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.     

From monolithic to component-based performance evaluation of software architectures

Model-based performance evaluation methods for software architectures can help architects to assess design alternatives and save costs for late life-cycle performance fixes. A recent trend is component-based performance modelling, which aims at creating reusable performance models; a number of such methods have been proposed during the last decade. Their accuracy and the needed effort for modelling are heavily influenced by human factors, which are so far hardly understood empirically. Do component-based methods allow to make performance predictions with a comparable accuracy while saving effort in a reuse scenario? We examined three monolithic methods (SPE, umlPSI, Capacity Planning (CP)) and one component-based performance evaluation method (PCM) with regard to their accuracy and effort from the viewpoint of method users. We conducted a series of three experiments (with different levels of control) involving 47 computer science students. In the first experiment, we compared the applicability of the monolithic methods in order to choose one of them for comparison. In the second experiment, we compared the accuracy and effort of this monolithic and the component-based method for the model creation case. In the third, we studied the effort reduction from reusing component-based models. Data were collected based on the resulting artefacts, questionnaires and screen recording. They were analysed using hypothesis testing, linear models, and analysis of variance. For the monolithic methods, we found that using SPE and CP resulted in accurate predictions, while umlPSI produced over-estimates. Comparing the component-based method PCM with SPE, we found that creating reusable models using PCM takes more (but not drastically more) time than using SPE and that participants can create accurate models with both techniques. Finally, we found that reusing PCM models can save time, because effort to reuse can be explained by a model that is independent of the inner complexity of a component. The tasks performed in our experiments reflect only a subset of the actual activities when applying model-based performance evaluation methods in a software development process. Our results indicate that sufficient prediction accuracy can be achieved with both monolithic and component-based methods, and that the higher effort for component-based performance modelling will indeed pay off when the component models incorporate and hide a sufficient amount of complexity.     

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.     

Insights from Dividing 3D Goal-Directed Movements into Meaningful Phases

Existing measures for evaluating user performance on interaction tasks in virtual environments don't often provide sufficient information for improving these interactions. A new method for analyzing 3D goal-directed movements divides them into meaningful phases. The authors applied this method to experimental data collected for a 3D task resembling a standardized 2D multidirectional pointing task (ISO 9241-9). The results and analysis demonstrate that the method provides a more detailed insight into 3D goal-directed movements. This analysis can help researchers better identify input devices' and interaction techniques' strengths and weaknesses. This article is part of a special issue on 3D user interfaces.