174 research outputs found

    Management of chronic urticaria in Asia: 2010 AADV consensus guidelines

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    This guideline is a result of a consensus reached during the 19th Asian-Australasian Regional Conference of Dermatology by the Asian Academy of Dermatology and Venereology Study Group in collaboration with the League of Asian Dermatological Societies in 2010. Urticaria has a profound impact on the quality of life in Asia and the need for effective treatment is required. In line with the EAACI/GA2LEN/EDF/WAO guideline for the management of urticaria the recommended first-line treatment is new generation, non-sedating H1-antihistamines. If standard dosing is ineffective, increasing the dosage up to four-fold is recommended. For patients who do not respond to a four-fold increase in dosage of non-sedating H1-antihistamines, it is recommended that therapies such as H2-antihistamine, leukotriene antagonist, and cyclosporine A should be added to the antihistamine treatment. In the choice of second-line treatment, both their costs and risk/benefit profiles are the most important considerations

    A study of the impact of individual thermal control on user comfort in the workplace: Norwegian cellular vs. British open plan offices

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    In modern offices, user control is being replaced by centrally operated thermal systems, and in Scandinavia, personal offices by open plan layouts. This study examined the impact of user control on thermal comfort and satisfaction. It compared a workplace, which was designed entirely based on individual control over the thermal environment, to an environment that limited thermal control was provided as a secondary option for fine-tuning: Norwegian cellular and British open plan offices. The Norwegian approach provided each user with control over a window, door, blinds, heating and cooling as the main thermal control system. In contrast, the British practice provided a uniform thermal environment with limited openable windows and blinds to refine the thermal environment for occupants seated around the perimeter of the building. Field studies of thermal comfort were applied to measure users’ perception of thermal environment, empirical building performance and thermal control. The results showed a 30% higher satisfaction and 18% higher comfort level in the Norwegian offices compared to the British practices. However, the energy consumption of the Norwegian case studies was much higher compared to the British ones. A balance is required between energy efficiency and user thermal comfort in the workplace

    Meta-analysis of the relation between European and American smokeless tobacco and oral cancer

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    <p>Abstract</p> <p>Background</p> <p>Smokeless tobacco is often referred to as a major contributor to oral cancer. In some regions, especially Southeast Asia, the risk is difficult to quantify due to the variety of products, compositions (including non-tobacco ingredients) and usage practices involved. In Western populations, the evidence of an increased risk in smokeless tobacco users seems unclear, previous reviews having reached somewhat differing conclusions. We report a detailed quantitative review of the evidence in American and European smokeless tobacco users, and compare our findings with previous reviews and meta-analyses.</p> <p>Methods</p> <p>Following literature review a meta-analysis was conducted of 32 epidemiological studies published between 1920 and 2005 including tests for homogeneity and publication bias.</p> <p>Results</p> <p>Based on 38 heterogeneous study-specific estimates of the odds ratio or relative risk for smokeless tobacco use, the random-effects estimate was 1.87 (95% confidence interval 1.40–2.48). The increase was mainly evident in studies conducted before 1980. No increase was seen in studies in Scandinavia. Restricting attention to the seven estimates adjusted for smoking and alcohol eliminated both heterogeneity and excess risk (1.02; 0.82–1.28). Estimates also varied by sex (higher in females) and by study design (higher in case-control studies with hospital controls) but more clearly in studies where estimates were unadjusted, even for age. The pattern of estimates suggests some publication bias. Based on limited data specific to never smokers, the random-effects estimate was 1.94 (0.88–4.28), the eight individual estimates being heterogeneous and based on few exposed cases.</p> <p>Conclusion</p> <p>Smokeless tobacco, as used in America or Europe, carries at most a minor increased risk of oral cancer. However, elevated risks in specific populations or from specific products cannot definitely be excluded.</p

    Morot eller piska? Gymnasielevers tankar om vad som pÄverkar motivationen i matematikÀmnet

