From exploitative to regenerative tourism: Tino rangatiratanga and tourism in Aotearoa New Zealand

Aotearoa New Zealand’s environmental management has long been considered short-sighted and focused on economic development over environmental, cultural or social imperatives. Tourism contributes to those pressures on our environments and communities. While Māori have always been involved in tourism, there is a concerted movement by many Māori towards engagement with tourism as a means of reconnecting with cultural traditions, protecting natural resources and providing employment for whānau. However, a definitive framework is lacking for establishing the limits of acceptable environmental change for different taonga from the effects of tourism. Such a framework is essential for bridging the implementation gap between the goals of national tourism and environmental strategies, and the actual outcomes on the ground. Here, we advance the Mauriora Systems Framework (MSF) (Matunga, 1993) as a conceptually robust and generic framework that is unique to Aotearoa New Zealand and provides a language and process centred on mauri for mana whenua to come together with management agencies in setting outcomes for places and taonga. We suggest the MSF is consistent with the aspiration for the emerging notion of regenerative tourism and that it can also contribute to a greater understanding and valuing of mātauranga and tikanga Māori within the tourism industry and its host communities

면역화학측정법을 이용한 혈청 Transferrin 측정에 관한 연구

Various methods are available for measuring total iron·binding capacity in serum (TIBC) which is an indirect measure of serum trans· ferrin content. All of these methods are cumbersome and have methodological disadvantages such as a high sample amount , possibility for iron contamination of the laboratory ware unspecificity because of other iron-binding proteins in serum and problems to optimize the method (Koepke, 1965; Williams and Conrad, 1972; Von der Heul et aI., 1972; Frazer, 197:1; Haeckel et aI. , 1973; Schmidt et aI. , 1975; Tsung ct al 1975; Graham and Bates, 1976; Rajamacki ct aI., 1979; Seiffert, 1981). Immunochemical methods have made a direct immunological measurement of serum transferrin possible (Goodman et aI., 1958; Wilding and Rollason, 1972; Haeckel et aI., 1973; Schmidt et aI., 1975; Tsung et aI., 1975; Kreutzer. 1976) . The purpose of the present work was to study the correlation hetween serum transferrin and TIBC values in healthy and anemic persons. * This research was supported in part by scholarship from the State Government for Bessen in Federal R('public of Germany in the year of 10m Further to determine reference values of serum transferrin for adults of both sexes and for 2 groups of children at different age

Marine guardians – A novel solution to improving our marine environment

New Zealand’s coastal and marine ecosystems are in ecological trouble. In 2016 the Government reported on the state of our seas, as required by the Environmental Reporting Act 2015 (ERA). “Our marine environment 2016” identified serious and widespread issues with seabed habitat damage and destruction, numerous threatened seabird and marine mammals, and massive loss of topsoil into our coastal waters causing deterioration in water quality and ecosystem services

Predicting and understanding urban perception with convolutional neural networks

Cities' visual appearance plays a central role in shaping human perception and response to the surrounding urban environment. For example, the visual qualities of urban spaces affect the psychological states of their inhabitants and can induce negative social outcomes. Hence, it becomes critically important to understand people's perceptions and evaluations of urban spaces. Previous works have demonstrated that algorithms can be used to predict high level attributes of urban scenes (e.g. safety, attractiveness, uniqueness), accurately emulating human perception. In this paper we propose a novel approach for predicting the perceived safety of a scene from Google Street View Images. Opposite to previous works, we formulate the problem of learning to predict high level judgments as a ranking task and we employ a Convolutional Neural Network (CNN), significantly improving the accuracy of predictions over previous methods. Interestingly, the proposed CNN architecture relies on a novel pooling layer, which permits to automatically discover the most important areas of the images for predicting the concept of perceived safety. An extensive experimental evaluation, conducted on the publicly available Place Pulse dataset, demonstrates the advantages of the proposed approach over state-of-the-art methods