Ferritin Protein Regulates the Degradation of Iron Oxide Nanoparticles

Proteins implicated in iron homeostasis are assumed to be also involved in the cellular processing of iron oxide nanoparticles. In this work, the role of an endogenous iron storage protein—namely the ferritin—is examined in the remediation and biodegradation of magnetic iron oxide nanoparticles. Previous in vivo studies suggest the intracellular transfer of the iron ions released during the degradation of nanoparticles to endogenous protein cages within lysosomal compartments. Here, the capacity of ferritin cages to accommodate and store the degradation products of nanoparticles is investigated in vitro in the physiological acidic environment of the lysosomes. Moreover, it is questioned whether ferritin proteins can play an active role in the degradation of the nanoparticles. The magnetic, colloidal, and structural follow‐up of iron oxide nanoparticles and proteins in lysosome‐like medium confirms the efficient remediation of potentially harmful iron ions generated by nanoparticles within ferritins. The presence of ferritins, however, delays the degradation of particles due to a complex colloidal behavior of the mixture in acidic medium. This study exemplifies the important implications of intracellular proteins in processes of degradation and metabolization of iron oxide nanoparticles.     

Managing sequential ambidexterity in the electronics industry: roles of temporal switching capability and contingent factors

Researchers on organisational ambidexterity have proposed several solutions to address the potential conflicts between exploration activities and exploitation activities. Unlike simultaneous ambidexterity, sequential ambidexterity – defined as temporal switching between exploration and exploitation – has not been examined fully, and the conditions under which this temporal switching can be successful are unclear. This paper proposes the concept of temporal switching capability to better understand the process by which sequential ambidexterity is executed. In addition, we hypothesise that performance effects are contingent upon firm-specific factors: a firm’s business strategy and absorptive capacity. Utilising three sources of data – a secondary database, annual reports and a survey administered to 145 firms in the electronics industry with 10-year observations – we find support for our hypotheses. The results show that the temporal switching capability positively relates to new product performance and that business strategy type and absorptive capacity have moderating effects. The results are meaningful in both theory and practice.     

SOA adoption in business networks: do service-oriented architectures really advance inter-organizational integration?

The emergence of the Internet as a global communication infrastructure has dramatically reduced interaction costs within and across organizations, with significant impact on inter-organizational relationships, vertical industry structures, and markets. More recently, service-oriented architectures (SOA) and Web services have introduced the next paradigm shift and foster the idea of dynamic business networks with quick connect and disconnect relationships. However, little research has systematically analyzed how companies leverage SOA to improve their inter-organizational relationships and reshape their business networks. In addition, the mature research stream on inter-organizational information systems (IOS) has not yet sufficiently considered SOA. In order to close this gap, our research seeks to improve the fundamental understanding of how SOA is applied in business networks and how it differs from prior forms of IOS. Using an exploratory research approach, we investigate 33 SOA cases to identify focus areas and patterns of SOA adoption in business networks. Our case analysis builds on a multi-dimensional classification scheme which we derived from prior literature. While our empirical findings do not confirm all promising propositions related to SOA, they underline the specific contribution of SOA compared to prior forms of IOS. We conclude by suggesting five clusters of SOA adoption in the inter-organizational domain, each of those introducing new aspects in the coordination of distributed business networks.     

Solving subgraph isomorphism problems with constraint programming

The subgraph isomorphism problem consists in deciding if there exists a copy of a pattern graph in a target graph. We introduce in this paper a global constraint and an associated filtering algorithm to solve this problem within the context of constraint programming. The main idea of the filtering algorithm is to label every node with respect to its relationships with other nodes of the graph, and to define a partial order on these labels in order to express compatibility of labels for subgraph isomorphism. This partial order over labels is used to filter domains. Labelings can also be strengthened by adding information from the labels of neighbors. Such a strengthening can be applied iteratively until a fixpoint is reached. Practical experiments illustrate that our new filtering approach is more effective on difficult instances of scale free graphs than state-of-the-art algorithms and other constraint programming approaches.     

