Support vector machine classification for large data sets via minimum enclosing ball clustering

Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is highly dependent on the size of data set. This paper presents a novel SVM classification approach for large data sets by using minimum enclosing ball clustering. After the training data are partitioned by the proposed clustering method, the centers of the clusters are used for the first time SVM classification. Then we use the clusters whose centers are support vectors or those clusters which have different classes to perform the second time SVM classification. In this stage most data are removed. Several experimental results show that the approach proposed in this paper has good classification accuracy compared with classic SVM while the training is significantly faster than several other SVM classifiers.

Experimental assessment of oyster transfers as a vector for macroalgal introductions

Introduction of non-indigenous species can alter marine communities and ecosystems. In shellfish farming, transfer of livestock, especially oysters, is a common practice and potentially constitutes a pathway for non-indigenous introductions. Many species of seaweeds are believed to have been accidentally introduced in association with these transfers, but there is little direct evidence.

Building on IUCN regional red lists to produce lists of species of conservation priority: a model with Irish bees

A World Conservation Union (IUCN) regional red list is an objective assessment of regional extinction risk and is not the same as a list of conservation priority species. Recent research reveals the widespread, but incorrect, assumption that IUCN Red List categories represent a hierarchical list of priorities for conservation action. We developed a simple eight-step priority-setting process and applied it to the conservation of bees in Ireland. Our model is based on the national red list but also considers the global significance of the national population; the conservation status at global, continental, and regional levels; key biological, economic, and societal factors; and is compatible with existing conservation agreements and legislation. Throughout Ireland, almost one-third of the bee fauna is threatened (30 of 100 species), but our methodology resulted in a reduced list of only 17 priority species. We did not use the priority species list to broadly categorize species to the conservation action required; instead, we indicated the individual action required for all threatened, near-threatened, and data-deficient species on the national red list based on the IUCN's conservation-actions template file. Priority species lists will strongly influence prioritization of conservation actions at national levels, but action should not be exclusive to listed species. In addition, all species on this list will not necessarily require immediate action. Our method is transparent, reproducible, and readily applicable to other taxa and regions.

Hull fouling on commercial ships as a vector of macroalgal introduction

Hull fouling is thought to have been the vector of introduction for many algal species. We studied ships arriving at a Mediterranean harbour to clarify the present role of commercial cargo shipping in algal introductions. A total of 31 macroalgal taxa were identified from 22 sampled hulls. The majority of records (58%) were of species with a known cosmopolitan geographical distribution. Due to a prevalence of cosmopolitan species and a high turnover of fouling communities, species composition of assemblages did not appear to be influenced by the area of origin, length of ship or age of coating. In the light of the present results, hull fouling on standard trading commercial vessels does not seem to pose a significant risk for new macroalgal species introductions. However, a high proportion of non-cosmopolitan species found on a ship with non-toxic coating may modify this assessment, especially in the light of the increasing use of such coatings and the potential future changes in shipping routes.

Determination of the molecular weight distribution of non-enzymatic browning products formed by roasting of glucose and glycine and studies on their effects on NADPH-cytochrome c-reductase and glutathione-S-transferase in Caco-2 cells

After thermal treatment of a mixture of glucose and glycine for 2 h at 125 degreesC, about 60% of the starting material was converted into nonsoluble, black pigments, whereas 40% of the mixture was still water-soluble. Dialysis of the latter fraction revealed 30.4% of low molecular weight compounds (LMWs; MW <10 000 De) and 10.0% high-molecular weight products [HMWs; MW greater than or equal to 10000 Dal. The water-soluble Maillard reaction products (MRPs) were separated by gel permeation chromatography and ultrafiltration, revealing that 60% of the water-soluble products of the total carbohydrate/amino acid mixture had MWs <1 000 Da and consisted mainly of non-coloured reaction products. MRPs with MWs between 1000 and 30000 Da were Found in comparatively low yields (about 1.3%). In contrast, about 31.1% of the MRPs exhibited MWs > 30000 Da, amongst which 14.5% showed MWs > 100000 Da, thus indicating an oligomerisation of LMWs to melanoidins under roasting conditions. To investigate the physiological effects of these MRPs, xenobiotic enzyme activities were analysed in intestinal Caco-2 cells. For Phase-I NADPH-cytochrome c-reductase, the activity in the presence of the LMW and HMW fraction was decreased by 13% and 22%: respectively. Phase-II glutathione-S-transferase activity decreased by 15% and 18%, respectively, after incubation with the LMW and the HMW fractions. Considering the different yields, 30% and 10%, respectively, of the LMW and the HMW fractions, the total amount of the LMW fraction present in the glucose-glycine mixture is more active in modulating three enzyme activities than that of the HMW fraction.

