Pretend To Be Mine By P.G. Van

For their friends and family, Dheeraj and Anjali are a loving couple who fell in love at first sight, but they both have an agenda. Their reasons for the marriage contract were different, but what they never expected is what happens when two people start living under the same roof pretending to be a couple.

Pretend To Be Mine by P.G. Van

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Elaine Paige, a British actress and singer, heard of the success of the 1987 Broadway production and made sure to attend a performance. After seeing the production herself, she was determined to bring it to London.[21] To secure a place in the show's cast, Paige decided it was best she co-produced the show with her then-partner, lyricist Tim Rice. The London production opened in July 1989 at the Prince Edward Theatre. Paige starred as Reno Sweeney[22] (she was replaced later in the run by Louise Gold). The original cast also starred Howard McGillin as Billy Crocker[22] (who was replaced later in the show's run by John Barrowman),[23] Bernard Cribbins as Moonface, and Kathryn Evans as Erma. The other principals included Ursula Smith, Martin Turner, and Ashleigh Sendin.

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Concluding, it was a great experience as not only I had the chance to improve my network and meet peers with a similar background as mine but most important because in these two days I had increased my awareness and motivations.

A similar phenomenon to predatory journals is the predatory conference (Moital 2014; Nobes 2017; Grove 2017). These are pretend academic conferences of questionable value, established first and foremost to make money, not for the greater good of the academic discipline.

Part of the explanation for the problem may lie with studies wherethe exposure is a clinical condition in itself. The researcher istherefore tempted to label these exposed individuals as "cases". Howeverin the case-control study, the term "case" is reserved for the outcomeonly. Whilst epidemiologists and statisticians pretend not to fall intothese traps, the problem of mislabelling matched cohort studies is stillcommon and is associated with misleading results and interpretation.

Our analysis of short and long term mortality after foodbornebacterial infections was unique in several ways. The study group comprisedunselected patients with infectious gastroenteritis, by and large personswith no underlying illness, who sought care at their family doctor. It wastherefore expected that only a fraction of these patients had severeunderlying illness (i.e., a comorbidity diagnosis). Sec-ondly, our studywas the first study that determined mortality after foodborne in-fectionswhile adjusting for background mortality. This was pivotal because gas-trointestinal infections frequently occur among elderly persons. Theunexposed group was not randomly selected as suggested by Jacobs, butcarefully matched by age, gender, and place of residence. Finally, weadjusted for comorbidity by collecting data from the national hospitaldischarge registry. We applied the prin-ciples described by Charlson, butdid not use the weight proposed in her original work (2). Based on theactual survival rates of the large background population, we calculatedempirical weights. This approach was used to ensure that the weights werevalid and appropriate in the given context, and had the correct pre-dictive power. Although this approach may have been improved by obtainingmore detailed clinical information and data on additional confoundingfactors, our work represents a great improvement compared with previousattempts to deter-mine mortality after foodborne infections.

The biologic plausibility is supported by the fact that our estimatesare in line with common knowledge of the different agents. For example,mortality after salmo-nella was higher than after campylobacter, andwithin the group of salmonella-infections, serotype Dublin, known to beinvasive, was associated with a marked excess mortality. Although a longterm mortality was observed for salmonella, campylobacter and yersinia,the proportion of deaths attributable to the infection was highest in theacute phase. The table below was prepared based on the figures in table 2in our paper (1). The relative mortality rate has been converted to the at-tributable proportion of deaths among exposed, ((RR-1)/RR), i.e., ameasure of the probability of a death being related to thegastrointestinal infection. To deter-mine the estimated attributable riskof death in a given time-interval, the mortality risk must be multipliedby the attributable proportion. In our opinion, the pattern presented inthe table makes sense from a clinical point of view, and support thenotion that our findings are more than artefacts. 041b061a72