101 resultados para Management models and fashions


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1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviour-based models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley's declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

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This article is the second part of a review of the historical evolution of mathematical models applied in the development of building technology. The first part described the current state of the art and contrasted various models with regard to the applications to conventional buildings and intelligent buildings. It concluded that mathematical techniques adopted in neural networks, expert systems, fuzzy logic and genetic models, that can be used to address model uncertainty, are well suited for modelling intelligent buildings. Despite the progress, the possible future development of intelligent buildings based on the current trends implies some potential limitations of these models. This paper attempts to uncover the fundamental limitations inherent in these models and provides some insights into future modelling directions, with special focus on the techniques of semiotics and chaos. Finally, by demonstrating an example of an intelligent building system with the mathematical models that have been developed for such a system, this review addresses the influences of mathematical models as a potential aid in developing intelligent buildings and perhaps even more advanced buildings for the future.

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Consideration of the quality, relevance and utility of research in educational leadership and management has been a growing concern of researchers, policy-makers and practitioners, but there is little agreement about its current state or priorities for development. The article reflects on the key criticisms that have been made of research in educational leadership and management in this issue, and elsewhere. It considers how we might begin to devise better ways of understanding its audiences, judging its quality and identifying priorities for the future. It argues that the research reflects its capture by those with particular interests or values, and impacts in ways which are complex and indirect. If educational leadership and management research is to be secure in its perceived value and contribution in the future, several developments are needed, including a greater emphasis on interdisciplinarity, an expansion of the range of methodologies, particularly qualtitative studies; and these shifts must be evident in training researchers as well as in the conduct of research.

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Purpose: The purpose of this paper is to address a classic problem – pattern formation identified by researchers in the area of swarm robotic systems – and is also motivated by the need for mathematical foundations in swarm systems. Design/methodology/approach: The work is separated out as inspirations, applications, definitions, challenges and classifications of pattern formation in swarm systems based on recent literature. Further, the work proposes a mathematical model for swarm pattern formation and transformation. Findings: A swarm pattern formation model based on mathematical foundations and macroscopic primitives is proposed. A formal definition for swarm pattern transformation and four special cases of transformation are introduced. Two general methods for transforming patterns are investigated and a comparison of the two methods is presented. The validity of the proposed models, and the feasibility of the methods investigated are confirmed on the Traer Physics and Processing environment. Originality/value: This paper helps in understanding the limitations of existing research in pattern formation and the lack of mathematical foundations for swarm systems. The mathematical model and transformation methods introduce two key concepts, namely macroscopic primitives and a mathematical model. The exercise of implementing the proposed models on physics simulator is novel.

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The aim of this review article is to provide an overview of the role of pigs as a biomedical model for humans. The usefulness and limitations of porcine models have been discussed in terms of metabolic, cardiovascular, digestive and bone diseases in humans. Domestic pigs and minipigs are the main categories of pigs used as biomedical models. One drawback of minipigs is that they are in short supply and expensive compared with domestic pigs, which in contrast cost more to house, feed and medicate. Different porcine breeds show different responses to the induction of specific diseases. For example, ossabaw minipigs provide a better model than Yucatan for the metabolic syndrome as they exhibit obesity, insulin resistance and hypertension, all of which are absent in the Yucatan. Similar metabolic/physiological differences exist between domestic breeds (e.g. Meishan v. Pietrain). The modern commercial (e.g. Large White) domestic pig has been the preferred model for developmental programming due to the 2- to 3-fold variation in body weight among littermates providing a natural form of foetal growth retardation not observed in ancient (e.g. Meishan) domestic breeds. Pigs have been increasingly used to study chronic ischaemia, therapeutic angiogenesis, hypertrophic cardiomyopathy and abdominal aortic aneurysm as their coronary anatomy and physiology are similar to humans. Type 1 and II diabetes can be induced in swine using dietary regimes and/or administration of streptozotocin. Pigs are a good and extensively used model for specific nutritional studies as their protein and lipid metabolism is comparable with humans, although pigs are not as sensitive to protein restriction as rodents. Neonatal and weanling pigs have been used to examine the pathophysiology and prevention/treatment of microbial-associated diseases and immune system disorders. A porcine model mimicking various degrees of prematurity in infants receiving total parenteral nutrition has been established to investigate gut development, amino acid metabolism and non-alcoholic fatty liver disease. Endoscopic therapeutic methods for upper gastrointestinal tract bleeding are being developed. Bone remodelling cycle in pigs is histologically more similar to humans than that of rats or mice, and is used to examine the relationship between menopause and osteoporosis. Work has also been conducted on dental implants in pigs to consider loading; however with caution as porcine bone remodels slightly faster than human bone. We conclude that pigs are a valuable translational model to bridge the gap between classical rodent models and humans in developing new therapies to aid human health.

