807 resultados para web-based language learning


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Prenatal ultrasound can often reliably distinguish fetal anatomic anomalies, particularly in the hands of an experienced ultrasonographer. Given the large number of existing syndromes and the significant overlap in prenatal findings, antenatal differentiation for syndrome diagnosis is difficult. We constructed a hierarchic tree of 1140 sonographic markers and submarkers, organized per organ system. Subsequently, a database of prenatally diagnosable syndromes was built. An internet-based search engine was then designed to search the syndrome database based on a single or multiple sonographic markers. Future developments will include a database with magnetic resonance imaging findings as well as further refinements in the search engine to allow prioritization based on incidence of syndromes and markers.

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BACKGROUND: Patients with rare diseases such as congenital hypogonadotropic hypogonadism (CHH) are dispersed, often challenged to find specialized care and face other health disparities. The internet has the potential to reach a wide audience of rare disease patients and can help connect patients and specialists. Therefore, this study aimed to: (i) determine if web-based platforms could be effectively used to conduct an online needs assessment of dispersed CHH patients; (ii) identify the unmet health and informational needs of CHH patients and (iii) assess patient acceptability regarding patient-centered, web-based interventions to bridge shortfalls in care. METHODS: A sequential mixed-methods design was used: first, an online survey was conducted to evaluate health promoting behavior and identify unmet health and informational needs of CHH men. Subsequently, patient focus groups were held to explore specific patient-identified targets for care and to examine the acceptability of possible online interventions. Descriptive statistics and thematic qualitative analyses were used. RESULTS: 105 male participants completed the online survey (mean age 37 ± 11, range 19-66 years) representing a spectrum of patients across a broad socioeconomic range and all but one subject had adequate healthcare literacy. The survey revealed periods of non-adherence to treatment (34/93, 37%) and gaps in healthcare (36/87, 41%) exceeding one year. Patient focus groups identified lasting psychological effects related to feelings of isolation, shame and body-image concerns. Survey respondents were active internet users, nearly all had sought CHH information online (101/105, 96%), and they rated the internet, healthcare providers, and online community as equally important CHH information sources. Focus group participants were overwhelmingly positive regarding online interventions/support with links to reach expert healthcare providers and for peer-to-peer support. CONCLUSION: The web-based needs assessment was an effective way to reach dispersed CHH patients. These individuals often have long gaps in care and struggle with the psychosocial sequelae of CHH. They are highly motivated internet users seeking information and tapping into online communities and are receptive to novel web-based interventions addressing their unmet needs.

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OBJECTIVE: To evaluate web-based information on bipolar disorder and to assess particular content quality indicators. METHODS: Two keywords, "bipolar disorder" and "manic depressive illness" were entered into popular World Wide Web search engines. Websites were assessed with a standardized proforma designed to rate sites on the basis of accountability, presentation, interactivity, readability and content quality. "Health on the Net" (HON) quality label, and DISCERN scale scores were used to verify their efficiency as quality indicators. RESULTS: Of the 80 websites identified, 34 were included. Based on outcome measures, the content quality of the sites turned-out to be good. Content quality of web sites dealing with bipolar disorder is significantly explained by readability, accountability and interactivity as well as a global score. CONCLUSIONS: The overall content quality of the studied bipolar disorder websites is good.

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In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

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BACKGROUND: No previous studies have explored how closely women follow their psychotropic drug regimens during pregnancy. This study aimed to explore patterns of and factors associated with low adherence to psychotropic medication during pregnancy. METHODS: Multinational web-based study was performed in 18 countries in Europe, North America, and Australia. Uniform data collection was ensured via an electronic questionnaire. Pregnant women were eligible to participate. Adherence was measured via the 8-item Morisky Medication Adherence Scale (MMAS-8). The Beliefs about Prescribed Medicines Questionnaire (BMQ-specific), the Edinburgh Postnatal Depression Scale (EPDS), and a numeric rating scale were utilized to measure women's beliefs, depressive symptoms, and antidepressant risk perception, respectively. Participants reporting use of psychotropic medication during pregnancy (n = 160) were included in the analysis. RESULTS: On the basis of the MMAS-8, 78 of 160 women (48.8%, 95% CI: 41.1-56.4%) demonstrated low adherence during pregnancy. The rates of low adherence were 51.3% for medication for anxiety, 47.2% for depression, and 42.9% for other psychiatric disorders. Smoking during pregnancy, elevated antidepressant risk perception (risk≥6), and depressive symptoms were associated with a significant 3.9-, 2.3-, and 2.5-fold increased likelihood of low medication adherence, respectively. Women on psychotropic polytherapy were less likely to demonstrate low adherence. The belief that the benefit of pharmacotherapy outweighed the risks positively correlated (r = .282) with higher medication adherence. CONCLUSIONS: Approximately one of two pregnant women using psychotropic medication demonstrated low adherence in pregnancy. Life-style factors, risk perception, depressive symptoms, and individual beliefs are important factors related to adherence to psychotropic medication in pregnancy.

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In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance.

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Tämän tutkimuksen tavoitteena oli tutkia langattomien internet palveluiden arvoverkkoa ja liiketoimintamalleja. Tutkimus oli luonteeltaan kvalitatiivinen ja siinä käytettiin strategiana konstruktiivista case-tutkimusta. Esimerkkipalveluna oli Treasure Hunters matkapuhelinpeli. Tutkimus muodostui teoreettisesta ja empiirisestä osasta. Teoriaosassa liitettiin innovaatio, liiketoimintamallit ja arvoverkko käsitteellisesti toisiinsa, sekä luotiin perusta liiketoimintamallien kehittämiselle. Empiirisessä osassa keskityttiin ensin liiketoimintamallien luomiseen kehitettyjen innovaatioiden pohjalta. Lopuksi pyrittiin määrittämään arvoverkko palvelun toteuttamiseksi. Tutkimusmenetelminä käytettiin innovaatiosessiota, haastatteluja ja lomakekyselyä. Tulosten pohjalta muodostettiin useita liiketoimintakonsepteja sekä kuvaus arvoverkon perusmallista langattomille peleille. Loppupäätelmänä todettiin että langattomat palvelut vaativat toteutuakseen useista toimijoista koostuvan arvoverkon.

