887 resultados para Specific theories and interaction models


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Service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific self-service technology (SST), the personal shopping assistant (PSA), and estimates retailer benefits from implementing that innovation. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the technology acceptance model (TAM), this study develops specific hypotheses and tests them on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device. Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in-store service innovations. Incorporation of technology within physical stores affords opportunities for the retailer to reduce costs, while enhancing service provided to consumers. Therefore, service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific SST in the retail context, the PSA, and estimates retailer benefits from implementing that innovation. In so doing, the study contributes to the nascent area of research on SSTs in the retail sector. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the TAM, this study develops specific hypotheses regarding the (1) antecedent effects of technological anxiety, novelty seeking, market mavenism, and trust in the retailer on trial of the service innovation; (2) the effects of ease of use, perceived waiting time, and need for interaction on continuous use of the innovation; and (3) the effect of use of innovation on consumer spending at the store. The hypotheses were tested on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device, one of the early adopters of PSA in Germany. Data were analyzed using logistic regression (antecedents of trial), multiple regression (antecedents of continuous use), and propensity score matching (assessing retailer benefits). Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use, while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in-store service innovations. The study contributes to the literature through its (1) simultaneous examination of antecedents of trial and continuous usage of a specific SST, (2) the demonstration of economic benefits of SST introduction for the retailer, and (3) contribution to the stream of research on service innovation, as against product innovation.

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The notion model of development and distribution of software (MDDS) is introduced and its role for the efficiency of the software products is stressed. Two classical MDDS are presented and some attempts to adapt them to the contemporary trends in web-based software design are described. Advantages and shortcomings of the obtained models are outlined. In conclusion the desired features of a better MDDS for web-based solutions are given.

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The conceptual foundations of the models and procedures for prediction of the avalanche-dangerous situations initiation are considered. The interpretation model for analysis of the avalanche-dangerous situations initiation based on the definition of probabilities of correspondence of studied parameters to the probabilistic distributions of avalanche-dangerous or avalanche non-dangerous situations is offered. The possibility to apply such a model to the real data is considered. The main approaches to the use of multiple representations for the avalanche dangerous situations initiation analysis are generalized.

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eLearning at universities is taking an increasingly larger part of academic teaching methodologies. In part this is caused by different pedagogical concepts behind interactive learning system, in part it is because of larger numbers of students that can be reached within one given course and, most important, actively integrated into the teaching process. We present here the development of a novel concept of teaching, allowing students to explore theoretical and experimental aspects of act of magnetic field on moving charge through real experiments and simulation. This problem is not only part of the basic education of physics students, but also element of the academic education of almost all engineers.

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This article describes methodology for training teachers in Maths, Physics, Astronomy and Professional subjects in basic and specific computer skills.

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In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning implementation, which are used in some contemporary web-interfaced Learning Management Systems (LMSs). The problem is not how to create electronic learning materials, but how to locate and utilize the available information in personalized way. Different attitudes to personalization are briefly described in section 1. The real personalization requires a user profile containing information about preferences, aims, and educational history to be stored and used by the system. These issues are considered in section 2. A method for development and design of adaptive learning content in terms of learning strategy system support is represented in section 3. Section 4 includes a set of innovative personalization services that are suggested by several very important research projects (SeLeNe project, ELENA project, etc.) dated from the last few years. This section also describes a model for role- and competency-based learning customization that uses Web Services approach. The last part presents how personalization techniques are implemented in Learning Grid-driven applications.

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* This work was financially supported by the Russian Foundation for Basic Research, project no. 04-01-00858a.

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Our approach for knowledge presentation is based on the idea of expert system shell. At first we will build a graph shell of both possible dependencies and possible actions. Then, reasoning by means of Loglinear models, we will activate some nodes and some directed links. In this way a Bayesian network and networks presenting loglinear models are generated.

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In a complicated business network finding a supplier can be a very time consuming task. The technology of competence management is aimed to support such kind of tasks. The paper presents an approach to support interaction between business network members based on such technologies as competence management and knowledge management. The conceptual models of the context-driven competence management system and production network member competence profile are described. The usage of the competence management system is illustrated via an example from automotive industry.

