Multi-point Estimation Research Articles

A novel generalized prognostic method of proton exchange membrane fuel cell using multi-point estimation under various operating conditions

The proton exchange membrane fuel cell has been introduced into the fields of transportation, power production, and mobile devices. Especially, priority is given to promoting the application in commercial vehicles. However, more severe fluctuations in power demands give new challenges to the lifespan of fuel cells. The accurate state estimation and reasonable degradation prediction can assist in improving the lifetime of fuel cell devices. To realize the on-road prediction, herein, a novel generalized prognostic method called the Multi-point Square-root central difference Kalman filter (MP-SRCDKF) is proposed. First of all, an extended mathematical model is introduced. Later, the sensitivity analysis and parameter recognition are conducted based on the Sobol’ method and the jellyfish searching algorithm. The performance of the SRCDKF method is compared under static and quasi-dynamic conditions, which is further extended into the road condition and verified under the dynamic cycle condition temporarily. In the end, the remaining useful life prediction under various operating conditions is discussed. Furthermore, the generalized method can provide an approach for prognostic decision-making and the updating of the dynamic polarization curve to expand the lifetime and optimize the control system.

Uncertainty propagation of turbulence parameters for typhoon and Non-typhoon winds in buffeting analysis of Long-span bridges

Wind turbulence-induced buffeting vibration affects the serviceability of long-span bridges and lead to fatigue problems. The randomness of turbulence parameters in the power spectrum density function is always disregarded, failing to well reproduce the dispersion of structural buffeting responses and achieve the extreme vibration amplitude. This study proposes a probabilistic buffeting analysis approach based on multi-point estimation, dimension reduction techniques, and the principle of maximum entropy accounting for the uncertainty of turbulence parameters. The uncertainties in turbulence power spectral density functions are quantified based on the long-term real observational wind data captured by the sensors installed at Xihoumen Bridge. These uncertainties are propagated into the buffeting response of the bridge using the proposed method. The results are compared with those of Monte Carlo simulation, suggesting a good agreement with substantially lower computational costs can be attained by the proposed method. Then, the probability density evolution of buffeting response versus wind speed is calculated. Results reveal that typhoon-induced buffeting response is greater than non-typhoon’s under low mean wind speeds (e.g., 25 m/s), whereas it is the opposite at high wind speeds (e.g., 30 m/s). The predicted probability density evolution of buffeting response exhibits a great consistency with real observations. By introducing the mean wind speed hazard curves for both typhoon and non-typhoon winds, the exceeding probability of vibration within a given period can be easily attained. It allows the estimation of return periods of structural responses and development of the uniform-risk approach for structure design rather than the conventional uniform-hazard design method.

Real-time low-carbon scheduling for the wind–thermal–hydro-storage resilient power system using linear stochastic robust optimization

With the large-scale wind power integration, power systems have to address not only the conventional power demand fluctuations but also the wind uncertainty. To improve the economical effectiveness, resilience, and environmental protection of power systems in the source-load uncertainty, a real-time low-carbon scheduling for the wind–thermal–hydro-storage integrated system is proposed. The power imbalance caused by the uncertainty is neutralized by the synergetic linear decision of multiple resources. To address the source-load uncertainty, a stochastic robust optimization is introduced, which establishes the system constraints by robust optimization for the resilience operation, while optimizing the expected operation cost in the empirical uncertainty distribution for economic efficiency. Moreover, a multi-point estimation is applied to formulate the expected operation cost precisely and quickly. By using the dual theory, the proposed real-time power scheduling is derived as a mixed integer bilinear constrained programming. A multi-step sequential convexified solution is developed to solve the complex scheduling problem, which linearizes the bilinear constraints with alternate optimization and relaxes the state variables of energy storages with an “estimation–correction” strategy. Finally, case studies show the superiority of the proposed scheduling method and convexified solution.

