Classification and fault detection methods for fuel cell monitoring and quality control

In this paper, various types of fault detection methods for fuel cells are compared. For example, those that use a model based approach or a data driven approach or a combination of the two. The potential advantages and drawbacks of each method are discussed and comparisons between methods are made. In particular, classification algorithms are investigated, which separate a data set into classes or clusters based on some prior knowledge or measure of similarity. In particular, the application of classification methods to vectors of reconstructed currents by magnetic tomography or to vectors of magnetic field measurements directly is explored. Bases are simulated using the finite integration technique (FIT) and regularization techniques are employed to overcome ill-posedness. Fisher's linear discriminant is used to illustrate these concepts. Numerical experiments show that the ill-posedness of the magnetic tomography problem is a part of the classification problem on magnetic field measurements as well. This is independent of the particular working mode of the cell but influenced by the type of faulty behavior that is studied. The numerical results demonstrate the ill-posedness by the exponential decay behavior of the singular values for three examples of fault classes.

Acoustic scattering : high frequency boundary element methods and unified transform methods

We describe some recent advances in the numerical solution of acoustic scattering problems. A major focus of the paper is the efficient solution of high frequency scattering problems via hybrid numerical-asymptotic boundary element methods. We also make connections to the unified transform method due to A. S. Fokas and co-authors, analysing particular instances of this method, proposed by J. A. De-Santo and co-authors, for problems of acoustic scattering by diffraction gratings.

Sensory and consumer science methods used with older adults: a review of current methods and recommendations for the future

Capturing the sensory perception and preferences of older adults, whether healthy or with particular disease states, poses major methodological challenges for the sensory community. Currently a vastly under researched area, it is at the same time a vital area of research as alterations in sensory perception can affect daily dietary food choices, intake, health and wellbeing. Tailored sensory methods are needed that take into account the challenges of working with such populations including poor access leading to low patient numbers (study power), cognitive abilities, use of medications, clinical treatments and context (hospitals and care homes). The objective of this paper was to review current analytical and affective sensory methodologies used with different cohorts of healthy and frail older adults, with focus on food preference and liking. We particularly drew attention to studies concerning general ageing as well as to those considering age-related diseases that have an emphasis on malnutrition and weight loss. Pubmed and Web of Science databases were searched to 2014 for relevant articles in English. From this search 75 papers concerning sensory acuity, 41 regarding perceived intensity and 73 relating to hedonic measures were reviewed. Simpler testing methods, such as directional forced choice tests and paired preference tests need to be further explored to determine whether they lead to more reliable results and better inter-cohort comparisons. Finally, sensory quality and related quality of life for older adults suffering from dementia must be included and not ignored in our future actions.

Approximate Gauss-Newton methods for nonlinear least squares problems

The Gauss–Newton algorithm is an iterative method regularly used for solving nonlinear least squares problems. It is particularly well suited to the treatment of very large scale variational data assimilation problems that arise in atmosphere and ocean forecasting. The procedure consists of a sequence of linear least squares approximations to the nonlinear problem, each of which is solved by an “inner” direct or iterative process. In comparison with Newton’s method and its variants, the algorithm is attractive because it does not require the evaluation of second-order derivatives in the Hessian of the objective function. In practice the exact Gauss–Newton method is too expensive to apply operationally in meteorological forecasting, and various approximations are made in order to reduce computational costs and to solve the problems in real time. Here we investigate the effects on the convergence of the Gauss–Newton method of two types of approximation used commonly in data assimilation. First, we examine “truncated” Gauss–Newton methods where the inner linear least squares problem is not solved exactly, and second, we examine “perturbed” Gauss–Newton methods where the true linearized inner problem is approximated by a simplified, or perturbed, linear least squares problem. We give conditions ensuring that the truncated and perturbed Gauss–Newton methods converge and also derive rates of convergence for the iterations. The results are illustrated by a simple numerical example. A practical application to the problem of data assimilation in a typical meteorological system is presented.

Methods and resources for climate impacts research: achieving synergy

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.

Comparison of ammonium lactate, sodium bicarbonate and double calcium lactate methods for extraction of phosphorus from wetland peat soils

