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The inflammatory markers sST2, HSP27 and hsCRP have already been identified as prognostic markers in chronic heart failure (HF). Though individual biomarkers have proven their value in mortality risk prediction, the role of a multimarker strategy needs further evaluation.This is an exploratory reanalysis in chronic HF patients. Plasma HSP27, sST2 and hsCRP in outpatients with chronic HF were analysed. Patients were followed for a minimum of twelve months for the endpoint cardiovascular mortality and unplanned HF associated hospitalisation (=event). 15 year overall mortality was assessed retrospectively. The prognostic impact was assessed using a Cox proportional hazard model.113 chronic HF patients were included. Median follow up time was 614 days and 37 patients (32.7%) experienced an event. A Kaplan-Meier analysis revealed that patients with increased sST2, HSP27 and hsCRP levels have significantly worse prognosis (p 0.001). The use of a three-biomarker combination was superior in an independent risk prediction of an event (one high vs. two high: HR = 4.5, 95% CI: 1.3-15.5, p = 0.018; and one high vs. all high: HR = 9.8, 95% CI: 2.8-34.3, p 0.001) as shown in a multivariable cox proportional hazard model. However, the biomarker panel did not predict 15 year overall mortality, in contrast to elevated HSP27 levels (p = 0.012).The combination of all three markers is an independent predictor of cardiovascular death and unplanned HF associated hospitalisation but not overall mortality. Our findings suggest that adding those markers in combination to well established risk assessment parameters may improve risk stratification.

This work presents the first experimental results obtained with a single stage absorption heat transformer (AHT), which was operated with the working fluid water/ionic liquid. The ionic liquid (IL) used in this work was 1-ethyl-3-methyl-imidazolium methanesulfonate (EMIM OMs). Several sets of experiments were conducted by varying the inlet temperatures of the external circuits and the internal flow rates. The coefficient of performance (COP) decreases with increasing high temperature and decreasing medium temperature. At higher internal flow rates, the COP increases due to the improved efficiency of the solution heat exchanger and higher heat flows in the apparatuses. The comparison of the experimental results with simulation results shows a good agreement at low temperature lifts. At higher temperature lifts and lower heat flows in the apparatuses, the influences of heat losses, pump duties and uncertainties let the experimental results diverge from the simulated ones. The highest experimental COP was 0.43 at a heat flow of 5.5 kW in the absorber and a temperature lift of 18.5 K. The highest temperature lift was 47 K. The corresponding COP was 0.27 and the heat flow in the absorber 1.7 kW.

IntroductionLung cancer represents a major healthcare problem. Accordingly, there is an urgent need to identify serum biomarkers for early diagnosis of lung pathology. We have recently described that patients with manifest COPD evidence elevated levels of heat shock proteins (HSPs). Based on these data, we speculated whether HSPs are also increased in patients with diagnosed lung cancer.MethodsSerum levels of HSP27, phospho-HSP27 (pHSP27) and HSP70 in patients with non-small cell lung cancer (NSCLC) diagnosed at an early (stages I–II, n=37) or advanced (stages IIIA–IV, n=72) stage were determined by using ELISA. Healthy smokers (n=24), healthy never-smoker volunteers (n=33) and COPD patients (n=34) according to GOLD classification served as control population.ResultsSerum levels of HSP27 were elevated in patients with NSCLC diagnosed at an early or advanced stage when compared with both healthy control groups (P

This paper investigates rejection strategies for unconstrained offline handwritten text line recognition. The rejection strategies depend on various confidence measures that are based on alternative word sequences. The alternative word sequences are derived from specific integration of a statistical language model in the hidden Markov model based recognition system. Extensive experiments on the IAM database validate the proposed schemes and show that the novel confidence measures clearly outperform two baseline systems which use normalised likelihoods and local n-best lists, respectively.

In order to bear the challenge of global competition, the realisation of value adding processes within networked production structures gains significance. To optimise the supply chain in these production networks hereby is one major challenge in order to assure success. This contribution focuses the procedure of performance evaluation in production networks as one part of the network controlling. Thereby the specific model of a non-hierarchical production network based on competence cells (CCs) serves as the theoretical background. The evaluation of performances of the involved CCs is one important task in that context. It is realised during the final phase of an ideal-typical life cycle of a production network. In order to quantify the evaluation data, suitable performance attributes need to be identified. The evaluation process is realised by an adapted value benefit analysis. As the final result a measure for the valuation of the performance of participating CCs is ascertained. In case of an unsatisfying performance the profit shares will be shortened. Thereby a specific approach for the distribution of profit serves as the basis.

The concept of key characters in a cursively handwritten word image is introduced and a method for extracting the key characters is presented. Key characters capture the unambiguous parts of the cursive words that can be reliably segmented and recognized. We propose a method for lexicon reduction using key characters in conjunction with a word-length estimation.

We propose an off-line system for the recognition of handwritten numeral strings. The system is built upon four main components. A presegmentation module divides the input numeral string into independent groups of digits which are processed by a cascade of two recognition methods. The digit detection module identifies and recognizes groups containing isolated digits and a segmentation-free module recognizes the remaining groups containing an arbitrary number of digits. The global decision module merges all results and makes an accept/reject decision. Experimental results on data from both the CEDAR and NIST SD3 database compare favorably to other published methods.