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Työssä tutkittiin tehokasta tietojohtamista globaalin metsäteollisuusyrityksen tutkimus ja kehitys verkostossa. Työn tavoitteena oli rakentaa kuvaus tutkimus ja kehitys sisällön hallintaan kohdeyrityksen käyttämän tietojohtamisohjelmiston avulla. Ensin selvitettiin käsitteitä tietämys ja tietojohtaminen kirjallisuuden avulla. Selvityksen perusteella esitettiin prosessimalli, jolla tietämystä voidaan tehokkaasti hallita yrityksessä. Seuraavaksi analysoitiin tietojohtamisen asettamia vaatimuksia informaatioteknologialle ja informaatioteknologian roolia prosessimallissa. Verkoston vaatimukset tietojohtamista kohtaan selvitettiin haastattelemalla yrityksen avainhenkilöitä. Haastatteluiden perusteella järjestelmän tuli tehokkaasti tukea virtuaalisten projektiryhmien työskentelyä, mahdollistaa tehtaiden välinen tietämyksen jakaminen ja tukea järjestelmään syötetyn sisällön hallintaa. Ensiksi järjestelmän käyttöliittymän rakenne ja salaukset muokattiin vastaamaan verkoston tarpeita. Rakenne tarjoaa työalueen työryhmille ja alueet tehtaiden väliseen tietämyksen jakamiseen. Sisällönhallintaa varten järjestelmään kehitettiin kategoria, profiloitu portaali ja valmiiksi määriteltyjä hakuja. Kehitetty malli tehostaa projektiryhmien työskentelyä, mahdollistaa olemassa olevan tietämyksen hyväksikäytön tehdastasolla sekä helpottaa tutkimus ja kehitys aktiviteettien seurantaa. Toimenpide-ehdotuksina esitetään järjestelmän integrointia tehtaiden operatiivisiin ohjausjärjestelmiin ja ohjelmiston käyttöönottoa tehdastason projektinhallinta työkaluksi.Ehdotusten tavoitteena on varmistaa sekä tehokas tietämyksen jakaminen tehtaiden välillä että tehokas tietojohtaminen tehdastasolla.

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This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

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The article discusses the development of WEBDATANET established in 2011 which aims to create a multidisciplinary network of web-based data collection experts in Europe. Topics include the presence of 190 experts in 30 European countries and abroad, the establishment of web-based teaching and discussion platforms and working groups and task forces. Also discussed is the scope of the research carried by WEBDATANET. In light of the growing importance of web-based data in the social and behavioral sciences, WEBDATANET was established in 2011 as a COST Action (IS 1004) to create a multidisciplinary network of web-based data collection experts: (web) survey methodologists, psychologists, sociologists, linguists, economists, Internet scientists, media and public opinion researchers. The aim was to accumulate and synthesize knowledge regarding methodological issues of web-based data collection (surveys, experiments, tests, non-reactive data, and mobile Internet research), and foster its scientific usage in a broader community.

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In this paper we study student interaction in English and Swedish courses at a Finnish university. We focus on language choices made in task-related activities in small group interaction. Our research interests arose from the change in the teaching curriculum, in which content and language courses were integrated at Tampere University of Technology in 2013. Using conversation analysis, we analysed groups of 4-5 students who worked collaboratively on a task via a video conference programme. The results show how language alternation has different functions in 1) situations where students orient to managing the task, e.g., in transitions into task, or where they orient to technical problems, and 2) situations where students accomplish the task. With the results, we aim to show how language alternation can provide interactional opportunities for language learning. The findings will be useful in designing tasks in the future.

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Occupational hygiene practitioners typically assess the risk posed by occupational exposure by comparing exposure measurements to regulatory occupational exposure limits (OELs). In most jurisdictions, OELs are only available for exposure by the inhalation pathway. Skin notations are used to indicate substances for which dermal exposure may lead to health effects. However, these notations are either present or absent and provide no indication of acceptable levels of exposure. Furthermore, the methodology and framework for assigning skin notation differ widely across jurisdictions resulting in inconsistencies in the substances that carry notations. The UPERCUT tool was developed in response to these limitations. It helps occupational health stakeholders to assess the hazard associated with dermal exposure to chemicals. UPERCUT integrates dermal quantitative structure-activity relationships (QSARs) and toxicological data to provide users with a skin hazard index called the dermal hazard ratio (DHR) for the substance and scenario of interest. The DHR is the ratio between the estimated 'received' dose and the 'acceptable' dose. The 'received' dose is estimated using physico-chemical data and information on the exposure scenario provided by the user (body parts exposure and exposure duration), and the 'acceptable' dose is estimated using inhalation OELs and toxicological data. The uncertainty surrounding the DHR is estimated with Monte Carlo simulation. Additional information on the selected substances includes intrinsic skin permeation potential of the substance and the existence of skin notations. UPERCUT is the only available tool that estimates the absorbed dose and compares this to an acceptable dose. In the absence of dermal OELs it provides a systematic and simple approach for screening dermal exposure scenarios for 1686 substances.