Python tools for ESA’s Swarm mission: VirES for Swarm and surrounding ecosystem

ESA’s Swarm mission is a constellation probing both Earth’s interior and geospace, delivering magnetic and plasma measurements which are used to generate many derived data products. From empirical magnetic field models of the core, crust, ionosphere, and magnetosphere, to multi-point estimates of ionospheric currents and in-situ plasma properties, these are challenging to navigate, process, and visualize. The VirES for Swarm platform (https://vires.services) has been built to tackle this problem, providing tools to increase usability of Swarm data products. The VirES (Virtual environments for Earth Scientists) platform provides both a graphical web interface and an API to access and visualise Swarm data and models. This is extended with a cloud-hosted development environment powered by JupyterHub (the “Virtual Research Environment/VRE”). VirES provides two API’s: the full VirES API for which a dedicated Python client is provided, viresclient, and the more interoperable Heliophysics API (HAPI). The VRE is furnished with a bespoke Python environment containing thematic libraries supporting science with Swarm. This service aims to ease the pathway for scientists writing computer code to analyze Swarm data products, increase opportunities for collaboration, and leverage cloud technologies. Beyond simply providing data and model access to Python users, it is extremely helpful to provide higher-level analysis and visualization tools, and ready-to-use code recipes that people can explore and extend. Critically for space physics, this involves crossover with many other datasets and so it is highly valuable to embed such tools within the wider data and software ecosystems. Through Swarm DISC (Data, Innovation, and Science Cluster), we are tackling this through cookbooks and Python libraries. Cookbooks are built and presented using Jupyter technologies, and tested to work within the VRE. A new library we are building is SwarmPAL, which includes tools for time-frequency analysis and inversion of magnetic field measurements for electric current systems, among others, while relying on the VirES server to provide data portability and other utilities. This paper reviews the current state of these tools and services for Swarm, particularly in the context of the Python in Heliophysics Community, and the wider heliophysics and geospace data environment.

DNN-based optical performance monitoring and its application for soft failure localization by multipoint estimation

In current optical communication networks, it is becoming increasingly important to use optical performance monitoring (OPM), which monitors the transmission characteristics of optical signals, to detect early degradation of features that may affect communication quality. This paper describes a method to realize OPM by training a deep neural network (DNN) with data obtained from digital coherent transceivers. In addition, we propose a dataset generation method, Data Augmentation using Differential Image (DADI), to enable the DNN to train with fewer data. We demonstrate that this method simultaneously classifies the optical signal to noise ratio and polarization mode dispersion with high accuracy. Furthermore, we apply DNN-based OPM to detect and localize soft failure in a multi-span environment. We develop a method to identify the location of soft failure by collecting information from DNN-based OPM estimated at multiple points in multi-span optical transmission links. We demonstrate that the method correctly localizes the soft failure with more than 90% accuracy on average (min, 85%; max, 98%) under single-channel experimental conditions.

Improved Multi-point estimation method based probabilistic transient stability assessment for power system with wind power

With the increasing penetration of wind power, probabilistic transient stability assessment becomes critical to deal with the uncertainties and correlations of wind power, thus improving the reliability of power system. This paper proposes an improved multi-point estimation based probabilistic transient stability assessment method. Extreme learning machine (ELM) is introduced to describe the uncertainty of practical wind power output. Gauss-Hermite integral based multi-point estimation method is proposed to calculate transient stability criterion derived through practical dynamic security region (PDSR). Optimal number of the sampling points is determined based on PDSR hyperplanes and an improved particle swarm optimization algorithm (IPSO). Test results on the New England 10-generators 39-buses system and a practical provincial power system in China show that the calculation accuracy of the proposed method is higher than that of other commonly-used point-estimation methods without much loss of computational efficiency under different wind power penetration and correlation levels.

Translation Initiator EIF4G1 Mutations in Familial Parkinson Disease

Genome-wide analysis of a multi-incident family with autosomal-dominant parkinsonism has implicated a locus on chromosomal region 3q26-q28. Linkage and disease segregation is explained by a missense mutation c.3614G>A (p.Arg1205His) in eukaryotic translation initiation factor 4-gamma (EIF4G1). Subsequent sequence and genotype analysis identified EIF4G1 c.1505C>T (p.Ala502Val), c.2056G>T (p.Gly686Cys), c.3490A>C (p.Ser1164Arg), c.3589C>T (p.Arg1197Trp) and c.3614G>A (p.Arg1205His) substitutions in affected subjects with familial parkinsonism and idiopathic Lewy body disease but not in control subjects. Despite different countries of origin, persons with EIF4G1 c.1505C>T (p.Ala502Val) or c.3614G>A (p.Arg1205His) mutations appear to share haplotypes consistent with ancestral founders. eIF4G1 p.Ala502Val and p.Arg1205His disrupt eIF4E or eIF3e binding, although the wild-type protein does not, and render mutant cells more vulnerable to reactive oxidative species. EIF4G1 mutations implicate mRNA translation initiation in familial parkinsonism and highlight a convergent pathway for monogenic, toxin and perhaps virally-induced Parkinson disease.

