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Developing causal loop diagrams (CLDs) involves identifying stakeholders and endogenous variables and formulating variable causal relationships. Traditionally, the CLDs are developed mainly using a qualitative approach such as literature review, observations and interviews with stakeholders. However, modellers may question which stakeholders should be approached, whether the relevant variables are selected, and what to do when stakeholders perceive different variable relationships in the CLDs differently. Applying in a case study, this research proposes a multi-method approach by combining both quantitative and qualitative methods to select stakeholders, identify endogenous/exogenous variables, and develop the CLDs. The proposed quantitative method is expected to provide modellers with a justifiable stakeholder and variable selection process. The method also highlights possible hidden variables and relationships, which were further explored with a traditional qualitative approach.

Developing causal loop diagrams (CLDs) involves identifying stakeholders and endogenous variables and formulating variable causal relationships. Traditionally, the CLDs are developed mainly using a qualitative approach such as literature review, observations and interviews with stakeholders. However, modellers may question which stakeholders should be approached, whether the relevant variables are selected, and what to do when stakeholders perceive different variable relationships in the CLDs differently. Applying in a case study, this research proposes a multi-method approach by combining both quantitative and qualitative methods to select stakeholders, identify endogenous/exogenous variables, and develop the CLDs. The proposed quantitative method is expected to provide modellers with a justifiable stakeholder and variable selection process. The method also highlights possible hidden variables and relationships, which were further explored with a traditional qualitative approach.

AbstractObjectiveTo assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission.MethodsFollowing PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer‐reviewed, freely available and full‐text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review.ResultsTwenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors.ConclusionsDue to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems.

AbstractObjectiveTo assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission.MethodsFollowing PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer‐reviewed, freely available and full‐text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review.ResultsTwenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors.ConclusionsDue to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems.

One of main concepts involved in regional small nuclear reactors is unmanned remote control. Internet-based virtual private networks provide environments for the remote monitoring and control of geographically-dispersed systems, and with the advances in communication technologies, the potential of networks for real time control and automation becomes enormous. However, networked control has some problems. The most critical is delay in signal transmission, which degrades system stability and performance. Therefore, a networked control system should be designed to account for delay. This paper proposes some design approaches for a delay-tolerant system that can guarantee predetermined stability margins and performance. To accomplish this, the reactor plant is modeled with consideration of uncertainties. With this model, three kinds of controllers are developed using different methods. The designed systems are compared with respect to stability and performance, and a second-order controller designed using the table lookup method was found to give the most satisfactory results.

One of main concepts involved in regional small nuclear reactors is unmanned remote control. Internet-based virtual private networks provide environments for the remote monitoring and control of geographically-dispersed systems, and with the advances in communication technologies, the potential of networks for real time control and automation becomes enormous. However, networked control has some problems. The most critical is delay in signal transmission, which degrades system stability and performance. Therefore, a networked control system should be designed to account for delay. This paper proposes some design approaches for a delay-tolerant system that can guarantee predetermined stability margins and performance. To accomplish this, the reactor plant is modeled with consideration of uncertainties. With this model, three kinds of controllers are developed using different methods. The designed systems are compared with respect to stability and performance, and a second-order controller designed using the table lookup method was found to give the most satisfactory results.

A natural holm oak forest was selectively thinned to test thinning as a tool to reduce tree mortality, increase productivity, and reverse the recent regression of the dominant species (Quercus ilex) induced by climate change. Thinning increased aboveground productivity and reduced stem mortality in this Mediterranean forest during four years just after thinning, contributing to the maintenance of forest functioning under changing climatic conditions. Q. ilex was the only species positively affected by the thinning: stem growth increased for all stem sizes, and mortality was significantly lower in thinned plots. On the contrary, mortality rates of Phillyrea latifolia and Arbutus unedo were not significantly lower. Stem growth increased for P. latifolia only in the smallest stem-size class. Our results highlight the suitability of selective thinning for improving the forest productivity and ensuring the conservation of Mediterranean coppices. Other benefits of selective thinning, such as a decrease in the risk of fire dispersion and an increase in the water supply for human populations, are also discussed.