Benchmarking Least Squares Support Vector Machine Classifiers

In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set of equations in the dual space. While the SVM classifier has a large margin interpretation, the LS-SVM formulation is related in this paper to a ridge regression approach for classification with binary targets and to Fisher's linear discriminant analysis in the feature space. Multiclass categorization problems are represented by a set of binary classifiers using different output coding schemes. While regularization is used to control the effective number of parameters of the LS-SVM classifier, the sparseness property of SVMs is lost due to the choice of the 2-norm. Sparseness can be imposed in a second stage by gradually pruning the support value spectrum and optimizing the hyperparameters during the sparse approximation procedure. In this paper, twenty public domain benchmark datasets are used to evaluate the test set performance of LS-SVM classifiers with linear, polynomial and radial basis function (RBF) kernels. Both the SVM and LS-SVM classifier with RBF kernel in combination with standard cross-validation procedures for hyperparameter selection achieve comparable test set performances. These SVM and LS-SVM performances are consistently very good when compared to a variety of methods described in the literature including decision tree based algorithms, statistical algorithms and instance based learning methods. We show on ten UCI datasets that the LS-SVM sparse approximation procedure can be successfully applied.     

The effect of random grain distributions on fatigue crack initiation in a notched coarse grained superalloy specimen

Coarse grained superalloys are of large interest in high temperature applications, and can be found in e.g. gas turbine components, where great care must be given with respect to high temperature fatigue. Due to the large grain size, the material behaviour at e.g. sharp notches cannot be considered homogeneous. As a consequence, the fatigue behaviour is likely to expose a large variation. In order to numerically investigate this variation, a Monte Carlo analysis has been carried out by 100 FE-simulations of notched specimens, where placements and orientations of the grains were randomised. Furthermore, each grain was modelled as a unique single-crystal, displaying both anisotropic elastic and plastic behaviour and tension/compression asymmetry. The effect of randomness was investigated by the obtained dispersion in fatigue crack initiation life. It was concluded that the fatigue life behaviour of coarse grained nickel-base superalloys may show a considerable variation, which cannot be captured by one single deterministic analysis based on data for a homogenised material. Furthermore, the dispersion is of such a magnitude that it needs to be taken into account in industrial applications where highly stressed coarse grained materials are used.     

Natural Language and Logic of Agency

This light piece reflects on analogies between two often disjoint streams of research: the logical semantics and pragmatics of natural language and dynamic logics of general information-driven agency. The two areas show significant overlap in themes and tools, and yet, the focus seems subtly different in each, defying a simple comparison. We discuss some unusual questions that emerge when the two are put side by side, without any pretense at covering the whole literature or at reaching definitive conclusions.     

Escape trajectories are deflected when fish larvae intercept their own C-start wake

Fish larvae may intercept their own wake during sharp turns, which might affect their escape performance. We analysed C-starts of larval zebrafish (Danio rerio, Hamilton, 1822) using a computational fluid dynamics approach that simulates free swimming (swimming trajectory is determined by fluid forces) by coupling hydrodynamics and body dynamics. The simulations show that fish may intercept their own wake when they turn by 100–180°. During stage 1 of a C-start, the fish generates a strong jet at the tail that is shed into the wake. During stage 2, the fish intercepts this wake. Counterfactual simulations showed that wake interception increased the lateral force on the fish and reduced the fish''s turning angle by more than 5°. Wake interception caused no significant acceleration tangential to the trajectory of the fish and did not affect total power output. While experimental and simulation evidence suggests that fish larvae can either undershoot or intercept but not overshoot their wake, our simulations show that larger fish might be able to avoid intercepting their wake by either under- or overshooting. As intercepting its own wake modifies the fish''s escape trajectory, fish should account for this effect when planning their escape route.     

Separation of L‐aspartic acid and L‐glutamic acid mixtures for use in the production of bio‐based chemicals

BACKGROUND: Amino acids are promising feedstocks for the chemical industry due to their chemical functionality. They can be obtained by the hydrolysis of potentially inexpensive protein streams such as the byproduct of biofuel production. However, individual amino acids are required before they can be used for the further production of chemicals. Here, the separation of L‐aspartic acid (Asp) and L‐glutamic acid (Glu) mixture, which can be isolated from protein hydrolysis solutions at low pH or from electrodialysis of complex amino acid mixtures, was studied. RESULTS: Glu was converted into L‐pyroglutamic acid (pGlu) which can be separated from the mixture of Asp and Glu due to its higher solubility in water. The conversion was carried out under aqueous or melt conditions. Under aqueous conditions, the conversion was studied as a factor of time, temperature and the amount of Glu. The conversion was specific with high yield and not effected by Asp. After pGlu was separated from Asp and residual Glu by solubility difference, it can be transferred back to Glu through hydrolysis. CONCLUSION: The conversion of Glu to pGlu is specific and can be applied to separation Asp and Glu for their use in the production of bio‐based chemicals. Copyright © 2012 Society of Chemical Industry     

Degradation of erythromycin in honey and selection of suitable marker residues for food safety analysis

Extra-label use of veterinary medications in apiculture is a practice which is known to result in the presence of drug residues in honey. Erythromycin has been used by some beekeepers in an attempt to control foulbrood diseases in honey bees. It is recognised that erythromycin degrades in acidic aqueous solutions to yield predominantly anhydroerythromycin. Honey is an acidic medium in which erythromycin should also degrade. Three degradation products with a molecular weight of 715 Da (anhydroerythromycin, erythromycin enol ether, and an unidentified but suspected related isomer) have been confirmed to be formed in honey. Erythromycin was found to degrade rapidly in honey at typical hive temperature with a half-life of less than one day. Based on these results, it is recommended that food safety laboratories include degradation products in analytical testing protocols when examining honey for erythromycin residues.     

Bark as feedstock for dual fluidized bed gasifiers—Operability,efficiency, and economics

The demand for biofuels and biochemicals is expected to increase in the future, which will in turn increase the demand for biomass feedstock. Large gasification plants fueled with biomass feedstock are likely to be a key enabling technology in a resource‐efficient, bio‐based economy. Furthermore, the costs for producing biofuels and biochemicals in such plants could potentially be decreased by utilizing inexpensive low‐grade residual biomass as feedstock. This study investigates the usage of shredded tree bark as a feedstock for the production of biomethane in the GoBiGas demonstration plant in Gothenburg, Sweden, based on a 32 MW_th industrial dual fluidized bed gasification unit. The plant was operated with bark feedstock for 12 000 hours during the period 2014 to 2018. Data from the measurement campaign were processed using a stochastic approach to establish the plant's mass and energy balances, which were then compared with operation of the plant with wood pellets. For this comparison, an extrapolation algorithm was developed to predict plant performance using bark dried to the same moisture content as wood pellets, ie, 8%_w.b. Plant operation with bark feedstock was evaluated for operability, efficiency, and feedstock‐related cost. The gas quality achieved during the test period was similar to that obtained for operation with wood pellets. Furthermore, no significant ash sintering or agglomeration problems were observed more than 750 hours of operation. The calculated biomass‐to‐biomethane efficiency is 43% to 47% (lower heating value basis) for operation with wet bark. However, the predicted biomass‐to‐biomethane efficiency can be increased to 55%–65% for operation with bark feedstock dried to 8% moisture content, with corresponding feedstock costs in the range of 24.2 to 32.7 EUR/MWh; ie, a cost reduction of about 40% compared with wood pellets.