Local Power of Fixed‐T Panel Unit Root Tests With Serially Correlated Errors and Incidental Trends

The asymptotic local power properties of various fixed T panel unit root tests with serially correlated errors and incidental trends are studied. Asymptotic (over N) local power functions are analytically derived, and through them, the effects of general forms of serial correlation are examined. We find that a test based on an instrumental variables (IV) estimator dominates the tests based on the within‐groups (WG) estimator. These functions also show that in the presence of incidental trends, an instrumental variables test based on the first differences of the model has non‐trivial local power in an N^?1/2 neighbourhood of unity. Furthermore, for a test based on the within‐groups estimator, although it is found that it has trivial power in the presence of incidental trends, this ceases to be the case if there is serial correlation as well.     

Transformation of stainless steel slag toward a reactive cementitious binder

Argon oxygen decarburization (AOD) slag represents more than 50 wt% of the slag from stainless steel production. Although some applications are available, e.g., as aggregates for road constructions or fertilizers, they are characterized by low economic value and limited applicability. In order to increase the economic value of AOD slag, alternative applications have been proposed, e.g., as partial or full replacement for Ordinary Portland Cement (OPC). The work presented here investigates whether the adaptation of the AOD slag chemistry within a high temperature process leads to an improvement of its hydraulic properties and thereby can demonstrate its potential to be converted into a hydraulic binder suitable for OPC replacement. For this purpose, three synthetic AOD slags with basicities (CaO/SiO₂) of 2.0, 2.2, and 2.4 were synthesized, and the effect of the CaO/SiO₂ ratio on the material stability, the amount of tricalcium silicate formed, and their hydraulic properties investigated. X‐ray diffraction, scanning electron microscope (SEM), and isothermal calorimetry analysis were used to characterize the microstructure and the hydraulic activity. The results show that the proposed method is indeed a promising way to stabilize a stainless steel AOD slag and convert it into a hydraulic binder.     

Collaborative control for a robotic wheelchair: evaluation of performance, attention, and workload

Powered wheelchair users often struggle to drive safely and effectively and, in more critical cases, can only get around when accompanied by an assistant. To address these issues, we propose a collaborative control mechanism that assists users as and when they require help. The system uses a multiple-hypothesis method to predict the driver's intentions and, if necessary, adjusts the control signals to achieve the desired goal safely. The main emphasis of this paper is on a comprehensive evaluation, where we not only look at the system performance but also, perhaps more importantly, characterize the user performance in an experiment that combines eye tracking with a secondary task. Without assistance, participants experienced multiple collisions while driving around the predefined route. Conversely, when they were assisted by the collaborative controller, not only did they drive more safely but also they were able to pay less attention to their driving, resulting in a reduced cognitive workload. We discuss the importance of these results and their implications for other applications of shared control, such as brain-machine interfaces, where it could be used to compensate for both the low frequency and the low resolution of the user input.     

Bi-linear adaptive estimation of Fuzzy Cognitive Networks

Fuzzy Cognitive Networks (FCNs) have been introduced by the authors as an operational extension of Fuzzy Cognitive Maps (FCMs), initially introduced by Kosko to model complex behavioral systems in various scientific areas. FCNs rely on the admission that the underlying cognitive graph reaches a certain equilibrium point after an initial perturbation. Weight conditions for reaching equilibrium points have been recently derived in [54] along with an algorithm for weight estimation. In this paper, the conditions are extended to take into account not only the weights of the map but also the inclination parameters of the involved sigmoid functions, increasing the structural flexibility of the network. This in turn gives rise to the development of a new adaptive bilinear weight and sigmoid parameter estimation algorithm, which employs appropriate weight projection criteria to assure that the equilibrium is always achieved.     

