Search

To meet the demand for unmanned observation of tropical cyclones and to improve the tracking efficiency of multiple autonomous underwater vehicles (Multi-AUV), a forecast path correction model is proposed in this paper. Four types of points, which are mainly treated as model computational objects, are defined for abstracting the specific tropical cyclone (TC) tracking process. Necessary methodologies and a simplified model are harnessed and applied to Multi-AUV, facilitating the determination of points essential for solving the computations of the model. A correction algorithm is designed, serving as a guide for the tracking trajectory of Multi-AUV while concurrently ameliorating the errors inherent in conventional TC forecast data generation. The algorithm is proved to be effective. Finally, a simulation process is constructed to verify the effectiveness of the model, and the results conform well to the theory. This model furnishes a comprehensive blueprint for the realization of unmanned real-time observation of TCs. • Proposing a forecast path correction model for autonomous underwater vehicles. • Improving the accuracy of tracking the tropical cyclones. • Using current data and multilateration to determine the optimal center of tropical cyclones. • Reducing the position errors of traditional forecasting method. [ABSTRACT FROM AUTHOR]

Subgroup analysis, as the key component of personalized medicine development, has attracted a lot of interest in recent years. While a number of exploratory subgroup searching approaches have been proposed, informative evaluation criteria and scenario-based systematic comparison of these methods are still underdeveloped topics. In this article, we propose two evaluation criteria in connection with traditional type I error and power concepts, and another criterion to directly assess recovery performance of the underlying treatment effect structure. Extensive simulation studies are carried out to investigate empirical performance of a variety of tree-based exploratory subgroup methods under the proposed criteria. A real data application is also included to illustrate the necessity and importance of method evaluation. [ABSTRACT FROM AUTHOR]

Abstract An effective multi-walled carbon nanotubes/manganese dioxide (MWCNTs/MnO 2) nanocomposite-based polythiophene coating was prepared by electrodepositing MWCNTs, MnO 2 , and poly(3,4-ethylenedioxythiophene) (PEDOT) on a stainless-steel wire. After the headspace solid-phase microextraction (HS-SPME) based on the prepared coating, four polycyclic aromatic hydrocarbons (PAHs) with lower boiling point were determined by gas chromatography-flame ionization detection (GC-FID). The extraction efficiency of MWCNTs/MnO 2 /PEDOT composite coating was nearly 100 times higher than that of pure PEDOT coating, and nearly 20% higher than MWCNTs/PEDOT coating. The proposed HS-SPME-GC-FID analytical method had superior performance with good linearities (0.5–250 ng·g−1) and low limits of detection (LOD) (0.1–0.8 ng·g−1), which was successfully applied to the determination of PAHs in real soil samples. Highlights • A novel and effective composite coating (MWCNTs/MnO 2 /PEDOT) was prepared on a stainless-steel wire by electrodeposition. • The modified fiber was used for solid-phase microextraction of PAHs coupled with gas chromatography-flame ionization detection. • The extraction efficiency of the composite coating was nearly 100 times higher than that of the PEDOT coating, and nearly 20% higher than MWCNTs/PEDOT coating. • The established method was successfully applied to the extraction and determination of four PAHs in contaminated soil. [ABSTRACT FROM AUTHOR]

This article investigates the policy iteration (PI) method for the discounted optimal control (DOC) problem of continuous‐time linear systems. We show the properties and convergence of the PI method. The theory analysis shows that the convergence of PI can be ensured without requiring the initial admissible control gain. The convergence rate of the PI method is provided. An iteration‐termination criterion is established for detecting the stability of the closed‐loop system under the control gain obtained by executing PI. Two kinds of data‐driven implementations are constructed without using prior information of the system dynamics. A simulation example is presented to validated the properties of the PI method. [ABSTRACT FROM AUTHOR]

In a complex environment, in order to improve the efficiency of multi-AUV collaborative work, this paper proposes a new collaborative hunting algorithm based on the Bionic Neural Wave Network (BNWN) algorithm. This algorithm integrates search, tracking and capture of targets by multi-AUV under the incomplete navigation graphs. A search mechanism with memory tabu that to avoid redundant search and improve global search efficiency is designed. Then a real-time redistribution method is embedded into this algorithm to ensure the optimal matching state during the tracking and capture process. Further, multi-AUV track and capture prey based on energy consumption models and self-learning models, and recast time-varying navigation maps through the recognition mechanisms, under the whole collaborative operations. Simulation results have proved that the number of multi-AUV path turns is reduced and the execution time is shortened by an average of 81%. In this way, the optimal matching state is maintained, the repeated search and partial self-locking problems are overcome, and the efficient capture of intelligent prey is realized. • A mechanism for identifying unknown obstacles is proposed, which is integrated into the time-varying navigation map. • A search mechanism with memory tabu is proposed to improve the efficiency of global search. • A real-time redistribution mechanism is proposed to ensure the optimal matching state. • An energy consumption model and a self-learning model are proposed to complete the intelligent processing of prey. [ABSTRACT FROM AUTHOR]

