42 resultados para model categories homotopy theory quillen functor equivalence derived adjunction cofibrantly generated

em CentAUR: Central Archive University of Reading - UK


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The constructivist model of 'soft' value management (VM) is contrasted with the VM discourse appropriated by cost consultants who operate from within UK quantity surveying (QS) practices. The enactment of VM by cost consultants is shaped by the institutional context within which they operate and is not necessarily representative of VM practice per se. Opportunities to perform VM during the formative stages of design are further constrained by the positivistic rhetoric that such practitioners use to conceptualize and promote their services. The complex interplay between VM theory and practice is highlighted and analysed from a non-deterministic perspective. Codified models of 'best practice' are seen to be socially constructed and legitimized through human interaction in the context of interorganizational networks. Published methodologies are seen to inform practice in only a loose and indirect manner, with extensive scope for localized improvization. New insights into the relationship between VM theory and practice are derived from the dramaturgical metaphor. The social reality of VM is seen to be constituted through scripts and performances, both of which are continuously contested across organizational arenas. It is concluded that VM defies universal definition and is conceptualized and enacted differently across different localized contexts.

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An efficient model identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and robustness. The derived model parameters in each forward regression step are initially estimated via the orthogonal least squares (OLS), followed by being tuned with a new gradient-descent learning algorithm based on the basis pursuit that minimises the l(1) norm of the parameter estimate vector. The model subset selection cost function includes a D-optimality design criterion that maximises the determinant of the design matrix of the subset to ensure model robustness and to enable the model selection procedure to automatically terminate at a sparse model. The proposed approach is based on the forward OLS algorithm using the modified Gram-Schmidt procedure. Both the parameter tuning procedure, based on basis pursuit, and the model selection criterion, based on the D-optimality that is effective in ensuring model robustness, are integrated with the forward regression. As a consequence the inherent computational efficiency associated with the conventional forward OLS approach is maintained in the proposed algorithm. Examples demonstrate the effectiveness of the new approach.

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The constant-density Charney model describes the simplest unstable basic state with a planetary-vorticity gradient, which is uniform and positive, and baroclinicity that is manifest as a negative contribution to the potential-vorticity (PV) gradient at the ground and positive vertical wind shear. Together, these ingredients satisfy the necessary conditions for baroclinic instability. In Part I it was shown how baroclinic growth on a general zonal basic state can be viewed as the interaction of pairs of ‘counter-propagating Rossby waves’ (CRWs) that can be constructed from a growing normal mode and its decaying complex conjugate. In this paper the normal-mode solutions for the Charney model are studied from the CRW perspective. Clear parallels can be drawn between the most unstable modes of the Charney model and the Eady model, in which the CRWs can be derived independently of the normal modes. However, the dispersion curves for the two models are very different; the Eady model has a short-wave cut-off, while the Charney model is unstable at short wavelengths. Beyond its maximum growth rate the Charney model has a neutral point at finite wavelength (r=1). Thereafter follows a succession of unstable branches, each with weaker growth than the last, separated by neutral points at integer r—the so-called ‘Green branches’. A separate branch of westward-propagating neutral modes also originates from each neutral point. By approximating the lower CRW as a Rossby edge wave and the upper CRW structure as a single PV peak with a spread proportional to the Rossby scale height, the main features of the ‘Charney branch’ (0model where the positive PV gradient exists only at the tropopause

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We present a kinetic double layer model coupling aerosol surface and bulk chemistry (K2-SUB) based on the PRA framework of gas-particle interactions (Poschl-Rudich-Ammann, 2007). K2-SUB is applied to a popular model system of atmospheric heterogeneous chemistry: the interaction of ozone with oleic acid. We show that our modelling approach allows de-convoluting surface and bulk processes, which has been a controversial topic and remains an important challenge for the understanding and description of atmospheric aerosol transformation. In particular, we demonstrate how a detailed treatment of adsorption and reaction at the surface can be coupled to a description of bulk reaction and transport that is consistent with traditional resistor model formulations. From literature data we have derived a consistent set of kinetic parameters that characterise mass transport and chemical reaction of ozone at the surface and in the bulk of oleic acid droplets. Due to the wide range of rate coefficients reported from different experimental studies, the exact proportions between surface and bulk reaction rates remain uncertain. Nevertheless, the model results suggest an important role of chemical reaction in the bulk and an approximate upper limit of similar to 10(-11) cm(2) s(-1) for the surface reaction rate coefficient. Sensitivity studies show that the surface accommodation coefficient of the gas-phase reactant has a strong non-linear influence on both surface and bulk chemical reactions. We suggest that K2-SUB may be used to design, interpret and analyse future experiments for better discrimination between surface and bulk processes in the oleic acid-ozone system as well as in other heterogeneous reaction systems of atmospheric relevance.

