Lessons learned in effective community-university-industry collaboration models for smart and connected communities research

In 2017, the Boston University Hariri Institute for Computing and the Initiative on Cities co-hosted two workshops on “Effective Community-University-Industry Collaboration Models for Smart and Connected Communities Research,” with the support of the National Science Foundation (NSF). These efforts brought together over one hundred principal investigators and research directors from universities across the country, as well as city officials, community partners, NSF program managers and other federal agency representatives, MetroLab Network representatives and industry experts. The focus was on transdisciplinary “smart city” projects that bring technical fields such as engineering and computer science together with social scientists and community stakeholders to tackle community-sourced problems. Presentations, panel discussions, working sessions and participant white papers surfaced operational models as well as barriers and levers to enabling effective research partnerships. To capture the perspectives and beliefs of all participants, in addition to the presenters, attendees were asked to synthesize lessons on each panel topic. This white paper summarizes the opportunities and recommendations that emerged from these sessions, and provides guidance to communities and researchers interested in engaging in these types of partnerships as well as universities and funders that endeavor to nurture them. It draws on the collective wisdom of the assembled participants and the authors. While many of the examples noted are drawn from medium and large cities, the lessons may still be applicable to communities of various sizes.National Science Foundatio

An analysis of the regional impact of the Kapuni ammonia / urea plant : a research report constituting two 14.499 Research Reports, in partial fulfilment of the requirements for the degree of Master of Agricultural Business and Administration, Massey University

Successive post war governments in New Zealand have emphasised industrial development as the basis of economic growth. During this period national-level planning has become institutionalised. Central to the choice of planning policy for industrial development is the balance of payments problem. This has tended to mask other considerations which can be identified as pertinent to national and regional level decision making by private and public organisations . A major difficulty for the researcher is establishing which questions are relevant in a New Zealand context. This research exercise pursues the perspectives and questions which might be brought to bear on specific national development projects. The research focuses on the Kapuni Amronia/urea plant and analyses the regional impact of that project

Conifer-angiosperm interactions: Physiological ecology and life history.

Worldwide, conifers are most successful on sites subject to chronic stresses that limit productivity (low temperatures, nutrient poverty, poor drainage). They are poorly represented in the lowland tropics but are often important in Montane tropical forests. Here I explore some functional differences between leaf and xylem traits of conifer and angiosperm trees and their implications for the distributions of these two groups on environmental gradients. Analysis of a global data set shows that compared with angiosperm trees, conifers tend to have longer-lived leaves with greater mass per area (LMA) and lower mass-based photosynthetic capacity. As leaf life span is thought to be the main determinant of nutrient retention time, the prominence of conifers on infertile soils worldwide is at least partly attributable to thrifty use of nutrients through long leaf life spans. Furthermore, because leaf life span correlates with litter decomposition rates, these leaf trait differences could potentially influence the competitive balance between conifers and angiosperms via positive feedbacks on nutrient cycling. Although scaling of leaf life span with LMA is similar in the two groups, angiosperms achieve slightly longer leaf life spans than conifers of similar photosynthetic capacity. This might be caused by less-efficient leaf display in conifers, resulting in the useful life span of leaves being curtailed by self-shading. Representatives of both lineages have narrower conduits in the temperate zone than in the lowland tropics/subtropics, reflecting selection for resistance to freeze-thaw embolism in cold climates. However, conduit diameters of conifers and angiosperm trees differ more in tropical and subtropical forests than at higher latitudes. This probably reflects mechanical constraints on maximum tracheid diameters in the homoxylous wood of conifers, preventing this group from producing the highly conductive wood typical of fast-growing angiosperm pioneers in tropical forests. This pattern might explain why coexistence of conifers and angiosperms is more common in temperate forests and on tropical mountains than in the lowland tropics. Impairment of angiosperm carbon gain by freeze-thaw embolism during cold weather may further narrow performance differences between the two lineages on temperate sites. Differences in canopy residence time probably deserve more attention as a determinant of conifer-angiosperm coexistence in many temperate forests, the longer life span of conifers compensating for infrequent recruitment

Rule Based Forecasting [RBF] - Improving Efficacy of Judgmental Forecasts Using Simplified Expert Rules

Rule-based Forecasting (RBF) has emerged to be an effective forecasting model compared to well-accepted benchmarks. However, the original RBF model, introduced in1992, incorporates 99 production rules and is, therefore, difficult to apply judgmentally. In this research study, we present a core rule-set from RBF that can be used to inform both judgmental forecasting practice and pedagogy. The simplified rule-set, called coreRBF, is validated by asking forecasters to judgmentally apply the rules to time series forecasting tasks. Results demonstrate that forecasting accuracy from judgmental use of coreRBF is not statistically different from that reported from similar applications of RBF. Further, we benchmarked these coreRBF forecasts against forecasts from (a) untrained forecasters, (b) an expert system based on RBF, and (c) the original 1992 RBF study. Forecast accuracies were in the hypothesized direction, arguing for the generalizability and validity of the coreRBF rules

Are Choice Experiments Incentive Compatible? A Test with Quality Differentiated Beef Steaks

This study compares hypothetical and nonhypothetical responses to choice experiment questions. We test for hypothetical bias in a choice experiment involving beef ribeye steaks with differing quality attributes. In general, hypothetical responses predicted higher probabilities of purchasing beef steaks than nonhypothetical resposnes. Thus, hypothetical choices overestimate total willingness-to-pay for beef steaks. However, marginal willingness-to-pay for a change in steak quality is, in general, not statistically different across hypothetical and actual payment settings.CVM, conjoint analysis, heteroskedastic extreme value model, hypothetical bias, multinomial probit, random parameters logit.