Algorithms for deterministic balanced subspace identification

New algorithms for identification of a balanced state space representation are proposed. They are based on a procedure for the estimation of impulse response and sequential zero input responses directly from data. The proposed algorithms are more efficient than the existing alternatives that compute the whole Hankel matrix of Markov parameters. It is shown that the computations can be performed on Hankel matrices of the input–output data of various dimensions. By choosing wider matrices, we need persistency of excitation of smaller order. Moreover, this leads to computational savings and improved statistical accuracy when the data is noisy. Using a finite amount of input–output data, the existing algorithms compute finite time balanced representation and the identified models have a lower bound on the distance to an exact balanced representation. The proposed algorithm can approximate arbitrarily closely an exact balanced representation. Moreover, the finite time balancing parameter can be selected automatically by monitoring the decay of the impulse response. We show what is the optimal in terms of minimal identifiability condition partition of the data into “past” and “future”

A note on persistency of excitation

We prove that if a component of the response signal of a controllable linear time-invariant system is persistently exciting of sufficiently high order, then the windows of the signal span the full system behavior. This is then applied to obtain conditions under which the state trajectory of a state representation spans the whole state space. The related question of when the matrix formed from a state sequence has linearly independent rows from the matrix formed from an input sequence and a finite number of its shifts is of central importance in subspace system identification

Direct Awards in Germany – Design And Effects

Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne

Satisfactory cross cultural equivalence of the Dutch WOMAC in patients with hip osteoarthritis waiting for arthroplasty

Background: Cross cultural validity is of vital importance for international comparisons. Objective: To investigate the validity of international Dutch-English comparisons when using the Dutch translation of the Western Ontario and McMaster Universities osteoarthritis index (WOMAC). Patients and Methods: The dimensionality, reliability, construct validity, and cross cultural equivalence of the Dutch WOMAC in Dutch and Canadian patients waiting for primary total hip arthroplasty was investigated. Unidimensionality and cross cultural equivalence was quantified by principal component and Rasch analysis. Intratest reliability was quantified with Cronbach's α, and test-retest reliability with the intraclass correlation coefficient. Construct validity was quantified by correlating sum scores of the Dutch WOMAC, Arthritis Impact Measurement Scales (Dutch AIMS2), Health Assessment Questionnaire (Dutch HAQ), and Harris Hip Score (Dutch HHS). Results: The WOMAC was completed by 180 Dutch and 244 English speaking Canadian patients. Unidimensionality of the Dutch WOMAC was confirmed by principal component and Rasch analysis (good fit for 20/22 items). The intratest reliability of the Dutch WOMAC for pain and physical functioning was 0.88 and 0.96, whereas the test-retest reliability was 0.77 and 0.92, respectively. Dutch WOMAC pain sum score correlated 0.69 with Dutch HAQ pain, and 0.39 with Dutch HHS pain. Dutch WOMAC physical functioning sum score correlated 0.46 with Dutch AIMS2 mobility, 0.62 with Dutch AIMS2 walking and bending, 0.67 with Dutch HAQ disability, and 0.49 with Dutch HHS function. Differential item functioning (DIF) was shown for 6/22 Dutch items. Conclusions: The Dutch WOMAC permits valid international Dutch-English comparisons after correction for DIF

Enhanced Sarcolemmal FAT/CD36 Content and Triacylglycerol Storage in Cardiac Myocytes From Obese Zucker Rats

International audienc

Plasma Metabolomics Identifies Markers of Impaired Renal Function: A Meta-analysis of 3089 Persons with Type 2 Diabetes

CONTEXT: There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease. OBJECTIVE: To investigate associations between plasma metabolites and kidney function in people with type 2 diabetes (T2D). DESIGN: 3089 samples from individuals with T2D, collected between 1999 and 2015, from 5 independent Dutch cohort studies were included. Up to 7 years follow-up was available in 1100 individuals from 2 of the cohorts. MAIN OUTCOME MEASURES: Plasma metabolites (n = 149) were measured by nuclear magnetic resonance spectroscopy. Associations between metabolites and estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and eGFR slopes were investigated in each study followed by random effect meta-analysis. Adjustments included traditional cardiovascular risk factors and correction for multiple testing. RESULTS: In total, 125 metabolites were significantly associated (PFDR = 1.5×10-32 - 0.046; β = -11.98-2.17) with eGFR. Inverse associations with eGFR were demonstrated for branched-chain and aromatic amino acids (AAAs), glycoprotein acetyls, triglycerides (TGs), lipids in very low-density lipoproteins (VLDL) subclasses, and fatty acids (PFDR < 0.03). We observed positive associations with cholesterol and phospholipids in high-density lipoproteins (HDL) and apolipoprotein A1 (PFDR < 0.05). Albeit some metabolites were associated with UACR levels (P < 0.05), significance was lost after correction for multiple testing. Tyrosine and HDL-related metabolites were positively associated with eGFR slopes before adjustment for multiple testing (PTyr = 0.003; PHDLrelated < 0.05), but not after. CONCLUSIONS: This study identified metabolites associated with impaired kidney function in T2D, implying involvement of lipid and amino acid metabolism in the pathogenesis. Whether these processes precede or are consequences of renal impairment needs further investigation

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and