Evaluation of CTOA from load vs. load-line displacement for C(T) specimen

A method to evaluate crack length and crack tip opening angle (CTOA) using only load vs. load-line data (P vs. Δ) is proposed for sheet materials for the C(T) specimen. The method has been applied to high-strength steel sheet and reasonable agreement was found with results from the surface optical method.     

Trade-off analysis approach for interactive nonlinear multiobjective optimization

When solving multiobjective optimization problems, there is typically a decision maker (DM) who is responsible for determining the most preferred Pareto optimal solution based on his preferences. To gain confidence that the decisions to be made are the right ones for the DM, it is important to understand the trade-offs related to different Pareto optimal solutions. We first propose a trade-off analysis approach that can be connected to various multiobjective optimization methods utilizing a certain type of scalarization to produce Pareto optimal solutions. With this approach, the DM can conveniently learn about local trade-offs between the conflicting objectives and judge whether they are acceptable. The approach is based on an idea where the DM is able to make small changes in the components of a selected Pareto optimal objective vector. The resulting vector is treated as a reference point which is then projected to the tangent hyperplane of the Pareto optimal set located at the Pareto optimal solution selected. The obtained approximate Pareto optimal solutions can be used to study trade-off information. The approach is especially useful when trade-off analysis must be carried out without increasing computation workload. We demonstrate the usage of the approach through an academic example problem.     

Weighting effect on the discrete time Fourier transform of noisysignals

The effect of weighting on the uncertainty of the discrete time Fourier transform (DTFT) samples of a signal corrupted by additive noise is investigated. Making very weak assumptions, it is shown how the adopted window sequence and the autocovariance function of the noise affect the second-order stochastic moments of the frequency-domain data. The relationship obtained extends the results reported in the literature and is useful in many frequency-domain estimation problems. It is shown how the knowledge of the second-order moments of the transform has allowed the application of the least squares technique for the estimation of the parameters of a multifrequency signal in the frequency-domain. The estimator obtained is very useful when high-accuracy results are required under real-time constraints. The procedure exhibits a better accuracy than similar frequency-domain methods proposed in the literature     

Prediction and optimization of a ceramic casting process using a hierarchical hybrid system of neural networks and fuzzy logic

This paper is a case study that describes a hybrid system integrating fuzzy logic, neural networks and algorithmic optimization for use in the ceramics industry. A prediction module estimates two quality metrics of slip-cast pieces through the simultaneous execution of two neural networks. A process improvement algorithm optimizes controllable process settings using the neural network prediction module in the objective function. An expert system module contains a hierarchy of two fuzzy logic rule bases. The rule bases prescribe processing times customized to individual production lines given ambient conditions, mold characteristics and the neural network predictions. This paper demonstrates the applicability of newer computational techniques to a very traditional manufacturing process and the system has been implemented at a major US plant.     

A methodology integrating Petri nets and knowledge-based systems to support process family planning

Planning production processes for product families have been well recognised as an effective means of achieving successful product family development. However, most existing approaches do not lend themselves to planning production processes with focus on the optimality of the cohort of a product family. This paper addresses process family planning for product families. In view of the advantages of Petri nets (PNs) for modelling large systems, the potential of knowledge-based systems (KBSs) for solving complex problems and the analogy in between, we develop a methodology by integrating PNs and KBSs to support process family planning. An integrated product–process family structure, called IP²S, is proposed to organise all data pertaining to a product family and the corresponding process family, thereby anchoring planning to one platform. With the IP²S, a formal PN model of process family planning is further developed by integrating the principles of several well-defined PN extensions. Thus, this paper also contributes to visualising the dynamic behaviours and reasoning behind process family planning. The methodology is applied to process family planning for a truck family. The preliminary results demonstrate the feasibility and potential of using the methodology to support process family planning.     

Regulation of adherence and virulence by the Entamoeba histolytica lectin cytoplasmic domain, which contains a beta2 integrin motif

Killing of human cells by the parasite Entamoeba histolytica requires adherence via an amebic cell surface lectin. Lectin activity in the parasite is regulated by inside-out signaling. The lectin cytoplasmic domain has sequence identity with a region of the beta2 integrin cytoplasmic tail implicated in regulation of integrin-mediated adhesion. Intracellular expression of a fusion protein containing the cytoplasmic domain of the lectin has a dominant negative effect on extracellular lectin-mediated cell adherence. Mutation of the integrin-like sequence abrogates the dominant negative effect. Amebae expressing the dominant negative mutant are less virulent in an animal model of amebiasis. These results suggest that inside-out signaling via the lectin cytoplasmic domain may control the extracellular adhesive activity of the amebic lectin and provide in vivo demonstration of the lectin's role in virulence.     

What company characteristics are associated with the adoption of social media?

ABSTRACT

In just one decade, social media have moved from being marginal phenomena to having three billion active monthly users globally in 2017. We use a large representative sample to study which company characteristics are associated with the early adoption of social media. Our findings suggest that digital orientation (outside social media), innovativeness, external collaboration in marketing and sales, and orientation towards consumer markets all increase a company’s probability of adopting social media. In addition, larger and younger companies are more likely to be early movers. Overall, business use of social media has only reached its early maturity; thus, it still has plenty of room to grow.     

Homological scaffolds of brain functional networks

Networks, as efficient representations of complex systems, have appealed to scientists for a long time and now permeate many areas of science, including neuroimaging (Bullmore and Sporns 2009 Nat. Rev. Neurosci. 10, 186–198. (doi:10.1038/nrn2618)). Traditionally, the structure of complex networks has been studied through their statistical properties and metrics concerned with node and link properties, e.g. degree-distribution, node centrality and modularity. Here, we study the characteristics of functional brain networks at the mesoscopic level from a novel perspective that highlights the role of inhomogeneities in the fabric of functional connections. This can be done by focusing on the features of a set of topological objects—homological cycles—associated with the weighted functional network. We leverage the detected topological information to define the homological scaffolds, a new set of objects designed to represent compactly the homological features of the correlation network and simultaneously make their homological properties amenable to networks theoretical methods. As a proof of principle, we apply these tools to compare resting-state functional brain activity in 15 healthy volunteers after intravenous infusion of placebo and psilocybin—the main psychoactive component of magic mushrooms. The results show that the homological structure of the brain''s functional patterns undergoes a dramatic change post-psilocybin, characterized by the appearance of many transient structures of low stability and of a small number of persistent ones that are not observed in the case of placebo.     

Toward preserving the structure of the antigenic peptide p17-1 from the HIV-1 p17 protein in nanostructured films

Antigenic peptides may be immobilized in nanostructured films in order to build highly specific immunosensors and other devices that require molecular recognition, with no need to use complex molecules. A major challenge for such endeavors, however, is to preserve the secondary structure of the peptides after immobilization. In this study, we show that the peptide p17-1 (LSGGELDRWEKIRLRPGG), derived from the HIV-1 p17 protein, may be immobilized in Layer-by-Layer (LbL) films made with polyelectrolytes. Its structure was preserved only if incorporated into phospholipid liposomes, according to fluorescence and circular dichroism (CD) spectroscopy. The lack of secondary structure for the peptide in the LbL film may be associated with the film-forming procedure in which p17-1 was adsorbed from an aqueous solution, where it does not form alpha helices. The importance of structure preservation was clear in the attempts to produce electrochemical immunosensors with the p17-1 peptide without being protected in liposomes in an LbL film. There was no detectable influence of the presence of anti-p17 antibodies, though some molecular interaction could be inferred from the voltammograms. In contrast, for p17-1 incorporated in liposomes electrochemical immunosensors could be obtained with the voltamogramms showing strong molecular recognition with the antibodies. These results indicated that phospholipids serve as a suitable matrix for immobilization of peptides, and confirmed the importance of structure preservation in electrochemical immunosensors.