Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Genome-wide analysis in a murine Dnmt1 knockdown model identifies epigenetically silenced genes in primary human pituitary tumors

DNA methylation at promoter CpG islands (CGI) is an epigenetic modification associated with inappropriate gene silencing in multiple tumor types. In the absence of a human pituitary tumor cell line, small interfering RNA-mediated knockdown of the maintenance methyltransferase DNA methyltransferase (cytosine 5)-1 (Dnmt1) was used in the murine pituitary adenoma cell line AtT-20. Sustained knockdown induced reexpression of the fully methylated and normally imprinted gene neuronatin (Nnat) in a time-dependent manner. Combined bisulfite restriction analysis (COBRA) revealed that reexpression of Nnat was associated with partial CGI demethylation, which was also observed at the H19 differentially methylated region. Subsequent genome-wide microarray analysis identified 91 genes that were significantly differentially expressed in Dnmt1 knockdown cells (10% false discovery rate). The analysis showed that genes associated with the induction of apoptosis, signal transduction, and developmental processes were significantly overrepresented in this list (P < 0.05). Following validation by reverse transcription-PCR and detection of inappropriate CGI methylation by COBRA, four genes (ICAM1, NNAT, RUNX1, and S100A10) were analyzed in primary human pituitary tumors, each displaying significantly reduced mRNA levels relative to normal pituitary (P < 0.05). For two of these genes, NNAT and S100A10, decreased expression was associated with increased promoter CGI methylation. Induced expression of Nnat in stable transfected AtT-20 cells inhibited cell proliferation. To our knowledge, this is the first report of array-based "epigenetic unmasking" in combination with Dnmt1 knockdown and reveals the potential of this strategy toward identifying genes silenced by epigenetic mechanisms across species boundaries.

Corporate credit risk prediction under stochastic volatility and jumps

This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.

Including nonequilibrium interface kinetics in a continuum model for melting nanoscaled particles

The melting temperature of a nanoscaled particle is known to decrease as the curvature of the solid-melt interface increases. This relationship is most often modelled by a Gibbs--Thomson law, with the decrease in melting temperature proposed to be a product of the curvature of the solid-melt interface and the surface tension. Such a law must break down for sufficiently small particles, since the curvature becomes singular in the limit that the particle radius vanishes. Furthermore, the use of this law as a boundary condition for a Stefan-type continuum model is problematic because it leads to a physically unrealistic form of mathematical blow-up at a finite particle radius. By numerical simulation, we show that the inclusion of nonequilibrium interface kinetics in the Gibbs--Thomson law regularises the continuum model, so that the mathematical blow up is suppressed. As a result, the solution continues until complete melting, and the corresponding melting temperature remains finite for all time. The results of the adjusted model are consistent with experimental findings of abrupt melting of nanoscaled particles. This small-particle regime appears to be closely related to the problem of melting a superheated particle.

A numerical method for the fractional Fitzhugh–Nagumo monodomain model

A fractional FitzHugh–Nagumo monodomain model with zero Dirichlet boundary conditions is presented, generalising the standard monodomain model that describes the propagation of the electrical potential in heterogeneous cardiac tissue. The model consists of a coupled fractional Riesz space nonlinear reaction-diffusion model and a system of ordinary differential equations, describing the ionic fluxes as a function of the membrane potential. We solve this model by decoupling the space-fractional partial differential equation and the system of ordinary differential equations at each time step. Thus, this means treating the fractional Riesz space nonlinear reaction-diffusion model as if the nonlinear source term is only locally Lipschitz. The fractional Riesz space nonlinear reaction-diffusion model is solved using an implicit numerical method with the shifted Grunwald–Letnikov approximation, and the stability and convergence are discussed in detail in the context of the local Lipschitz property. Some numerical examples are given to show the consistency of our computational approach.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.

