Coupled acoustic-shell model for experimental study of cell stiffness under acoustophoresis

Under the influence of acoustic radiation force, particles can be trapped and deformed at the pressure node in a microfluidic channel. Based on this principle, the elastic modulus of biological cells can be estimated. In this study, a numerical framework, consisting of a boundary element model for acoustic field and an axisymmetric shell model, is developed to simulate the cell deformation under acoustic radiation force. The boundary element model is used to calculate the radiation traction exerted on the cell surface. The cell membrane deformation due to this traction is simulated by using the axisymmetric shell model. The Young’s moduli of algae and red blood cell membranes are then estimated by comparing the experimental observation with the simulated membrane deformation. It is found that the value of Young’s modulus of the red blood cell membrane is lower than that of algae cell membrane. Furthermore, for both cells, the estimated Young’s moduli are negligible compared to the bulk moduli of the cells reported in the previous studies.     

Morphology controlled synthesis of polyaniline nanostructures using swollen liquid crystal templates

Preparation of zero‐dimensional and one‐dimensional nanostructures of polyaniline (PANI) were achieved by using swollen liquid crystals (SLCs) as ‘soft' templates. The monomer (aniline) was first entrapped in SLCs by replacing the oil phase (cyclohexane) with a mixture of aniline and cyclohexane. Zero‐dimensional nanostructures of PANI were obtained by thorough mixing of APS with the mesophases. One‐dimensional nanostructures were prepared by allowing slow diffusion of APS through the mesophase. PANI nanostructures were extracted from the mesophase and were characterized by UV‐visible spectroscopy, FTIR spectroscopy, powder X‐ray diffraction, atomic force microscopy, scanning electron microscopy (SEM), and conductivity measurements. A plausible mechanism for the formation of the nanostructures has been proposed. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40800.     

Der Wertbeitrag von Prozessflexibilität

Promising to cope with increasing demand variety and uncertainty, flexibility in general and process flexibility in particular are becoming ever more desired corporate capabilities. During the last years, the business process management and the production/operations management communities have proposed numerous approaches that investigate how to valuate and determine an appropriate level of process flexibility. Most of these approaches are very restrictive regarding their application domain, neglect characteristics of the involved processes and outputs other than demand and capacity, and do not conduct a thorough economic analysis of process flexibility. Against this backdrop, the authors propose an optimization model that determines an appropriate level of process flexibility in line with the principles of value-based business process management. The model includes demand uncertainty, variability, criticality, and similarity as process characteristics. The paper also reports on the insights gained from applying the optimization model to the coverage switching processes of an insurance broker pool company.     

Evaluation of the mechanical behavior of W7-X central support connections by means of semi-automated FE analysis

The stellarator Wendelstein 7-X is under construction at the Max-Planck-Institut für Plasmaphysik in Greifswald. Its superconducting coil system is fixed by a massive structure. During machine operation the coils exert high forces and moments against each other and the central support structure (CSS). Therefore, the detailed analysis of the coil to CSS connections, the so-called central support elements (CSE), is a critical item. The major details of the design have been frozen; nevertheless, there is still need for detailed analysis of the CSEs due to assembly issues, and later on for exploring operational limits of the machine. These analyses have to be performed quickly, reliably, and shall provide results in a standardized form to enable timely responses to the assembly team. Special numerical tools – finite element (FE) parametric models of CSEs – have been developed for the purpose of such analyses. In the models, the geometry, material properties, contact conditions, loads as well as results presentation are defined in a parametric way. The use of the developed models for the definition of the final weld parameters, bolt preloads, assessment of acceptable tolerances, and optimal positions of the CSE-wedges before welding is also discussed.     

New concepts for lithium minerals processing

A new concept for the enrichment of lithium minerals is offering higher purity and higher yield by applying new processing technologies addressing the specific properties of the pegmatitic host rock. Additional value is created from high quality by-products which will improve the sustainability of mining activity and the overall cost base. Within the new concept, flotation may even be avoided where wet separation techniques are not applicable.Two innovative processing technologies have been integrated in the new concept: electrodynamic fragmentation and optical sorting. Detailed results of lab-technical tests show that the new process design can achieve highly selective liberation and separation processes. Optical and mineralogical analyses of the test products indicate a high benefit for commercial applications.     