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A number of urban land-surface models have been developed in recent years to satisfy the growing requirements for urban weather and climate interactions and prediction. These models vary considerably in their complexity and the processes that they represent. Although the models have been evaluated, the observational datasets have typically been of short duration and so are not suitable to assess the performance over the seasonal cycle. The First International Urban Land-Surface Model comparison used an observational dataset that spanned a period greater than a year, which enables an analysis over the seasonal cycle, whilst the variety of models that took part in the comparison allows the analysis to include a full range of model complexity. The results show that, in general, urban models do capture the seasonal cycle for each of the surface fluxes, but have larger errors in the summer months than in the winter. The net all-wave radiation has the smallest errors at all times of the year but with a negative bias. The latent heat flux and the net storage heat flux are also underestimated, whereas the sensible heat flux generally has a positive bias throughout the seasonal cycle. A representation of vegetation is a necessary, but not sufficient, condition for modelling the latent heat flux and associated sensible heat flux at all times of the year. Models that include a temporal variation in anthropogenic heat flux show some increased skill in the sensible heat flux at night during the winter, although their daytime values are consistently overestimated at all times of the year. Models that use the net all-wave radiation to determine the net storage heat flux have the best agreement with observed values of this flux during the daytime in summer, but perform worse during the winter months. The latter could result from a bias of summer periods in the observational datasets used to derive the relations with net all-wave radiation. Apart from these models, all of the other model categories considered in the analysis result in a mean net storage heat flux that is close to zero throughout the seasonal cycle, which is not seen in the observations. Models with a simple treatment of the physical processes generally perform at least as well as models with greater complexity.

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A stand-alone sea ice model is tuned and validated using satellite-derived, basinwide observations of sea ice thickness, extent, and velocity from the years 1993 to 2001. This is the first time that basin-scale measurements of sea ice thickness have been used for this purpose. The model is based on the CICE sea ice model code developed at the Los Alamos National Laboratory, with some minor modifications, and forcing consists of 40-yr ECMWF Re-Analysis (ERA-40) and Polar Exchange at the Sea Surface (POLES) data. Three parameters are varied in the tuning process: Ca, the air–ice drag coefficient; P*, the ice strength parameter; and α, the broadband albedo of cold bare ice, with the aim being to determine the subset of this three-dimensional parameter space that gives the best simultaneous agreement with observations with this forcing set. It is found that observations of sea ice extent and velocity alone are not sufficient to unambiguously tune the model, and that sea ice thickness measurements are necessary to locate a unique subset of parameter space in which simultaneous agreement is achieved with all three observational datasets.

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Coconut, Cocos nucifera L. is a major plantation crop, which ensures income for millions of people in the tropical region. Detailed molecular studies on zygotic embryo development would provide valuable clues for the identification of molecular markers to improve somatic embryogenesis. Since there is no ongoing genome project for this species, coconut expressed sequence tags (EST) would be an interesting technique to identify important coconut embryo specific genes as well as other functional genes in different biochemical pathways. The goal of this study was to analyse the ESTs by examining the transcriptome data of the different embryo tissue types together with one somatic tissue. Here, four cDNA libraries from immature embryo, mature embryo, microspore derived embryo and mature leaves were constructed. cDNA was sequenced by the Roche-454 GS-FLX system and assembled into 32621 putative unigenes and 155017 singletons. Of these unigenes, 18651 had significant sequence similarities to non-redundant protein database, from which 16153 were assigned to one or more gene ontology categories. Homologue genes, which are responsible for embryo development such as chitinase, beta-1,3-glucanase, ATP synthase CF0 subunit, thaumatin-like protein and metallothionein-like protein were identified among the embryo EST collection. Of the unigenes, 6694 were mapped into 139 KEGG pathways including carbohydrate metabolism, energy metabolism, lipid metabolism, amino acid metabolism and nucleotide metabolism. This collection of 454-derived EST data generated from different tissue types provides a significant resource for genome wide studies and gene discovery of coconut, a non-model species.

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The general 1-D theory of waves propagating on a zonally varying flow is developed from basic wave theory, and equations are derived for the variation of wavenumber and energy along ray paths. Different categories of behaviour are found, depending on the sign of the group velocity (cg) and a wave property, B. For B positive the wave energy and the wave number vary in the same sense, with maxima in relative easterlies or westerlies, depending on the sign of cg. Also the wave accumulation of Webster and Chang (1988) occurs where cg goes to zero. However for B negative they behave in opposite senses and wave accumulation does not occur. The zonal propagation of the gravest equatorial waves is analysed in detail using the theory. For non-dispersive Kelvin waves, B reduces to 2, and analytic solution is possible. B is positive for all the waves considered, except for the westward moving mixed Rossby-gravity (WMRG) wave which can have negative as well as positive B. Comparison is made between the observed climatologies of the individual equatorial waves and the result of pure propagation on the climatological upper tropospheric flow. The Kelvin wave distribution is in remarkable agreement, considering the approximations made. Some aspects of the WMRG and Rossby wave distributions are also in qualitative agreement. However the observed maxima in these waves in the winter westerlies in the eastern Pacific and Atlantic are not consistent with the theory. This is consistent with the importance of the sources of equatorial waves in these westerly duct regions due to higher latitude wave activity.