Soluble mediators in platelet concentrates modulate dendritic cell inflammatory responses in an experimental model of transfusion

The transfusion of platelet concentrates (PCs) is widely used to treat thrombocytopenia and severe trauma. Ex vivo storage of PCs is associated with a storage lesion characterized by partial platelet activation and the release of soluble mediators, such as soluble CD40 ligand (sCD40L), RANTES, and interleukin (IL)-8. An in vitro whole blood culture transfusion model was employed to assess whether mediators present in PC supernatants (PC-SNs) modulated dendritic cell (DC)-specific inflammatory responses (intracellular staining) and the overall inflammatory response (cytometric bead array). Lipopolysaccharide (LPS) was included in parallel cultures to model the impact of PC-SNs on cell responses following toll-like receptor-mediated pathogen recognition. The impact of both the PC dose (10%, 25%) and ex vivo storage period was investigated [day 2 (D2), day 5 (D5), day 7 (D7)]. PC-SNs alone had minimal impact on DC-specific inflammatory responses and the overall inflammatory response. However, in the presence of LPS, exposure to PC-SNs resulted in a significant dose associated suppression of the production of DC IL-12, IL-6, IL-1a, tumor necrosis factor-a (TNF-a), and macrophage inflammatory protein (MIP)-1b and storage-associated suppression of the production of DC IL-10, TNF-a, and IL-8. For the overall inflammatory response, IL-6, TNF-a, MIP-1a, MIP-1b, and inflammatory protein (IP)-10 were significantly suppressed and IL-8, IL-10, and IL-1b significantly increased following exposure to PC-SNs in the presence of LPS. These data suggest that soluble mediators present in PCs significantly suppress DC function and modulate the overall inflammatory response, particularly in the presence of an infectious stimulus. Given the central role of DCs in the initiation and regulation of the immune response, these results suggest that modulation of the DC inflammatory profile is a probable mechanism contributing to transfusion-related complications.

Homology between jacalin and artocarpin from jackfruit (Artocarpus integrifolia) seeds. Partial sequence and preliminary crystallographic studies of artocarpin

Jacalin and artocarpin, the two lectins from jackfruit (Artocarpus integrifolia) seeds, have different physicochemical properties and carbohydrate-binding specificities. However, comparison of the partial amino-acid sequence of artocarpin with the known sequence of jacalin indicates close to 50% sequence identity. Artocarpin crystallizes in two forms, both monoclinic P2(1), with one and two tetramic molecules, respectively, in the asymmetric units of form I (a = 69.9, b = 73.7, c = 60.6 Angstrom and beta = 95.1 degrees) and form II (a = 87.6, b = 72.2, c = 92.6 Angstrom and beta = 101.1 degrees). Both the crystal structures have been solved by the molecular replacement method using the known structure of jacalin as the search model and ope of them partially refined, confirming that the two lectins are indeed homologous.

Assessment of internal quality attributes of mandarin fruit. 1. NIR calibration model development

The utility of near infrared spectroscopy as a non-invasive technique for the assessment of internal eating quality parameters of mandarin fruit (Citrus reticulata cv. Imperial) was assessed. The calibration procedure for the attributes of TSS (total soluble solids) and DM (dry matter) was optimised with respect to a reference sampling technique, scan averaging, spectral window, data pre-treatment (in terms of derivative treatment and scatter correction routine) and regression procedure. The recommended procedure involved sampling of an equatorial position on the fruit with 1 scan per spectrum, and modified partial least squares model development on a 720–950-nm window, pre-treated as first derivative absorbance data (gap size of 4 data points) with standard normal variance and detrend scatter correction. Calibration model performance for the attributes of TSS and DM content was encouraging (typical Rc2 of >0.75 and 0.90, respectively; typical root mean squared standard error of calibration of <0.4 and 0.6%, respectively), whereas that for juiciness and total acidity was unacceptable. The robustness of the TSS and DM calibrations across new populations of fruit is documented in a companion study.

