Multichannel direct detection of light dark matter: Target comparison

Direct-detection experiments for light dark matter are making enormous leaps in reaching previously unexplored model space. Several recent proposals rely on collective excitations, where the experimental sensitivity is highly dependent on detailed properties of the target material, well beyond just nucleus mass numbers as in conventional searches. It is thus important to optimize the target choice when considering which experiment to build. We carry out a comparative study of target materials across several detection channels, focusing on electron transitions and single (acoustic or optical) phonon excitations in crystals, as well as the traditional nuclear recoils. We compare materials currently in use in nuclear recoil experiments (Si, Ge, NaI, CsI, CaWO4), a few of which have been proposed for light dark matter experiments (GaAs, Al2O3, diamond), as well as 16 other promising polar crystals across all detection channels. We find that target- and dark-matter-model-dependent reach is largely determined by a small number of material parameters: speed of sound, electronic band gap, mass number, Born effective charge, high-frequency dielectric constant, and optical phonon energies. We showcase, for each of the two benchmark models, an exemplary material that has a better reach than in any currently proposed experiment

Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment

Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for AU detection. Most existing AU detection works often treat face alignment as a preprocessing and handle the two tasks independently. In this paper, we propose a novel end-to-end deep learning framework for joint AU detection and face alignment, which has not been explored before. In particular, multi-scale shared features are learned firstly, and high-level features of face alignment are fed into AU detection. Moreover, to extract precise local features, we propose an adaptive attention learning module to refine the attention map of each AU adaptively. Finally, the assembled local features are integrated with face alignment features and global features for AU detection. Experiments on BP4D and DISFA benchmarks demonstrate that our framework significantly outperforms the state-of-the-art methods for AU detection.Comment: This paper has been accepted by ECCV 201

BIM collaboration: A conceptual model and its characteristics

Relationship management has become an important issue for both academics and practitioners in construction project management. Few study provide a clear picture of what specifically constitute collaboration in a construction project in the existing literature and the practical approach. Limit research focus on developing a collaboration theory in construction management. The advent of Building Information Modeling (BIM) has been proved to be helpful for improving project coordination and productivity. However, widely adoption of BIM does not change the fragmented nature of construction sector. An understanding of how to promote such collaborative relationships in BIM enabled projects is crucial to achieve the full potential of BIM. By analysing the characteristics of collaboration from a management perspective and investigating current BIM implementation strategy, this research develops a conceptual model of collaboration in BIM enabled projects and identifies main factors of collaboration. The model categorizes collaboration into three dimension, they are collaboration team characteristics, collaborative environment, and collaborative process. Model also presents high level of collaboration can result better project outcomes and participants satisfaction. This model can be generalized to construction sector and standardized to collaborative process for future BIM implementation.published_or_final_versio

An inequality between the diameter and the inverse dual degree of a tree

Let T be a nontrivial tree with diameter D(T) and radius R(T). Let I(T) be the inverse dual degree of T which is defined to be , where for uV(T). For any longest path P of T, denote by a(P) the number of vertices outside P with degree at least 2, b(P) the number of vertices on P with degree at least 3 and distance at least 2 to each of the end-vertices of P, and c(P) the number of vertices adjacent to one of the end-vertices of P and with degree at least 3. In this note we prove that . As a corollary we then get with equality if and only if T is a path of at least four vertices. The latter inequality strengthens a conjecture made by the program Graffiti.postprin

Blended learning in dentistry: 3-D resources for inquiry-based learning

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A novel phase-aligned analysis on motion patterns of table tennis strokes

© 2016, Routledge. All rights reserved. A wide range of human motion represent repetitive patterns particularly in racket sports. Quantitative analysis of the continuous variables during the different phases of the motion cycle helps to investigate more deeply the specific movement of the racket or player. Table tennis biomechanics research to date lacks the necessary detail of phase decomposition and phase-based quantitative analysis. Therefore, this study proposes a novel velocity-based piecewise alignment method to identify the different phases of a table tennis forehand stroke. A controlled experiment was conducted on a number of players of two differing ability levels (experts vs. novices) to implement this novel methodology. Detailed results are shown for the quantitative analysis on multiple strokes of the two groups of participants. Significant differences were found in both the displacement and velocity of the racket movement in the backswing, forward swing and follow-through phases. For example, it is clear that experts’ strokes show higher racket resultant velocity than novices during both the forward swing and follow-through phases by up to a factor of two. Furthermore, the phase-based approach to analysing racket motions leads to interrogation over a greater duration than the traditional time-based method which is generally only concerned with impact ±0.25s

Applying a new interatomic potential for the modelling of hexagonal and orthorhombic YMnO3

We develop and apply an interatomic potential for YMnO3, based on the shell model together with the angular overlap model, which can model ligand field effects. The potential parameters accurately reproduce the complex structure of both hexagonal and orthorhombic phases of YMnO3. The rotation of the MnO6 octahedra in o-YMnO3 suggests the E-type AFM order. The potential is further employed to investigate the energies of intrinsic defects in the material. Lower defect energies were found in o-YMnO3. Oxygen Frenkel and Y2O3 partial Schottky are the most favourable defects in h-YMnO3 and o-YMnO3, respectively. The defect models proposed have implications for the properties of the related non-stoichiometric phases