 years, respectively. Method. A multiple case study of 50 stroke survivors for symptoms of poststroke depression was done with Beck’s Depression Inventory, mini mental status examination tool, and Modified Motor Assessment Scale. The tests were performed independently by the participants except otherwise stated and scored on a scale of 0–6. Data were analyzed using -test for proportional significance and chi-square test for determining relationship between variables, at p < 0.05. Results. Twenty-one (42.0%) stroke survivors had symptoms of PSD, which was significantly dependent on duration of stroke ( = 21.680, df = 6, and p = 0.001), yet none of the participants had a psychiatry review. Conclusions. Symptoms of PSD may be common in cold compared to new cases of stroke and may need psychiatry care while on physiotherapy rehabilitation.
The medical devices sector helps save lives by providing innovative health care solutions regarding diagnosis, prevention, monitoring, treatment, and alleviation. Medical devices are classified into 1 of 3 categories in the order of increasing risk: Class I, Class II, and Class III.1 Medical devices are distinguished from drugs for regulatory purposes based on mechanism of action. Unlike drugs, medical devices operate via physical or mechanical means and are not dependent on metabolism to accomplish their primary intended effect.
Immunization is the most cost-effective intervention for infectious diseases, which are the major cause of morbidity and mortality worldwide. Vaccines not only protect the individual who is vaccinated but also reduce the burden of infectious vaccine-preventable diseases for the entire community.
1 Adult vaccination is very important given that >25% of mortality is due to infectious diseases.
2 There is a scarcity of information on the vaccination status of young adults and the role of socioeconomic conditions in India.
Research question: Rivalries in team sports are commonly conceptualized as a threat to the fans’ identity. Therefore, past research has mainly focused on the negative consequences. However, theoretical arguments and empirical evidence suggest that rivalry has both negative and positive effects on fans’ self-concept. This research develops and empirically tests a model which captures and integrates these dual effects of rivalry.
Research methods: Data were collected via an on-site survey at home games of eight German Bundesliga football teams (N = 571). Structural equation modeling provides strong support for the proposed model.
Results and findings: In line with previous research, the results show that rivalry threatens fans’ identity as reflected in lower public collective self-esteem in relation to supporters of the rival team. However, the results also show that there are crucial positive consequences, such as higher perceptions of public collective self-esteem in relation to supporters of non-rival opponents, perceived ingroup distinctiveness and ingroup cohesion. These positive effects are mediated through increases in disidentification with the rival and perceived reciprocity of rivalry.
Implications: We contribute to the literature by providing a more balanced view of one of team sports’ key phenomena. Our results indicate that the prevalent conceptualization of rivalry as an identity threat should be amended by the positive consequences. Our research also offers guidance for the promotion of rivalries, where the managerial focus should be on creating a perception that a rivalry is reciprocal.
According to the third-person effect or the influence of presumed media influence approach, the presumption that the media has strong effects on other people can affect individuals’ attitudes and behavior. For instance, if people believe in strong media influences on others, they are more likely to increase their communication activities or support demands for restrictions on media. A standardized online survey among German journalists (N = 960) revealed that the stronger the journalists perceive the political online influence on the public to be, the more frequently they contradict unwanted political views in their articles. Moreover, even journalists are more likely to approve of restrictions on the Internet’s political influence, the stronger they believe the effects of online media to be. The data reveal no connections between communication activities and demands for restrictions.
Background:
The increase in food intolerances poses a burgeoning problem in our society. Food intolerances not only lead to physical impairment of the individual patient but also result in a high socio-economic burden due to factors such as the treatment required as well as absenteeism. The present study aimed to explore whether lactose intolerant (LI) patients exhibit more frequent comorbidities than non-LI patients.
Methods:
The study was conducted on a case-control basis and the results were determined using routine data analysis. Routine data from the IMS Disease Analyzer database were used for this purpose. A total of 6,758 data records were processed and analyzed.
Results:
There were significant correlations between LI and the incidence of osteoporosis, changes in mental status, and the presence of additional food intolerances. Comparing 3,379 LI vs. 3,379 non-LI patients, 34.5% vs. 17.7% (P<0.0001) suffered from abdominal pain; 30.6% vs. 17.2% (P<0.0001) from gastrointestinal infections; and 20.9% vs. 16.0% (P=0.0053) from depression. Adjusted odds ratios (OR) were the highest for fructose intolerance (n=229 LI vs. n=7 non-LI; OR 31.06; P<0.0001), irritable bowel syndrome (n=247 LI vs. n=44 non-LI; OR 5.23; P<0.0001), and bloating (n=351 LI vs. n=68 non-LI; OR 4.94; P<0.0001).
Conclusion:
The study confirms that LI should not be regarded as an isolated illness but considered a possible trigger for further diseases. Additional research is necessary to assert more precise statements.