An ethnobotanical study of traditional anti-inflammatory plants used by the Lohit community of Arunachal Pradesh, India

Aim of the study: Most people especially in rural areas depend on herbal medicines to treat many diseases including inflammation-related ailments such as rheumatism, muscle swelling, cut wound, accidental bone fracture, insect bites, pains and burn by fire and hot water. The objectives of this study were: to catalog ethno-medicinal plants of Lohit community, ecological status, indigenous folk medicinal uses, morphological parts used and to determine their reported pharmacological studies. Materials and methods: The ethnobotanical information on traditional medicinal plants exclusively used for management of inflammation-related ailments by the Khampti community of Arunachal Pradesh, India was based on first-hand field survey work through semi-structured interviews. Results and conclusion: A total of 34 species in 32 genera and 22 families were encountered during the field survey. Botanical families such as Asteraceae, Euphorbiaceae, Zingiberaceae and Lamiaceae were represented by the highest numbers of species reported in this study. Thirteen plant species, namely: Bombax ceiba, Canarium strictum, Chloranthus erectus, Xanthium indicum, Lycopodium clavatum, Coleus blumei, Batrachospermum atrum, Chlorella vulgaris, Marchantia palmata, Marchantia polymorpha, Eria pannea, Sterculia villosa and Alpinia galanga are reported for the first time for the treatment of inflammation-related diseases.

Application of an evolutionary fuzzy system for the estimation of workforce deployment and cross-training in an assembly environment

Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.