Analysis of the Earthʼs magnetic field variations on the basis of a wavelet-based approach

In the present paper we will discuss a new wavelet-based approach aimed at processing and analyzing different features of complex geomagnetic signals. This approach makes it possible to automatically extract different kinds of disturbances in the Earth?s magnetic field variations, which characterize solar activity and help to predict magnetic storms. In order to analyze geomagnetic signals wavelet packets are used in order to isolate local variations for quiet and perturbed periods and determine their intensity. Furthermore, a new automatic method of calculating the index of geomagnetic activity K is suggested on the basis of forming a quiet-day diurnal variation (Sq-curve). This method allows us to do calculations in the way that is closest to that developed by J. Bartels, who introduced the K-index in 1938. The results are compared with those obtained by INTERMAGNET and the original method of J. Bartels and the advantages of the suggested method are clearly demonstrated. For geomagnetic data collected in high-latitude regions of our planet it has become possible to reduce the error of estimating the K-index by 20% and unlike the technique used by INTERMAGNET here all the calculations can be done automatically. We will use geomagnetic signals that were kindly provided to us by the Institute of Cosmophysical Research and Radio Wave Propagation (Paratunka, Kamchatka region, Far East of Russia) for the period from January, 2002 till December, 2010.     

Influence of Unmodified and β-Glycerophosphate Cross-Linked Chitosan on Anti-Candida Activity of Clotrimazole in Semi-Solid Delivery Systems

The combination of an antifungal agent and drug carrier with adjunctive antimicrobial properties represents novel strategy of complex therapy in pharmaceutical technology. The goal of this study was to investigate the unmodified and ion cross-linked chitosan’s influence on anti-Candida activity of clotrimazole used as a model drug in hydrogels. It was particularly crucial to explore whether the chitosans’ structure modification by β-glycerophosphate altered its antifungal properties. Antifungal studies (performed by plate diffusion method according to CLSI reference protocol) revealed that hydrogels obtained with chitosan/β-glycerophosphate displayed lower anti-Candida effect, probably as a result of weakened polycationic properties of chitosan in the presence of ion cross-linker. Designed chitosan hydrogels with clotrimazole were found to be more efficient against tested Candida strains and showed more favorable drug release profile compared to commercially available product. These observations indicate that novel chitosan formulations may be considered as promising semi-solid delivery system of clotrimazole.     

Evaluation of quadratic cost functionals for neutral systems: the frequency-domain approach

As shown in Grabowski (1983), the problem of evaluation of the quadratic performance index for delay-differential systems of neutral type can be effectively solved by the use of Lyapunov functionals. In this paper another solution to that problem, based on the frequency-domain approach, is proposed. With the use of Plancherel's theorem and other tools of complex analysis, this task is reduced to a Riemann-Hilbert problem, an explicit solution to which is found by elementary methods. Our results can be regarded as a generalization of those due to Walton and Marshall (1984, 1987). Two simple examples of application are also provided.     

Modified Low Density Lipoprotein and Lipoprotein-Containing Circulating Immune Complexes as Diagnostic and Prognostic Biomarkers of Atherosclerosis and Type 1 Diabetes Macrovascular Disease

In atherosclerosis; blood low-density lipoproteins (LDL) are subjected to multiple enzymatic and non-enzymatic modifications that increase their atherogenicity and induce immunogenicity. Modified LDL are capable of inducing vascular inflammation through activation of innate immunity; thus, contributing to the progression of atherogenesis. The immunogenicity of modified LDL results in induction of self-antibodies specific to a certain type of modified LDL. The antibodies react with modified LDL forming circulating immune complexes. Circulating immune complexes exhibit prominent immunomodulatory properties that influence atherosclerotic inflammation. Compared to freely circulating modified LDL; modified LDL associated with the immune complexes have a more robust atherogenic and proinflammatory potential. Various lipid components of the immune complexes may serve not only as diagnostic but also as essential predictive markers of cardiovascular events in atherosclerosis. Accumulating evidence indicates that LDL-containing immune complexes can also serve as biomarker for macrovascular disease in type 1 diabetes.     

A two-pronged approach for springback variability assessment using sparse polynomial chaos expansion and multi-level simulations

In this study, we show that stochastic analysis of metal forming process requires both a high precision and low cost numerical models in order to take into account very small perturbations on inputs (physical as well as process parameters) and to allow for numerous repeated analysis in a reasonable time. To this end, an original semi-analytical model dedicated to plain strain deep drawing based on a Bending-Under-Tension numerical model (B-U-T model) is used to accurately predict the influence of small random perturbations around a nominal solution estimated with a full scale Finite Element Model (FEM). We introduce a custom sparse variant of the Polynomial Chaos Expansion (PCE) to model the propagation of uncertainties through this model at low computational cost. Next, we apply this methodology to the deep drawing process of U-shaped metal sheet considering up to 8 random variables.     

