Energy transfer and frequency upconversion involving triads of Pr3+ ions in (Pr3+, Gd3+) doped fluoroindate glass

Blue and ultraviolet luminescence in (Pr3+, Gd3+) doped fluoroindate glass is studied for excitation in the red region (≈590 nm). Frequency upconversion (UC) is observed due to energy transfer (ET) among three Pr3+ ions initially excited to the D21 state corresponding to the ET process D21 + D21 + D21 → S01 + H53 + H53. Additionally, UC luminescence from states P 72 6 and I 72 6 of Gd3+ is observed for an excitation wavelength resonant with transitions of the Pr3+ ions. The characterization of the luminescence signals allowed to determine ET rate among the Pr3+ ions and provides evidence of interconfigurational ET between Gd3+ and Pr3+ ions. © 2006 American Institute of Physics.

Frequency upconversion involving triads and quartets of ions in a Pr3+/Nd3+ codoped fluoroindate glass

Frequency upconversion (UC) processes involving energy transfer (ET) among Nd 3+ and Pr 3+ ions in a fluoroindate glass are reported. In a first experiment, the excitation of Pr 3+ [transition 3H 4→ 1D 2] and of Nd 3+ [transition 4I 9/2→( 2G 7/2+ 4G 5/2)] was achieved with a dye laser operating in the 575-590 nm range. In a second experiment, the Nd 3+ ions were excited with the second harmonic of a Nd: YAG laser at 532 nm. The ET processes leading to UC in both experiments were studied by monitoring the blue fluorescence decay at 480 nm due to the transition 3P 0→ 3H 4 in Pr 3+. In the more relevant UC process, quartets of ions (Nd-Nd-Pr-Pr) are excited due to absorption of three laser photons by two Nd 3+ ions which transfer their energy to two Pr 3+ ions. Each Pr 3+ ion promoted to the 3P 0 level decays to the ground state emitting one photon in the blue region. This conclusion was achieved investigating the dependence of the UC fluorescence intensity as a function of laser intensity, samples concentrations, and temporal behavior of the UC signal. Other UC processes involving nonisoionic groups of three ions are also reported. © 2002 American Institute of Physics.

Reducing wastewater from cucumber pickling process by controlled culture fermentation / by Linda W. Little ... [et al.].

Mode of access: Internet.

Towards a Business Process Management Maturity Model

Business Process Management (BPM) has been identified as the number one business priority by a recent Gartner study (Gartner, 2005). However, BPM has a plethora of facets as its origins are in Business Process Reengineering, Process Innovation, Process Modelling, and Workflow Management to name a few. Organisations increasingly recognize the requirement for an increased process orientation and require appropriate comprehensive frameworks, which help to scope and evaluate their BPM initiative. This research project aims toward the development of a holistic and widely accepted BPM maturity model, which facilitates the assessment of BPM capabilities. This paper provides an overview about the current model with a focus on the actual model development utilizing a series of Delphi studies. The development process includes separate studies that focus on further defining and expanding the six core factors within the model, i.e. strategic alignment, governance, method, Information Technology, people and culture.