Identity by descent estimation with dense genome-wide genotype data

We present a novel method, IBDLD, for estimating the probability of identity by descent (IBD) for a pair of related individuals at a locus, given dense genotype data and a pedigree of arbitrary size and complexity. IBDLD overcomes the challenges of exact multipoint estimation of IBD in pedigrees of potentially large size and eliminates the difficulty of accommodating the background linkage disequilibrium (LD) that is present in high-density genotype data. We show that IBDLD is much more accurate at estimating the true IBD sharing than methods that remove LD by pruning SNPs and is highly robust to pedigree errors or other forms of misspecified relationships. The method is fast and can be used to estimate the probability for each possible IBD sharing state at every SNP from a high-density genotyping array for hundreds of thousands of pairs of individuals. We use it to estimate point-wise and genomewide IBD sharing between 185,745 pairs of subjects all of whom are related through a single, large and complex 13-generation pedigree and genotyped with the Affymetrix 500 k chip. We find that we are able to identify the true pedigree relationship for individuals who were misidentified in the collected data and estimate empirical kinship coefficients that can be used in follow-up QTL mapping studies. IBDLD is implemented as an open source software package and is freely available.

FASTKD2 Nonsense Mutation in an Infantile Mitochondrial Encephalomyopathy Associated with Cytochrome C Oxidase Deficiency

In two siblings we found a mitochondrial encephalomyopathy, characterized by developmental delay, hemiplegia, convulsions, asymmetrical brain atrophy, and low cytochrome c oxidase (COX) activity in skeletal muscle. The disease locus was identified on chromosome 2 by homozygosity mapping; candidate genes were prioritized for their known or predicted mitochondrial localization and then sequenced in probands and controls. A homozygous nonsense mutation in the KIAA0971 gene segregated with the disease in the proband family. The corresponding protein is known as fas activated serine-threonine kinase domain 2, FASTKD2. Confocal immunofluorescence colocalized a tagged recombinant FASTKD2 protein with mitochondrial markers, and membrane-potential-dependent in vitro mitochondrial import was demonstrated in isolated mitochondria. In staurosporine-induced-apoptosis experiments, decreased nuclear fragmentation was detected in treated mutant versus control fibroblasts. In conclusion, we found a loss-of-function mutation in a gene segregating with a peculiar mitochondrial encephalomyopathy associated with COX deficiency in skeletal muscle. The corresponding protein is localized in the mitochondrial inner compartment. Preliminary data indicate that FASTKD2 plays a role in mitochondrial apoptosis.

Quantitative trait loci influencing low density lipoprotein particle size in African Americans

Genomic regions that influence LDL particle size in African Americans are not known. We performed family-based linkage analyses to identify genomic regions that influence LDL particle size and also exert pleiotropic effects on two closely related lipid traits, high density lipoprotein cholesterol (HDL-C) and triglycerides, in African Americans. Subjects (n = 1,318, 63.0 +/- 9.5 years, 70% women, 79% hypertensive) were ascertained through sibships with two or more individuals diagnosed with essential hypertension before age 60. LDL particle size was measured by polyacrylamide gel electrophoresis, and triglyceride levels were log-transformed to reduce skewness. Genotypes were measured at 366 microsatellite marker loci distributed across the 22 autosomes. Univariate and bivariate linkage analyses were performed using a variance components approach. LDL particle size was highly heritable (h(2) = 0.78) and significantly (P < 0.0001) genetically correlated with HDL-C (rho(G) = 0.32) and log triglycerides (rho(G) = -0.43). Significant evidence of linkage for LDL particle size was present on chromosome 19 [85.3 centimorgan (cM), log of the odds (LOD) = 3.07, P = 0.0001], and suggestive evidence of linkage was present on chromosome 12 (90.8 cM, LOD = 2.02, P = 0.0011). Bivariate linkage analyses revealed tentative evidence for a region with pleiotropic effects on LDL particle size and HDL-C on chromosome 4 (52.9 cM, LOD = 2.06, P = 0.0069). These genomic regions may contain genes that influence interindividual variation in LDL particle size and potentially coronary heart disease susceptibility in African Americans.

