Polaronic effect in the x-ray absorption spectra of La1-x Ca x MnO3 manganites.

X-ray absorption spectroscopy (XAS) is performed to study changes in the electronic structures of colossal magnetoresistance (CMR) and charged ordered (CO) La1-x Ca x MnO3 manganites with respect to temperature. The pre-edge features in O and Mn K-edge XAS spectra, which are highly sensitive to the local distortion of MnO6 octahedral, exhibit contrasting temperature dependence between CMR and CO samples. The seemingly counter-intuitive XAS temperature dependence can be reconciled in the context of polarons. These results help identify the most relevant orbital states associated with polarons and highlight the crucial role played by polarons in understanding the electronic structures of manganites

Introduction to the ACM TIST Special Issue on Intelligent Healthcare Informatics

Healthcare Informatics is a research area dealing with the study and application of computer science and information and communication technology to face both theoretical/methodological and practical issues in healthcare, public health, and everyday wellness. Intelligent Healthcare Informatics may be defined as the specific area focusing on the use of artificial intelligence (AI) theories and techniques to offer important services (such as a component of complex systems) to allow integrated systems to perceive, reason, learn, and act intelligently in the healthcare arena. One of the many peculiarities of healthcare is that decision support systems need to be integrated with several heterogeneous systems supporting both collaborative work and process coordination and the management and analysis of a huge amount of clinical and health data, to compose intelligent, process-aware health information systems. After some pioneering work focusing explicitly on specific medical aspects and providing some efficient, even ad hoc, solutions, in recent years, AI in healthcare has been faced by researchers with different backgrounds and interests, taking into consideration the main results obtained in the more general and theoretical/methodological area of intelligent systems. Moreover, from a focus on reasoning strategies and deep knowledge representation, research in healthcare intelligent systems moved to data-intensive clinical tasks, where there is the need for supporting healthcare decision making in the presence of overwhelming amounts of clinical data. Significant solutions have been provided through a multidisciplinary combination of the results from the different research areas and their associated cultures, ranging from algorithms, to information systems and databases, to human-computer interaction, to medical informatics. To this regard, it is interesting to observe that, from one side, medical informaticians benefited by the general solutions coming from the generic computer science area, tailoring them to specific medical domains, while from the other side, computer scientists found several (still open) challenges in the medical and, more generally, health domains. This ACM Transactions on Intelligent Systems and Technology (ACM TIST) special issue contains articles discussing fundamental principles, algorithms, or applications for process-aware health information systems. Such articles are a sound answer to the research challenges for novel techniques, combinations of tools, and so forth to build effective ways to manage and deal in an integrated way with healthcare processes and data

Magnetic field controlled reversal of ferroelectric polarization in conical spin ordered multiferroics : Monte Carlo simulation

Author name used in this publication: 姚晓燕Author name used in this publication: 羅永祥Author name used in this publication: 刘俊明2009-2010 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Monte Carlo simulation on ferroelectric response to magnetic field in an elastic lsing spin chain

Author name used in this publication: 姚晓燕Author name used in this publication: Veng Cheong Lo, 羅永祥Author name used in this publication: 刘俊明2009-2010 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Magnetoelectric coupling induced by exchange striction in frustrated Ising spin chain : Monte Carlo simulation

Author name used in this publication: Veng Cheong Lo2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

The influence of magnetic anisotropy on magnetoelectric behavior in conical spin ordered multiferroic state

2009-2010 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Bayesian Nonparametric Estimation of Ex Post Variance

Variance estimation is central to many questions in finance and economics. Until now ex post variance estimation has been based on infill asymptotic assumptions that exploit high-frequency data. This article offers a new exact finite sample approach to estimating ex post variance using Bayesian nonparametric methods. In contrast to the classical counterpart, the proposed method exploits pooling over high-frequency observations with similar variances. Bayesian nonparametric variance estimators under no noise, heteroskedastic and serially correlated microstructure noise are introduced and discussed. Monte Carlo simulation results show that the proposed approach can increase the accuracy of variance estimation. Applications to equity data and comparison with realized variance and realized kernel estimators are included

Genome-wide profiling of uncapped mRNA

Gene transcripts are under extensive posttranscriptional regulation, including the regulation of their stability. A major route for mRNA degradation produces uncapped mRNAs, which can be generated by decapping enzymes, endonucleases, and small RNAs. Profiling uncapped mRNA molecules is important for the understanding of the transcriptome, whose composition is determined by a balance between mRNA synthesis and degradation. In this chapter, we describe a method to profile these uncapped mRNAs at the genome scale

Thermoelectric power of hot carriers in the nonequilibrium-statistical- operator approach

The thermoelectric power of charge carriers heated under a strong applied electric field in semiconductors is obtained by use of the nonequilibrium- statistical-operator (NSO) method. The balance equations are derived in terms of the NSO density matrix and the force-force correlation functions which can easily be calculated for a system with electron-impurity and electron-phonon interactions. A numerical study has been performed for hole-doped Ge. It is shown that the hot-electron thermoelectric power is sensitively affected by the applied electric field and that its sign is reversed at higher electric fields. © 1995 The American Physical Society.published_or_final_versio