Dimerization of protegrin-1 in different environments

The dimerization of the cationic β-hairpin antimicrobial peptide protegrin-1 (PG1) is investigated in three different environments: water, the surface of a lipid bilayer membrane, and the core of the membrane. PG1 is known to kill bacteria by forming oligomeric membrane pores, which permeabilize the cells. PG1 dimers are found in two distinct, parallel and antiparallel, conformations, known as important intermediate structural units of the active pore oligomers. What is not clear is the sequence of events from PG1 monomers in solution to pores inside membranes. The step we focus on in this work is the dimerization of PG1. In particular, we are interested in determining where PG1 dimerization is most favorable. We use extensive molecular dynamics simulations to determine the potential of mean force as a function of distance between two PG1 monomers in the aqueous subphase, the surface of model lipid bilayers and the interior of these bilayers. We investigate the two known distinct modes of dimerization that result in either a parallel or an antiparallel β-sheet orientation. The model bilayer membranes are composed of anionic palmitoyl-oleoyl-phosphatidylglycerol (POPG) and palmitoyl-oleoyl-phosphatidylethanolamine (POPE) in a 1:3 ratio (POPG:POPE). We find the parallel PG1 dimer association to be more favorable than the antiparallel one in water and inside the membrane. However, we observe that the antiparallel PG1 β-sheet dimer conformation is somewhat more stable than the parallel dimer association at the surface of the membrane. We explore the role of hydrogen bonds and ionic bridges in peptide dimerization in the three environments. Detailed knowledge of how networks of ionic bridges and hydrogen bonds contribute to peptide stability is essential for the purpose of understanding the mechanism of action for membrane-active peptides as well as for designing peptides which can modulate membrane properties. The findings are suggestive of the dominant pathways leading from individual PG1 molecules in solution to functional pores in bacterial membranes.     

Optimal robot arm control using the minimum variance model

Models of human movement from computational neuroscience provide a starting point for building a system that can produce flexible adaptive movement on a robot. There have been many computational models of human upper limb movement put forward, each attempting to explain one or more of the stereotypical features that characterize such movements. While these models successfully capture some of the features of human movement, they often lack a compelling biological basis for the criteria they choose to optimize. One that does provide such a basis is the minimum variance model (and its extension—task optimization in the presence of signal‐dependent noise). Here, the variance of the hand position at the end of a movement is minimized, given that the control signals on the arm's actuators are subject to random noise with zero mean and variance proportional to the amplitude of the signal. Since large control signals, required to move fast, would have higher amplitude noise, the speed‐accuracy trade‐off emerges as a direct result of the optimization process. We chose to implement a version of this model that would be suitable for the control of a robot arm, using an optimal control scheme based on the discrete‐time linear quadratic regulator. This implementation allowed us to examine the applicability of the minimum variance model to producing humanlike movement. In this paper, we describe our implementation of the minimum variance model, both for point‐to‐point reaching movements and for more complex trajectories involving via points. We also evaluate its performance in producing humanlike movement and show its advantages over other optimization based models (the well‐known minimum jerk and minimum torque‐change models) for the control of a robot arm. © 2005 Wiley Periodicals, Inc.     

Effect of mechanical activation on the hydraulic properties of stainless steel slags

This work aims to assess the possibility of using ladle metallurgy and argon oxygen decarburization stainless steel slag as a hydraulic binder after mechanical activation. Prolonged milling in ethanol suspension resulted in 10-fold increase of the surface area and increase of the amorphous phase. Calorimetric analysis of slags mixed with water indicated the occurrence of exothermic reactions. XRD results revealed that periclase, merwinite, γ-C₂S and bredigite, decreased with hydration time. Thermogravimetric analyses indicated that the main hydration products are most probably C–S–H, CH and MH. The hydrated products in both slags were similar to C–S–H gel. WDS analysis demonstrated Ca and Si to be widespread in the structure. Formation of M–S–H gel or incorporation of Mg in the C–S–H gel remains uncertain. The 90 days compressive strength of mortars prepared from slags reached approximately 20% for LM and 10% for AOD of the compressive strength of mortars prepared from OPC.     

Nonintrusive collection and management of data provenance in scientific workflows

In this paper, we introduce an efficient mechanism to collect, store, and retrieve data provenance information in workflows of multiphysics simulations. Using notifications, we enable the nonintrusive collection of information about workflow events during workflow execution. Combining these events with workflow structure information, constant for every execution of a workflow, we obtain the data provenance information for the specific run of the workflow. Data provenance information is structured into a graph that represents workflow events on the basis of their causal dependency. We use a graph database to store this graph and utilize the traversal framework provided, to efficiently retrieve data provenance information from the graph by traversing backwards from a data object to every workflow event that is part of its provenance. Finally, we integrate data provenance information with semantics of workflow services to provide complete and meaningful data provenance information. Copyright © 2012 John Wiley & Sons, Ltd.