Feasibility of a Clinical Chemical Analysis Approach to Predict Misuse of Growth Promoting Hormones in Cattle

A study was performed to determine if targeted metabolic profiling of cattle sera could be used to establish a predictive tool for identifying hormone misuse in cattle. Metabolites were assayed in heifers (n ) 5) treated with nortestosterone decanoate (0.85 mg/kg body weight), untreated heifers (n ) 5), steers (n ) 5) treated with oestradiol benzoate (0.15 mg/kg body weight) and untreated steers (n ) 5). Treatments were administered on days 0, 14, and 28 throughout a 42 day study period. Two support vector machines (SVMs) were trained, respectively, from heifer and steer data to identify hormonetreated animals. Performance of both SVM classifiers were evaluated by sensitivity and specificity of treatment prediction. The SVM trained on steer data achieved 97.33% sensitivity and 93.85% specificity while the one on heifer data achieved 94.67% sensitivity and 87.69% specificity. Solutions of SVM classifiers were further exploited to determine those days when classification accuracy of the SVM was most reliable. For heifers and steers, days 17-35 were determined to be the most selective. In summary, bioinformatics applied to targeted metabolic profiles generated from standard clinical chemistry analyses, has yielded an accurate, inexpensive, high-throughput test for predicting steroid abuse in cattle.

A low molecular weight hydro and organogelator derived from an isohexide and sol-gel transcription of the alcogel

Heating 2,5-di-O-methanesulfonyl-1,4:3,6-dianhydro-D-sorbitol (1) in a range of solvents led to the formation of a gel state at low concentrations. 1 was found to gel aromatics, alcohols and water. The structure of 1 in the solid state was solved by single crystal X-ray crystallography; no strong hydrogen bonds or associated solvents were found in the crystal. Electron micrographs revealed the morphology of the gels to be predominantly rod-like. The ethanol alcogel was used to template silica by sol-gel transcription.

Low-fat versus low-carbohydrate weight reduction diets:Effects on weight loss, insulin resistance, and cardiovascular risk: a randomized control trial

OBJECTIVE Low-fat hypocaloric diets reduce insulin resistance and prevent type 2 diabetes in those at risk. Low-carbohydrate, high-fat diets are advocated as an alternative, but reciprocal increases in dietary fat may have detrimental effects on insulin resistance and offset the benefits of weight reduction.

RESEARCH DESIGN AND METHODS We investigated a low-fat (20% fat, 60% carbohydrate) versus a low-carbohydrate (60% fat, 20% carbohydrate) weight reduction diet in 24 overweight/obese subjects ([mean ± SD] BMI 33.6 ± 3.7 kg/m2, aged 39 ± 10 years) in an 8-week randomized controlled trial. All food was weighed and distributed, and intake was calculated to produce a 500 kcal/day energy deficit. Insulin action was assessed by the euglycemic clamp and insulin secretion by meal tolerance test. Body composition, adipokine levels, and vascular compliance by pulse-wave analysis were also measured.

RESULTS Significant weight loss occurred in both groups (P < 0.01), with no difference between groups (P = 0.40). Peripheral glucose uptake increased, but there was no difference between groups (P = 0.28), and suppression of endogenous glucose production was also similar between groups. Meal tolerance–related insulin secretion decreased with weight loss with no difference between groups (P = 0.71). The change in overall systemic arterial stiffness was, however, significantly different between diets (P = 0.04); this reflected a significant decrease in augmentation index following the low-fat diet, compared with a nonsignificant increase within the low-carbohydrate group.

CONCLUSIONS This study demonstrates comparable effects on insulin resistance of low-fat and low-carbohydrate diets independent of macronutrient content. The difference in augmentation index may imply a negative effect of low-carbohydrate diets on vascular risk.