From imagery to intention: A dual route model of imagined contact effects

Imagined intergroup contact (Crisp & R. Turner, 2009) is a new indirect contact strategy for promoting tolerance and more positive intergroup relations. In this chapter, we review existing research on imagined contact and propose two routes-cognitive and affective-through which it can exert a positive influence on contact-related attitudes and intentions. We first review research that has established the beneficial impacts of imagined contact on intergroup attitudes via reduced intergroup anxiety, supporting its efficacy as an intervention where there exists little or no opportunity for direct contact. We then review more recent research showing that imagined contact not only improves attitudes, but can also enhance intentions to engage in future contact. These studies suggest that contact imagery provides a behavioural script that forms the cognitive basis for subsequent judgements about future contact intentions. Collectively, the findings from this research programme support the idea that imagined contact can complement more direct forms of contact-providing a way of initially encouraging an interest in engaging positively with outgroups before introducing face-to-face encounters. We discuss the implications of these findings for future theory and research, and how they can inform prejudice-reduction interventions seeking to capitalise on the beneficial effects of mental imagery.

Integrating intrinsic and global kinetics as a dual kinetic model for automotive catalysis

The majority of the kinetic models employed in catalytic after-treatment of exhaust emissions use a global kinetic approach owing to the simplicity because one expression can account for all the steps in a reaction. The major drawback of this approach is the limited predictive capabilities of the models. The intrinsic kinetic approach offers much more information about the processes occurring within the catalytic converter; however, it is significantly more complex and time consuming to develop. In the present work, a methodology which allows accessing a model that combines the simplicity of the global kinetic approach and the accuracy of the intrinsic kinetic approach is reported. To assess the performance of this new approach, the oxidation of carbon monoxide in the presence of nitric oxide as well as a driving cycle was investigated. The modelling of carbon monoxide oxidation with oxygen which utilised the intrinsic kinetic approach with the global kinetic approach was used for the carbon monoxide + nitric oxide reaction (and all remaining reactions for the driving cycle). The comparison of the model results for the dual intrinsic + global kinetic approach with the experimental data obtained for both the reactor and the driving cycle indicate that the dual approach is promising with results significantly better than those obtained with only the global kinetics approach.

The stress process in palliative cancer care:A qualitative study on informal caregiving and its implication for the delivery of care

Objective: The primary objective of this study was to examine how the comprehensive nature of the Stress Process Model could elucidate on the stressors associated with caring for a palliative cancer patient. Method: A qualitative research strategy involving home-based face-to-face interviews with 12 bereaved family caregivers was used to examine the caregiving experience. Results: The primary stressors associated with caring for the palliative cancer care patients stemmed from care recipient symptoms and personal care needs. The absence of adequate support from the formal health care delivery system was a consistent message from all participants. There was evidence of financial stress primarily associated with the purchase of private home care to supplement formal care. In contrast, the resources that family caregivers relied on to moderate the stressful effects of caregiving included extended family, friends, and neighbors. While the stress of direct caregiving was high, the study revealed that formal care was also a significant source of stress for family caregivers. Conclusion: It was concluded that an appropriately financed, integrated system of care that followed a person-centered philosophy of care would best meet the needs of the patient and his or her family. © The Author(s) 2010.

Stress processes in caring for an end-of-life family member:Application of a theoretical model

Objectives: Family caregivers play a vital role in maintaining the lives of individuals with advanced illness living in the community. However, the responsibility of caregiving for an end-of-life family member can have profound consequences on the psychological, physical and financial well-being of the caregiver. While the literature has identified caregiver stress or strain as a complex process with multiple contributing factors, few comprehensive studies exist. This study examined a wide range of theory-driven variables contributing to family caregiver stress. Method: Data variables from interviews with primary family caregivers were mapped onto the factors within the Stress Process Model theoretical framework. A hierarchical multiple linear regression analysis was used to determine the strongest predictors of caregiver strain as measured by a validated composite index, the Caregiver Strain Index. Results: The study included 132 family caregivers across south-central/western Ontario, Canada. About half of these caregivers experienced high strain, the extent of which was predicted by lower perceived program accessibility, lower functional social support, greater weekly amount of time caregivers committed to the care recipient, younger caregiver age and poorer caregiver self-perceived health. Conclusion: This study examined the influence of a multitude of factors in the Stress Process Model on family caregiver strain, finding stress to be a multidimensional construct. Perceived program accessibility was the strongest predictor of caregiver strain, more so than intensity of care, highlighting the importance of the availability of community resources to support the family caregiving role.

