Agile preference models based on soft constraints

An accurate model of the user’s preferences is a crucial element of most decision support systems. It is often assumed that users have a well-defined and stable set of preferences that can be elicited through a set of questions. However, recent research has shown that people very often construct their preferences on the fly depending on the available decision options. Thus, their answers to a series of questions before seeing decision options are likely to be inconsistent and often lead to erroneous models. To accurately capture preference expressions as people make them, it is necessary for the preference model to be agile: it should allow decision making with an incomplete preference model, and it should let users add, retract or revise individual preferences easily. We show how constraint satisfaction and in particular soft constraints provide the right formalism to do this, and give examples of its implementation in a travel planning tool

Control of Spin-Orbit Interaction in Conventional Semiconductor Quantum Wells

In this chapter, we demonstrate, focusing on GaAs quantum wells (QWs), a full control of spin-orbit (SO) interaction including both the Rashba and Dresselhaus terms in conventional semiconductor QWs. We determine the SO interaction in GaAs from single to double and triple wells, involving the electron occupation of either one or two subbands. Both the intraband and interband SO coefficients are computed. Two distinct regimes, depending on the QW width, for the control of SO terms, are found. Furthermore, we determine the persistent-spin-helix (PSH) symmetry points, where the Rashba and the renormalized (due to cubic corrections) Dresselhaus couplings are matched. These PSH symmetry points, at which quantum transport is diffusive (2D) for charge while ballistic (1D) for spin, are important for longtime and long-distance coherent spin control that is the keystone in spintronic devices

Design and evaluation issues for user-centric online product search

Nowadays more and more people are looking for products online, and a massive amount of products are being sold through e-commerce systems. It is crucial to develop effective online product search tools to assist users to find their desired products and to make sound purchase decisions. Currently, most existing online product search tools are not very effective in helping users because they ignore the fact that users only have limited knowledge and computational capacity to process the product information. For example, a search tool may ask users to fill in a form with too many detailed questions, and the search results may either be too minimal or too vast to consider. Such system-centric designs of online product search tools may cause some serious problems to end-users. Most of the time users are unable to state all their preferences at one time, so the search results may not be very accurate. In addition, users can either be impatient to view too much product information, or feel lost when no product appears in the search results during the interaction process. User-centric online product search tools can be developed to solve these problems and to help users make buying decisions effectively. The search tool should have the ability to recommend suitable products to meet the user's various preferences. In addition, it should help the user navigate the product space and reach the final target product without too much effort. Furthermore, according to behavior decision theory, users are likely to construct their preferences during the decision process, so the tool should be designed in an interactive way to elicit users' preferences gradually. Moreover, it should be decision supportive for users to make accurate purchasing decisions even if they don't have detail domain knowledge of the specific products. To develop effective user-centric online product search tools, one important task is to evaluate their performance so that system designers can obtain prompt feedback. Another crucial task is to design new algorithms and new user interfaces of the tools so that they can help users find the desired products more efficiently. In this thesis, we first consider the evaluation issue by developing a simulation environment to analyze the performance of generic product search tools. Compared to earlier evaluation methods that are mainly based on real-user studies, this simulation environment is faster and less expensive. Then we implement the CritiqueShop system, an online product search tool based on the well-known critiquing technique with two aspects of novelties: a user-centric compound critiquing generation algorithm which generates search results efficiently, and a visual user interface for enhancing user's satisfaction degree. Both the algorithm and the user interface are validated by large-scale comparative real-user studies. Moreover, the collaborative filtering approach is widely used to help people find low-risk products in domains such as movies or books. Here we further propose a recursive collaborative filtering approach that is able to generate search results more accurately without requiring additional effort from the users

Revealing nonclassicality beyond Gaussian states via a single marginal distribution

A standard method to obtain information on a quantum state is to measure marginal distributions along many different axes in phase space, which forms a basis of quantum state tomography. We theoretically propose and experimentally demonstrate a general framework to manifest nonclassicality by observing a single marginal distribution only, which provides a novel insight into nonclassicality and a practical applicability to various quantum systems. Our approach maps the 1-dim marginal distribution into a factorized 2-dim distribution by multiplying the measured distribution or the vacuum-state distribution along an orthogonal axis. The resulting fictitious Wigner function becomes unphysical only for a nonclassical state, thus the negativity of the corresponding density operator provides an evidence of nonclassicality. Furthermore, the negativity measured this way yields a lower bound for entanglement potential---a measure of entanglement generated using a nonclassical state with a beam splitter setting that is a prototypical model to produce continuous-variable (CV) entangled states. Our approach detects both Gaussian and non-Gaussian nonclassical states in a reliable and efficient manner. Remarkably, it works regardless of measurement axis for all non-Gaussian states in finite-dimensional Fock space of any size, also extending to infinite-dimensional states of experimental relevance for CV quantum informatics. We experimentally illustrate the power of our criterion for motional states of a trapped ion confirming their nonclassicality in a measurement-axis independent manner. We also address an extension of our approach combined with phase-shift operations, which leads to a stronger test of nonclassicality, i.e. detection of genuine non-Gaussianity under a CV measurement.Comment: 6 pages, 4 figures with Supplemental Informatio

Genetic Evolution and Molecular Selection of the HE Gene of Influenza C Virus

Influenza C virus (ICV) was first identified in humans and swine, but recently also in cattle, indicating a wider host range and potential threat to both the livestock industry and public health than was originally anticipated. The ICV hemagglutinin-esterase (HE) glycoprotein has multiple functions in the viral replication cycle and is the major determinant of antigenicity. Here, we developed a comparative approach integrating genetics, molecular selection analysis, and structural biology to identify the codon usage and adaptive evolution of ICV. We show that ICV can be classified into six lineages, consistent with previous studies. The HE gene has a low codon usage bias, which may facilitate ICV replication by reducing competition during evolution. Natural selection, dinucleotide composition, and mutation pressure shape the codon usage patterns of the ICV HE gene, with natural selection being the most important factor. Codon adaptation index (CAI) and relative codon deoptimization index (RCDI) analysis revealed that the greatest adaption of ICV was to humans, followed by cattle and swine. Additionally, similarity index (SiD) analysis revealed that swine exerted a stronger evolutionary pressure on ICV than humans, which is considered the primary reservoir. Furthermore, a similar tendency was also observed in the M gene. Of note, we found HE residues 176, 194, and 198 to be under positive selection, which may be the result of escape from antibody responses. Our study provides useful information on the genetic evolution of ICV from a new perspective that can help devise prevention and control strategies

Testing nonclassicality and non-Gaussianity in phase space

We theoretically propose and experimentally demonstrate a nonclassicality test of single-mode field in phase space, which has an analogy with the nonlocality test proposed by Banaszek and Wodkiewicz [Phys. Rev. Lett. 82, 2009 (1999)]. Our approach to deriving the classical bound draws on the fact that the Wigner function of a coherent state is a product of two independent distributions as if the orthogonal quadratures (position and momentum) in phase space behave as local realistic variables. Our method detects every pure nonclassical Gaussian state, which can also be extended to mixed states. Furthermore, it sets a bound for all Gaussian states and their mixtures, thereby providing a criterion to detect a genuine quantum non-Gaussian state. Remarkably, our phase-space approach with invariance under Gaussian unitary operations leads to an optimized test for a given non-Gaussian state. We experimentally show how this enhanced method can manifest quantum non-Gaussianity of a state by simply choosing phase-space points appropriately, which is essentially equivalent to implementing a squeezing operation on a given state.Comment: 5 pages and 3 figures with Supplemental Material, published versio