Decision trees for uplift modeling with single and multiple treatments

Most classification approaches aim at achieving high prediction accuracy on a given dataset. However, in most practical cases, some action such as mailing an offer or treating a patient is to be taken on the classified objects, and we should model not the class probabilities themselves, but instead, the change in class probabilities caused by the action. The action should then be performed on those objects for which it will be most profitable. This problem is known as uplift modeling, differential response analysis, or true lift modeling, but has received very little attention in machine learning literature. An important modification of the problem involves several possible actions, when for each object, the model must also decide which action should be used in order to maximize profit. In this paper, we present tree-based classifiers designed for uplift modeling in both single and multiple treatment cases. To this end, we design new splitting criteria and pruning methods. The experiments confirm the usefulness of the proposed approaches and show significant improvement over previous uplift modeling techniques.     

Optimization of reinforcement layout of scissor‐type bridge using differential evolution algorithm

Scissors mechanisms are commonly used in safety engineering during the construction of temporary structures, owing to their inherent advantages of foldability, transformability, and reusability. We effectively utilized these scissors mechanism features to develop a lightweight, deployable emergency Mobile Bridge (MB) based on optimization, and control of the folding structure. Here, we discuss the problems of optimal reinforcement layout for the MB by formulating and solving three optimization problems, namely: (a) the load capacity maximization problem, (b) the weight minimization problem, and (c) coupling the load capacity maximization problem and the weight minimization problem. The potential benefits resulting from the application of reinforcement were evaluated using a combination of finite element analysis and an optimization algorithm based on the differential evolution method. The results demonstrate the significant positive influence of the additional reinforcing members. In particular, the limit load was increased by over 10 times, while the weight was decreased to approximately half. The proposed methodology enabled the development of a substantially improved version of the MB characterized by a higher load capacity and lower weight in comparison to the initial bridge design.     

Power system stability enhancement by WAMS-based supplementary control of multi-terminal HVDC networks

This paper deals with supplementary control of a MTDC network designed for the stability enhancement of a AC power system. The proposed control is a WAMS-based control modulating the real and reactive power at the terminals of the DC network. Relevant control formulas have been derived for a linear multi-machine system model with the application of the direct Lyapunov method. Validity and robustness of the proposed control has been verified by computer simulation for a multi-machine test system using a nonlinear model and detailed modeling of power system components. The proposed control is robust and insensitive to changes in the network configuration and loading conditions in the AC power system. In the case, when more of the MTDC networks and/or the HVDC links are used in one interconnected power system the proposed stabilizing control produces additive damping i.e. each controlled network element contributes to the positive damping. Some practical aspects have also been discussed. The proposed WAMS-based stabilizing control of the MTDC network is innovative by both its main concept and the derivation of control formulas using the direct Lyapunov method.     

Life-cycle assessment of hydrogen technologies with the focus on EU critical raw materials and end-of-life strategies

We present the results of a life-cycle assessment (LCA) for the manufacturing and end-of-life (EoL) phases of the following fuel-cell and hydrogen (FCH) technologies: alkaline water electrolyser (AWE), polymer-electrolyte-membrane water electrolyser (PEMWE), high-temperature (HT) and low-temperature (LT) polymer-electrolyte-membrane fuel cells (PEMFCs), together with the balance-of-plant components. New life-cycle inventories (LCIs), i.e., material inputs for the AWE, PEMWE and HT PEMFC are developed, whereas the existing LCI for the LT PEMFC is adopted from a previous EU-funded project. The LCA models for all four FCH technologies are created by modelling the manufacturing phase, followed by defining the EoL strategies and processes used and finally by assessing the effects of the EoL approach using environmental indicators. The effects are analysed with a stepwise approach, where the CML2001 assessment method is used to evaluate the environmental impacts. The results show that the environmental impacts of the manufacturing phase can be substantially reduced by using the proposed EoL strategies (i.e., recycled materials being used in the manufacturing phase and replacing some of the virgin materials). To point out the importance of critical materials (in this case, the platinum-group metals or PGMs) and their recycling strategies, further analyses were made. By comparing the EoL phase with and without the recycling of PGMs, an increase in the environmental impacts is observed, which is much greater in the case of both fuel-cell systems, because they contain a larger quantity of PGMs.