Template-free synthesis of functional 3D BN architecture for removal of dyes from water.

Three-dimensional (3D) architectures are of interest in applications in electronics, catalysis devices, sensors and adsorption materials. However, it is still a challenge to fabricate 3D BN architectures by a simple method. Here, we report the direct synthesis of 3D BN architectures by a simple thermal treatment process. A 3D BN architecture consists of an interconnected flexible network of nanosheets. The typical nitrogen adsorption/desorption results demonstrate that the specific surface area for the as-prepared samples is up to 1156 m(2) g(-1), and the total pore volume is about 1.17 cm(3) g(-1). The 3D BN architecture displays very high adsorption rates and large capacities for organic dyes in water without any other additives due to its low densities, high resistance to oxidation, good chemical inertness and high surface area. Importantly, 88% of the starting adsorption capacity is maintained after 15 cycles. These results indicate that the 3D BN architecture is potential environmental materials for water purification and treatment.

An enhanced fuzzy min-max neural network for pattern classification

An enhanced fuzzy min-max (EFMM) network is proposed for pattern classification in this paper. The aim is to overcome a number of limitations of the original fuzzy min-max (FMM) network and improve its classification performance. The key contributions are three heuristic rules to enhance the learning algorithm of FMM. First, a new hyperbox expansion rule to eliminate the overlapping problem during the hyperbox expansion process is suggested. Second, the existing hyperbox overlap test rule is extended to discover other possible overlapping cases. Third, a new hyperbox contraction rule to resolve possible overlapping cases is provided. Efficacy of EFMM is evaluated using benchmark data sets and a real medical diagnosis task. The results are better than those from various FMM-based models, support vector machine-based, Bayesian-based, decision tree-based, fuzzy-based, and neural-based classifiers. The empirical findings show that the newly introduced rules are able to realize EFMM as a useful model for undertaking pattern classification problems.

Examining performance of aggregation algorithms for neural network-based electricity demand forecasting

The aim of this research is to examine the efficiency of different aggregation algorithms to the forecasts obtained from individual neural network (NN) models in an ensemble. In this study an ensemble of 100 NN models are constructed with a heterogeneous architecture. The outputs from NN models are combined by three different aggregation algorithms. These aggregation algorithms comprise of a simple average, trimmed mean, and a Bayesian model averaging. These methods are utilized with certain modifications and are employed on the forecasts obtained from all individual NN models. The output of the aggregation algorithms is analyzed and compared with the individual NN models used in NN ensemble and with a Naive approach. Thirty-minutes interval electricity demand data from Australian Energy Market Operator (AEMO) and the New York Independent System Operator's web site (NYISO) are used in the empirical analysis. It is observed that the aggregation algorithm perform better than many of the individual NN models. In comparison with the Naive approach, the aggregation algorithms exhibit somewhat better forecasting performance.

Adding a new anticoagulant or antiplatelet agent for patient receiving aspirin after an acute coronary syndrome? - Results from a pairwise and network meta-analysis of randomized-controlled trials

