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.

What limits insect fecundity? Body size- and temperature-dependent egg maturation and oviposition in a butterfly

1. Large female insects usually have high potential fecundity. Therefore selection should favour an increase in body size given that these females get opportunities to realize their potential advantage by maturing and laying more eggs. However, ectotherm physiology is strongly temperature-dependent, and activities are carried out sufficiently only within certain temperature ranges. Thus it remains unclear if the fecundity advantage of a large size is fully realized in natural environments, where thermal conditions are limiting. 2. Insect fecundity might be limited by temperature at two levels; first eggs need to mature, and then the female needs time for strategic ovipositing of the egg. Since a female cannot foresee the number of oviposition opportunities that she will encounter on a given day, the optimal rate of egg maturation will be governed by trade-offs associated with egg- and time-limited oviposition. As females of different sizes will have different amounts of body reserves, size-dependent allocation trade-offs between the mother’s condition and her egg production might be expected. 3. In the temperate butterfly Pararge aegeria , the time and temperature dependence of oviposition and egg maturation, and the interrelatedness of these two processes were investigated in a series of laboratory experiments, allowing a decoupling of the time budgets for the respective processes. 4. The results show that realized fecundity of this species can be limited by both the temperature dependence of egg maturation and oviposition under certain thermal regimes. Furthermore, rates of oviposition and egg maturation seemed to have regulatory effects upon each other. Early reproductive output was correlated with short life span, indicating a cost of reproduction. Finally, large females matured more eggs than small females when deprived of oviposition opportunities. Thus, the optimal allocation of resources to egg production seems dependent on female size. 5. This study highlights the complexity of processes underlying rates of egg maturation and oviposition in ectotherms under natural conditions. We further discuss the importance of temperature variation for egg- vs. time-limited fecundity and the consequences for the evolution of female body size in insects.

Overexpression of marA, soxS and acrB in veterinary isolates of Salmonella enterica rarely correlates with cyclohexane tolerance

Objectives: To determine the contribution of the AcrAB efflux system to cyclohexane tolerance in Salmonella enterica. Methods: The expression of the efflux pump gene, acrB, and regulators marA and soxS from 46 isolates of S. enterica of 14 different serovars was determined by comparative RT-PCR and denaturing HPLC analysis. Results: Twenty-one of the 46 isolates were cyclohexane tolerant, a phenotype associated with multiple antibiotic resistance (MAR) and overexpression of efflux pumps. Of the cyclohexane-tolerant isolates 81% were MAR, whereas only 44% of the cyclohexane-susceptible isolates were MAR, confirming the association between cyclohexane tolerance and MAR. However, there was no correlation between cyclohexane tolerance or MAR and overexpression of acrB, soxS or marA. Conclusions: These data suggest that cyclohexane tolerance in S. enterica can be mediated by an acrB-independent mechanism.

Optimal estimation of sea surface temperature from split-window observations

Optimal estimation (OE) improves sea surface temperature (SST) estimated from satellite infrared imagery in the “split-window”, in comparison to SST retrieved using the usual multi-channel (MCSST) or non-linear (NLSST) estimators. This is demonstrated using three months of observations of the Advanced Very High Resolution Radiometer (AVHRR) on the first Meteorological Operational satellite (Metop-A), matched in time and space to drifter SSTs collected on the global telecommunications system. There are 32,175 matches. The prior for the OE is forecast atmospheric fields from the Météo-France global numerical weather prediction system (ARPEGE), the forward model is RTTOV8.7, and a reduced state vector comprising SST and total column water vapour (TCWV) is used. Operational NLSST coefficients give mean and standard deviation (SD) of the difference between satellite and drifter SSTs of 0.00 and 0.72 K. The “best possible” NLSST and MCSST coefficients, empirically regressed on the data themselves, give zero mean difference and SDs of 0.66 K and 0.73 K respectively. Significant contributions to the global SD arise from regional systematic errors (biases) of several tenths of kelvin in the NLSST. With no bias corrections to either prior fields or forward model, the SSTs retrieved by OE minus drifter SSTs have mean and SD of − 0.16 and 0.49 K respectively. The reduction in SD below the “best possible” regression results shows that OE deals with structural limitations of the NLSST and MCSST algorithms. Using simple empirical bias corrections to improve the OE, retrieved minus drifter SSTs are obtained with mean and SD of − 0.06 and 0.44 K respectively. Regional biases are greatly reduced, such that the absolute bias is less than 0.1 K in 61% of 10°-latitude by 30°-longitude cells. OE also allows a statistic of the agreement between modelled and measured brightness temperatures to be calculated. We show that this measure is more efficient than the current system of confidence levels at identifying reliable retrievals, and that the best 75% of satellite SSTs by this measure have negligible bias and retrieval error of order 0.25 K.