Multi-point estimation of total energy expenditure: a comparison between zinc-reduction and platinum-equilibration methodologies

Reducing water to hydrogen gas by zinc or uranium metal for determining D/H ratio is both tedious and time consuming. This has forced most energy metabolism investigators to use the “two-point” technique instead of the “Multi-point” technique for estimating total energy expenditure (TEE). Recently, we purchased a new platinum (Pt)-equilibration system that significantly reduces both time and labor required for D/H ratio determination. In this study, we compared TEE obtained from nine overweight but healthy subjects, estimated using the traditional Zn-reduction method to that obtained from the new Pt-equilibration system. Rate constants, pool spaces, and CO 2 production rates obtained from use of the two methodologies were not significantly different. Correlation analysis demonstrated that TEEs estimated using the two methods were significantly correlated ( r=0.925, p=0.0001). Sample equilibration time was reduced by 66% compared to those of similar methods. The data demonstrated that the Zn-reduction method could be replaced by the Pt-equilibration method when TEE was estimated using the “Multi-Point” technique. Furthermore, D equilibration time was significantly reduced.

Prediction of in vivo hepatic clearance from in vitro data using cryopreserved human hepatocytes

1. Cryopreserved human hepatocytes were used to predict in vivo hepatic clearance (CL hepatic) from estimates of in vitro intrinsic clearance (). 2. was estimated for phenytoin, valproic acid, carbamazepine, theophylline, quinidine and procainamide after their addition to hepatocytes suspended either in human serum or in serum-free media. was estimated from in vitro concentration versus time data fitted to a monoexponential decay model. was estimated from concentrations measured at four time points and from just two-point measures, namely the initial concentration (C 0) and the final concentration measurement (C last). 3. Predicted CL hepatic was within twofold of reported in vivo values of CL hepatic for all substrates. Moreover, predictions were not significantly different whether derived from hepatocytes suspended in serum or in serum-free medium. 4. Two-point estimates of were just as accurate in predicting CL hepatic as were multipoint estimates of. 5. Although the data set was limited, the findings suggest that the measurement of the disappearance of xenobiotics from serum or serum-free media in which primary human hepatocytes have been suspended provides a physiologically relevant estimate of hepatic clearance that can be employed early in the drug development process to eliminate xenobiotics with unacceptable clearances.

Multipoint Estimation of Identity-by-Descent Probabilities at Arbitrary Positions among Marker Loci on General Pedigrees

Objectives: To describe, implement, and test an efficient algorithm to obtain multipoint identity-by-descent (IBD) probabilities at arbitrary positions among marker loci for general pedigrees. Unlike existing programs, our algorithm can analyze data sets with large numbers of people and markers. The algorithm has been implemented in the SimWalk2 computer package. Methods: Using a rigorous testing regimen containing five pedigrees of various sizes with realistic marker data, we compared several widely used IBD computation programs: Allegro, Aspex, GeneHunter, MapMaker/Sibs, Mendel, Sage, SimWalk2, and Solar. Results: The testing revealed a few discrepancies, particularly on consanguineous pedigrees, but overall excellent results in the deterministic multipoint packages. SimWalk2 was also found to be in good agreement with the deterministic multipoint programs, usually matching to two decimal places the kinship coefficient that ranges from 0 to 1. However, the packages based on single-point IBD estimation, while consistent with each other, often showed poor results, disagreeing with the multipoint kinship results by as much as 0.5. Conclusions: Our testing has clearly shown that multipoint IBD estimation is much better than single-point estimation. In addition, our testing has validated our algorithm for estimating IBD probabilities at arbitrary positions on general pedigrees.

