A coupled SPH-DEM model for micro-scale structural deformations of plant cells during drying

A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.

Cascaded multilevel converter based bidirectional inductive power transfer (BIPT) system

A typical low power IPT system employs an H-Bridge converter with a simple control strategy to generate a high frequency current from DC power supply. This paper proposes a cascaded multilevel converter for bidirectional IPT (BIPT) systems, which is suitable for low to medium power applications as well as for situations such as PV cells where several individual DC sources are to be utilized. A novel modulation strategy is proposed for the multilevel converter with the aim of minimizing switching losses. Series - Series (SS) compensation circuit is adopted for the IPT system and a mathematical model is presented to minimize the coil losses of the system under varying output power. Theoretical results presented in comparison to the simulations to demonstrate the applicability of the proposed concept and the validity of the developed model. The experimental results show the feasibility of the proposed phase shift modulation.

Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model

This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.

A dual inverter with integrated energy storage for wind power systems

This paper explores the possibility of using grid side inverter as an interface to connect energy storage systems. A dual inverter system, formed by cascading two 2-level inverters through a coupling transformer, is used as the testing model. The inverters are named as “main inverter” and “auxiliary inverter”. The main inverter is powered by the rectified output of the wind generator while the auxiliary inverter is attached to a Battery Energy Storage System (BESS). If there is a surplus of wind power compared to the demand, then that would be stored in BESS while if there is a deficit in wind power then the demand will be satisfied by supplying power from the BESS. This enables constant power dispatch to the grid irrespective of wind changes. Novel modulation and control techniques are proposed to address the problem of non-integer, dynamically-varying dc-link voltage ratio, which is due to random wind changes. Furthermore, a maximum power tracking controller for this unique system is explained in detail. Simulation results verify the efficacy of proposed modulation and control techniques in suppressing random power fluctuations.

Cost efficiency of Japanese steam power generation companies : a Bayesian comparison of random and fixed frontier models

This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

Regulation, pollution and heterogeneity in Japanese steam power generation companies

In this paper, the random stochastic frontier model is used to estimate the technical efficiency of Japanese steam power generation companies taking into regulation and pollution. The companies are ranked according to their productivity for the period 1976-2003 and homogenous and heterogeneous variables in the cost function are disentangled. Policy implication is derived.

Engineering thin film semiconductor gas sensors to increase sensitivity and decrease operation temperature

Thin film nanostructured gas sensors typically operate at temperatures above 400°C, but lower temperature operation is highly desirable, especially for remote area field sensing as this reduces significantly power consumption. We have investigated a range of sensor materials based on both pure and doped tungsten oxide (mainly focusing on Fe-doping), deposited using both thermal evaporation and electron-beam evaporation, and using a variety of post-deposition annealing. The films show excellent sensitivity at operating temperatures as low as 150°C for detection of NO2. There is a definite relationship between the sensitivity and the crystallinity and nanostructure obtained through the deposition and heat treatment processes, as well as variations in the conductivity caused both by doping and heat treatmetn. The ultimate goal of this work is to control the sensing properties, including selectivity to specific gases through the engineering of the electronic properties and the nanostructure of the films.

Business model adaptation in new ventures: are technology-based firms different?

A firm’s business model (BM) is an important driver of its relative performance. Constructive adaptation to elements of the BM can therefore sustain the position in light of changing conditions. This study takes a configurational approach to understanding drivers of business model adaptation (BMA) in new ventures. We investigate the effect of human capital, social capital, and technological environment on BMA. We find that a universal, direct effects, analysis can provide useful information, but also risks painting a distorted picture. Contingent, two-way interactions add further explanatory power, but configurational models combining elements of all three (internal resource, external activities, environment) are superior.

A non-linear interface element model for thin layer high adhesive mortared masonry

A nonlinear interface element modelling method is formulated for the prediction of deformation and failure of high adhesive thin layer polymer mortared masonry exhibiting failure of units and mortar. Plastic flow vectors are explicitly integrated within the implicit finite element framework instead of relying on predictor–corrector like approaches. The method is calibrated using experimental data from uniaxial compression, shear triplet and flexural beam tests. The model is validated using a thin layer mortared masonry shear wall, whose experimental datasets are reported in the literature and is used to examine the behaviour of thin layer mortared masonry under biaxial loading.

Increased sensitivity to tryptophan bioavailability is a positive adaptation by the human strains of Chlamydia pneumoniae

One of the most significant activities induced by interferon-gamma against intracellular pathogens is the induction of IDO (indoleamine 2,3-dioxygenase) expression, which subsequently results in the depletion of tryptophan. We tested the hypothesis that human strains of Chlamydia pneumoniae are more sensitive to tryptophan limitation than animal C. pneumoniae strains. The human strains were significantly more sensitive to IFN-γ than the animal strains in a lung epithelia cell model (BEAS-2B), with exposure to 1 U ml(-1) IFN-γ resulting in complete loss of infectious yield of human strains, compared to the animal strains where reductions in infectious progeny were around 3.5-4.0 log. Strikingly, the IFN-γ induced loss of ability to form infectious progeny production was completely rescued by removal of the IFN-γ and addition of exogenous tryptophan for the human strains, but not the animal strains. In fact, a human heart strain was more capable of entering a non-infectious, viable persistent stage when exposed to IFN-γ and was also more effectively rescued, compared to a human respiratory strain. Exquisite susceptibility to IFN-γ, specifically due to tryptophan availability appears to be a core adaptation of the human C. pneumoniae strains, which may reflect the chronic nature of their infections in this host.

Power and paradigms : the Dutch response to pressures for shareholder value

In recent years, research aimed at identifying and relating the antecedents and consequences of diffusing organizational practices/ideas has turned its attention to debating the international adoption and implementation of the Anglo-American model of corporate governance, i.e., a shareholder-value-orientation (SVO). While financial economists characterize the adoption of an SVO as necessary and performance-enhancing, behavioral scientists have disputed such claims, invoking institutional contingencies in the appropriateness of an SVO. Our study seeks to provide some resolution to the debate by developing an overarching socio-political perspective that links the antecedents and consequences of the adoption of the contested practice of SVO. We test our framework using extensive longitudinal data from 1992-2006 from the largest listed corporations in the Netherlands, and we find a negative relationship between SVO adoption and subsequent firm performance, although this effect is attenuated when accompanied by greater SVO-alignment among major owners and a firm’s visible commitment to an SVO. This study extends prior research on the diffusion of contested organizational practices that has taken a socio-political perspective by offering an original contingency perspective that addresses how and why the misaligned preferences of corporate owners will affect (i) a company’s inclination to espouse an SVO, and (ii) the performance consequences of such misalignment.This study suggests when board members are considering the adoption of new ideas/practices (e.g., SVO), they should consider the contextual fitness of the idea/practice with the firm’s owners and their interests.

A sensitivity analysis of train speed and its effect on railway capacity

Increasing train speeds is conceptually a simple and straight forward method to expand railway capacity, for example in comparison to other more extensive and elaborate alternatives. In this article an analytical capacity model has been investigated as a means of performing a sensitivity analysis of train speeds. The results of this sensitivity analysis can help improve the operation of this railway system and to help it cope with additional demands in the future. To test our approach a case study of the Rah Ahane Iran (RAI) national railway network has been selected. The absolute capacity levels for this railway network have been determined and the analysis shows that increasing trains speeds may not be entirely cost effective in all circumstances.

A model predictive approach for community battery energy storage system optimization

This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.

Development of a log-quadratic model to describe microbial inactivation, illustrated by thermal inactivation of Clostridium botulinum

In the commercial food industry, demonstration of microbiological safety and thermal process equivalence often involves a mathematical framework that assumes log-linear inactivation kinetics and invokes concepts of decimal reduction time (DT), z values, and accumulated lethality. However, many microbes, particularly spores, exhibit inactivation kinetics that are not log linear. This has led to alternative modeling approaches, such as the biphasic and Weibull models, that relax strong log-linear assumptions. Using a statistical framework, we developed a novel log-quadratic model, which approximates the biphasic and Weibull models and provides additional physiological interpretability. As a statistical linear model, the log-quadratic model is relatively simple to fit and straightforwardly provides confidence intervals for its fitted values. It allows a DT-like value to be derived, even from data that exhibit obvious "tailing." We also showed how existing models of non-log-linear microbial inactivation, such as the Weibull model, can fit into a statistical linear model framework that dramatically simplifies their solution. We applied the log-quadratic model to thermal inactivation data for the spore-forming bacterium Clostridium botulinum and evaluated its merits compared with those of popular previously described approaches. The log-quadratic model was used as the basis of a secondary model that can capture the dependence of microbial inactivation kinetics on temperature. This model, in turn, was linked to models of spore inactivation of Sapru et al. and Rodriguez et al. that posit different physiological states for spores within a population. We believe that the log-quadratic model provides a useful framework in which to test vitalistic and mechanistic hypotheses of inactivation by thermal and other processes. Copyright © 2009, American Society for Microbiology. All Rights Reserved.

Comparison of eight published lumbar spine finite element models

Due to its ability to represent intricate systems with material nonlinearities as well as irregular loading, boundary, geometrical and material domains, the finite element (FE) method has been recognized as an important computational tool in spinal biomechanics. Current FE models generally account for a single distinct spinal geometry with one set of material properties despite inherently large inter-subject variability. The uncertainty and high variability in tissue material properties, geometry, loading and boundary conditions has cast doubt on the reliability of their predictions and comparability with reported in vitro and in vivo values. A multicenter study was undertaken to compare the results of eight well-established models of the lumbar spine that have been developed, validated and applied for many years. Models were subjected to pure and combined loading modes and their predictions were compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges; their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with previously published median in vitro values. However, the ranges of predictions were larger and exceeded the in vitro ranges, especially for facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with in vivo values. The simulations yielded median facet joint forces of 0 N in flexion, 38 N in extension, 14 N in lateral bending and 60 N in axial rotation that could not be validated due to the paucity of in vivo facet joint forces. In light of high inter-subject variability, one must be cautious when generalizing predictions obtained from one deterministic model. This study demonstrates however that the predictive power increases when FE models are combined together. The median of individual numerical results can hence be used as an improved tool in order to estimate the response of the lumbar spine.