[Display omitted] • A porous polythiophene/GO coating was prepared by electrodeposition. • Adsorption isotherm indicated π stacking effect played dominant role in extraction. • Four types of PAHs in food contact materials were determined by HS-SPME/GC-FID. A covalent complex of 3,4-ethylenedioxythiophene (EDOT) and graphene oxide (GO) was electrodeposited on an etched stainless-steel wire to obtain a robust polymeric film. The film presents a more fluffy porous morphology and higher thermal stability, which can be acted as solid phase microextraction (SPME) coating. The adsorption isotherms of the polycyclic aromatic hydrocarbons (PAHs) on the covalent PEDOT-GO coating showed the π stacking interaction happened between them. The coating showed high extraction efficiency for four PAHs, including naphthalene, 1-methyl naphthalene, acenaphthene and fluorene, which was nearly three times that of the PEDOT coating and higher than the commercial coatings. The covalent PEDOT-GO coating was applied to headspace SPME coupled with gas chromatography for the determination of PAHs. The linear range was 0.015–15 μg/L (R2 >0.99) and the limit of detection was 0.005–0.01 μg/L (S/N=3). It was successfully applied for the migration determination of PAHs in three types of food contact materials and the recovery was satisfactory in the range of 70–103%. [ABSTRACT FROM AUTHOR]

Accurate simulation of the hysteresis loop is challeng-ing, especially using manufacturer data. Traditional parameter extraction methods (e.g., using optimization algorithm and solving transcendental equation) can extract the static Jiles-Atherton (JA) hysteresis model parameters under an arbitrary condition, but it requires fitting parameters because the model parameters vary with flux density. To reduce the dependence on measurement data, this paper proposes a simple but effective parameter extraction method. Firstly, an identification procedure of minor loop is presented using only static B-P loss curves by investigating the influence of model parameters on hysteresis loop, where the average root-mean-square error of the hysteresis loop is decreased by 4. To estimate the dynamic loss coefficients under DC bias, a calculation method based on the Statistical Theory of Losses (STL) is established by investigating the law of influence of DC bias on hysteresis loss and dynamic loss. The effectiveness of the proposed method is verified. [ABSTRACT FROM AUTHOR]

Accurate prediction of core losses has been a crucial aspect in the field of electromagnetics for several decades. Extensive experimental results have shown that the core loss under harmonic excitation is more complicated than that under sinusoidal excitations, which means that the traditional core loss calculation methods are no longer applicable under distorted flux. In order to determine an efficient numerical approach when minor hysteresis loops occur, a harmonic magnetic test platform is used to study the effect of the variation of B–H properties on the iron loss and magnetic flux density of grain oriented silicon steel lamination under different supply voltages. A simple method, which could be used to predict the iron losses in thin laminations due to a number of non-sinusoidal waveforms with or without minor loops, for estimating the iron loss based on the loss separation method is proposed. The errors are substantially lower than those of conventional models while saving time. [ABSTRACT FROM AUTHOR]

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial. [ABSTRACT FROM AUTHOR]

Deficiency of β-Glucocerebrosidase (GBA) activity causes Gaucher Disease (GD). GD can be diagnosed by measuring GBA activity (Beutler and Kuhl, 1990). In this study, we assayed dried blood spots from a cohort (n = 528) enriched for GBA mutation carriers (n = 78) and GD patients (n = 18) using both the tandem mass spectrometry (MS/MS) and fluorescence assays and their respective synthetic substrates. The MS/MS assay differentiated normal controls, which included GBA mutation carriers, from GD patients with no overlap. The fluorescence assay did not always differentiate normal controls including GBA mutation carriers from GD patients and false positives were observed. The MS/MS assay improved specificity compared to the fluorescence assay. [ABSTRACT FROM AUTHOR]

Summary LY3009120 is a pan-RAF and RAF dimer inhibitor that inhibits all RAF isoforms and occupies both protomers in RAF dimers. Biochemical and cellular analyses revealed that LY3009120 inhibits ARAF, BRAF, and CRAF isoforms with similar affinity, while vemurafenib or dabrafenib have little or modest CRAF activity compared to their BRAF activities. LY3009120 induces BRAF-CRAF dimerization but inhibits the phosphorylation of downstream MEK and ERK, suggesting that it effectively inhibits the kinase activity of BRAF-CRAF heterodimers. Further analyses demonstrated that LY3009120 also inhibits various forms of RAF dimers including BRAF or CRAF homodimers. Due to these unique properties, LY3009120 demonstrates minimal paradoxical activation, inhibits MEK1/2 phosphorylation, and exhibits anti-tumor activities across multiple models carrying KRAS , NRAS , or BRAF mutation. [ABSTRACT FROM AUTHOR]

The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 16 cancer subtypes and identified 486 genes that were amplified in two or more datasets. The list was narrowed to 75 cancer-associated genes with potential “druggable” properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 42 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 42 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapters GRB2 and GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer drug targets and we further discuss potential novel opportunities for drug discovery efforts. [ABSTRACT FROM AUTHOR]