Nonlinear set-membership estimation: a support vector machine approach

In this paper a support vector machine (SVM) approach for characterizing the feasible parameter set (FPS) in non-linear set-membership estimation problems is presented. It iteratively solves a regression problem from which an approximation of the boundary of the FPS can be determined. To guarantee convergence to the boundary the procedure includes a no-derivative line search and for an appropriate coverage of points on the FPS boundary it is suggested to start with a sequential box pavement procedure. The SVM approach is illustrated on a simple sine and exponential model with two parameters and an agro-forestry simulation model.

The effect of cruciferous and leguminous sprouts on genotoxicity, in vitro and in vivo

Vegetable consumption is associated with a reduced risk of colorectal cancer, which is the second most common cancer after lung/breast cancer within Europe. Some putative protective phytochemicals are found in higher amounts in young sprouts than in mature plants. The effect of an extract of mixed cruciferous and legume sprouts on DNA damage induced by H(2)O(2) was measured in HT29 cells using single cell microgelelectrophoresis (comet). Significant antigenotoxic effect (P < or = 0.05) was observed when HT29 cells were pre-incubated with the extract (100 and 200 microL/mL) for 24 hours and then challenged with H(2)O(2). A parallel design intervention study was carried out on 10 male and 10 female healthy adult volunteers (mean age = 25.5 years) fed 113 g of cruciferous and legume sprouts daily for 14 days. The effect of the supplementation was measured on a range of parameters, including DNA damage in lymphocytes (comet), the activity of various detoxifying enzymes (glutathione S-transferase, glutathione peroxidase, and superoxide dismutase), antioxidant status using the ferric reducing ability of plasma assay, plasma antioxidants (uric acid, ascorbic acid, and alpha-tocopherol), blood lipids, plasma levels of lutein, and lycopene. A significant antigenotoxic effect against H(2)O(2)-induced DNA damage was shown in peripheral blood lymphocytes of volunteers who consumed the supplemented diet when compared with the control diet (P = 0.04). No significant induction of detoxifying enzymes was observed during the study, neither were plasma antioxidant levels or activity altered. The results support the theory that consumption of cruciferous vegetables is linked to a reduced risk of cancer via decreased damage to DNA.

Parallel induction of modular classification rules

The Distributed Rule Induction (DRI) project at the University of Portsmouth is concerned with distributed data mining algorithms for automatically generating rules of all kinds. In this paper we present a system architecture and its implementation for inducing modular classification rules in parallel in a local area network using a distributed blackboard system. We present initial results of a prototype implementation based on the Prism algorithm.

Parallel rule induction with information theoretic pre-pruning

In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to inducing classification rules, one is the divide and conquer approach, also known as the top down induction of decision trees; the other approach is called the separate and conquer approach. A considerable amount of work has been done on scaling up the divide and conquer approach. However, very little work has been conducted on scaling up the separate and conquer approach.In this work we describe a parallel framework that allows the parallelisation of a certain family of separate and conquer algorithms, the Prism family. Parallelisation helps the Prism family of algorithms to harvest additional computer resources in a network of computers in order to make the induction of classification rules scale better on large datasets. Our framework also incorporates a pre-pruning facility for parallel Prism algorithms.

P-Prism: a computationally efficient approach to scaling up classification rule induction

Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unseen data. Alternative algorithms have been developed such as the Prism algorithm. Prism constructs modular rules which produce qualitatively better rules than rules induced by TDIDT. However, along with the increasing size of databases, many existing rule learning algorithms have proved to be computational expensive on large datasets. To tackle the problem of scalability, parallel classification rule induction algorithms have been introduced. As TDIDT is the most popular classifier, even though there are strongly competitive alternative algorithms, most parallel approaches to inducing classification rules are based on TDIDT. In this paper we describe work on a distributed classifier that induces classification rules in a parallel manner based on Prism.

Towards a computationally efficient approach to modular classification rule induction

Induction of classification rules is one of the most important technologies in data mining. Most of the work in this field has concentrated on the Top Down Induction of Decision Trees (TDIDT) approach. However, alternative approaches have been developed such as the Prism algorithm for inducing modular rules. Prism often produces qualitatively better rules than TDIDT but suffers from higher computational requirements. We investigate approaches that have been developed to minimize the computational requirements of TDIDT, in order to find analogous approaches that could reduce the computational requirements of Prism.