An intelligent system for monitoring and diagnosis of the CO2 capture process

Amine-based carbon dioxide capture has been widely considered as a feasible ideal technology for reducing large-scale CO₂ emissions and mitigating global warming. The operation of amine-based CO₂ capture is a complicated task, which involves monitoring over 100 process parameters and careful manipulation of numerous valves and pumps. The current research in the field of CO₂ capture has emphasized the need for improving CO₂ capture efficiency and enhancing plant performance. In the present study, artificial intelligence techniques were applied for developing a knowledge-based expert system that aims at effectively monitoring and controlling the CO₂ capture process and thereby enhancing CO₂ capture efficiency. In developing the system, the inferential modeling technique (IMT) was applied to analyze the domain knowledge and problem-solving techniques, and a knowledge base was developed on DeltaV Simulate.The expert system helps to enhance CO₂ capture system performance and efficiency by reducing the time required for diagnosis and problem solving if abnormal conditions occur. The expert system can be used as a decision-support tool that helps inexperienced operators control the plant; it can be used also for training novice operators.     

Stability analysis and time-varying walking control for an under-actuated planar biped robot

This paper presents two walking controllers for a planar biped robot with unactuated point feet. The control is based on the tracking of reference motions expressed as a function of time. First, the reference motions are adapted at each step in order to create a hybrid zero dynamic (HZD) system. Next, the stability of the walking gait under closed-loop control is evaluated with the linearization of the restricted Poincaré map of the HZD. When the controlled outputs are selected to be the actuated coordinates, most periodic walking gaits for this robot are unstable, that is, the eigenvalues of the linearized Poincaré map (ELPM) is larger than one. Therefore, two control strategies are explored to produce stable walking. The first strategy uses an event-based feedback controller to modify the ELPM and the second one is based on the choice of controlled outputs. The stability analysis show that, for the same robot and for the same reference trajectory, the stability of the walking (or ELPM) can be modified by some pertinent choices of controlled outputs. Moreover, by studying some walking characteristics of many stable cases, a necessary condition for stable walking is proposed. It is that the height of swing foot is nearly zero at the desired moment of impact. Based on this condition, the duration of the step is almost constant in presence of initial error, so a method for choosing controlled outputs for the second controller is given. By using this method, two stable domains for the controlled outputs selection are obtained.     

Regression output from a remote analysis server

This paper is concerned with the problem of balancing the competing objectives of allowing statistical analysis of confidential data while maintaining standards of privacy and confidentiality. Remote analysis servers have been proposed as a way to address this problem by delivering results of statistical analyses without giving the analyst any direct access to data. Several national statistical agencies operate remote analysis servers [Australian Bureau of Statistics Remote Access Data Laboratory (RADL), <www.abs.gov.au>; Luxembourg Income Study, <www.lisproject.org>].Remote analysis servers are not free from disclosure risk, and current implementations address this risk by “confidentialising” the underlying data and/or by denying some queries. In this paper we explore the alternative solution of “confidentialising” the output of a server so that no confidential information is revealed or can be inferred.In this paper we review results on remote analysis servers, and provide a list of measures for confidentialising the output from a single regression query to a remote server as developed by Sparks et al. [R. Sparks, C. Carter, J. Donnelly, J. Duncan, C.M. O’Keefe, L. Ryan, A framework for performing statistical analyses of unit record health data without violating either privacy or confidentiality of individuals, in: Proceedings of the 55th Session of the International Statistical Institute, Sydney, 2005; R. Sparks, C. Carter, J. Donnelly, C.M. O’Keefe, J. Duncan, T. Keighley, D. McAullay, Remote access methods for exploratory data analysis and statistical modelling: privacy-preserving Analytics^™, Comput. Meth. Prog. Biomed. 91 (2008) 208–222.] We provide a fully worked example, and compare the confidentialised output from the query with the output from a traditional statistical package. Finally, we provide a comparison the confidentialised regression diagnostics with the synthetic regression diagnostics generated by the alternative method of Reiter [J.P. Reiter, Model diagnostics for remote-access regression servers, Statistics and Computing 13 (2003) 371–380].     

ARMAX modelling of international tourism demand

Box–Jenkins (1970) models are often used to capture the autoregressive moving average of past observations of tourist arrivals from Japan to Taiwan and New Zealand. However, other explanatory variables, such as real income in the origin country, have also affected the demand for international travel. The purpose of this paper is to use the ARMAX model to investigate the dynamic relationship between tourism demand and real income of Japan, and to compare the findings with the single-equation model. Unit root tests and diagnostics are performed before estimating the income elasticity of travel demand by Japan for New Zealand and Taiwan based on seasonally unadjusted quarterly data for 1980(1) to 2004(2). The empirical results of the ARMAX model support the economic theory that the demand for international travel is positively related to income of the origin country.