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A survey of the knowledge, attitudes and practices (KAP) of 100 rice farmers and 50 coconut farmers was conducted in the coastal lowland agro-ecosystems of the Sierra Madre Biodiversity Corridor, Luzon, Philippines to identify current rodent management practices and to understand the extent of rat damage and the attitudes of farmers to community actions for rodent management. Pests were most commonly listed as one of the three most important rice and coconut production constraints. Other major crop production constraints were typhoons and insufficient water. Farmers consider rats to be the major pest of coconut and of rice during the wet season rice crop, with average yield losses of 3.0% and 13.2%, respectively. Rice and coconut farmers practised a wide range of rodent management techniques. These included scrub clearance, hunting and trapping. Of the 42 rice farmers and 3 coconut farmers that applied rodenticides to control rodents, all used the acute rodenticide, zinc phosphide. However, only ten rice farmers (23.8%) applied rodenticides prior to the booting stage and only seven farmers (15.6%) conducted pre-baiting before applying zinc phosphide. The majority of farmers belonged to farmer organisations and believed that rat control can only be done by farmers working together. However, during the last cropping season, less than a third of rice farmers (31.2%) applied rodent management as a group. In order to reduce the impact of rodents on the farmers of the coastal lowlands of the Sierra Madre Biodiversity Corridor, integrated management strategies need to be developed that specifically target the pest rodents in a sustainable manner, and community actions for rodent management should be promoted.

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Depreciation is a key element of understanding the returns from and price of commercial real estate. Understanding its impact is important for asset allocation models and asset management decisions. It is a key input into well-constructed pricing models and its impact on indices of commercial real estate prices needs to be recognised. There have been a number of previous studies of the impact of depreciation on real estate, particularly in the UK. Law (2004) analysed all of these studies and found that the seemingly consistent results were an illusion as they all used a variety of measurement methods and data. In addition, none of these studies examined impact on total returns; they examined either rental value depreciation alone or rental and capital value depreciation. This study seeks to rectify this omission, adopting the best practice measurement framework set out by Law (2004). Using individual property data from the UK Investment Property Databank for the 10-year period between 1994 and 2003, rental and capital depreciation, capital expenditure rates, and total return series for the data sample and for a benchmark are calculated for 10 market segments. The results are complicated by the period of analysis which started in the aftermath of the major UK real estate recession of the early 1990s, but they give important insights into the impact of depreciation in different segments of the UK real estate investment market.

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This paper considers the relationship between value management and facilities management. The findings are particularly relevant to large client organisations which procure new buildings on a regular basis. It is argued that the maximum effectiveness of value management can only be achieved if it is used in conjunction with an ongoing commitment to post-occupancy evaluation. SMART value management is seen to provide the means of ensuring that an individual building design is in alignment with the client’s strategic property needs. However, it is also necessary to recognise that an organisation’s strategic property needs will continually be in a state of change. Consequentially, economic and functional under-performance can only be avoided by a regular performance audit of existing property stock in accordance with changing requirements. Such a policy will ensure ongoing competitiveness through organisational learning. While post-occupancy evaluation represents an obvious additional service to be provided by value management consultants, it is vital that the necessary additional skills are acquired. Process management skills and social science research techniques are clearly important. However, there is also a need to improve mechanisms for data manipulation. Success can only be achieved if equal attention is given to issues of process, structure and content.

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Purpose – The purpose of this paper is to present the findings and lessons learned from three case studies conducted for facilities located in California, North America. The findings aim to focus on energy and maintenance management practices and the interdependent link between energy and maintenance. Design/methodology/approach – The research is based on a positivist epistemological philosophical approach informed by action research. The research cycle was completed for each case study. A case study report was provided to each facility management team to foster collaboration with the researcher and to document case study process and results. Findings – Composite findings of the case studies include: there is an interdependent link between energy and maintenance management; reactive maintenance and energy management methods are commonly used; and more proactively operated and managed buildings require the interdependent link between energy maintenance management to be better understood. Research limitations/implications – The three case studies were located in California. Although the case study results can be generalized, determination of how to generalize and apply the results to commercial buildings outside of the USA is beyond the scope of this paper. Practical implications – Detailed discussion of the needs of the three facility management teams are discussed by identifying a current challenge, developing a solution and documenting lessons learned using the research cycle. Originality/value – The paper seeks to demonstrate the interdependencies of energy and maintenance management, two topics which are often researched interdependently. Additionally, the paper provides insight about maintenance management, a topic often cited as being under researched.

