A phase-field model of relaxor ferroelectrics based on random field theory

A mechanically coupled phase-field model is proposed for the first time to simulate the peculiar behavior of relaxor ferroelectrics. Based on the random field theory for relaxors, local random fields are introduced to characterize the effect of chemical disorder. This generic model is developed from a thermodynamic framework and the microforce theory and is implemented by a nonlinear finite element method. Simulation results show that the model can reproduce relaxor features, such as domain miniaturization, small remnant polarization and large piezoelectric response. In particular, the influence of random field strength on these features are revealed. Simulation results on domain structure and hysteresis behavior are discussed and compared with related experimental results.Comment: 8 figure

Affective Music Information Retrieval

Much of the appeal of music lies in its power to convey emotions/moods and to evoke them in listeners. In consequence, the past decade witnessed a growing interest in modeling emotions from musical signals in the music information retrieval (MIR) community. In this article, we present a novel generative approach to music emotion modeling, with a specific focus on the valence-arousal (VA) dimension model of emotion. The presented generative model, called \emph{acoustic emotion Gaussians} (AEG), better accounts for the subjectivity of emotion perception by the use of probability distributions. Specifically, it learns from the emotion annotations of multiple subjects a Gaussian mixture model in the VA space with prior constraints on the corresponding acoustic features of the training music pieces. Such a computational framework is technically sound, capable of learning in an online fashion, and thus applicable to a variety of applications, including user-independent (general) and user-dependent (personalized) emotion recognition and emotion-based music retrieval. We report evaluations of the aforementioned applications of AEG on a larger-scale emotion-annotated corpora, AMG1608, to demonstrate the effectiveness of AEG and to showcase how evaluations are conducted for research on emotion-based MIR. Directions of future work are also discussed.Comment: 40 pages, 18 figures, 5 tables, author versio

Space Reclamation for Uncoordinated Checkpointing in Message-Passing Systems

Checkpointing and rollback recovery are techniques that can provide efficient recovery from transient process failures. In a message-passing system, the rollback of a message sender may cause the rollback of the corresponding receiver, and the system needs to roll back to a consistent set of checkpoints called recovery line. If the processes are allowed to take uncoordinated checkpoints, the above rollback propagation may result in the domino effect which prevents recovery line progression. Traditionally, only obsolete checkpoints before the global recovery line can be discarded, and the necessary and sufficient condition for identifying all garbage checkpoints has remained an open problem. A necessary and sufficient condition for achieving optimal garbage collection is derived and it is proved that the number of useful checkpoints is bounded by N(N+1)/2, where N is the number of processes. The approach is based on the maximum-sized antichain model of consistent global checkpoints and the technique of recovery line transformation and decomposition. It is also shown that, for systems requiring message logging to record in-transit messages, the same approach can be used to achieve optimal message log reclamation. As a final topic, a unifying framework is described by considering checkpoint coordination and exploiting piecewise determinism as mechanisms for bounding rollback propagation, and the applicability of the optimal garbage collection algorithm to domino-free recovery protocols is demonstrated

Characterisation of CD9 as a functional marker of cancer stem cells in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most common and most aggressive type of pancreatic cancer, with a five-year survival rate of approximately 5%. PDAC tumours are heterogeneous, containing morphologically, genetically and epigenetically distinct cancer cells, as well as large numbers of stromal and immune cells. To date there is no consensus on any well-defined cancer stem or tumour- initiating cell (CSC/TIC) in PDAC that might explain the tumour cell heterogeneity. Our laboratory recently identified the tetraspanin protein CD9 as a marker of PDAC CSCs/TICs. In this thesis, I further characterised CD9 as being a functional marker of these cells: in vitro, knocking down or overexpressing CD9 in mouse PDAC organoids decreased or increased organoid growth, respectively. These growth differences were recapitulated in tumour grafts in immuno-compromised mice. Furthermore, heterozygous deletion of CD9 in the embryonic pancreas in the commonly used Pdx1-Cre; LSL-KRasG12D; p53F/F and Pdx1-Cre; LSL-KRasG12D; p53F/+ mice prolonged overall survival. CD9 was therefore important in PDAC tumour initiation. Knocking out CD9 heterozygously in already-established tumours using a dual-recombinase genetic system showed that CD9 is also involved in tumour maintenance. Human PDAC patients with high levels of CD9 expression have a worse overall survival than patients with low levels of CD9 expression. Additionally, about 10% of patients have genomic amplifications of the CD9 locus. Mechanistically, CD9 interacted with several metabolite transporters in primary PDAC cells. In particular, CD9 promoted the plasma membrane localisation of the glutamine transporter ASCT2, which enhanced glutamine uptake. ASCT2 overexpression could rescue the growth defect of CD9-depleted PDAC cells, and CD9-depleted PDAC cells were more sensitive to a glutaminase inhibitor in vitro, supporting the functional link between CD9 and ASCT2. Overall, this work identifies the tetraspanin CD9 as an important functional marker of PDAC CSCs, which may have therapeutic implications in pancreatic cancer patients

Revisiting B_s\to\mu^+\mu^- and B\to K^{(*)}\mu^+\mu^- decays in the MSSM with and without R-parity

The rare decays B_s -> \mu^+\mu^- and B -> K^{(*)}\mu^+\mu^- are sensitive to new particles and couplings via their interferences with the standard model contributions. Recently, the upper bound on B(B_s -> \mu^+\mu^-) has been improved significantly by the CMS, LHCb, CDF, and D{\O} experiments. Combining with the measurements of B(B-> K^{(*)}\mu^+\mu^-), we derive constraints on the relevant parameters of minimal supersymmetic standard model with and without R-parity, and examine their contributions to the dimuon forward-backward asymmetry in B-> K^{*}\mu^+\mu^- decay. We find that (i) the contribution of R-parity violating coupling products \lambda^{\prime}_{2i2}\lambda^{\prime*}_{2i3} due to squark exchange is comparable with the theoretical uncertainties in B-> K \mu^+\mu^- decay, but still could be significant in B-> K^{*}\mu^+\mu^- decay and could account for the forward-backward asymmetry in all dimuon invariant mass regions; (ii) the constrained mass insertion (\delta^{u}_{LL})_{23} could have significant contribution to dA_{FB}(B-> K^{*}\mu^+\mu^-)/ds, and such effects are favored by thr recent results of the Belle, CDF, and LHCb experiments.Comment: 20 pages, 9 figures, published versio

Research on the Application of Blockchain in SMEs Credit Risk

The credit of an enterprise is related to its own development. This paper mainly discusses the relationship between the credit risk of small and medium enterprises (SMEs) and the application degree of blockchain. 64 listed companies with block chain technology as the core theme are selected to analyze their comprehensive financial data. Factor analysis is used to quantitatively evaluate the application degree of blockchain in SMEs, and then the Logistic model is used to evaluate the credit risk of SMEs. Finally, combining the application degree of blockchain in small and medium-sized enterprises and the credit risk assessment of these two groups of data. It confirms the conclusion that the higher the degree of blockchain application, the closer the supply chain finance relationship, and the better the credit status