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Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

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Cryptococcus neoformans is an opportunistic fungal pathogen that causes significant disease worldwide. Even though this fungus has not evolved specifically to cause human disease, it has a remarkable ability to adapt to many different environments within its infected host. C. neoformans adapts by utilizing conserved eukaryotic and fungal-specific signaling pathways to sense and respond to stresses within the host. Upon infection, two of the most significant environmental changes this organism experiences are elevated temperature and high pH.

Conserved Rho and Ras family GTPases are central regulators of thermotolerance in C. neoformans. Many GTPases require prenylation to associate with cellular membranes and function properly. Using molecular genetic techniques, microscopy, and infection models, I demonstrated that the prenyltransferase, geranylgeranyl transferase I (GGTase I) is required for thermotolerance and pathogenesis. Using fluorescence microscopy, I found that only a subset of conserved GGTase I substrates requires this enzyme for membrane localization. Therefore, the C. neoformans GGTase I may recognize its substrate in a slightly different manner than other eukaryotic organisms.

The alkaline response transcription factor, Rim101, is a central regulator of stress-response genes important for adapting to the host environment. In particular, Rim101 regulates cell surface alterations involved in immune avoidance. In other fungi, Rim101 is activated by alkaline pH through a conserved signaling pathway, but this pathway had yet been characterized in C. neoformans. Using molecular genetic techniques, I identified and analyzed the conserved members of the Rim pathway. I found that it was only partially conserved in C. neoformans, missing the components that sense pH and initiate pathway activation. Using a genetic screen, I identified a novel Rim pathway component named Rra1. Structural prediction and genetic epistasis experiments suggest that Rra1 may serve as the Rim pathway pH sensor in C. neoformans and other related basidiomycete fungi.

To explore the relevance of Rim pathway signaling in the interaction of C neoformans with its host, I characterized the Rim101-regulated cell wall changes that prevent immune detection. Using HPLC, enzymatic degradation, and cell wall stains, I found that the rim101Δ mutation resulted in increased cell wall chitin exposure. In vitro co-culture assays demonstrated that increased chitin exposure is associated with enhanced activation of macrophages and dendritic cells. To further test this association, I demonstrated that other mutant strains with increased chitin exposure induce macrophage and dendritic cell responses similar to rim101Δ. We used primary macrophages from mutant mouse lines to demonstrate that members of both the Toll-like receptor and C-type lectin receptor families are involved in detecting strains with increased chitin exposure. Finally, in vivo immunological experiments demonstrated that the rim101Δ strain induced a global inflammatory immune response in infected mouse lungs, expanding upon our previous in vivo rim101Δ studies. These results demonstrate that cell wall organization largely determines how fungal cells are detected by the immune system.

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At all normative levels, family migration law can disproportionally and negatively affect immigrant women’s rights in this field, producing gendered effects. In some cases, such effects are related to the normative and judicial imposition of unviable family-related models (e.g., the ʻgood mother ̕ the one-breadwinner family, or a rigid distinction between productive and reproductive work). In other cases, they are due to family migration law’s overlooking of the specific needs and difficulties of immigrant women, within their families and in the broader context of their host countries’ social and normative framework.To effectively expose and correct this gender bias, in this article I propose an alternative view of immigrant women’s right to family life, as a cluster of rights and entitlements rather than as a mono-dimensional right. As a theoretical approach, this construction is better equipped to capture the complex experiences of immigrant women in the European legal space, and to shed light on the gendered effects generated not by individual norms but by the interaction of norms that are traditionally assigned to separated legal domains (e.g., immigration law and criminal law). As a judicial strategy, this understanding is capable of prompting a consideration by domestic and supranational courts of immigrant women not as isolated individuals, but as ‘individuals in context’. I shall define this type of approach as ‘contextual interpretation’, understood as the consideration of immigrant women in the broader contexts of their families, their host societies and the normative frameworks applicable to them. Performed in a gendersensitive manner, a contextual judicial interpretation has the potential to neutralize the gendered effects of certain family migration norms. To illustrate these points, I will discuss selected judicial examples offered by the European Court on Human Rights, as well as from domestic jurisdictions of countries with a particularly high incidence of immigrant women (Italy and Spain).