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Ice cloud representation in general circulation models remains a challenging task, due to the lack of accurate observations and the complexity of microphysical processes. In this article, we evaluate the ice water content (IWC) and ice cloud fraction statistical distributions from the numerical weather prediction models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office, exploiting the synergy between the CloudSat radar and CALIPSO lidar. Using the last three weeks of July 2006, we analyse the global ice cloud occurrence as a function of temperature and latitude and show that the models capture the main geographical and temperature-dependent distributions, but overestimate the ice cloud occurrence in the Tropics in the temperature range from −60 °C to −20 °C and in the Antarctic for temperatures higher than −20 °C, but underestimate ice cloud occurrence at very low temperatures. A global statistical comparison of the occurrence of grid-box mean IWC at different temperatures shows that both the mean and range of IWC increases with increasing temperature. Globally, the models capture most of the IWC variability in the temperature range between −60 °C and −5 °C, and also reproduce the observed latitudinal dependencies in the IWC distribution due to different meteorological regimes. Two versions of the ECMWF model are assessed. The recent operational version with a diagnostic representation of precipitating snow and mixed-phase ice cloud fails to represent the IWC distribution in the −20 °C to 0 °C range, but a new version with prognostic variables for liquid water, ice and snow is much closer to the observed distribution. The comparison of models and observations provides a much-needed analysis of the vertical distribution of IWC across the globe, highlighting the ability of the models to reproduce much of the observed variability as well as the deficiencies where further improvements are required.

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This paper identifies some significant gaps in our knowledge of the configuration and performance of the property asset management sector. It is argued that, as many leading academic property researchers have focussed on financial vehicles and modelling, in-depth analysis of property assets and their management has been neglected. In terms of potential for future in-depth research, three key broad preliminary research themes or questions are identified. First, how do the active management opportunities presented, costs of management and the key management tasks vary with market conditions, asset type and life-cycle stage? Second, how is property asset management delivered and what are the main costs and benefits of different models of procurement? Finally, what are the appropriate metrics for measuring the performance of different property managers and approaches to property management? It is concluded that the lack of published materials addressing these issues has implications for educating property students.

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Linear models of property market performance may be misspecified if there exist distinct states where the market drivers behave in different ways. This paper examines the applicability of non-linear regime-based models. A Self Exciting Threshold Autoregressive (SETAR) model is applied to property company share data, using the real rate of interest to define regimes. Distinct regimes appear exhibiting markedly different market behaviour. The model both casts doubt on the specification of conventional linear models and offers the possibility of developing effective trading rules for real estate equities.

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An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km. The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10–50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency, precipitation intensity, and quantiles of the frequency distribution. For mean precipitation, the models reproduce the characteristics of the annual cycle and the spatial distribution. The domain mean bias varies between −23% and +3% in winter and between −27% and −5% in summer. Larger errors are found for other statistics. In summer, all models underestimate precipitation intensity (by 16–42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models. Similar intermodel differences are found for other European subregions. Interestingly, the model errors are very similar between the two models with the same dynamical core (but different parameterizations) and they differ considerably between the two models with similar parameterizations (but different dynamics). Despite considerable biases, the models reproduce prominent mesoscale features of heavy precipitation, which is a promising result for their use in climate change downscaling over complex topography.

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The extra-tropical response to El Niño in configurations of a coupled model with increased horizontal resolution in the oceanic component is shown to be more realistic than in configurations with a low resolution oceanic component. This general conclusion is independent of the atmospheric resolution. Resolving small-scale processes in the ocean produces a more realistic oceanic mean state, with a reduced cold tongue bias, which in turn allows the atmospheric model component to be forced more realistically. A realistic atmospheric basic state is critical in order to represent Rossby wave propagation in response to El Niño, and hence the extra-tropical response to El Niño. Through the use of high and low resolution configurations of the forced atmospheric-only model component we show that, in isolation, atmospheric resolution does not significantly affect the simulation of the extra-tropical response to El Niño. It is demonstrated, through perturbations to the SST forcing of the atmospheric model component, that biases in the climatological SST field typical of coupled model configurations with low oceanic resolution can account for the erroneous atmospheric basic state seen in these coupled model configurations. These results highlight the importance of resolving small-scale oceanic processes in producing a realistic large-scale mean climate in coupled models, and suggest that it might may be possible to “squeeze out” valuable extra performance from coupled models through increases to oceanic resolution alone.