Shape estimation of distorted flexible structures

The present work discusses the optimal placement of sensors in truss structures in order to obtain best possible information regarding the distortions of the structure. The estimation goal is to reconstruct the deformed shape of the structure, at the controlled degrees of freedom, from the sensor readings. A basic assumption is that the structure is subjected to a parametric disturbance field. We distinguish between disturbances which cause uniform or arbitrary distortions of the structure, and disturbances which cause structured distortions. Uniform distortions can be construed as white noise, that is, distortions which have no characteristics. Structured distortions are chromatic, they have some characteristics which can be helpful in estimating the shape. Although the disturbance in either case is random it is assumed that its magnitude is confined to a hyper sphere. The estimator is based on the least squares method, hence the estimated shape is the one with least RMS displacement for the given sensor readings. To evaluate the performance of each set of sensors a measure is derived based on the concept of the worst case distortion. The measure is the largest possible error between the estimated and the actual displacements, at the CDOF. For small number of sensors all possible arrangements can be generated and compared. Larger trusses with a moderate number of sensors generate prohibitively large number of possible configurations, hence heuristic search techniques are employed. The theory has been applied to 2D and 3D flexible trusses. Results show that for reasonable shape estimation a relatively large number of sensors is needed. It is also shown that when using sensors which measure mainly the distortions of the controlled degrees of freedom, significant improvements in the shape estimation can be obtained.     

Analysis of information exchange activities to actualize and validate situation awareness during shift changeovers in nuclear power plants

Shift work situations occur in almost all safety‐critical organizations, and the investigations of some catastrophes like Chernobyl, Exxon Valdez, and the Gol/Legacy mid‐air collision indicated that shift work information exchange played an important role during the evolution of the situation before the accidents. Inadequate communications during shift changeovers challenged operators' work in the moments that preceded these accidents, because they got inadequate information about the current situation. Our research focuses on the information exchange activities (verbal, written, and nonverbal) of nuclear power plant control operators during shift changeovers. Our aim is to investigate how verbal exchanges and other representations enable operator crews to share information regarding the events that occurred in the previous shift to achieve adequate situation awareness. Our findings indicated the importance and richness of the information exchange during the shift changeover process to update and validate individual and collective situation awareness, showing that information adequately shared enables the ad hoc configurations of regulation loops and a safer use of simplified strategies that can be understood and be validated by other operators, reducing the occurrence of cognitive overloads and contributing to the construction of a common cognitive ground that enhances system resilience. © 2010 Wiley Periodicals, Inc.     

Surface Modification of Titania Nanoparticles Using Ultrathin Ceramic Films

Surface modification of titania nanoparticles was achieved by coating them with ultrathin alumina films using atomic layer deposition. The coating process was performed in a fluidized bed reactor at low pressure and under mechanical vibration. Films were deposited using self-limiting, sequential surface reactions of trimethylaluminum and water. The composition of alumina-coated particles was verified using infrared spectroscopy. The deposited films had an average growth rate of 0.2 nm/coating cycle and were highly uniform and conformal as demonstrated by transmission electron microscopy and X-ray spectroscopy. Deposited alumina films were amorphous as verified through X-ray diffraction and high-resolution electron microscopy. The coating process did not promote particle sintering as validated via particle size and surface area analysis.     

Self-generation of reward by logarithmic transformation of multiple sensor evaluations

Artificial Life and Robotics - Although the design of the reward function in reinforcement learning is important, it is difficult to design a system that can adapt to a variety of environments and...     

Copper/copper oxide nanoparticles synthesis using Stachys lavandulifolia and its antibacterial activity

Nanoparticles of copper/cuprous oxide (Cu/Cu₂ O) were successfully synthesised by a green chemistry route. The synthesis process was carried out using an extract of Stachys lavandulifolia as both reducing and capping agents with a facile procedure. The nanoparticles were characterised by different techniques including X‐ray diffraction, indicating that the synthesised sample comprised both copper and cuprous oxide entity. The nanoparticles had a mean size of 80 nm and represented an impressive bactericidal effect on Pseudomonas aeruginosa.Inspec keywords: copper, copper compounds, nanoparticles, nanofabrication, nanomedicine, antibacterial activity, X‐ray diffractionOther keywords: nanoparticles synthesis, Stachys lavandulifolia, antibacterial activity, green chemistry route, reducing agents, capping agents, X‐ray diffraction, bactericidal effect, Pseudomonas aeruginosa, Cu‐Cu₂ O     

