Essential oil of aerial parts of Ziziphora tenuior growing in Shahrbabak in central Iran are isolated by hydrodistillation. Due to complexity of essential oils, there are fundamental problems such as co-elution in their direct gas chromatography-mass spectrometry analysis. These problems can result in low similarity matches in MS library search, so that true identification and determination of individual components may fail. In the present work, each component was identified and determined using GC-MS coupled with multivariate curve resolution (MCR) techniques. In this way, more information along with higher accuracy and precision can be extracted from pure experimental GC-MS data. The number of identified components found increased from 37 in direct similarity search to 80 in GC-MS/MCR method. To identify each individual component, similarity search and Kovat's retention index comparison were implemented. The results found showed that pulegone (38.3%), 3¢,5¢-dihydroxyacetophenone (22.83%), isomenthone (7.06%), 2-methyl-5-(1-methylethyl)-phenol (3.41%), limonene (2.59%) and 2-acetyl-4,4-dimethylcyclopent-2-enone (2.49%) were the most abundant components. The reported compounds accounted for 94.39% of total content of the essential oil. A characteristic feature of the Iranian Ziziphora tenuior is the absence of piperitenone in its constituents compared with the oil of other Ziziphora species from Turkey.
In the last few years, the number of projects studying the human hand from the robotic point of view has increased rapidly, due to the growing interest in academic and industrial applications. Nevertheless, the complexity of the human hand given its large number of degrees of freedom (DoF) within a significantly reduced space requires an exhaustive analysis, before proposing any applications. The aim of this paper is to provide a complete summary of the kinematic and dynamic characteristics of the human hand as a preliminary step towards the development of hand devices such as prosthetic/robotic hands and exoskeletons imitating the human hand shape and functionality. A collection of data and constraints relevant to hand movements is presented, and the direct and inverse kinematics are solved for all the fingers as well as the dynamics; anthropometric data and dynamics equations allow performing simulations to understand the behavior of the finger.
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