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This paper critically reviews the application of a post-development analysis to sustainable development by employing a defined target for post-development analysis – the Environmental Kuznets Curve (EKC). Data from the 2005 Environmental Sustainability Index (ESI) for 146 countries are used to generate statistically significant EKC models, and the approach is deconstructed by employing post-development theory. While an ESI derived EKC is an easy target for post-development critique, there are foundations upon which both rest, and are not easily dismissed. Neither is the typical post-development 'alternative' of encouraging 'endogenous discourse' and grassroots movements at odds with sustainable development. As a result, this paper argues that sustainable development theory already incorporates much of the critique and alternatives raised by post-developmentalists. Indeed, what is more disconcerting is that sustainable development readily encompasses such apparently divergent ideas represented by the ESI, EKC and post-developmental critique and solutions.

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It is sometimes argued that experimental economists do not have to worry about external validity so long as the design sticks closely to a theoretical model. This position mistakes the model for the theory. As a result, applied economics designs often study phenomena distinct from their stated objects of inquiry. Because the implemented models are abstract, they may provide improbable analogues to their stated subject matter. This problem is exacerbated by the relational character of the social world, which also sets epistemic limits for the social science laboratory more generally.

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Measured process data normally contain inaccuracies because the measurements are obtained using imperfect instruments. As well as random errors one can expect systematic bias caused by miscalibrated instruments or outliers caused by process peaks such as sudden power fluctuations. Data reconciliation is the adjustment of a set of process data based on a model of the process so that the derived estimates conform to natural laws. In this paper, techniques for the detection and identification of both systematic bias and outliers in dynamic process data are presented. A novel technique for the detection and identification of systematic bias is formulated and presented. The problem of detection, identification and elimination of outliers is also treated using a modified version of a previously available clustering technique. These techniques are also combined to provide a global dynamic data reconciliation (DDR) strategy. The algorithms presented are tested in isolation and in combination using dynamic simulations of two continuous stirred tank reactors (CSTR).

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Consideration is given to a standard CDMA system and determination of the density function of the interference with and without Gaussian noise using sampling theory concepts. The formula derived provides fast and accurate results and is a simple, useful alternative to other methods

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The domestic (residential) sector accounts for 30% of the world’s energy consumption hence plays a substantial role in energy management and CO2 emissions reduction efforts. Energy models have been generally developed to mitigate the impact of climate change and for the sustainable management and planning of energy resources. Although there are different models and model categories, they are generally categorised into top down and bottom up. Significantly, top down models are based on aggregated data while bottom up models are based on disaggregated data. These approaches create fundamental differences which have been the centre of debate since the 1970’s. These differences have led to noticeable discrepancies in results which have led to authors arguing that the models are of a more complementary than a substituting nature. As a result developing methods suggest that there is the need to integrate either the two models (bottom up − top down) or aspects that combine two bottom up models or an upgrade of top down models to compensate for the documented limitations. Diverse schools of thought argue in favour of these integrations – currently known as hybrid models. In this paper complexities of identifying country specific and/or generic domestic energy models and their applications in different countries have been critically reviewed. Predominantly from the review it is evident that most of these methods have been adapted and used in the ‘western world’ with practically no such applications in Africa.

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A one-dimensional surface energy-balance lake model, coupled to a thermodynamic model of lake ice, is used to simulate variations in the temperature of and evaporation from three Estonian lakes: Karujärv, Viljandi and Kirjaku. The model is driven by daily climate data, derived by cubic-spline interpolation from monthly mean data, and was run for periods of 8 years (Kirjaku) up to 30 years (Viljandi). Simulated surface water temperature is in good agreement with observations: mean differences between simulated and observed temperatures are from −0.8°C to +0.1°C. The simulated duration of snow and ice cover is comparable with observed. However, the model generally underpredicts ice thickness and overpredicts snow depth. Sensitivity analyses suggest that the model results are robust across a wide range (0.1–2.0 m−1) of lake extinction coefficient: surface temperature differs by less than 0.5°C between extreme values of the extinction coefficient. The model results are more sensitive to snow and ice albedos. However, changing the snow (0.2–0.9) and ice (0.15–0.55) albedos within realistic ranges does not improve the simulations of snow depth and ice thickness. The underestimation of ice thickness is correlated with the overestimation of snow cover, since a thick snow layer insulates the ice and limits ice formation. The overestimation of snow cover results from the assumption that all the simulated winter precipitation occurs as snow, a direct consequence of using daily climate data derived by interpolation from mean monthly data.

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A ground source heat pump assisted by an array of photovoltaic (PV)-thermal modules was studied in this work. Extracting heat from an array of PV modules should improve the performance of both the PV cells and the heat pump. A series of computer simulations compare the performance of a ground source heat pump with a short ground circuit, used to provide space heating and domestic hot water at a house in southern England. The results indicate that extracting heat from an array of PV-thermal modules would improve the performance of a ground source heat pump with an undersized ground loop. Nevertheless, open air thermal collectors could be more effective, especially during winter. In one model more electricity was saved in ohmic heating than was generated by cooling the PV cells. Cooling the PV modules was found to increase their electrical output up to 4%, but much of the extra electricity was consumed by the cooling pumps.