Gaussian beta process

<p>This thesis presents a new framework for constituting a group of dependent completely random measures, unifying and extending methods in the literature. The dependent completely random measures are constructed based on a shared completely random measure, which is extended to the covariate space, and further differentiated by the covariate information associated with the data for which the completely random measures serve as priors. As a concrete example of the flexibility provided by the framework, a group of dependent feature learning measures are constructed based on a shared beta process, with Gaussian processes applied to build adaptive dependencies learnt from the practical data, denoted as the Gaussian beta process. Experiment results are presented for gene-expression series data (time as covariate), as well as digital image data (spatial location as covariate).</p>Thesi

Probing the effects of heterocyclic functionality in [(Benzene) Ru(TsDPENR) Cl] catalysts for asymmetric transfer hydrogenation

A range of TsDPEN catalysts containing heterocyclic groups on the amine nitrogen atom were prepared and evaluated in the asymmetric transfer hydrogenation of ketones. Bidentate and tridentate ligands demonstrated a mutual exclusivity directly related to their function as catalysts. A broad series of ketones were reduced with these new catalysts, permitting the ready identification of an optimal catalyst for each substrate and revealing the subtle effects that changes to nearby donor groups can exhibit

Applications of N′-monofunctionalised TsDPEN derivatives in asymmetric catalysis

This review contains an account of recent developments in the applications of N′-monoalkylated or N′-mono(thio)acylated(N-sulfonyl)-1,2-diphenylethylene-1,2-diamine (TsDPEN) derivatives to asymmetric catalysis. The coverage features examples of applications of derivatives as ligands in organometallic complexes for use in asymmetric reduction and oxidation reactions. The use of TsDPEN derivatives as catalysts in a diverse range of C–C and C–S bond formation reactions is also described in detail

Chemical compositions, antioxidant and antiproliferative properties of wheat

To promote its use in nutraceutical and functional ingredients, different growing environments, genotypes, and processing fractions of soft wheat (Triticum aestivum L.) were investigated for their chemical compositions and biological activities. The first study of this research investigated phytochemicals composition and antiproliferative activities of ten wheat bran samples. It was found that the individual wheat bran samples significantly differed in their chemical and biological properties. The second part of this research further studied influences of genotype (G), growing environment (E), and their interaction (G × E) on the phytochemical compositions and antioxidant properties of the same ten wheat bran cultivars. The results indicated that larger variability for health beneficial components and antioxidant properties of soft winter wheat bran were attributed more by E than G and G ×E. The third study was to investigate phytochemical profiles and antiproliferative properties of bread processing fractions (dough, crumb, and upper crust) from refined and whole-wheat flours. The results showed that baking reduced the concentrations of carotenoids and tocopherols, however, the upper crust fraction had significant higher levels of phenolic acids than in the dough and crumb fractions, suggesting that total phenolic acids content might not decrease during baking breads made from refined and whole wheat flours

Evaluation of drilling performance and penetration mechanisms using seismic while drilling and acoustic emission methods

In oil and gas industry, drilling provides the path to exploit underground resources. Increasing rate of penetration (ROP) is one of the goal of drilling engineers to build this path. This dissertation focuses on study of a novel drilling technique, i.e. passive Vibration Assisted Rotary Drilling (pVARD) technique, and characterization of drilling mechanisms in comparison to the other two widely used drilling techniques, i.e. rotary drilling and rotary-percussion drilling (RPD). In terms of the fundamental differences between drill bit vibrations from three drilling techniques, seismic while drilling (SWD) and acoustic emission (AE) technologies are used to study drill bit sources and corresponding drilling mechanisms. First, geomechanics response of synthetic rock is studied using AE technique based on standard confined compressive strength (CCS) tests. This research aims to compare synthetic to natural rock in terms of deformation properties and provides support for the following drill-off test (DOT). Second, pVARD tool drillings are conducted in comparison to rotary drilling both in laboratory and field tests using AE and SWD techniques, respectively. In laboratory, AE signal energy and cutting size distribution are correlated to polycrystalline diamond compact (PDC) bit drilling performance. Results show that micro crack is generated from drag bit shearing action and the higher AE energy, coarser cuttings and higher ROP are obtained. In field test, surface wave energy and frequency bandwidth are correlated to drill bit vibration and drilling performance. Third, laboratory active vibration DOTs are conducted to study the penetration mechanisms from a diamond coring bit using AE technique. Spectral and energy analysis of the AE signals indicate that the higher ROP and larger cutting size are correlated with a higher AE energy and a lower AE frequency, indicating larger fractures are being created to generate the larger size of cuttings. Fourth, rotary-percussion drilling sources are studied by two field experiments on weak shales and hard arkose using SWD technique. Characterization of these sources consist of spectral analysis and mean power study, along with field measurements of the source radiation patterns. In addition, polarization analysis is conducted on P-waves recorded at surface geophones for understanding the particle motions

CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion Recognition

Multimodal Emotion Recognition in Conversation (ERC) has garnered growing attention from research communities in various fields. In this paper, we propose a cross-modal fusion network with emotion-shift awareness (CFN-ESA) for ERC. Extant approaches employ each modality equally without distinguishing the amount of emotional information, rendering it hard to adequately extract complementary and associative information from multimodal data. To cope with this problem, in CFN-ESA, textual modalities are treated as the primary source of emotional information, while visual and acoustic modalities are taken as the secondary sources. Besides, most multimodal ERC models ignore emotion-shift information and overfocus on contextual information, leading to the failure of emotion recognition under emotion-shift scenario. We elaborate an emotion-shift module to address this challenge. CFN-ESA mainly consists of the unimodal encoder (RUME), cross-modal encoder (ACME), and emotion-shift module (LESM). RUME is applied to extract conversation-level contextual emotional cues while pulling together the data distributions between modalities; ACME is utilized to perform multimodal interaction centered on textual modality; LESM is used to model emotion shift and capture related information, thereby guide the learning of the main task. Experimental results demonstrate that CFN-ESA can effectively promote performance for ERC and remarkably outperform the state-of-the-art models.Comment: 13 pages, 10 figure