Quasi-optimal assimilation of satellite retrievals for incremental 4D-Var

An interface between satellite retrievals and the incremental version of the four-dimensional variational assimilation scheme is developed, making full use of the information content of satellite measurements. In this paper, expressions for the function that calculates simulated observations from model states (called “observation operator”), together with its tangent linear version and adjoint, are derived. Results from our work can be used for implementing a quasi-optimal assimilation of satellite retrievals (e.g., of atmospheric trace gases) in operational meteorological centres.

Spectral design and verification of HIRDLS filters and antireflection coatings using an integrated system performance approach

The HIRDLS instrument contains 21 spectral channels spanning a wavelength range from 6 to 18mm. For each of these channels the spectral bandwidth and position are isolated by an interference bandpass filter at 301K placed at an intermediate focal plane of the instrument. A second filter cooled to 65K positioned at the same wavelength but designed with a wider bandwidth is placed directly in front of each cooled detector element to reduce stray radiation from internally reflected in-band signals, and to improve the out-of-band blocking. This paper describes the process of determining the spectral requirements for the two bandpass filters and the antireflection coatings used on the lenses and dewar window of the instrument. This process uses a system throughput performance approach taking the instrument spectral specification as a target. It takes into account the spectral characteristics of the transmissive optical materials, the relative spectral response of the detectors, thermal emission from the instrument, and the predicted atmospheric signal to determine the radiance profile for each channel. Using this design approach an optimal design for the filters can be achieved, minimising the number of layers to improve the in-band transmission and to aid manufacture. The use of this design method also permits the instrument spectral performance to be verified using the measured response from manufactured components. The spectral calculations for an example channel are discussed, together with the spreadsheet calculation method. All the contributions made by the spectrally active components to the resulting instrument channel throughput are identified and presented.

On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Genetic algorithms for optimal control of beer fermentation

This paper uses genetic algorithms to optimise the mathematical model of a beer fermentation process that operates in batch mode. The optimisation is based in adjusting the temperature profile of the mixture during a fixed period of time in order to reach the required ethanol levels but considering certain operational and quality restrictions.

Optimal control of nonlinear systems represented by differential algebraic equations

An iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified simplified model based problem with parameter updating in such a manner that the correct solution of the original nonlinear problem is achieved.

Optimal control of nonlinear differential algebraic equation systems

A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

Inhibition of synaptic transmission and G protein modulation by synthetic CaV2.2 Ca2+ channel peptides

Abstract: Modulation of presynaptic voltage-dependent Ca+ channels is a major means of controlling neurotransmitter release. The CaV 2.2 Ca2+ channel subunit contains several inhibitory interaction sites for Gβγ subunits, including the amino terminal (NT) and I–II loop. The NT and I–II loop have also been proposed to undergo a G protein-gated inhibitory interaction, whilst the NT itself has also been proposed to suppress CaV 2 channel activity. Here, we investigate the effects of an amino terminal (CaV 2.2[45–55]) ‘NT peptide’ and a I–II loop alpha interaction domain (CaV 2.2[377–393]) ‘AID peptide’ on synaptic transmission, Ca2+ channel activity and G protein modulation in superior cervical ganglion neurones (SCGNs). Presynaptic injection of NT or AID peptide into SCGN synapses inhibited synaptic transmission and also attenuated noradrenaline-induced G protein modulation. In isolated SCGNs, NT and AID peptides reduced whole-cell Ca2+ current amplitude, modified voltage dependence of Ca2+ channel activation and attenuated noradrenaline-induced G protein modulation. Co-application of NT and AID peptide negated inhibitory actions. Together, these data favour direct peptide interaction with presynaptic Ca2+ channels, with effects on current amplitude and gating representing likely mechanisms responsible for inhibition of synaptic transmission. Mutations to residues reported as determinants of Ca2+ channel function within the NT peptide negated inhibitory effects on synaptic transmission, Ca2+ current amplitude and gating and G protein modulation. A mutation within the proposed QXXER motif for G protein modulation did not abolish inhibitory effects of the AID peptide. This study suggests that the CaV 2.2 amino terminal and I–II loop contribute molecular determinants for Ca2+ channel function; the data favour a direct interaction of peptides with Ca2+ channels to inhibit synaptic transmission and attenuate G protein modulation. Non-technical summary: Nerve cells (neurones) in the body communicate with each other by releasing chemicals (neurotransmitters) which act on proteins called receptors. An important group of receptors (called G protein coupled receptors, GPCRs) regulate the release of neurotransmitters by an action on the ion channels that let calcium into the cell. Here, we show for the first time that small peptides based on specific regions of calcium ion channels involved in GPCR signalling can themselves inhibit nerve cell communication. We show that these peptides act directly on calcium channels to make them more difficult to open and thus reduce calcium influx into native neurones. These peptides also reduce GPCR-mediated signalling. This work is important in increasing our knowledge about modulation of the calcium ion channel protein; such knowledge may help in the development of drugs to prevent signalling in pathways such as those involved in pain perception.