Procedures for routine analysis of soil phosphorus (P) have been used for assessment of P status, distribution and P losses from cultivated mineral soils. No similar studies have been carried out on wetland peat soils. The objective was to compare extraction efficiency of ammonium lactate (PAL), sodium bicarbonate (P-Olsen), and double calcium lactate (P-DCaL) and P distribution in the soil profile of wetland peat soils. For this purpose, 34 samples of the 0-30, 30-60 and 60-90 cm layers were collected from peat soils in Germany, Israel, Poland, Slovenia, Sweden and the United Kingdom and analysed for P. Mean soil pH (CaCl2, 0.01 M) was 5.84, 5.51 and 5.47 in the 0-30, 30-60 and 60-90 cm layers, respectively. The P-DCaL was consistently about half the magnitude of either P-AL or P-Olsen. The efficiency of P extraction increased in the order P-DCaL < P-AL &LE; P-Olsen, with corresponding means (mg kg(-1)) for all soils (34 samples) of 15.32, 33.49 and 34.27 in 0-30 cm; 8.87, 17.30 and 21.46 in 30-60 cm; and 5.69, 14.00 and 21.40 in 60-90 cm. The means decreased with depth. When examining soils for each country separately, P-Olsen was relatively evenly distributed in the German, UK and Slovenian soils. P-Olsen was linearly correlated (r = 0.594, P = 0.0002) with pH, whereas the three P tests (except P-Olsen vs P-DCaL) significantly correlated with each other (P = 0.017850.0001). The strongest correlation (r = 0.617, P = 0.0001) was recorded for P-AL vs P-DCaL) and the two methods were inter-convertible using a regression equation: P-AL = -22.593 + 5.353 pH + 1.423 P-DCaL, R-2 = 0.550.

Cyclins, cyclin-dependent kinases, and cyclin-dependent kinase inhibitors: detection methods and activity measurements

The cyclin/cyclin-dependent kinase (Cdk) complexes and the Cdk inhibitors (CDKI) are crucial regulators of cell cycle progression in all eukaryotic cells. Using rat cardiac myocytes as a model system, this chapter provides a detailed account of methods that can be employed to measure both cyclin/Cdk activity in cells and the extent of CDKI inhibitory activity present in a particular cell type.

Combining physical, cultural and biological methods: prospects for integrated non-chemical weed management strategies

Physical, cultural and biological methods for weed control have developed largely independently and are often concerned with weed control in different systems: physical and cultural control in annual crops and biocontrol in extensive grasslands. We discuss the strengths and limitations of four physical and cultural methods for weed control: mechanical, thermal, cutting, and intercropping, and the advantages and disadvantages of combining biological control with them. These physical and cultural control methods may increase soil nitrogen levels and alter microclimate at soil level; this may be of benefit to biocontrol agents, although physical disturbance to the soil and plant damage may be detrimental. Some weeds escape control by these methods; we suggest that these weeds may be controlled by biocontrol agents. It will be easiest to combine biological control with. re and cutting in grasslands; within arable systems it would be most promising to combine biological control (especially using seed predators and foliar pathogens) with cover-cropping, and mechanical weeding combined with foliar bacterial and possibly foliar fungal pathogens. We stress the need to consider the timing of application of combined control methods in order to cause least damage to the biocontrol agent, along with maximum damage to the weed and to consider the wider implications of these different weed control methods.

Fine-root turnover rates of European forests revisited: an analysis of data from sequential coring and ingrowth cores

Background and Aims Forest trees directly contribute to carbon cycling in forest soils through the turnover of their fine roots. In this study we aimed to calculate root turnover rates of common European forest tree species and to compare them with most frequently published values. Methods We compiled available European data and applied various turnover rate calculation methods to the resulting database. We used Decision Matrix and Maximum-Minimum formula as suggested in the literature. Results Mean turnover rates obtained by the combination of sequential coring and Decision Matrix were 0.86 yr−1 for Fagus sylvatica and 0.88 yr−1 for Picea abies when maximum biomass data were used for the calculation, and 1.11 yr−1 for both species when mean biomass data were used. Using mean biomass rather than maximum resulted in about 30 % higher values of root turnover. Using the Decision Matrix to calculate turnover rate doubled the rates when compared to the Maximum-Minimum formula. The Decision Matrix, however, makes use of more input information than the Maximum-Minimum formula. Conclusions We propose that calculations using the Decision Matrix with mean biomass give the most reliable estimates of root turnover rates in European forests and should preferentially be used in models and C reporting.

Optimizing the methods of synthesis for barium hexagonal ferrite: an experimental and theoretical study

M-type barium hexaferrite (BaM) is a hard ferrite, crystallizing in space group P6(3)/mmc possessing a hexagonal magneto-plumbite structure, which consists of alternate hexagonal and spinel blocks. The structure of BaM is thus related to those of garnet and spinel ferrite. However the material has proved difficult to synthesize. By taking into account the presence of the spinel block in barium hexagonal ferrite, highly efficient new synthetic methods were devised with routes significantly different from existing ones. These successful variations in synthetic methods have been derived by taking into account a detailed investigation of the structural features of barium hexagonal ferrite and the least change principle whereby configuration changes are kept to a minimum. Thus considering the relevant mechanisms has helped to improve the synthesis efficiencies for both hydrothermal and co-precipitation methods by choosing conditions that invoke the formation of the cubic block or the less stable Fe3O4. The role played by BaFe2O4 in the synthesis is also discussed. The distribution of iron from reactants or intermediates among different sites was also successfully explained. The proposed mechanisms are based on the principle that the cubic block must be self-assembled to form the final product. Thus, it is believed that these formulated mechanisms should be helpful in designing experiments to obtain a deeper understanding of the synthesis process and to investigate the substitution of magnetic ions with doping ions.