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    Tidigare forskning pekar pÄ att elevernas motivation i skolarbetet sjunker ju högre upp i Ärskurserna man kommer, och att detta Àr sÀrskilt tydligt i matematiken. Syftet med denna studie var att undersöka vilka faktorer som pÄverkar gymnasieelevers motivation i matematikÀmnet. Studien utgick frÄn följande frÄgestÀllning: - Vilka faktorer anser eleverna pÄverkar deras motivation i matematikÀmnet? UtifrÄn resultatet av undersökningen diskuterades Àven frÄgan: - Hur kan man som lÀrare arbeta för att stÀrka elevernas motivation i matematikÀmnet? Undersökningen genomfördes med hjÀlp av en enkÀt som distribuerades till totalt sex gymnasieklasser frÄn det samhÀllsvetenskapliga programmet och ekonomiprogrammet pÄ tre slumpvis utvalda skolor i en större svensk stad. EnkÀten utformades och genomfördes digitalt via Google Drive. Resultaten sammanstÀlldes i diagram, och i vissa fall berÀknades den statistiska felmarginalen för att möjliggöra slutsatser med en högre grad av sÀkerhet. Resultatet av undersökningen visade att de faktorer som enligt eleverna pÄverkar motivationen i matematikÀmnet i störst utstrÀckning Àr kÀnslan av att lyckas med sina uppgifter, betyg, lÀrarens undervisning, prov, nytta för framtida studier och kÀnslan av att se hur matematiken hÀnger ihop. UtifrÄn detta resultat diskuterades hur lÀraren kan arbeta för att stÀrka elevernas motivation i matematikÀmnet. Ur ett lÀrarperspektiv kan resultatet av denna undersökning ses som positivt dÄ det indikerade att lÀraren har stor möjlighet att pÄverka elevernas motivation. Denna studie pekar pÄ att lÀraren kan stÀrka elevernas motivation genom att öka variationen i undervisningen, skapa optimala utmaningar för eleverna, visa pÄ den nytta matematiken kan ge i framtiden samt genom att ge tydligare och mer framÄtsyftande Äterkoppling

    The use of GM(1,1) to predict tolerance in manufacturing

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    Vid tillverkningsteknik kan förutsÀgelse av fel vara fördelaktigt av flera anledningar. Att veta nÀrmaskinen kommer att börja orsaka avvikelser som uppstÄr utanför den accepterade toleransenkan kraftigt minska mÀngden defekta produkter. Dessa fel Àr ofta orsakade av fixturerna, detmaterialet och slitaget av maskinverktyget.Idag anvÀnds statistiska metoder frÀmst för att förutspÄ detta, nÄgot som ger bra resultat men oftainte utförs eftersom det krÀver stora mÀngder data. MÄnga produktionslinor tillÄter inte att storamÀngder produkter dras undan för mÀtning eftersom det kommer att störa flödet av linjen ochdÀrigenom orsaka en större förlust jÀmfört med nÄgra defektprodukter. DÀrför Àr behovet avmetoder som anvÀnder en mindre mÀngd data en intressant aspekt att undersöka.Denna rapport avser att undersöka hur algoritmen GM(1,1) kan anvÀndas för att förutspÄ fel iproduktionslinor. Fel som kan uppstÄ och som avhandlas i följande rapport inkluderarsystematiska orsakade av felaktigheter med instÀllningar pÄ arbetsverktyget samt fel orsakadeutav nötning pÄ arbetsverktyget, arbetet har grundat sig i att undersöka hur effektiv GM(1,1) Àrför att förutspÄ ojÀmnheter pÄ ytan i ett arbetsstycke.GM(1,1) har tidigare anvÀnts inom omrÄden som ekonomi, medicin och samhÀllsanalyser för attförutse risker och tillvÀxt. Inom produktion har sÄdant tidigare gjorts bland annat genomtraditionella statistiska analyser samt genom approximationer utifrÄn verktygets geometri. DetförstnÀmnda Àr nÄgonting som krÀver stora mÀngder data för att ge gedigna resultat, nÄgot somofta gör att det inte lönar sig för företag att utföra detta. GM(1,1) har visat sig fungera vÀl medsmÄ mÀngder data och denna rapport avser att undersöka denna modells lÀmplighet för attförutspÄ dessa fel och se om ett intervall för toleranser kan tas fram.Denna studie har tagit fram förslag pÄ modeller samt problemformuleringar som kan utgÄs ifrÄnnÀr modellera olika typer av produktionsfel nÀr man ska förutspÄ dessa med GM(1,1).In manufacturing engineering, predicting errors can be beneficial for several reasons, knowingwhen the machine will start to cause deviations occurring outside the accepted tolerance cangreatly reduce the amount of defect products. These errors are often caused by the fixtures, theblank as well as abrasion of the machine tool.Today, statistical methods are primarily used to predict this, something that gives good resultsbut is often not performed because it requires large sample sizes. Many production lines does notallow withdrawal of larger samples for measurement since it will interfere with the flow of theline thus causing a larger loss compared to a few defect products. Therefore, the need ofprediction methods that uses a smaller amount of samples is of great interest.This report aims to investigate how the algorithm GM(1,1) can be used to predict errors inproduction lines. The work has been based on examining how effective GM(1,1) is to predictunevenness on the surface of the machines part.GM(1,1) has previously been used in areas such as economics, medicine and social analyzes topredict risks and growth. In production, such has been done in the past through, among otherthings, traditional statistical analyzes and approximations based on the geometry of the tool. Theformer is something that requires large amounts of data to produce solid results, something thatmakes companies not do these kinds of studies. GM(1,1) has proven to work well with smallamounts of data and this report intends to investigate the suitability of this model to predict theseerrors and see if an interval for tolerances can be obtained.The findings in this study supports the idea to some extent that grey models, specifically theGM(1,1) can be useful to predict certain errors/changes in manufacturing
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