Adaptive beam search lookahead algorithms for the circular packing problem

This paper addresses the circular packing problem (CPP), which consists in packing n circles C_i, each of known radius r_i, i∈N={1, …, n}, into the smallest containing circle C. The objective is to determine the radius r of C as well as the coordinates (x_i, y_i) of the center of C_i, i∈N. CPP is solved using two adaptive algorithms that adopt a binary search to determine r, and a beam search to check the feasibility of packing n circles into C when the radius is fixed at r. A node of level ?, ?=1, …, n, of the beam search tree corresponds to a partial packing of ? circles of N into C. The potential of each node of the tree is assessed using a lookahead strategy that, starting with the partial packing of the current node, assigns each unpacked circle to its maximum hole degree position. The beam search stops either when the lookahead strategy identifies a feasible packing or when it has fathomed all nodes. The computational tests on a set of benchmark instances show the effectiveness of the proposed adaptive algorithms.     

Forecasting conditional correlations in stock,bond and foreign exchange markets

The paper forecasts conditional correlations between three classes of international financial assets, namely stock, bond and foreign exchange. Two countries are considered, namely Australia and New Zealand. Forecasting will be conducted using three multivariate GARCH models, namely the CCC model [T. Bollerslev, Modelling the coherence in short-run nominal exchange rates: a multivariate generalized ARCH model, Rev. Econ. Stat. 72 (1990) 498–505], VARMA-GARCH model [S. Ling, M. McAleer, Asymptotic theory for a vector ARMA-GARCH model, Econometric Theory 19 (2003) 280–310], and VARMA-AGARCH model [M. McAleer, S. Hoti, F. Chan, Structure and asymptotic theory for multivariate asymmetric volatility, Econometric Rev., in press]. A rolling window technique is used to forecast 1-day ahead conditional correlations. To evaluate the impact of model specification on conditional correlations forecasts, this paper calculates and compares the correlations between conditional correlations forecasts resulted from the three models. The paper finds the evidence of volatility spillovers and asymmetric effect of negative and positive shock on the conditional variance in most pairs of series. However, it suggests that incorporating volatility spillovers and asymmetric do not contribute to better conditional correlations forecasts.     

Enhancement of the neural network modeling accuracy using a submodeling decomposition-based technique, application in gas sensor

This paper presents an algorithm based on the use of artificial neural networks (ANNs) in order to reduce the processing time and to improve the accuracy in ANN modeling, which can be accomplished with a division of the model to submodels by input subintervals. We apply this method with a gas sensor aiming to accurately control the small gas leaks, thus decreasing the risk of false alarms and missed detections. The sensor model accurately, especially in small concentrations, expresses the nonlinear character of the response and the dependence on temperature and relative humidity in addition to the gas nature dependency. The corrector linearizes and compensates the sensor’s responses. The results obtained show the effectiveness of the proposed technique.     

Histone Deacetylases Function in the Control of Early Hematopoiesis and Erythropoiesis

Numerous studies have highlighted the role of post-translational modifications in the regulation of cell proliferation, differentiation and death. Among these modifications, acetylation modifies the physicochemical properties of proteins and modulates their activity, stability, localization and affinity for partner proteins. Through the deacetylation of a wide variety of functional and structural, nuclear and cytoplasmic proteins, histone deacetylases (HDACs) modulate important cellular processes, including hematopoiesis, during which different HDACs, by controlling gene expression or by regulating non-histone protein functions, act sequentially to provide a fine regulation of the differentiation process both in early hematopoietic stem cells and in more mature progenitors. Considering that HDAC inhibitors represent promising targets in cancer treatment, it is necessary to decipher the role of HDACs during hematopoiesis which could be impacted by these therapies. This review will highlight the main mechanisms by which HDACs control the hematopoietic stem cell fate, particularly in the erythroid lineage.