What have dendritic cells ever done for adjuvant design? Cellular and molecular methods for the rational development of vaccine adjuvants

Our new molecular understanding of immune priming states that dendritic cell activation is absolutely pivotal for expansion and differentiation of naïve T lymphocytes, and it follows that understanding DC activation is essential to understand and design vaccine adjuvants. This chapter describes how dendritic cells can be used as a core tool to provide detailed quantitative and predictive immunomics information about how adjuvants function. The role of distinct antigen, costimulation, and differentiation signals from activated DC in priming is explained. Four categories of input signals which control DC activation – direct pathogen detection, sensing of injury or cell death, indirect activation via endogenous proinflammatory mediators, and feedback from activated T cells – are compared and contrasted. Practical methods for studying adjuvants using DC are summarised and the importance of DC subset choice, simulating T cell feedback, and use of knockout cells is highlighted. Finally, five case studies are examined that illustrate the benefit of DC activation analysis for understanding vaccine adjuvant function.

Some uniform stability and convergence results for integral equations on the real line and projection methods for their solution

The paper considers second kind equations of the form (abbreviated x=y + K2x) in which and the factor z is bounded but otherwise arbitrary so that equations of Wiener-Hopf type are included as a special case. Conditions on a set are obtained such that a generalized Fredholm alternative is valid: if W satisfies these conditions and I − Kz, is injective for each z ε W then I − Kz is invertible for each z ε W and the operators (I − Kz)−1 are uniformly bounded. As a special case some classical results relating to Wiener-Hopf operators are reproduced. A finite section version of the above equation (with the range of integration reduced to [−a, a]) is considered, as are projection and iterated projection methods for its solution. The operators (where denotes the finite section version of Kz) are shown uniformly bounded (in z and a) for all a sufficiently large. Uniform stability and convergence results, for the projection and iterated projection methods, are obtained. The argument generalizes an idea in collectively compact operator theory. Some new results in this theory are obtained and applied to the analysis of projection methods for the above equation when z is compactly supported and k(s − t) replaced by the general kernel k(s,t). A boundary integral equation of the above type, which models outdoor sound propagation over inhomogeneous level terrain, illustrates the application of the theoretical results developed.

Assessment of intercalibration methods for satellite microwave humidity sounders

Three methods for intercalibrating humidity sounding channels are compared to assess their merits and demerits. The methods use the following: (1) natural targets (Antarctica and tropical oceans), (2) zonal average brightness temperatures, and (3) simultaneous nadir overpasses (SNOs). Advanced Microwave Sounding Unit-B instruments onboard the polar-orbiting NOAA 15 and NOAA 16 satellites are used as examples. Antarctica is shown to be useful for identifying some of the instrument problems but less promising for intercalibrating humidity sounders due to the large diurnal variations there. Owing to smaller diurnal cycles over tropical oceans, these are found to be a good target for estimating intersatellite biases. Estimated biases are more resistant to diurnal differences when data from ascending and descending passes are combined. Biases estimated from zonal-averaged brightness temperatures show large seasonal and latitude dependence which could have resulted from diurnal cycle aliasing and scene-radiance dependence of the biases. This method may not be the best for channels with significant surface contributions. We have also tested the impact of clouds on the estimated biases and found that it is not significant, at least for tropical ocean estimates. Biases estimated from SNOs are the least influenced by diurnal cycle aliasing and cloud impacts. However, SNOs cover only relatively small part of the dynamic range of observed brightness temperatures.

Differentiating core and co-opted mechanisms in calculation: The neuroimaging of calculation in aphasia

The role of language in exact calculation is the subject of debate. Some behavioral and functional neuroimaging investigations of healthy participants suggest that calculation requires language resources. However, there are also reports of individuals with severe aphasic language impairment who retain calculation ability. One possibility in resolving these discordant findings is that the neural basis of calculation has undergone significant reorganization in aphasic calculators. Using fMRI, we examined brain activations associated with exact addition and subtraction in two patients with severe agrammatic aphasia and retained calculation ability. Behavior and brain activations during two-digit addition and subtraction were compared to those of a group of 11 healthy, age-matched controls. Behavioral results confirmed that both patients retained calculation ability. Imaging findings revealed individual differences in processing, but also a similar activation pattern across patients and controls in bilateral parietal cortices. Patients differed from controls in small areas of increased activation in peri-lesional regions, a shift from left fronto-temporal activation to the contralateral region, and increased activations in bilateral superior parietal regions. Our results suggest that bilateral parietal cortex represents the core of the calculation network and, while healthy controls may recruit language resources to support calculation, these mechanisms are not mandatory in adult cognition.

Portmanteau model diagnostics and tests for nonlinearity: a comparative Monte Carlo study of two alternative methods

This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes