Probing polymer chain constraint and synergistic effects in nylon 6-clay nanocomposites and nylon 6-silica flake sub-micro composites with nanomechanics

In this study, we report that a synergistic effect exists in the surface mechanical properties of nylon 6–clay nanocomposites (NC) that can be shown by nanomechanical testing. The hardness, elastic modulus, and nanoindentation creep behavior of nylon 6 and its nanocomposites with different filler loading produced by melt compounding were contrasted to those of model nylon 6 sub-microcomposites (SMC) reinforced by sub-micro-thick silica flakes in which constraint cannot occur due to the difference in filler geometry. Polymer chain constraint was assessed by the analysis of nanoindentation creep data. Time-dependent creep decreased with increasing the filler loading in the NC consistent with the clay platelets exerting a constraint effect on the polymer chains which increases with filler loading. In contrast, there was no evidence of any reduced time-dependent creep for the SMC samples, consistent with a lack of constraint expected due to much lower aspect ratio of the silica flake

Baseline susceptibility and cross-resistance in aphis gossypii glover (Aphididae: Hemiptera) to phorate and sulfoxaflor

© 2013 State of New South Wales. Susceptible discriminating doses of phorate (0.2 g/L) and sulfoxaflor (0.01 g/L) against cotton aphid Aphis gossypii Glover were determined by laboratory bioassay where aphids were sprayed with insecticide with the aid of a Potter spray tower. All of the populations tested were susceptible to sulfoxaflor, and only a pirimicarb resistant strain had cross-resistance to phorate. If phorate is used as a side dressing in Australian cotton for insect control, neither pirimicarb, or any other chemical associated with insensitive acetylcholinesterase type one resistance, should be used as the first foliar spray for any subsequent aphid control

Analytical and numerical analyses of the micromechanics of soft fibrous connective tissues

State of the art research and treatment of biological tissues require accurate and efficient methods for describing their mechanical properties. Indeed, micromechanics motivated approaches provide a systematic method for elevating relevant data from the microscopic level to the macroscopic one. In this work the mechanical responses of hyperelastic tissues with one and two families of collagen fibers are analyzed by application of a new variational estimate accounting for their histology and the behaviors of their constituents. The resulting, close form expressions, are used to determine the overall response of the wall of a healthy human coronary artery. To demonstrate the accuracy of the proposed method these predictions are compared with corresponding 3-D finite element simulations of a periodic unit cell of the tissue with two families of fibers. Throughout, the analytical predictions for the highly nonlinear and anisotropic tissue are in agreement with the numerical simulations

Polyostotic osteoid osteoma: A case report.

Osteoid osteomas are common, benign osteoblastic tumors that can occur in any bone in the body. They are almost always solitary, with only rare reports of multiple tumors in the same patient. When multiple, they typically are found within the same bone. We present a unique case of a young female athlete who presented initially at 16 years old with a right tibial osteoid osteoma and later at 18 years old with a right acetabular osteoid osteoma. Our case demonstrates the rare entity of polyostotic osteoid osteoma, the potential limitations of MRI in the diagnosis of osteoid osteoma, and the utility of radiofrequency ablation in the treatment of osteoid osteoma

Preventing Advanced Persistent Threats in Complex Control Networks

An Advanced Persistent Threat (APT) is an emerging attack against Industrial Control and Automation Systems, that is executed over a long period of time and is difficult to detect. In this context, graph theory can be applied to model the interaction among nodes and the complex attacks affecting them, as well as to design recovery techniques that ensure the survivability of the network. Accordingly, we leverage a decision model to study how a set of hierarchically selected nodes can collaborate to detect an APT within the network, concerning the presence of changes in its topology. Moreover, we implement a response service based on redundant links that dynamically uses a secret sharing scheme and applies a flexible routing protocol depending on the severity of the attack. The ultimate goal is twofold: ensuring the reachability between nodes despite the changes and preventing the path followed by messages from being discovered.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Tracking advanced persistent threats in critical infrastructures through opinion dynamics

Advanced persistent threats pose a serious issue for modern industrial environments, due to their targeted and complex attack vectors that are difficult to detect. This is especially severe in critical infrastructures that are accelerating the integration of IT technologies. It is then essential to further develop effective monitoring and response systems that ensure the continuity of business to face the arising set of cyber-security threats. In this paper, we study the practical applicability of a novel technique based on opinion dynamics, that permits to trace the attack throughout all its stages along the network by correlating different anomalies measured over time, thereby taking the persistence of threats and the criticality of resources into consideration. The resulting information is of essential importance to monitor the overall health of the control system and cor- respondingly deploy accurate response procedures. Advanced Persistent Threat Detection Traceability Opinion Dynamics.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Quantification of the pirimicarb resistance allele frequency in pooled cotton aphid (Aphis gossypii glover) samples by TaqMan SNP genotyping assay

Background: Pesticide resistance monitoring is a crucial part to achieving sustainable integrated pest management (IPM) in agricultural production systems. Monitoring of resistance in arthropod populations is initially performed by bioassay, a method that detects a phenotypic response to pesticides. Molecular diagnostic assays, offering speed and cost improvements, can be developed when the causative mutation for resistance has been identified. However, improvements to throughput are limited as genotyping methods cannot be accurately applied to pooled DNA. Quantifying an allele frequency from pooled DNA would allow faster and cheaper monitoring of pesticide resistance. Methodology/Principal Findings: We demonstrate a new method to quantify a resistance allele frequency (RAF) from pooled insects via TaqMan assay by using raw fluorescence data to calculate the transformed fluorescence ratio k′ at the inflexion point based on a four parameter sigmoid curve. Our results show that k′ is reproducible and highly correlated with RAF (r >0.99). We also demonstrate that k′ has a non-linear relationship with RAF and that five standard points are sufficient to build a prediction model. Additionally, we identified a non-linear relationship between runs for k′, allowing the combination of samples across multiple runs in a single analysis. Conclusions/Significance: The transformed fluorescence ratio (k′) method can be used to monitor pesticide resistance in IPM and to accurately quantify allele frequency from pooled samples. We have determined that five standards (0.0, 0.2, 0.5, 0.8, and 1.0) are sufficient for accurate prediction and are statistically-equivalent to the 13 standard points used experimentally © 2014 Chen et al

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2

Hidden attractors in fundamental problems and engineering models

Recently a concept of self-excited and hidden attractors was suggested: an attractor is called a self-excited attractor if its basin of attraction overlaps with neighborhood of an equilibrium, otherwise it is called a hidden attractor. For example, hidden attractors are attractors in systems with no equilibria or with only one stable equilibrium (a special case of multistability and coexistence of attractors). While coexisting self-excited attractors can be found using the standard computational procedure, there is no standard way of predicting the existence or coexistence of hidden attractors in a system. In this plenary survey lecture the concept of self-excited and hidden attractors is discussed, and various corresponding examples of self-excited and hidden attractors are considered

Testing stock market convergence: a non-linear factor approach

This paper applies the Phillips and Sul (Econometrica 75(6):1771–1855, 2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US between 1973 and 2008. We carry out the analysis on both sectors and individual industries within sectors. As a first step, we use the Stock and Watson (J Am Stat Assoc 93(441):349–358, 1998) procedure to filter the data in order to extract the long-run component of the series; then, following Phillips and Sul (Econometrica 75(6):1771–1855, 2007), we estimate the relative transition parameters. In the case of sectoral indices we find convergence in the middle of the sample period, followed by divergence, and detect four (two large and two small) clusters. The analysis at a disaggregate, industry level again points to convergence in the middle of the sample, and subsequent divergence, but a much larger number of clusters is now found. Splitting the cross-section into two subgroups including euro area countries, the UK and the US respectively, provides evidence of a global convergence/divergence process not obviously influenced by EU policies