The importance of gestation process dynamics

Principal Topic In this paper we seek to highlight the important intermediate role that the gestation process plays in entrepreneurship by examining its key antecedents and its consequences for new venture emergence. In doing so we take a behavioural perspective and argue that it is not only what a nascent venture is, but what it does (Katz & Gartner, 1988; Shane & Delmar, 2004; Reynolds, 2007) and when it does it during start-up (Reynolds & Miller, 1992; Lichtenstein, Carter, Dooley & Gartner, 2007) that is important. To extend an analogy from biological development, what we suggest is that the way a new venture is nurtured is just as fundamental as its nature. Much prior research has focused on the nature of new ventures and attempted to attribute variations in outcomes directly to the impact resource endowments and investments have. While there is little doubt that venture resource attributes such as human capital, and specifically prior entrepreneurial experience (Alsos & Kolvereid, 1998), access to social (Davidsson & Honig, 2003) and financial capital have an influence. Resource attributes themselves are distal from successful start-up endeavours and remain inanimate if not for the actions of the nascent venture. The key contribution we make is to shift focus from whether or not actions are taken, but when these actions happen and how that is situated in the overall gestation process. Thus, we suggest that it is gestation process dynamics, or when gestation actions occur, that is more proximal to venture outcomes and we focus on this. Recently scholars have highlighted the complexity that exists in the start-up or gestation process, be it temporal or contextual (Liao, Welsch & Tan, 2005; Lichtenstein et al. 2007). There is great variation in how long a start-up process might take (Reynolds & Miller, 1992), some processes require less action than others (Carter, Gartner & Reynolds, 1996), and the overall intensity of the start-up effort is also deemed important (Reynolds, 2007). And, despite some evidence that particular activities are more influential than others (Delmar & Shane, 2003), the order in which events may happen is, until now, largely indeterminate as regard its influence on success (Liao & Welsch, 2008). We suggest that it is this complexity of the intervening gestation process that attenuates the effect of resource endowment and has resulted in mixed findings in previous research. Thus, in order to reduce complexity we shall take a holistic view of the gestation process and argue that it is its’ dynamic properties that determine nascent venture attempt outcomes. Importantly, we acknowledge that particular gestation processes of themselves would not guarantee successful start-up, but it is more correctly the fit between the process dynamics and the ventures attributes (Davidsson, 2005) that is influential. So we aim to examine process dynamics by comparing sub-groups of venture types by resource attributes. Thus, as an initial step toward unpacking the complexity of the gestation process, this paper aims to establish the importance of its role as an intermediary between attributes of the nascent venture and the emergence of that venture. Here, we make a contribution by empirically examining gestation process dynamics and their fit with venture attributes. We do this by firstly, examining that nature of the influence that venture attributes such as human and social capital have on the dynamics of the gestation process, and secondly by investigating the effect that gestation process dynamics have on venture creation outcomes. Methodology and Propositions In order to explore the importance that gestation processes dynamics have in nascent entrepreneurship we conduct an empirical study of ventures start-ups. Data is drawn from a screened random sample of 625 Australian nascent business ventures prior to them achieving consistent outcomes in the market. This data was collected during 2007/8 and 2008/9 as part of the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) project (Davidsson et al., 2008). CAUSEE is a longitudinal panel study conducted over four years, sourcing information from annually administered telephone surveys. Importantly for our study, this methodology allows for the capture and tracking of active nascent venture creation as it happens, thus reducing hindsight and selection biases. In addition, improved tests of causality may be made given that outcome measures are temporally removed from preceding events. The data analysed in this paper represents the first two of these four years, and for the first time has access to follow-up outcome measures for these venture attempts: where 260 were successful, 126 were abandoned, and 191 are still in progress. With regards to venture attributes as gestation process antecedents, we examine specific human capital measured as successful prior experience in entrepreneurship, and direct social capital of the venture as ‘team start-ups’. In assessing gestation process dynamics we follow Lichtenstein et al. (2007) to suggest that the rate, concentration and timing of gestation activities may be used to summarise the complexity dynamics of that process. In addition, we extend this set of measures to include the interaction of discovery and exploitation by way of changes made to the venture idea. Those ventures with successful prior experience or those who conduct symbiotic parallel start-up attempts may be able to, or be forced to, leave their gestation action until later and still derive a successful outcome. In addition access to direct social capital may provide the support upon which the venture may draw in order to persevere in the face of adversity, turning a seemingly futile start-up attempt into a success. On the other hand prior experience may engender the foresight to terminate a venture attempt early should it be seen to be going nowhere. The temporal nature of these conjectures highlight the importance that process dynamics play and will be examined in this research Statistical models are developed to examine gestation process dynamics. We use multivariate general linear modelling to analyse how human and social capital factors influence gestation process dynamics. In turn, we use event history models and stratified Cox regression to assess the influence that gestation process dynamics have on venture outcomes. Results and Implications What entrepreneurs do is of interest to both scholars and practitioners’ alike. Thus the results of this research are important since they focus on nascent behaviour and its outcomes. While venture attributes themselves may be influential this is of little actionable assistance to practitioners. For example it is unhelpful to say to the prospective first time entrepreneur “you’ll be more successful if you have lots of prior experience in firm start-ups”. This research attempts to close this relevance gap by addressing what gestation behaviours might be appropriate, when actions best be focused, and most importantly in what circumstances. Further, we make a contribution to the entrepreneurship literature, examining the role that gestation process dynamics play in outcomes, by specifically attributing these to the nature of the venture itself. This extension is to the best of our knowledge new to the research field.