Special condition wind power forecasting based on Gaussian process and similar historical data

Due to the variability of wind power, it is imperative to accurately and timely forecast the wind generation to enhance the flexibility and reliability of the operation and control of real-time power. Special events such as ramps, spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken from both the local time and historic dataset is proposed and applied to make short-term predictions from 10 minutes to one hour ahead. A key idea is that the similar pattern data in history are properly selected and embedded in Gaussian Process model to make predictions. The results of the proposed algorithms are compared to those of standard Gaussian Process model and the persistence model. It is shown that the proposed method not only reduces magnitude error but also phase error.

An optimized process design for oxymethylene ether production from woody-biomass-derived syngas

The conversion of biomass for the production of liquid fuels can help reduce the greenhouse gas (GHG) emissions that are predominantly generated by the combustion of fossil fuels. Oxymethylene ethers (OMEs) are a series of liquid fuel additives that can be obtained from syngas, which is produced from the gasification of biomass. The blending of OMEs in conventional diesel fuel can reduce soot formation during combustion in a diesel engine. In this research, a process for the production of OMEs from woody biomass has been simulated. The process consists of several unit operations including biomass gasifi- cation, syngas cleanup, methanol production, and conversion of methanol to OMEs. The methodology involved the development of process models, the identification of the key process parameters affecting OME production based on the process model, and the development of an optimal process design for high OME yields. It was found that up to 9.02 tonnes day1 of OME3, OME4, and OME5 (which are suitable as diesel additives) can be produced from 277.3 tonnes day1 of wet woody biomass. Furthermore, an optimal combination of the parameters, which was generated from the developed model, can greatly enhance OME production and thermodynamic efficiency. This model can further be used in a techno- economic assessment of the whole biomass conversion chain to produce OMEs. The results of this study can be helpful for petroleum-based fuel producers and policy makers in determining the most attractive pathways of converting bio-resources into liquid fuels.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Implicit and explicit processes in a hypothesis testing task

We present the results of two experiments investigating the factors that determine responding on the pseudo-diagnosticity task. In Expt I we manipulated people's beliefs about the degree to which an initial piece of evidence supported a focal hypothesis and found decreased pseudo-diagnostic (PD) responding when the evidence offered low support for the focal hypothesis. In Expt 2 we manipulated the instructions given to participants. We found that instructions to select evidence to help decide between the focal and the complementary hypotheses produced fewer PD responses than both instructions to decide whether the focal hypothesis was the case and instructions to decide whether its complement was the case. The results are interpreted within the framework of recent dual process theories of reasoning.

Exploring the adoption and implementation of discrete and integrated IT systems: A Framework for analysis

Despite the substantial organisational benefits of integrated IT, the implementation of such systems – and particularly Enterprise Resource Planning (ERP) systems – has tended to be problematic, stimulating an extensive body of research into ERP implementation. This research has remained largely separate from the main IT implementation literature. At the same time, studies of IT implementation have generally adopted either a factor or process approach; both have major limitations. To address these imitations, factor and process perspectives are combined here in a unique model of IT implementation. We argue that • the organisational factors which determine successful implementation differ for integrated and traditional, discrete IT • failure to manage these differences is a major source of integrated IT failure. The factor/process model is used as a framework for proposing differences between discrete and integrated IT.

”Bricks vs. Clicks”: The impact of manufacturer encroachment with a dealer leasing and selling of durable goods

In durable goods markets, many brand name manufacturers, including IBM, HP, Epson, and Lenovo, have adopted dual-channel supply chains to market their products. There is scant literature, however, addressing the product durability and its impact on players’ optimal strategies in a dual-channel supply chain. To fill this void, we consider a two-period dual-channel model in which a manufacturer sells a durable product directly through both a manufacturer-owned e-channel and an independent dealer who adopts a mix of selling and leasing to consumers. Our results show that the manufacturer begins encroaching into the market in Period 1, but the dealer starts withdrawing from the retail channel in Period 2. Moreover, as the direct selling cost decreases, the equilibrium quantities and wholesale prices become quite angular and often nonmonotonic. Among other results, we find that both the dealer and the supply chain may benefit from the manufacturer’s encroachment. Our results also indicate that both the market structure and the nature of competition have an important impact on the player’s (dealer’s) optimal choice of leasing and selling.