 Objectives: To synthesize the efficacy and safety outcomes from randomized-controlled trials (RCTs) regarding new oral anticoagulant, protease-activated receptor-1 (PAR-1) antagonist, and warfarin adjunctive to aspirin for patients after acute coronary syndrome (ACS) via pair-wise and network meta-analyses.
Methods: A comprehensive literature search was performed in Embase, Medline, Cochrane Library Web of Knowledge, and Scopus. The pair-wise meta-analysis was undertaken respectively to each agent/treatment category via Revmen 5.1. In order to estimate the relative efficacy of each agent/treatment category whilst preserving the randomized comparisons within each trial, a Bayesian network meta-analysis was conducted in WinBUGS using both fixed- and random-effects model. Covariate analysis was performed to explore the effects of length of follow-up and age of subject on the final results.
Results: In total, 23 RCTs were included in the meta-analysis. As shown by the results (OR,95%CI) for the pair-wise meta-analysis, new oral anticoagulants (0.85, [0.78, 0.93] and 3.04, [2.21, 4.19]), PAR-1 antagonists (0.80, [0.52, 1.22] and 1.55, [1.25, 1.93]) and warfarin (0.87, [0.74, 1.02] and 1.77, [1.46, 2.14]) might be able to provide better outcome in the incidences of major adverse events (MAE) but with higher bleeding risk comparing to aspirin treatment alone. Based on the model fit assessment, the random-effects model was adopted. The network meta-analysis (treatment effect comparing to aspirin lone) identified ximelagatran (-0.3044, [-0.8601, 0.2502]), dabigatran (-0.2144, [-0.8666, 0.4525]), rivoroxaban (-0.2179, [-0.5986, 0.1628]) and vorapaxar (-0.2272, [-0.81, 0.1664]) produced better improvements in MAE incidences whereas vorapaxar (0.3764, [-0.4444, 1.124]), warfarin (0.663, [0.3375, 1.037]), ximelagatran (0.7509, [-0.4164, 2.002]) and apixaban (0.8594, [-0.0049, 1.7]) produced less major bleeding events. The indirect comparisons among drug category (difference in incidence comparing to aspirin lone) showed new oral anticoagulants (-0.1974, [-0.284, -0.111]) and PAR-1 antagonists (-0.1239, [-0.215, -0.033]) to besuperior to warfarin (-0.1004, [-0.166, -0.035]) in the occurrences of MAE whereas PAR-1 antagonists (0.4292, [0.2123, 0.6476]) afforded better outcomes in major bleeding events against warfarin (0.5742, [0.3889, 0.7619]) and new oral anticoagulants (1.169, [0.8667, 1.485]).
Conclusion: Based on the study results, we cannot recommend the routine administration of new oral anticoagulant as add-on treatment for patients after ACS. However, for ACS patients comorbid with atrial fibrillation, new oral anticoagulant might be superior to warfarin in both efficacy and safety outcomes.

Epidemiological and evolutionary inference of the transmission network of the 2014 highly pathogenic Avian Influenza H5N2 outbreak in British Columbia, Canada

The first North American outbreak of highly pathogenic avian influenza (HPAI) involving a virus of Eurasian A/goose/Guangdong/1/1996 (H5N1) lineage began in the Fraser Valley of British Columbia, Canada in late November 2014. A total of 11 commercial and 1 non-commercial (backyard) operations were infected before the outbreak was terminated. Control measures included movement restrictions that were placed on a total of 404 individual premises, 150 of which were located within a 3 km radius of an infected premise(s) (IP). A complete epidemiological investigation revealed that the source of this HPAI H5N2 virus for 4 of the commercial IPs and the single non-commercial IP likely involved indirect contact with wild birds. Three IPs were associated with the movement of birds or service providers and localized/environmental spread was suspected as the source of infection for the remaining 4 IPs. Viral phylogenies, as determined by Bayesian Inference and Maximum Likelihood methods, were used to validate the epidemiologically inferred transmission network. The phylogenetic clustering of concatenated viral genomes and the median-joining phylogenetic network of the viruses supported, for the most part, the transmission network that was inferred by the epidemiologic analysis.

Apicoplast-localized lysophosphatidic acid precursor assembly is required for bulk phospholipid synthesis in toxoplasma gondii and relies on an algal/plant-like glycerol 3-phosphate acyltransferase

Most apicomplexan parasites possess a non-photosynthetic plastid (the apicoplast), which harbors enzymes for a number of metabolic pathways, including a prokaryotic type II fatty acid synthesis (FASII) pathway. In Toxoplasma gondii, the causative agent of toxoplasmosis, the FASII pathway is essential for parasite growth and infectivity. However, little is known about the fate of fatty acids synthesized by FASII. In this study, we have investigated the function of a plant-like glycerol 3-phosphate acyltransferase (TgATS1) that localizes to the T. gondii apicoplast. Knock-down of TgATS1 resulted in significantly reduced incorporation of FASII-synthesized fatty acids into phosphatidic acid and downstream phospholipids and a severe defect in intracellular parasite replication and survival. Lipidomic analysis demonstrated that lipid precursors are made in, and exported from, the apicoplast for de novo biosynthesis of bulk phospholipids. This study reveals that the apicoplast-located FASII and ATS1, which are primarily used to generate plastid galactolipids in plants and algae, instead generate bulk phospholipids for membrane biogenesis in T. gondii.