A new look at leadership in collaborative networks : process catalysts

Collaborative networks have come to form a large part of the public sector’s strategy to address ongoing and often complex social problems. The relational power of networks, with its emphasis on trust, reciprocity and mutuality provides the mechanism to integrate previously dispersed and even competitive entities into a collective venture(Agranoff 2003; Agranoff and McGuire 2003; Mandell 1994; Mandell and Harrington 1999). It is argued that the refocusing of a single body of effort to a collective contributes to reducing duplication and overlap of services, maximizes increasingly scarce resources and contributes to solving intractable or 'wicked’problems (Clarke and Stewart 1997). Given the current proliferation of collaborative networks and the fact that they are likely to continue for some time, concerns with the management and leadership of such arrangements for optimal outcomes are increasingly relevant. This is especially important for public sector managers who are used to working in a top-down, hierarchical manner. While the management of networks (Agranoff and McGuire 2001, 2003), including collaborative or complex networks (Kickert et al. 1997; Koppenjan and Klijn 2004), has been the subject of considerable attention, there has been much less explicit discussion on leadership approaches in this context. It is argued in this chapter that the traditional use of the terms ‘leader’ or ‘leadership’ does not apply to collaborative networks. There are no ‘followers’ in collaborative networks or supervisor-subordinate relations. Instead there are equal, horizontal relationships that are focused on delivering systems change. In this way the emergent organizational forms such as collaborative networks challenge older models of leadership. However despite the questionable relevance of old leadership styles to the contemporary work environment, no clear alternative has come along to take its place.

Modelling issues on the railway resource management process using multi-agent system

Many infrastructure and necessity systems such as electricity and telecommunication in Europe and the Northern America were used to be operated as monopolies, if not state-owned. However, they have now been disintegrated into a group of smaller companies managed by different stakeholders. Railways are no exceptions. Since the early 1980s, there have been reforms in the shape of restructuring of the national railways in different parts of the world. Continuous refinements are still conducted to allow better utilisation of railway resources and quality of service. There has been a growing interest for the industry to understand the impacts of these reforms on the operation efficiency and constraints. A number of post-evaluations have been conducted by analysing the performance of the stakeholders on their profits (Crompton and Jupe 2003), quality of train service (Shaw 2001) and engineering operations (Watson 2001). Results from these studies are valuable for future improvement in the system, followed by a new cycle of post-evaluations. However, direct implementation of these changes is often costly and the consequences take a long period of time (e.g. years) to surface. With the advance of fast computing technologies, computer simulation is a cost-effective means to evaluate a hypothetical change in a system prior to actual implementation. For example, simulation suites have been developed to study a variety of traffic control strategies according to sophisticated models of train dynamics, traction and power systems (Goodman, Siu and Ho 1998, Ho and Yeung 2001). Unfortunately, under the restructured railway environment, it is by no means easy to model the complex behaviour of the stakeholders and the interactions between them. Multi-agent system (MAS) is a recently developed modelling technique which may be useful in assisting the railway industry to conduct simulations on the restructured railway system. In MAS, a real-world entity is modelled as a software agent that is autonomous, reactive to changes, able to initiate proactive actions and social communicative acts. It has been applied in the areas of supply-chain management processes (García-Flores, Wang and Goltz 2000, Jennings et al. 2000a, b) and e-commerce activities (Au, Ngai and Parameswaran 2003, Liu and You 2003), in which the objectives and behaviour of the buyers and sellers are captured by software agents. It is therefore beneficial to investigate the suitability or feasibility of applying agent modelling in railways and the extent to which it might help in developing better resource management strategies. This paper sets out to examine the benefits of using MAS to model the resource management process in railways. Section 2 first describes the business environment after the railway 2 Modelling issues on the railway resource management process using MAS reforms. Then the problems emerge from the restructuring process are identified in section 3. Section 4 describes the realisation of a MAS for railway resource management under the restructured scheme and the feasible studies expected from the model.

Multivariate Markov Process Models for the transmission of methicillin-resistant Staphylococcus Aureus in a hospital ward

Methicillin-resistant Staphylococcus Aureus (MRSA) is a pathogen that continues to be of major concern in hospitals. We develop models and computational schemes based on observed weekly incidence data to estimate MRSA transmission parameters. We extend the deterministic model of McBryde, Pettitt, and McElwain (2007, Journal of Theoretical Biology 245, 470–481) involving an underlying population of MRSA colonized patients and health-care workers that describes, among other processes, transmission between uncolonized patients and colonized health-care workers and vice versa. We develop new bivariate and trivariate Markov models to include incidence so that estimated transmission rates can be based directly on new colonizations rather than indirectly on prevalence. Imperfect sensitivity of pathogen detection is modeled using a hidden Markov process. The advantages of our approach include (i) a discrete valued assumption for the number of colonized health-care workers, (ii) two transmission parameters can be incorporated into the likelihood, (iii) the likelihood depends on the number of new cases to improve precision of inference, (iv) individual patient records are not required, and (v) the possibility of imperfect detection of colonization is incorporated. We compare our approach with that used by McBryde et al. (2007) based on an approximation that eliminates the health-care workers from the model, uses Markov chain Monte Carlo and individual patient data. We apply these models to MRSA colonization data collected in a small intensive care unit at the Princess Alexandra Hospital, Brisbane, Australia.

Exploring the process of implementing a smoking cessation intervention in pregnancy training program for midwives

The question of how to implement evidence effectively reveals a deficiency in our knowledge and understanding of the compound factors involved in such a process (Kitson, Rycroft-Malone et al. 2008). Although there is some awareness of the complexities of the process, there has been little exploration of the effectiveness of implementing evidence-based programs in health care. Despite public awareness of the dangers of smoking in pregnancy, and widespread public health measures to prevent smoking-related disease, women still continue to smoke in pregnancy (Ananth, Savitz et al. 1997; Laws and Hilder 2008). Evaluation of public health measures concludes that smoking cessation interventions during pregnancy increase quit rates among pregnant women (Melvin, Dolan-Mullen et al. 2000; Albrecht, Maloni et al. 2004; Lumley, Oliver et al. 2007). Notwithstanding the potential for improvement in health outcomes for pregnant women and their unborn babies, smoking interventions are often conducted poorly or not at all. Although midwives understand why women smoke in pregnancy and parenthood and are aware of the risks of smoking to both the pregnancy and the unborn child, they require specific knowledge and skills in the provision of support and advice on smoking for pregnant women (Bull and Whitehead 2006) . Organisational-change research demonstrates the complexity of the process of planned change in professionalised institutions such as health care (Greenhalgh, Robert et al. 2005). Some innovations and interventions are never accepted, and others are poorly supported (Greenhalgh, Robert et al. 2004). Comprehension of the change process around health promotion is crucial to the implementation of new health promotion interventions within health care (Riley, Taylor et al. 2003). This study utilised a case study approach to explore the process of implementing a smoking cessation training program for midwives in Queensland metropolitan and regional clinical areas, who attended a ‘Train-the-Trainer program’. The study draws on the organisational change work of Greenhalgh et al (2004) as the theoretical framework through which situational and structural factors are explored and examined as they inform the implementation of smoking cessation programs. The research data constituted staged interviews with midwives who instituted training programs for midwives, as well as organisational and policy documentation. Analysis of the data identified some areas that were not fully addressed in the theoretical model; these formed the basis of the Discussion and Implications for Future Research.