Measuring the acoustic properties of wood is not feasible for most luthiers, so identifying simple, valid criteria for diagnosis remains an exciting challenge when selecting materials for manufacturing musical instruments. This article aims to verify whether the bark qualities as a marker of resonance wood are indeed useful. The morphometric and colour traits (in CIELab space) of the bark scales were compared with the structural (width and regularity of the growth rings and of the latewood) and acoustic features (transverse sound velocity, radiation ratio, impedance, and wood basic density) of the wood from 145 standing and 10 felled spruce trees, which are considered a resource of the resonance wood in the Romanian Carpathians. It has been emphasized that the spruce trees with acoustic and structural features that match the requirements for the manufacture of violins have a bark phenotype distinguishable by colour (higher redness, lower yellowness and brightness)—as well as by scale shape (higher slenderness and width). The south-facing side of the trunk and the external side of the scale are best for identifying resonance trees by their bark. Additionally, the mature bark phenotypes denote topoclinal variations and do not depend on tree age. Moreover, the differences among bark phenotypes are noticeable to the naked eye.
The most serious quality issue of natural resources for human consumption or medicinal purposes is the contamination with pollutants harmful to consumers. Common blackberry (Rubus fruticosus L.) is a sought-after nutraceutical and an important component in herbal medicine in many places around the globe. The present study aims to analyze the level of heavy metal bioaccumulation in blackberry organs, as well as its spatial distribution in two consecutive years immediately after the interruption of the extended activity of the industrial source of pollution. The research was conducted in one of the most polluted areas in Romania and Eastern Europe, within a 26 km radius of the source of pollution. The Pb, Cd, Cu, and Zn concentrations in the leaves, flowers, and unwashed blackberry fruits were analyzed spectrophotometrically through flame atomic absorption spectroscopy (FAAS). The results show that blackberry is an important bioaccumulator of these heavy metals—71% of the Pb concentration values and 100% of the Cd concentration values exceeded the World Health Organization thresholds by up to 29 and 15 times, respectively. Also, the leaves are the largest reservoirs of Pb and Zn (the median values: 51.4 mg/kg dry weight and 105.2 mg/kg d.w., respectively), and the flowers contained the largest quantities of Cd and Cu (2.54 mg/kg d.w. and 11.3 mg/kg d.w., respectively). The Pb concentrations decreased by a power function in relation to the distance from the source of pollution. The implications of these results on the safety of the use of blackberry are discussed. The urgent necessity for food education of the local population which consumes contaminated nutraceutical products is emphasized.
Abstract. Time studies represent important tools that are used in forest operations research to produce empirical models or to comparatively assess the performance of two or more operational alternatives with the general aim to predict the performance of operational behavior, choose the most adequate equipment or eliminate the useless time. There is a long tradition in collecting the needed data in a traditional fashion, but this approach has its limitations, and it is likely that in the future the use of professional software would be extended is such preoccupations as this kind of tools have been already implemented. However, little to no information is available in what concerns the performance of data analyzing tasks when using purpose-built professional time studying software in such research preoccupations, while the resources needed to conduct time studies, including here the time may be quite intensive. Our study aimed to model the relations between the variation of time needed to analyze the video-recorded time study data and the variation of some measured independent variables for a complex organization of a work cycle. The results of our study indicate that the number of work elements which were separated within a work cycle as well as the delay-free cycle time and the software functionalities that were used during data analysis, significantly affected the time expenditure needed to analyze the data (α=0.01, p<0.01). Under the conditions of this study, where the average duration of a work cycle was of about 48 seconds and the number of separated work elements was of about 14, the speed that was used to replay the video files significantly affected the mean time expenditure which averaged about 273 seconds for half of the real speed and about 192 seconds for an analyzing speed that equaled the real speed. We argue that different study designs as well as the parameters used within the software are likely to produce different results, a fact that should trigger other studies based on variations of these parameters. However, the results of this study give an initial overview on the time resources needed in processing and analyzing the data, and may help researchers in allocating their resources.
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