RESUMEN
This work deals with the innovated complex process of tree risk assessment, from precise geometrical tree shape acquisition to building and analyzing a finite element model under specified load. The acquisition of the 3D geometry of the tree was performed by means of terrestrial laser scanning. Obtained point cloud was optimized and additionally converted to a 3D CAD model, representing the bearing skeleton compound of trunk and main branches. For structural analysis purposes, a finite element model (FEM) was built in the form of beam structure fixed to the ground. Particular beams were defined by geometry, material properties of wood, and cross sections. An acoustic tomography was applied for determination of the precise cross section on investigated locations of an analysis model. Finite element analysis performed on the computational model shows the bearing capacity and deformations of the whole tree structure caused by combinations of load cases like self-weight and static equivalent of wind load. The results of the structural analysis called attention to potentially dangerous places within the tree structure with extreme node displacements or tensile stresses on beams. Thus, we observed a maximal horizontal displacement of 280.4 mm in node N34 and dangerous tensile stress in node N26, where it reaches +23.6 MPa. After filtering some beams with an abnormal cross section geometry, the finite element analysis of the whole tree structure showed the highest tensile stress of +8.8 MPa and highest compressive stress of -8.9 MPa. The suggested method can be applied generally for the prediction of potentially risky tree suspected of breakage and especially for monumental trees, where the presented method can be mostly applicable.
RESUMEN
Many toxic substances in the workplace can modify human health and quality of life and there is still insufficient data on respiratory outcomes in adults exposed to phthalates. The aim of this work was to assess in waste management workers from the Nitra region of Slovakia (n = 30) the extent of exposure to phthalates and health-related outcomes. Four urinary phthalate metabolites mono(2-ethylhexyl) phthalate (MEHP), monobutyl phthalate (MnBP), monoethyl phthalate (MEP) and monoisononyl phthalate (MiNP) were determined by high-performance liquid chromatography with mass spectrometry (HPLC-MS/MS). Urinary concentration of MEHP was positively associated with ratio of forced expiratory volume in 1 s to forced vital capacity % (FEV1/FVC) (r = 0.431; p = 0.018) and MiNP with fat free mass index (FFMI) (r = 0.439; p = 0.015). The strongest predictor of pulmonary function was the pack/year index as smoking history that predicted a decrease of pulmonary parameters, the FEV1/FVC, % of predicted values of peak expiratory flow (PEF % of PV) and FEV1 % of PV. Unexpectedly, urinary MEHP and MINP were positively associated with pulmonary function expressed as PEF % of PV and FEV1/FVC. We hypothesize that occupational exposure to phthalates estimated from urinary metabolites (MEHP, MiNP) can modify pulmonary function on top of lifestyle factors.