Indigenous Knowledge for Biodiversity Conservation

Indigenous peoples with a historical continuity of resource-use practices often possess a broad knowledge base of the behavior of complex ecological systems in their own localities. This knowledge has accumulated through a long series of observations transmitted from generation to generation. Such ''diachronic'' observations can be of great value and complement the ''synchronic''observations on which western science is based. Where indigenous peoples have depended, for long periods of time, on local environments for the provision of a variety of resources, they have developed a stake in conserving, and in some cases, enhancing, biodiversity. They are aware that biological diversity is a crucial factor in generating the ecological services and natural resources on which they depend. Some indigenous groups manipulate the local landscape to augment its heterogeneity, and some have been found to be motivated to restore biodiversity in degraded landscapes. Their practices for the conservation of biodiversity were grounded in a series of rules of thumb which are apparently arrived at through a trial and error process over a long historical time period. This implies that their knowledge base is indefinite and their implementation involves an intimate relationship with the belief system. Such knowledge is difficult for western science to understand. It is vital, however, that the value of the knowledge-practice-belief complex of indigenous peoples relating to conservation of biodiversity is fully recognized if ecosystems and biodiversity are to be managed sustainably. Conserving this knowledge would be most appropriately accomplished through promoting the community-based resource-management systems of indigenous peoples.

Anti-malarial herbal remedies of northeast India, Assam: An ethnobotanical survey

Ethnopharmacological relevance: Malaria is a serious public health problem in the north-eastern region of India including Assam, in view of development of chloroquine resistant Plasmodium falciparum. There is need for alternative and affordable therapy. Aim of the study: This study was conducted to document indigenous knowledge, usage customs and practices of medicinal plant species traditionally used by the residents of Sonitpur district of Tezpur, Assam to treat malaria and its associated symptoms. Materials and methods:A total of 50 randomly selected sampling represented by male (38.76%) and female respondents (12.24%) were interviewed using a semi-structured questionnaire. Results: The present ethno-botanical survey revealed 22 species of plants belonging to 17 botanical families were reported to be used exclusively in this region for the treatment of malaria. Verbenaceae (three species), Menispermaceae (two species), and Acanthaceae (two species) botanical families represented the species that are most commonly cited in this survey work and the detailed use of plants has been collected and described. Conclusions: The most serious threat to the existing knowledge and practice on traditional medicinal plants included cultural change, particularly the influence of modernization and lack of interests shown by the next younger generations were the main problems reported by the informants during the field survey. Hence, the proper documentation of traditional medicinal plants being used as anti-malarial agents and related indigenous knowledge held by the tribal community is an important approach to control the spread of vector-borne diseases like malaria reported in this survey work. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

An inventory of the ethnobotanicals used as anti-diabetic by a rural community of Dhemaji district of Assam, Northeast India

Ethnopharmacological relevance: Traditional remedies used for treating diabetic ailments are very important in the primary health care of the people living in rural Dhemaji district of Assam, north-east India. Novel information gathered from the current survey is important in preserving folk indigenous knowledge. Materials and methods: Interviews were conducted amongst 80 households comprising of 240 individuals using semi-structured questionnaires. The focus was on plants used in treating diabetes mellitus. Results: The current survey documented 21 plant species (20 families) which are reportedly used to treat diabetes mellitus by the rural people in the study area. To the best of our knowledge, Amomum linguiforme, Cinnamomum impressinervium, Colocasia esculenta, Dillenia indica, Euphorbia ligularia, Garcinia pedunculata, Solanum indicum, Sterculia villosa and Tabernaemontana divaricata are recorded for the first time based on globally published literature as medicinal plants used for treating diabetes mellitus and related symptoms. Conclusions: The wide variety of plants that are used to treat diabetes mellitus in this area supports the traditional value that medicinal plants have in the primary health care system of the rural people of Dhemaji district of Assam. The finding of new plant uses in the current study reveals the importance of the documentation of such ethnobotanical knowledge. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Patent intelligence and its implications for patent productivity

The prevailing hypercompetitive environment has made it essential for organizations to gather competitive intelligence from environmental scanning. The knowledge gained leads to organizational learning, which stimulates increased patent productivity. This paper highlights five practices that aid in developing patenting intelligence and empirically verifies to what extent this organizational learning leads to knowledge gains and financial gains realized from consequent higher patent productivity. The model is validated based on the perceptions of professionals with patenting experience from two of the most aggressively patenting sectors in today’s economy, viz., IT and pharmaceutical sectors (n=119). The key finding of our study suggests that although organizational learning from environmental scanning exists, the application of this knowledge for increasing patent productivity lacks due appreciation. This missing link in strategic analysis and strategy implementation has serious implications for managers which are briefly discussed in this paper.

Supervised matching of comments with news article segments

Comments constitute an important part of Web 2.0. In this paper, we consider comments on news articles. To simplify the task of relating the comment content to the article content the comments are about, we propose the idea of showing comments alongside article segments and explore automatic mapping of comments to article segments. This task is challenging because of the vocabulary mismatch between the articles and the comments. We present supervised and unsupervised techniques for aligning comments to segments the of article the comments are about. More specifically, we provide a novel formulation of supervised alignment problem using the framework of structured classification. Our experimental results show that structured classification model performs better than unsupervised matching and binary classification model.

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset

In the design of practical web page classification systems one often encounters a situation in which the labeled training set is created by choosing some examples from each class; but, the class proportions in this set are not the same as those in the test distribution to which the classifier will be actually applied. The problem is made worse when the amount of training data is also small. In this paper we explore and adapt binary SVM methods that make use of unlabeled data from the test distribution, viz., Transductive SVMs (TSVMs) and expectation regularization/constraint (ER/EC) methods to deal with this situation. We empirically show that when the labeled training data is small, TSVM designed using the class ratio tuned by minimizing the loss on the labeled set yields the best performance; its performance is good even when the deviation between the class ratios of the labeled training set and the test set is quite large. When the labeled training data is sufficiently large, an unsupervised Gaussian mixture model can be used to get a very good estimate of the class ratio in the test set; also, when this estimate is used, both TSVM and EC/ER give their best possible performance, with TSVM coming out superior. The ideas in the paper can be easily extended to multi-class SVMs and MaxEnt models.

Sufficient conditions for formation of a network topology by self-interested agents

Networks such as organizational network of a global company play an important role in a variety of knowledge management and information diffusion tasks. The nodes in these networks correspond to individuals who are self-interested. The topology of these networks often plays a crucial role in deciding the ease and speed with which certain tasks can be accomplished using these networks. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a pairwise stable network with only that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation. In this model, nodes enter the network sequentially and the utility of a node captures principal determinants of network formation, namely (1) benefits from immediate neighbors, (2) costs of maintaining links with immediate neighbors, (3) benefits from indirect neighbors, (4) bridging benefits, and (5) network entry fee. Based on this model, we analyze relevant network topologies such as star graph, complete graph, bipartite Turan graph, and multiple stars with interconnected centers, and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks. We also study the social welfare properties of the above topologies.