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This thesis focused on medical students’ language learning strategies for patient encounters. The research questions concerned the types of learning strategies that medical students use and the differences between the preclinical students and the clinical students, two groups who have had varying amounts of experience with patients. Additionally, strategy use was examined through activity systems to gain information on the context of language learning strategy use in order to learn language for patient encounters. In total, 130 first-year medical students (preclinical) and 39 fifth-year medical students (clinical) participated in the study by filling in a questionnaire on language learning strategies. In addition, two students were interviewed in order to create activity systems for the medical students at different stages of their studies. The study utilised both quantitative and qualitative research methods; the analysis of the results relies on Oxford’s Strategic Self-Regulation Model in the quantitative part and on activity theory in the qualitative part. The theoretical sections of the study introduced earlier research and theories regarding English for specific purposes, language learning strategies and activity theory. The results indicated that the medical students use affective, sociocultural-interactive and metasociocultural-interactive strategies often and avoid using negative strategies, which hinder language learning or cease communication altogether. Slight differences between the preclinical and clinical students were found, as clinical students appear to use affective and metasociocultural-interactive strategies more frequently compared to the preclinical students. The activity systems of the two students interviewed were rather similar. The students were at different stages of their studies, but their opinions were very similar. Both reported the object of learning to be mutual understanding between the patient and the doctor, which in part explains the preference for strategies that support communication and interaction. The results indicate that the nature of patient encounters affects the strategy use of the medical students at least to some extent.

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Chains of interacting non-Abelian anyons with local interactions invariant under the action of the Drinfeld double of the dihedral group D-3 are constructed. Formulated as a spin chain the Hamiltonians are generated from commuting transfer matrices of an integrable vertex model for periodic and braided as well as open boundaries. A different anyonic model with the same local Hamiltonian is obtained within the fusion path formulation. This model is shown to be related to an integrable fusion interaction round the face model. Bulk and surface properties of the anyon chain are computed from the Bethe equations for the spin chain. The low-energy effective theories and operator content of the models (in both the spin chain and fusion path formulation) are identified from analytical and numerical studies of the finite-size spectra. For all boundary conditions considered the continuum theory is found to be a product of two conformal field theories. Depending on the coupling constants the factors can be a Z(4) parafermion or a M-(5,M-6) minimal model.

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Experiments with ultracold atoms in optical lattice have become a versatile testing ground to study diverse quantum many-body Hamiltonians. A single-band Bose-Hubbard (BH) Hamiltonian was first proposed to describe these systems in 1998 and its associated quantum phase-transition was subsequently observed in 2002. Over the years, there has been a rapid progress in experimental realizations of more complex lattice geometries, leading to more exotic BH Hamiltonians with contributions from excited bands, and modified tunneling and interaction energies. There has also been interesting theoretical insights and experimental studies on “un- conventional” Bose-Einstein condensates in optical lattices and predictions of rich orbital physics in higher bands. In this thesis, I present our results on several multi- band BH models and emergent quantum phenomena. In particular, I study optical lattices with two local minima per unit cell and show that the low energy states of a multi-band BH Hamiltonian with only pairwise interactions is equivalent to an effec- tive single-band Hamiltonian with strong three-body interactions. I also propose a second method to create three-body interactions in ultracold gases of bosonic atoms in a optical lattice. In this case, this is achieved by a careful cancellation of two contributions in the pair-wise interaction between the atoms, one proportional to the zero-energy scattering length and a second proportional to the effective range. I subsequently study the physics of Bose-Einstein condensation in the second band of a double-well 2D lattice and show that the collision aided decay rate of the con- densate to the ground band is smaller than the tunneling rate between neighboring unit cells. Finally, I propose a numerical method using the discrete variable repre- sentation for constructing real-valued Wannier functions localized in a unit cell for optical lattices. The developed numerical method is general and can be applied to a wide array of optical lattice geometries in one, two or three dimensions.