Induction of modular classification rules: using Jmax-pruning

The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree structure. Classifiers induced by Prism algorithms achieve a comparable accuracy compared with decision trees and in some cases even outperform decision trees. Both kinds of algorithms tend to overfit on large and noisy datasets and this has led to the development of pruning methods. Pruning methods use various metrics to truncate decision trees or to eliminate whole rules or single rule terms from a Prism rule set. For decision trees many pre-pruning and postpruning methods exist, however for Prism algorithms only one pre-pruning method has been developed, J-pruning. Recent work with Prism algorithms examined J-pruning in the context of very large datasets and found that the current method does not use its full potential. This paper revisits the J-pruning method for the Prism family of algorithms and develops a new pruning method Jmax-pruning, discusses it in theoretical terms and evaluates it empirically.

Scaling up classification rule induction through parallel processing

The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelization seems to be a natural and cost-effective way to scale up data mining technologies. One of the most important of these data mining technologies is the classification of newly recorded data. This paper surveys advances in parallelization in the field of classification rule induction.

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

Carbon monoxide induces cardiac arrhythmia via induction of the late Na+ current

Our data indicate that the proarrhythmic effects of CO arise from activation of NO synthase, leading to NO-mediated nitrosylation of Na(V)1.5 and to induction of the late Na(+) current. We also show that the antianginal drug ranolazine can abolish CO-induced early after-depolarizations, highlighting a novel approach to the treatment of CO-induced arrhythmias.

The induction of mental and contact contamination

Background: Extreme fear of contamination within Obsessive Compulsive Disorder is traditionally conceptualised as a physical phenomenon. More recent research has supported the notion of ‘mental’ contamination, in which people feel contaminated in the absence of physical contact. The current research sought to determine whether feelings of contact and mental contamination could be induced within a non-clinical sample, whether the impact of mental and contact contamination was comparable in terms of associated feelings and behaviour and whether related psychopathology related to the impact of the tasks. Methods: Undergraduate students (n=60) completed OCD relevant measures and were randomly assigned to either a contact contamination condition (CC: moving a bucket of fake vomit) or a mental contamination condition (MC: thinking about a bucket of vomit). Results: Both manipulations induced feelings of contamination. Participants in the contact condition had significantly greater urges to wash than those in the mental condition. Neutralising behaviour did not differ across conditions. Conclusions: Feelings of contamination can be induced in the absence of physical contact and for those in the MC group, some aspects of OCD-relevant psychopathology were related to the impact of the manipulation. These findings have implications for the understanding and treatment of contamination-related fears in OCD.

Incremental effect of a calcium salt of cis-monounsaturated fatty acids supplement on milk fatty acid composition in cows fed maize silage-based diets

In most Western countries, saturated fatty acid (SFA) intake exceeds recommended levels, which is considered a risk factor for cardiovascular disease (CVD). As milk and dairy products are major contributors to SFA intake in many countries, recent research has focused on sustainable methods of producing milk with a lower saturated fat concentration by altering dairy cow diets. Human intervention studies have shown that CVD risk can be reduced by consuming dairy products with reduced SFA and increased cis-monounsaturated fatty acid (MUFA) concentrations. This milk fatty acid profile can be achieved by supplementing dairy cow diets with cis-MUFA-rich unsaturated oils. However, rumen exposure of unsaturated oils also leads to enhanced milk trans fatty acid (TFA) concentrations. Because of concerns about the effects of TFA consumption on CVD, feeding strategies that increase MUFA concentrations in milk without concomitant increases in TFA concentration are preferred by milk processors. In an attempt to limit TFA production and increase the replacement of SFA by cis-MUFA, a preparation of rumen-protected unsaturated oils was developed using saponification with calcium salts. Four multiparous Holstein-Friesian cows in mid-late lactation were used in a 4 × 4 Latin square design with 21-d periods to investigate the effect of incremental dietary inclusion of a calcium salt of cis-MUFA product (Ca-MUFA; 20, 40, and 60 g/kg of dry matter of a maize silage-based diet), on milk production, composition, and fatty acid concentration. Increasing Ca-MUFA inclusion reduced dry matter intake linearly, but no change was observed in estimated ME intake. No change in milk yield was noted, but milk fat and protein concentrations were linearly reduced. Supplementation with Ca-MUFA resulted in a linear reduction in total SFA (from 71 to 52 g/100 g of fatty acids for control and 60 g/kg of dry matter diets, respectively). In addition, concentrations of both cis- and trans-MUFA were increased with Ca-MUFA inclusion, and increases in other biohydrogenation intermediates in milk fat were also observed. The Ca-MUFA supplement was very effective at reducing milk SFA concentration and increasing cis-MUFA concentrations without incurring any negative effects on milk and milk component yields. However, reduced milk fat and protein concentrations, together with increases in milk TFA concentrations, suggest partial dissociation of the calcium salts in the rumen

