Examining client perceptions of partnership quality and its dimensions in an IT outsourcing relationship

This paper reports on an empirical study of the multidimensionality of partnership quality in IT outsourcing arrangements and the relationships between these dimensions of partnership quality. A two-phase national survey was conducted to collect empirical data to confirm the dimensions of partnership quality in an IT outsourcing arrangement from the client organisation perspective and to identify the significant relationships between these dimensions using a second generation multivariate analysis technique—partial least squares (PLS). The findings from results of the data analyses show that inter-organisational trust, shared business understanding and to a lesser extent, functional and dysfunctional conflict between the client organisation and the outsourcing vendor in an IT outsourcing relationship are the key determinants of partnership quality. The key outcome variable for high partnership quality between the client organisation and the outsourcing vendor in an IT outsourcing relationship is mutual beneficial sharing of risks and benefits. Commitment in an IT outsourcing relationship is confirmed as a multidimensional construct of behaviour commitment and temporal/continuance commitment and was found to be influenced by the other dimensions of partnership quality. The key findings of this study provide support for the notion that trust and shared business understanding are key drivers in the IT outsourcing partnership style relationship ensuring that the sharing of risks and benefits are realised and conflict is minimised leading to a high quality and ultimately successful partnership between the client organisation and the outsourcing vendor. Furthermore our findings indicate that behavioural commitment to the contractual obligations of an IT outsourcing relationship sustains an ongoing temporal commitment to the partnership between the client organisation and the outsourcing vendor

An Invisible Quantum Tripwire

We present here a quantum tripwire, which is a quantum optical interrogation technique capable of detecting an intrusion with very low probability of the tripwire being revealed to the intruder. Our scheme combines interaction-free measurement with the quantum Zeno effect in order to interrogate the presence of the intruder without interaction. The tripwire exploits a curious nonlinear behaviour of the quantum Zeno effect we discovered, which occurs in a lossy system. We also employ a statistical hypothesis testing protocol, allowing us to calculate a confidence level of interaction-free measurement after a given number of trials. As a result, our quantum intruder alert system is robust against photon loss and dephasing under realistic atmospheric conditions and its design minimizes the probabilities of false positives and false negatives as well as the probability of becoming visible to the intruder.Comment: Improved based on reviewers comments; 5 figure

The bronchodilator response in preschool children: A systematic review

BACKGROUND: The bronchodilator response (BDR) is frequently used to support diagnostic and therapeutic decision-making for children who wheeze. However, there is little evidence-based guidance describing the role of BDR testing in preschool children and it is unclear whether published cut-off values, which are derived from adult data, can be applied to this population. METHODS: We searched MEDLINE, EMBASE, Web of Science, and Cochrane databases (inception-September 2015) for studies reporting response to a bronchodilator in healthy preschool children, response following placebo inhalation, and the diagnostic efficacy of BDR compared with a clinical diagnosis of asthma/recurrent wheezing. FINDINGS: We included 14 studies. Thirteen studies provided BDR data from healthy preschool children. Two studies reported response to placebo in preschool children with asthma/recurrent wheezing. Twelve studies compared BDR measurements from preschool children with asthma/recurrent wheeze to those from healthy children and seven of these studies reported diagnostic efficacy. Significant differences between the BDR measured in healthy preschool children compared with that in children with asthma/recurrent wheeze were demonstrated in some, but not all studies. Techniques such as interrupter resistance, oscillometry, and plethysmography were more consistently successfully completed than spirometry. Between study heterogeneity precluded determination of an optimum technique. INTERPRETATION: There is little evidence to suggest spirometry-based BDR can be used in the clinical assessment of preschool children who wheeze. Further evaluation of simple alternative techniques is required. Future studies should recruit children in whom airways disease is suspected and should evaluate the ability of BDR testing to predict treatment response

Virus Propagation in Multiple Profile Networks

Suppose we have a virus or one competing idea/product that propagates over a multiple profile (e.g., social) network. Can we predict what proportion of the network will actually get "infected" (e.g., spread the idea or buy the competing product), when the nodes of the network appear to have different sensitivity based on their profile? For example, if there are two profiles $\mathcal{A}$ and $\mathcal{B}$ in a network and the nodes of profile $\mathcal{A}$ and profile $\mathcal{B}$ are susceptible to a highly spreading virus with probabilities $\beta_{\mathcal{A}}$ and $\beta_{\mathcal{B}}$ respectively, what percentage of both profiles will actually get infected from the virus at the end? To reverse the question, what are the necessary conditions so that a predefined percentage of the network is infected? We assume that nodes of different profiles can infect one another and we prove that under realistic conditions, apart from the weak profile (great sensitivity), the stronger profile (low sensitivity) will get infected as well. First, we focus on cliques with the goal to provide exact theoretical results as well as to get some intuition as to how a virus affects such a multiple profile network. Then, we move to the theoretical analysis of arbitrary networks. We provide bounds on certain properties of the network based on the probabilities of infection of each node in it when it reaches the steady state. Finally, we provide extensive experimental results that verify our theoretical results and at the same time provide more insight on the problem

Adaptive Autocentering Control for an .Active Magnetic Bearing Supporting a Rotor with Unknown Mass Imbalance

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57790/1/LumAutocenteringTCST1996.pd