Genetic mapping of QTLs controlling vegetative propagation in Eucalyptus grandis and E. urophylla using a pseudo-testcross strategy and RAPD markers

We have extended the combined use of the "pseudo-testcross" mapping strategy and RAPD markers to map quantitative trait loci (QTLs) controlling traits related to vegetative propagation in Eucalyptus. QTL analyses were performed using two different interval mapping approaches, MAPMAKER-QTL (maximum likelihood) and QTL-STAT (non-linear least squares). A total of ten QTLs were detected for micropropagation response (measured as fresh weight of shoots, FWS), six for stump sprouting ability (measured as # stump sprout cuttings, #Cutt) and four for rooting ability (measured as % rooting of cuttings, %Root). With the exception of three QTLs, both interval-mapping methods yielded similar results in terms of QTL detection. Discrepancies in the most likely QTL location were observed between the two methods. In 75% of the cases the most likely position was in the same, or in an adjacent, interval. Standardized gene substitution effects for the QTLs detected were typically between 0.46 and 2.1 phenotypic standard deviations (σp), while differences between the family mean and the favorable QTL genotype were between 0.25 and 1.07 (σp). Multipoint estimates of the total genetic variation explained by the QTLs (89.0% for FWS, 67.1 % for#Cutt, 62.7% for %Root) indicate that a large proportion of the variation in these traits is controlled by a relatively small number of major-effect QTLs. In this cross, E. grandis is responsible for most of the inherited variation in the ability to form shoots, while E. urophylla contributes most of the ability in rooting. QTL mapping in the pseudo-testcross configuration relies on withinfamily linkage disequilibrium to establish marker/trait associations. With this approach QTL analysis is possible in any available full-sib family generated from undomesticated and highly heterozygous organisms such as forest trees. QTL mapping on two-generation pedigrees opens the possibility of using already existing families in retrospective QTL analyses to gather the quantitative data necessary for marker-assisted tree breeding.

Moduli of continuity, isoperimetric profiles, and multi-point estimates in geometric heat equations

Estimates on moduli of continuity, isoperimetric profiles of various kinds, and quantities involving function values at several points have been central in several recent results in geometric analysis. This paper surveys some of the techniques and their applications. 1. INTRODUCTORY COMMENTS In this article I want to describe some techniques which have been applied with some success recently to a variety of problems, ranging from my proof with Julie Clutterbuck of the sharp lower bound on the fundamental gap for Schrodinger operators [8] to Brendle’s proof of the Lawson conjecture [29] and my proof with Haizhong Li of the Pinkall-Sterling conjecture [17]. I will discuss several other interesting applications below. The common thread in these techniques is the application of the maximum principle to functions involving several points or to functions depending on the global structure of solutions. Such techniques are not entirely new: In the analysis of parabolic equations in one variable, functions involving two points have been used extensively, going back to the work of Kružkov [61]. Later work using related ideas include the ‘concavity maximum principle’ of Korevaar [59], who considered the function C(x, y, μ) = u(μy + (1− μ)x)− μu(y)− (1− μ)u(x) for μ ∈ (0, 1) and x, y in the domain of u, with u satisfying some elliptic or parabolic equation. He used a maximum principle to prove non-positivity of C, implying convexity of the function u, for several situations of interest. Korevaar’s argument was later extended by several authors, notably Kawohl [55] and Kennington [56, 57]. I will mention later some contributions of Hamilton [51, 52] and Huisken [54] where related ideas were developed for applications in geometric flow problems. It should be pointed out also that very similar ideas arise in the theory of viscosity solutions as expounded by Crandall, Ishii and Lions [41] — for example the proof of the comparison principle there is based on the use of a two-point function to characterise semi-jets of a non-smooth function, and the basic computations involved are similar to some of those I will employ below. 2. PRESERVING MODULUS OF CONTINUITY IN HEAT EQUATIONS Perhaps the simplest example of applying the maximum principle to a function of several points arises in controlling the modulus of continuity of a solution of a parabolic equation. Consider a smooth solution of the heat equation in Rn, either on a domain with suitable boundary conditions (Neumann is simplest but others can also be handled) or otherwise with good control — for simplicity let us consider here only the case where the solution is spatially periodic in some lattice. We will consider mostly the heat equation, but the techniques work well also for a wider class of parabolic equations, which might be described as ‘quasilinear equations with gradient-dependent coefficients’. In particular these are quasilinear flows which are invariant under rigid motions of space, and vertical translation of the graph. In the Euclidean setting these equations preserve any initial modulus of continuity: More generally, for any fixed vector w, any inequality of the form u(x + w) − u(x) ≤ f(w) is Date: November 21, 2014. This survey describes work supported by Discovery Projects grants DP0985802, DP120102462 and DP120100097 of the Australian Research Council. 1