Grontmij (Denmark)

Abstract Although the international standard CityGML has five levels of detail (LODs), the vast majority of available models are the coarse ones (up to LOD2, i.e. block‐shaped buildings with roofs). LOD3 and LOD4 models, which contain architectural details such as balconies, windows and rooms, rarely exist because, unlike coarser LODs, their construction requires several datasets that must be acquired with different technologies, and often extensive manual work is needed. In this article we investigate an alternative to obtaining CityGML LOD3 models: the automatic conversion from already existing architectural models (stored in the IFC format). Existing conversion algorithms mostly focus on the semantic mappings and convert all the geometries, which yields CityGML models having poor usability in practice (spatial analysis, for instance, is not possible). We present a conversion algorithm that accurately applies the correct semantics from IFC models and that constructs valid CityGML LOD3 buildings by performing a series of geometric operations in 3D. We have implemented our algorithm and we demonstrate its effectiveness with several real‐world datasets. We also propose specific improvements to both standards to foster their integration in the future.

The aim of this case-control study was to investigate characteristics of cleaners with good musculoskeletal health after years with physically heavy work. One hundred and 41 female seniority cleaners participated. Twenty-five reported no musculoskeletal symptoms, whereas 83 reported severe symptoms in the low back, neck shoulders or upper limbs. The groups were of matching age, height, body weight and seniority (19 years). Muscular strength was recorded by isometric maximal voluntary contractions on a day without pain. Exposure to physical risk factors at work, psychosocial work factors, and leisure time physical activity were assessed by a postal questionnaire. Cleaners with good musculoskeletal health were not reporting different exposure to physical risk factors at work or leisure time physical activity, but had higher muscular strength and reported higher influence at work than cleaners with severe symptoms. These findings suggest that muscular strength and influence at work are of relevance for sustaining good musculoskeletal health in workers with physically heavy work.

<div>I det sydvestlige Grønland, knap 40 km fra Nanortalik, ligger en fantastisk smuk dal, Kirkespirdalen. Den har sit navn efter den karakteristiske fjeldtop Kirkespiret. Toppen er med sine 1.590 m.o.h. et af de højeste fjelde i Sydgrønland. I denne dal har der siden maj 2004 været drevet minedrift 24 timer i døgnet. Det er Nalunaq Guldminen, Grønlands første guldmine, som langsomt sprænger sig vej gennem bjerget.</div>