Coprimeness properties of nonlinear fractional system realizations

In this paper, the relationship between the Bezout and the set-theoretic approaches to left coprimeness is studied. It is shown that left coprimeness in the set-theoretic sense implies left coprimeness in the Bezout sense. In addition to these results, we investigate whether some properties for linear left coprime realizations carry over to the nonlinear case, for example we examine the relations between two left coprime realizations of the same system.     

Bisimulations for Temporal Logic

We define bisimulations for temporal logic with Since and Until. This new notion is compared to existing notions of bisimulations, and then used to develop the basic model theory of temporal logic with Since and Until. Our results concern both invariance and definability. We conclude with a brief discussion of the wider applicability of our ideas.     

The cross-classified multilevel measurement model: an explanation and demonstration

The link between the hierarchical generalized linear model (HGLM) and the Rasch model's parameterization has already been demonstrated by several researchers. Extensions have been described that include higher clustering levels to model more appropriately the contextual effects that are frequently encountered in educational research. However, pure hierarchies are relatively rare and instead cross-classified data structures are more frequently encountered. Cross-classified random effect modeling (CCREM) is still not commonly used. Use of CCREM in combination with the multilevel measurement model (MMM) has been recently introduced and is described further in the current study. Specifically, the link between the MMM and the CCREM MMM (termed "CCMMM" model) is provided. A dataset was simulated to demonstrate interpretation of the CCMMM model's parameters and to compare results under a CCMMM versus HGLM analysis. An Appendix is provided to demonstrate SAS GLIMMIX code used to estimate HGLM and CCMMM models' parameters.     

Methods for characterizing plant fibers

The effectiveness of different microscopy techniques for measuring the dimensions of ultimate fibers from harakeke (Phormium tenax, New Zealand flax) was investigated using a factorial experimental design. Constant variables were geographical location, location of specimens along the leaf, season (winter), individual plant, a fourth leaf from a north-facing fan, age of plant, and cultivars (two). Experimental variables were microscopy techniques and measurement axis. Measurements of width and length of harakeke ultimate fibers depended on the microscopic preparation/technique used as well as the cultivar examined. The best methods were (i) transverse sections of leaf specimens 4 microm thick, embedded in Paraplast and observed using light microscopy, and (ii) nonfixed ultimate fibers observed using scanning electron microscopy.     

Elevated Circulating and Placental SPINT2 Is Associated with Placental Dysfunction

Biomarkers for placental dysfunction are currently lacking. We recently identified SPINT1 as a novel biomarker; SPINT2 is a functionally related placental protease inhibitor. This study aimed to characterise SPINT2 expression in placental insufficiency. Circulating SPINT2 was assessed in three prospective cohorts, collected at the following: (1) term delivery (n = 227), (2) 36 weeks (n = 364), and (3) 24–34 weeks’ (n = 294) gestation. SPINT2 was also measured in the plasma and placentas of women with established placental disease at preterm (<34 weeks) delivery. Using first-trimester human trophoblast stem cells, SPINT2 expression was assessed in hypoxia/normoxia (1% vs. 8% O2), and following inflammatory cytokine treatment (TNFα, IL-6). Placental SPINT2 mRNA was measured in a rat model of late-gestational foetal growth restriction. At 36 weeks, circulating SPINT2 was elevated in patients who later developed preeclampsia (p = 0.028; median = 2233 pg/mL vs. controls, median = 1644 pg/mL), or delivered a small-for-gestational-age infant (p = 0.002; median = 2109 pg/mL vs. controls, median = 1614 pg/mL). SPINT2 was elevated in the placentas of patients who required delivery for preterm preeclampsia (p = 0.025). Though inflammatory cytokines had no effect, hypoxia increased SPINT2 in cytotrophoblast stem cells, and its expression was elevated in the placental labyrinth of growth-restricted rats. These findings suggest elevated SPINT2 is associated with placental insufficiency.     

A Feature Selection Strategy to Optimize Retinal Vasculature Segmentation

Diabetic retinopathy (DR) is a complication of diabetes mellitus that appears in the retina. Clinitians use retina images to detect DR pathological signs related to the occlusion of tiny blood vessels. Such occlusion brings a degenerative cycle between the breaking off and the new generation of thinner and weaker blood vessels. This research aims to develop a suitable retinal vasculature segmentation method for improving retinal screening procedures by means of computer-aided diagnosis systems. The blood vessel segmentation methodology relies on an effective feature selection based on Sequential Forward Selection, using the error rate of a decision tree classifier in the evaluation function. Subsequently, the classification process is performed by three alternative approaches: artificial neural networks, decision trees and support vector machines. The proposed methodology is validated on three publicly accessible datasets and a private one provided by Hospital Sant Joan of Reus. In all cases we obtain an average accuracy above 96% with a sensitivity of 72% in the blood vessel segmentation process. Compared with the state-of-the-art, our approach achieves the same performance as other methods that need more computational power. Our method significantly reduces the number of features used in the segmentation process from 20 to 5 dimensions. The implementation of the three classifiers confirmed that the five selected features have a good effectiveness, independently of the classification algorithm.     

A reference isotope dilution headspace GC/MS method for the determination of nitrite and nitrate in meat samples

A novel method for the determination of nitrite and nitrate in meat products is presented. The samples were ground and extracted in hot water with the presence of and internal standards. The solution was buffered with sodium bicarbonate and reacted with triethyloxonium tetrafluoroborate to convert nitrite and nitrate into EtNO₂ and EtONO₂. Such derivatives could be detected by headspace GC/MS in positive chemical ionisation mode with 0.05 µg g⁻¹ and 1.0 µg g⁻¹ LOD. The method was used for and quantitation in the 0.5-300 and 2.5-300 µg g⁻¹ ranges. The method was applied for the analysis of fifteen meat products. Despite minimal sample preparation, the headspace sampling ensured a clean chromatography for over 135 analyses (throughput ten samples per hour). The proposed method offers selective GC/MS detection combined with high-precision isotope dilution calibration, it is suitable for metrological applications and can support regulations on meat safety (European Commission, 2011).