Effect of forage conservation method on plasma lipids, mammary lipogenesis, and milk fatty acid composition in lactating cows fed diets containing a 60:40 forage-to-concentrate ratio

The effects of forage conservation method on plasma lipids, mammary lipogenesis, and milk fat were examined in 2 complementary experiments. Treatments comprised fresh grass, hay, or untreated (UTS) or formic acid treated silage (FAS) prepared from the same grass sward. Preparation of conserved forages coincided with the collection of samples from cows fed fresh grass. In the first experiment, 5 multiparous Finnish Ayrshire cows (229 d in milk) were used to compare a diet based on fresh grass followed by hay during 2 consecutive 14-d periods, separated by a 5-d transition during which extensively wilted grass was fed. In the second experiment, 5 multiparous Finnish Ayrshire cows (53 d in milk) were assigned to 1 of 2 blocks and allocated treatments according to a replicated 3 × 3 Latin square design, with 14-d periods to compare hay, UTS, and FAS. Cows received 7 or 9 kg/d of the same concentrate in experiments 1 and 2, respectively. Arterial concentrations of triacylglycerol (TAG) and phospholipid were higher in cows fed fresh grass, UTS, and FAS compared with hay. Nonesterified fatty acid (NEFA) concentrations and the relative abundance of 18:2n-6 and 18:3n-3 in TAG of arterial blood were also higher in cows fed fresh grass than conserved forages. On all diets, TAG was the principle source of fatty acids (FA) for milk fat synthesis, whereas mammary extraction of NEFA was negligible, except during zero-grazing, which was associated with a lower, albeit positive calculated energy balance. Mammary FA uptake was higher and the synthesis of 16:0 lower in cows fed fresh grass than hay. Conservation of grass by drying or ensiling had no influence on mammary extraction of TAG and NEFA, despite an increase in milk fat secretion for silages compared with hay and for FAS than UTS. Relative to hay, milk fat from fresh grass contained lower 12:0, 14:0, and 16:0 and higher S3,R7,R11,15-tetramethyl-16:0, cis-9 18:1, trans-11 18:1, cis-9,trans-11 18:2, 18:2n-6, and 18:3n-3 concentrations. Even though conserved forages altered mammary lipogenesis, differences in milk FA composition were relatively minor, other than a higher enrichment of S3,R7,R11,15-tetramethyl-16:0 in milk from silages compared with hay. In conclusion, differences in milk fat composition on fresh grass relative to conserved forages were associated with a lower energy balance, increased uptake of preformed FA, and decreased synthesis of 16:0 de novo in the mammary glands, in the absence of alterations in stearoyl-coenzyme A desaturase activity.

Good machine performance in Turing’s imitation game

In this paper we consider transcripts which originated from a practical series of Turing’s Imitation Game which was held on 23rd June 2012 at Bletchley Park, England. In some cases the tests involved a 3-participant simultaneous comparison of two hidden entities whereas others were the result of a direct 2-participant interaction. Each of the transcripts considered here resulted in a human interrogator being fooled, by a machine, into concluding that they had been conversing with a human. Particular features of the conversation are highlighted, successful ploys on the part of each machine discussed and likely reasons for the interrogator being fooled are considered. Subsequent feedback from the interrogators involved is also included

Simulations of angular momentum evolution in wind-fed CV precursors

It is thought that the secondary stars in cataclysmic variables (CVs) may undergo a period of mass loss in the form of a wind during the evolution of the system (Mullan et al. 1992). This wind is thought to magnetically brake the secondary star with a time-scale ~ 10^8 yr (e.g. van Paradijs 1986). When the secondary’s spin has been brought close to synchronism with the orbit it is possible for tidal torques to lock the secondary in synchronous rotation.