Modelling time-varying higher moments with maximum entropy density

Since the introduction of the Autoregressive Conditional Heteroscedasticity (ARCH) model of Engle [R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica 50 (1982) 987–1007], the literature of modelling the conditional second moment has become increasingly popular in the last two decades. Many extensions and alternate models of the original ARCH have been proposed in the literature aiming to capture the dynamics of volatility more accurately. Interestingly, the Quasi Maximum Likelihood Estimator (QMLE) with normal density is typically used to estimate the parameters in these models. As such, the higher moments of the underlying distribution are assumed to be the same as those of the normal distribution. However, various studies reveal that the higher moments, such as skewness and kurtosis of the distribution of financial returns are not likely to be the same as the normal distribution, and in some cases, they are not even constant over time. These have significant implications in risk management, especially in the calculation of Value-at-Risk (VaR) which focuses on the negative quantile of the return distribution. Failed to accurately capture the shape of the negative quantile would produce inaccurate measure of risk, and subsequently lead to misleading decision in risk management. This paper proposes a solution to model the distribution of financial returns more accurately by introducing a general framework to model the distribution of financial returns using maximum entropy density (MED). The main advantage of MED is that it provides a general framework to estimate the distribution function directly based on a given set of data, and it provides a convenient framework to model higher order moments up to any arbitrary finite order k. However this flexibility comes with a high cost in computational time as k increases, therefore this paper proposes an alternative model that would reduce computation time substantially. Moreover, the sensitivity of the parameters in the MED with respect to the dynamic changes of moments is derived analytically. This result is important as it relates the dynamic structure of the moments to the parameters in the MED. The usefulness of this approach will be demonstrated using 5 min intra-daily returns of the Euro/USD exchange rate.     

Characterization of silica-based monoliths with bimodal pore size distribution

Band dispersion was studied and the retention thermodynamics addressed for insulin and angiotensin II on C18 silica monoliths with a bimodal pore size distribution, covering linear mobile-phase velocities up to 1 cm/s and different temperatures. These data suggest that the influence of average column pressure on retention (between 0 and 10 MPa) is not negligible. Plate height curves were interpreted with the van Deemter equation by assuming an independent contribution from mechanical and non-mechanical dispersion mechanisms. This analysis revealed diffusion-limited mass transfer in the mesoporous silica skeleton which, in turn, allowed us to calculate an equivalent dispersion particle diameter (d(disp) = 3 microm) using the C-term parameter of the van Deemter equation. The resulting superposition of reduced plate height curves for monolithic and particulate beds confirmed that this view presents an adequate analogy. The macroporous interskeleton network responsible for the hydraulic permeability of a monolith was translated to the interparticle pore space of particulate beds, and an equivalent permeability particle diameter (d(perm) = 15 microm) was obtained by scaling based on the Kozeny-Carman equation.     

Multicriterion genetic optimization for due date assigned distribution network problems

This paper focuses on the demand due date factor in multiechelon distribution network problems and its impact on the production scheduling in manufacturing plants. A reliable demand due date is critical in winning of customer orders. However, this may usually require high collaboration among entities in the network. Mismatching of one single schedule may seriously influence the reliability. In this connection, holistically optimizing the schedule of each entity among the network is essential. In addition, on time delivery may induce high operating cost. A trade-off between earliness, on time, and tardiness should also be considered. Hence, a multicriterion genetic optimization methodology is developed to holistically optimize them. It determines the optimized schedule to collaborate each entity to fulfill the demands. For enabling multicriterion decision-making, the proposed algorithm combines analytic hierarchy process with genetic algorithms (GAs). The problem is divided into two parts—(i) demand allocation and transportation problem, and (ii) production scheduling problem. The optimization approach is applied to iteratively optimize part (i), and then part (ii). Three experiments have been carried out, and the computation results show that the effect of due date is critical, and the ability of the proposed algorithms in taking trade-off between earliness and tardiness.     

Caching video objects: layers vs versions?

Because Internet access rates are highly heterogeneous, many video content providers today make available different versions of the videos, with each version encoded at a different rate. Multiple video versions, however, require more server storage and may also dramatically impact cache performance in a traditional cache or in a CDN server. An alternative to versions is layered encoding, which can also provide multiple quality levels. Layered encoding requires less server storage capacity and may be more suitable for caching; but it typically increases transmission bandwidth due to encoding overhead. In this paper we compare video streaming of multiple versions with that of multiple layers in a caching environment. We examine caching and distribution strategies that use both versions and layers. We consider two cases: the request distribution for the videos is known a priori; and adaptive caching, for which the request distribution is unknown. Our analytical and simulation results indicate that mixed distribution/caching strategies provide the best overall performance.A shorter version of this work has appeared in Proc. of IEEE International Conference on Multimedia and Expo (ICME), Vol. 2, pages 45–48, Lausanne, Switzerland, August 2002