Multi-model recursive identification for nonlinear systems with non-uniformly sampling

A recursive least squares based on Multi-model is proposed for non-uniformly sampled-data nonlinear (NUSDN) systems. The corresponding state space model of an NUSDN system is derived using lifting technique. Taking advantage of the Fuzzy c-Mean Clustering algorithm, NUSDN is divided into several local models. The basic idea is that the NUSDN system is viewed as a model switching system under a given rule. Once the local models are identified, the global model is determined. A pH neutralization process validate the performance of the proposed algorithm.     

The Revised Fibromyalgia Impact Questionnaire (FIQR): validation and psychometric properties

Introduction  

The Fibromyalgia Impact Questionnaire (FIQ) is a commonly used instrument in the evaluation of fibromyalgia (FM) patients. Over the last 18 years, since the publication of the original FIQ, several deficiencies have become apparent and the cumbersome scoring algorithm has been a barrier to widespread clinical use. The aim of this paper is to describe and validate a revised version of the FIQ: the FIQR.     

Predicting the future of anti-tumor necrosis factor therapy

Tumor necrosis factor (TNF) antagonists are approved worldwide for the treatment of rheumatoid arthritis (RA). Clinical experience revealed that TNF-blocking therapy is effective for only approximately two thirds of patients, reflecting that there are 'responders' as well as 'nonresponders'. Given the destructive nature of RA, the risk of adverse effects, and considerable costs for therapy, there is a strong need to make predictions on success before the start of therapy. In the current issue of Arthritis Research & Therapy, Hueber and colleagues become the first to present a multi-parameter serum protein biomarker set that has predictive value prior to the start of anti-TNF treatment. Ultimately, this finding may contribute to a personalized form of medicine, whereby a specific therapy will be applied that is best suited to an individual patient.     

Development and Application of a Process Window for Achieving High-Quality Coating in a Fluidized Bed Coating Process

Next to the coating formulation, process conditions play important roles in determining coating quality. This study aims to develop an operational window that separates layering from agglomeration regimes and, furthermore, the one that leads to the best coating quality in a fluidized bed coater. The bed relative humidity and the droplet size of the coating aerosol were predicted using a set of engineering models. The coating quality was characterized using a quantitative image analysis method, which measures the coating thickness distribution, the total porosity, and the pore size in the coating. The layering regime can be achieved by performing the coating process at a certain excess of the viscous Stokes number (ΔSt _v). This excess is dependent on the given bed relative humidity and droplet size. The higher the bed relative humidity, the higher is the ΔSt _v required to keep the process in the layering regime. Further, it is shown that using bed relative humidity and droplet size alone is not enough to obtain constant coating quality. The changes in bed relative humidity and droplet size have been identified to correlate to the fractional area of particles sprayed per unit of time. This parameter can effectively serve as an additional parameter to be considered for a better control on the coating quality. High coating quality is shown to be achieved by performing the process close to saturation and spraying droplets small enough to obtain high spraying rate, but not too small to cause incomplete coverage of the core particles.     

Photocurrent Enhancement in Si-Ge Photodetectors by Utilizing Surface Plasmons

A circular slit-groove surface plasmon polaritons (SPPs) launcher surrounding a photodetector is employed theoretically to enhance the photocurrent of atypical Si-Ge photodetectors. The slit and grooves are designed such that the SPPs are focused at the center of the absorption layer of the photodetector to result in additional electric current. Fabry–Perot resonance condition accurately calculates the period of the groove, slit-groove distance, photodetector radius, and slit-photodetector distance. The manipulation leads to constructive interference between the incident light impinging from the top and the SPPs propagating toward the photodetector. Simulation result shows that photocurrent increases by approximately 13-fold when the SPPs are introduced.     

Genome‐wide analysis of TNF‐alpha response in pigs challenged with porcine circovirus 2b

Tumor necrosis factor alpha (TNF‐α) is a pro‐inflammatory cytokine with a role in activating adaptive immunity to viral infections. By inhibiting the capacity of plasmacytoid dendritic cells to produce interferon‐α and TNF‐α, porcine circovirus 2 (PCV2) limits the maturation of myeloid dendritic cells and impairs their ability to recognize viral and bacterial antigens. Previously, we reported QTL for viremia and immune response in PCV2‐infected pigs. In this study, we analyzed phenotypic and genetic relationships between TNF‐α protein levels, a potential indicator of predisposition to PCV2 co‐infection, and PCV2 susceptibility. Following experimental challenge with PCV2b, TNF‐α reached the peak at 21 days post‐infection (dpi), at which time a difference was observed between pigs that expressed extreme variation in viremia and growth (P < 0.10). A genome‐wide association study (n = 297) revealed that genotypes of 56 433 SNPs explained 73.9% of the variation in TNF‐α at 21 dpi. Major SNPs were identified on SSC8, SSC10 and SSC14. Haplotypes based on SNPs from a SSC8 (9 Mb) 1‐Mb window were associated with variation in TNF‐α (P < 0.02), IgG (P = 0.05) and IgM (P < 0.13) levels at 21 dpi. Potential overlap of regulatory mechanisms was supported by the correlations between genomic prediction values of TNF‐α and PCV2 antibodies (21 dpi, r > 0.22), viremia (14–21 dpi, P > 0.29) and viral load (r = 0.31, P < 0.0001). Characterization of the QTL regions uncovered genes that could influence variation in TNF‐α levels as well as T‐ and B‐cell development, which can affect disease susceptibility.     

Denver Papillae Protocol for Objective Analysis of Fungiform Papillae

The goal of the Denver Papillae Protocol is to use a dichotomous key to define and prioritize the characteristics of fungiform papillae (FP) to ensure consistent scoring between scorers. This protocol builds off of a need that has arisen from the last two decades of taste research using FP as a proxy for taste pore density. FP density has historically been analyzed using Miller & Reedy’s 1990 characterizations of their morphology: round, stained lighter, large, and elevated. In this work, the authors forewarned that stricter definitions of FP morphology needed to be outlined. Despite this call to action, follow up literature has been scarce, with most studies continuing to cite Miller & Reedy’s original work. Consequently, FP density reports have been highly variable and, combined with small sample sizes, may contribute to the discrepant conclusions on the role of FP in taste sensitivity. The Genetics of Taste Lab explored this apparent inconsistency in counting and found that scorers were individually prioritizing the importance of these characteristics differently and had no guidance for when a papilla had some, but not all, of the reported qualities of FP. The result of this subjectivity is highly variable FP counts of the same tongue image. The Denver Papillae Protocol has been developed to remedy this consequence through use of a dichotomous key that further defines and prioritizes the importance of the characteristics put forth by Miller & Reedy. The proposed method could help create a standard way to quantify FP for researchers in the field of taste and nutritional studies.