Reduced space optimal interpolation of daily rain gauge precipitation in Switzerland

The coarse spacing of automatic rain gauges complicates near-real- time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high- resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real-time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near-real-time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near-real-time observations only. The benefit is particularly strong for larger- scale precipitation and prominent topographic effects. Small-scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.

Semi-dwarfing (Rht-B1b) improves nitrogen-use efficiency in wheat, but not at economically optimal levels of nitrogen availability

A UK field experiment compared a complete factorial combination of three backgrounds (cvs Mercia, Maris Huntsman and Maris Widgeon), three alleles at the Rht-B1 locus as Near Isogenic Lines (NILs: rht-B1a (tall), Rht-B1b (semi-dwarf), Rht-B1c (severe dwarf)) and four nitrogen (N) fertilizer application rates (0, 100, 200 and 350 kg N/ha). Linear+exponential functions were fitted to grain yield (GY) and nitrogen-use efficiency (NUE; GY/available N) responses to N rate. Averaged over N rate and background Rht-B1b conferred significantly (P<0.05) greater GY, NUE, N uptake efficiency (NUpE; N in above ground crop / available N) and N utilization efficiency (NUtEg; GY / N in above ground crop) compared with rht-B1a and Rht-B1c. However the economically optimal N rate (Nopt) for N:grain price ratios of 3.5:1 to 10:1 were also greater for Rht-B1b, and because NUE, NUpE and NUtE all declined with N rate, Rht-Blb failed to increase NUE or its components at Nopt. The adoption of semi-dwarf lines in temperate and humid regions, and the greater N rates that such adoption justifies economically, greatly increases land-use efficiency, but not necessarily, NUE.

Sizing reserves within a landscape: the roles of villagers' reactions and the ecological-socioeconomic setting

Traditionally, siting and sizing decisions for parks and reserves reflected ecological characteristics but typically failed to consider ecological costs created from displaced resource collection, welfare costs on nearby rural people, and enforcement costs. Using a spatial game-theoretic model that incorporates the interaction of socioeconomic and ecological settings, we show how incorporating more recent mandates that include rural welfare and surrounding landscapes can result in very different optimal sizing decisions. The model informs our discussion of recent forest management in Tanzania, reserve sizing and siting decisions, estimating reserve effectiveness, and determining patterns of avoided forest degradation in Reduced Emissions from Deforestation and Forest Degradation programs.

Contrasting effects of dwarfing alleles and nitrogen availability on mineral concentrations in wheat grain

Background and aim Concentrations of essential minerals in plant foods may have declined in modern high-yielding cultivars grown with large applications of nitrogen fertilizer (N). We investigated the effect of dwarfing alleles and N rate on mineral concentrations in wheat. Methods Gibberellin (GA)-insensitive reduced height (Rht) alleles were compared in near isogenic wheat lines. Two field experiments comprised factorial combinations of wheat variety backgrounds, alleles at the Rht-B1 locus (rht-B1a, Rht-B1b, Rht-B1c), and different N rates. A glasshouse experiment also included Rht-D1b and Rht-B1b+D1b in one background. Results In the field, depending on season, Rht-B1b increased crop biomass, dry matter (DM) harvest index, grain yield, and the economically-optimal N rate (Nopt). Rht-B1b did not increase uptake of Cu, Fe, Mg or Zn so these minerals were diluted in grain. Nitrogen increased DM yield and mineral uptake so grain concentrations were increased (Fe in both seasons; Cu, Mg and Zn in one season). Rht-B1b reduced mineral concentrations at Nopt in the most N responsive season. In the glasshouse experiment, grain yield was reduced, and mineral concentrations increased, with Rht allele addition. Conclusion Effects of Rht alleles on Fe, Zn, Cu and Mg concentrations in wheat grain are mostly due to their effects on DM, rather than of GA-insensitivity on Nopt or mineral uptake. Increased N requirement in semi-dwarf varieties partly offsets this dilution effect.