NIR model development and robustness in prediction of melon fruit total soluble solids

Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

Analytical model of reactive transport processes with spatially variable coefficients

Analytical solutions of partial differential equation (PDE) models describing reactive transport phenomena in saturated porous media are often used as screening tools to provide insight into contaminant fate and transport processes. While many practical modelling scenarios involve spatially variable coefficients, such as spatially variable flow velocity, v(x), or spatially variable decay rate, k(x), most analytical models deal with constant coefficients. Here we present a framework for constructing exact solutions of PDE models of reactive transport. Our approach is relevant for advection-dominant problems, and is based on a regular perturbation technique. We present a description of the solution technique for a range of one-dimensional scenarios involving constant and variable coefficients, and we show that the solutions compare well with numerical approximations. Our general approach applies to a range of initial conditions and various forms of v(x) and k(x). Instead of simply documenting specific solutions for particular cases, we present a symbolic worksheet, as supplementary material, which enables the solution to be evaluated for different choices of the initial condition, v(x) and k(x). We also discuss how the technique generalizes to apply to models of coupled multispecies reactive transport as well as higher dimensional problems.

Validation of a partial coherence interferometry method for estimating retinal shape

To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data.

Lactic acid bacteria and their antimicrobial peptides : Induction,detection,partial characterization, and potential applications

Bacteriocin-producing lactic acid bacteria and their isolated peptide bacteriocins are of value to control pathogens and spoiling microorganisms in foods and feed. Nisin is the only bacteriocin that is commonly accepted as a food preservative and has a broad spectrum of activity against Gram-positive organisms including spore forming bacteria. In this study nisin induction was studied from two perspectives, induction from inside of the cell and selection of nisin inducible strains with increased nisin induction sensitivity. The results showed that a mutation in the nisin precursor transporter NisT rendered L. lactis incapable of nisin secretion and lead to nisin accumulation inside the cells. Intracellular proteolytic activity could cleave the N-terminal leader peptide of nisin precursor, resulting in active nisin in the cells. Using a nisin sensitive GFP bioassay it could be shown, that the active intracellular nisin could function as an inducer without any detectable release from the cells. The results suggested that nisin can be inserted into the cytoplasmic membrane from inside the cell and activate NisK. This model of two-component regulation may be a general mechanism of how amphiphilic signals activate the histidine kinase sensor and would represent a novel way for a signal transduction pathway to recognize its signal. In addition, nisin induction was studied through the isolation of natural mutants of the GFPuv nisin bioassay strain L. lactis LAC275 using fl uorescence-activated cell sorting (FACS). The isolated mutant strains represent second generation of GFPuv bioassay strains which can allow the detection of nisin at lower levels. The applied aspect of this thesis was focused on the potential of bacteriocins in chicken farming. One aim was to study nisin as a potential growth promoter in chicken feed. Therefore, the lactic acid bacteria of chicken crop and the nisin sensitivity of the isolated strains were tested. It was found that in the crop Lactobacillus reuteri, L. salivarius and L. crispatus were the dominating bacteria and variation in nisin resistance level of these strains was found. This suggested that nisin may be used as growth promoter without wiping out the dominating bacterial species in the crop. As the isolated lactobacilli may serve as bacteria promoting chicken health or reducing zoonoosis and bacteriocin production is one property associated with probiotics, the isolated strains were screened for bacteriocin activity against the pathogen Campylobacter jejuni. The results showed that many of the isolated L. salivarius strains could inhibit the growth of C. jejuni. The bacteriocin of the L. salivarius LAB47 strain, with the strongest activity, was further characterized. Salivaricin 47 is heat-stable and active in pH range 3 to 8, and the molecular mass was estimated to be approximately 3.2 kDa based on tricine SDS-PAGE analysis.

The importance of a precise definition, comprehensive model, and critical discussion of successful aging at work

It is crucial to advance understanding of the concept of successful aging at work to guide rigorous future research and effective practice. Drawing on the gerontology and life-span developmental literatures, I recently proposed a definition and theoretical framework of successful aging at work that revolve around employees increasingly deviating from average developmental trajectories across the working life span. Based on sustainability, person–job fit, and proactivity theories, Kooij suggested an alternative perspective that emphasizes the active role of employees for successful aging at work. In this article, I compare the 2 approaches and attempt a partial integration. I highlight the importance of a precise definition, comprehensive model, and critical discussion of successful aging at work. Furthermore, I suggest that person–environment fit variables other than person–job fit (e.g., person–organization fit) and adapting to person–environment misfit may also contribute to successful aging at work. Finally, I argue that proactive behaviors must have age-differential effects on work outcomes to be considered personal resources for successful aging at work.