Improved Limits on B0B^{0} decays to invisible (+γ)(+\gamma) final states

We establish improved upper limits on branching fractions for B0 decays to final States 10 where the decay products are purely invisible (i.e., no observable final state particles) and for final states where the only visible product is a photon. Within the Standard Model, these decays have branching fractions that are below the current experimental sensitivity, but various models of physics beyond the Standard Model predict significant contributions for these channels. Using 471 million BB pairs collected at the Y(4S) resonance by the BABAR experiment at the PEP-II e+e- storage ring at the SLAC National Accelerator Laboratory, we establish upper limits at the 90% confidence level of 2.4x10^-5 for the branching fraction of B0-->Invisible and 1.7x10^-5 for the branching fraction of B0-->Invisible+gammaComment: 8 pages, 3 postscript figures, submitted to Phys. Rev. D (Rapid Communications

Exclusive Measurements of b -> s gamma Transition Rate and Photon Energy Spectrum

We use 429 fb$^{-1}$ of $e^+e^-$ collision data collected at the $\Upsilon(4S)$ resonance with the BABAR detector to measure the radiative transition rate of $b\rightarrow s\gamma$ with a sum of 38 exclusive final states. The inclusive branching fraction with a minimum photon energy of 1.9 GeV is found to be $\mathcal{B}(\bar B \rightarrow X_{s}\gamma)=(3.29\pm 0.19\pm 0.48)\times 10^{-4}$ where the first uncertainty is statistical and the second is systematic. We also measure the first and second moments of the photon energy spectrum and extract the best fit values for the heavy-quark parameters, $m_{b}$ and $\mu_{\pi}^{2}$, in the kinetic and shape function models.Comment: 18 pages, 14 pdf figures, submitted to Phys. Rev.

How to Identify Scientifc Revolutions?

Conceptualizing scientific revolutions by means of explicating their causes, their underlying structure and implications has been an important part of Kuhn's philosophy of science and belongs to its legacy. In this paper we show that such “explanatory concepts” of revolutions should be distinguished from a concept based on the identification criteria of scientific revolutions. The aim of this paper is to offer such a concept, and to show that it can be fruitfully used for a further elaboration of the explanatory conceptions of revolutions. On the one hand, our concept can be used to test the preciseness and accuracy of these conceptions, by examining to what extent their criteria fit revolutions as they are defined by our concept. On the other hand, our concept can serve as the basis on which these conceptions can be further specified. We will present four different explanatory concepts of revolutions – Kuhn's, Thagard's, Chen's and Barker's, and Laudan's – and point to the ways in which each of them can be further specified in view of our concept

Enhancing the integration of agri-food supply chains: theoretical issues and practical challenges in the UK malting barley supply chain

The purpose of this paper is to explore the issues that may affect the integration (i.e., the relationships) between the different actors that comprise a supply chain. Whist the theoretical part of the paper can be referred to any supply chain, the empirical part is focused on the UK barley to beer supply chain. The main motivation behind the topic is that improvements in the relationships amongst the different segments of a chain can enhance its efficiency and effectiveness, (e.g., through improvements in coordination and cooperation), and therefore, its competitiveness and long term sustainability. The paper is based on two complementary analyses: the first one consisted of a structural equation model (SEM) to determine those factors that affect the sustainability of relationships in the chain. The model is estimated based on a survey of 69 chain stakeholders. The second analysis comprised an in-depth case study based on an important malting-barley- to-beer supply chain in Eastern England, and had the purpose of providing further understanding of those aspects that were highlighted by the SEM. The overall results pointed out to five factors affecting the relationships in the malting barley to beer agri-food supply chain: communication, compatibility of aims in the supply chain, contractual relationships backed by professional regard and personal bonds; high levels of trust exist between the chain participants and a willingness to resolve any problems; and commercial benefit.supply chain management, malting barley supply chain, supply chain coordination, competitiveness, Agribusiness,

IMPROVING MARKET ORIENTATION IN THE SCOTTISH BEEF SUPPLY CHAIN THROUGH PERFORMANCE-RELATED COMMUNICATIONS: THE CASE OF THE MCINTOSH DONALD BEEF PRODUCER CLUB AND QBOXANALYSIS

The reform of the Common Agricultural Policy (CAP) in 2003 and particularly the introduction of the Single Payment Scheme (SPS) is intended to make farmers more market orientated and competitive. In this context, the purpose of this paper is to discuss whether performance-related communication strategies present the possibility of improving farmers’ market orientation. This is studied through the case of McIntosh Donald, a beef processor located in the North East of Scotland and a major red meat supplier for Tesco, and Qboxanalysis, a performance-related communication system, introduced by the processor to its beef Producer Club members in March 2005. Results indicate that the enhanced communication strategy has the potential to increase farmers’ performance and market orientation, not only through the use of the Qboxanalysis system but also through the Producers’ Club activities. However, additional efforts are required to engage producers that are less proactiveFood Consumption/Nutrition/Food Safety, Marketing,

EDI and intelligent agents integration to manage food chains

Electronic Data Interchange (EDI) is a type of inter-organizational information system, which permits the automatic and structured communication of data between organizations. Although EDI is used for internal communication, its main application is in facilitating closer collaboration between organizational entities, e.g. suppliers, credit institutions, and transportation carriers. This study illustrates how agent technology can be used to solve real food supply chain inefficiencies and optimise the logistics network. For instance, we explain how agribusiness companies can use agent technology in association with EDI to collect data from retailers, group them into meaningful categories, and then perform different functions. As a result, the distribution chain can be managed more efficiently. Intelligent agents also make available timely data to inventory management resulting in reducing stocks and tied capital. Intelligent agents are adoptive to changes so they are valuable in a dynamic environment where new products or partners have entered into the supply chain. This flexibility gives agent technology a relative advantage which, for pioneer companies, can be a competitive advantage. The study concludes with recommendations and directions for further research

Communicating 'dual citizenship' - how do charities manage their reputation for 'good works' while undertaking commercial activities

Charities and not-for-profit organisations have traditionally eschewed commercial operations in favour of direct fund-raising from supporters. Building on Goodall’s (2000) exploration of sectoral values, it can be said that competitive pressures are driving charities to take on ‘dual citizenship’ through activity in both profit (commercial) and nonprofit (voluntary) sectors. In the United Kingdom, there are some 170,000 charitable organisations in England and Wales which generate £46 billion in annual revenue (UK Charity Commission 2008). There has, however, been little scholarly attention or professional focus on the impact that commercial trading by charities has on relations with key stakeholders, such as supporters, and upon the reputation of the community-focused organisations. This paper reports a case study of a UK charity and explores, using document analysis and phone interviews with supporter-stakeholders, their perceptions of the impact of commercial trading upon the organisation’s reputation as well as their relationship and level of engagement with the organisation. It found that donors are overwhelmingly in support of commercial activities, as long as these are aligned with the charity’s values. The study, however, also found that commercial activities should not deflect the charity from its perceived and announced mission. There were also lessons arising from the study on frequency and style of communication, and the relevance of models of communication, c.f. Grunig’s four descriptors, and measurements of relationships (Hon and Grunig 1999). The paper concludes with proposals for further research

In Defense of Weak Scientism: A Reply to Brown

In “What’s So Bad about Scientism?” (Mizrahi 2017), I argue that Weak Scientism, the view that “Of all the knowledge we have, scientific knowledge is the best knowledge” (Mizrahi 2017, 354; emphasis in original) is a defensible position. That is to say, Weak Scientism “can be successfully defended against objections” (Mizrahi 2017, 354). In his response to Mizrahi (2017), Christopher Brown (2017) provides more objections against Weak Scientism, and thus another opportunity for me to show that Weak Scientism is a defensible position, which is what I will do in this reply. In fact, I think that I have already addressed Brown’s (2017) objections in Mizrahi (2017), so I will simply highlight these arguments here

An Artificial Neural Network Approach to Learning from Factory Performance in a Kanban-Based System

Many Just-In-Time (JIT) manufacturing environments generate operational data reflecting both efficient and inefficient factory performance. Frequently data for inefficient performance is lost or discarded for fear of replicating poor performance. The purpose of this paper is two fold. First, historical JIT shop data is analyzed using a genetic algorithm (GA) to determine which shop factors are important determinants offactory performance. Second, subsequent to these important factors being identified by a GA, an artificial neural network (ANN) is used to learn the relationships between these factors and factory performance. The ANN can then be used to predict factory performance for future shop conditions and enhance shop performance. While ANN learning techniques have previously been applied to JIT production systems (Wray, Rakes, and Rees, 1997) (Markham, Mathieu, and Wray, 2000), these techniques have only been trained on data sets that reflect an efficient factory. Mathieu, Wray, and Markham (2002) investigated inefficient and efficient JIT factory performance but did not deploy either ANNs or a GA. In this paper an example application is presented using a GA to specify important shop factors and to predict saturated, starved or efficient factory performance based on dynamic shop floor data