Abstract-Objective methods for assessing perceptual image quality have traditionally attempted to quantify the visibility of errors between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a Structural Similarity Index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. 1

The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore a measure of structural similarity can provide a good approximation to perceived image quality. This paper proposes a multi-scale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions. We develop an image synthesis method to calibrate the parameters that define the relative importance of different scales. Experimental comparisons demonstrate the effectiveness of the proposed method.

In this study, the mechanical properties of epoxy nanocomposites with graphene platelets, single-walled carbon nanotubes, and multi-walled carbon nanotube additives were compared at a nanofiller weight fraction of 0.1 +/- 0.002%. The mechanical properties measured were the Young's modulus, ultimate tensile strength, fracture toughness, fracture energy, and the material's resistance to fatigue crack propagation. The results indicate that graphene platelets significantly out-perform carbon nanotube additives. The Young's modulus of the graphene nanocomposite was approximately 31% greater than the pristine epoxy as compared to approximately 3% increase for single-walled carbon nanotubes. The tensile strength of the baseline epoxy was enhanced by approximately 40% with graphene platelets compared to approximately 14% improvement for multi-walled carbon nanotubes. The mode I fracture toughness of the nanocomposite with graphene platelets showed approximately 53% increase over the epoxy compared to approximately 20% improvement for multi-walled carbon nanotubes. The fatigue resistance results also showed significantly different trends. While the fatigue suppression response of nanotube/epoxy composites degrades dramatically as the stress intensity factor amplitude is increased, the reverse effect is seen for graphene-based nanocomposites. The superiority of graphene platelets over carbon nanotubes in terms of mechanical properties enhancement may be related to their high specific surface area, enhanced nanofiller-matrix adhesion/interlocking arising from their wrinkled (rough) surface, as well as the two-dimensional (planar) geometry of graphene platelets.

We report the WIMP dark matter search results using the first physics-run data of the PandaX-II 500 kg liquid xenon dual-phase time-projection chamber, operating at the China JinPing underground Laboratory. No dark matter candidate is identified above background. In combination with the data set during the commissioning run, with a total exposure of 3.3×10 4 kg-day, the most stringent limit to the spin-independent interaction between the ordinary and WIMP dark matter is set for a range of dark matter mass between 5 and 1000 GeV/c 2 . The best upper limit on the scattering cross section is found 2.5 × 10 −46 cm 2 for the WIMP mass 40 GeV/c 2 at 90% confidence level.Weakly interacting massive particles, WIMPs in short, are a class of hypothetical particles that came into existence shortly after the Big Bang. The WIMPs could naturally explain the astronomical and cosmological evidences of dark matter in the Universe. The weak interactions between WIMPs and ordinary matter could lead to the recoils of atomic nuclei that produce detectable signals in deep-underground direct detection experiments. Over the past decade, the dual-phase xenon time-projection chambers (TPC) emerged as a powerful technology for WIMP searches both in scaling up the target mass, as well as in improving background rejection [1][2][3]. LUX, a dark matter search experiment with a 250 kg liquid xenon target, has recently reported the best limit of 6×10 −46 cm 2 on the WIMP-nucleon scattering cross section [4] The PandaX-II experiment, a half-ton scale dual-phase xenon experiment at the China JinPing underground Laboratory (CJPL), has recently reported the dark matter search results from its commissioning run (Run 8,19.1 live days) with a 5845 kg-day exposure [5]. The data were contaminated with significant 85 Kr background. After a krypton distillation campaign in early 2016, PandaX-II commenced physics data taking in March 2016. In this paper, we report the combined WIMP search results using the data from the first physics run from March 9 to June 30, 2016 (Run 9, 79.6 live days) and Run 8, with a total of 3.3×10 4 kg-day exposure, the largest reported WIMP data set among dual-phase xenon detectors in the world to date.The PandaX-II detector has been described in detail in Ref. [5]. The liquid xenon target consists of a cylindrical TPC with dodecagonal cross section (opposite-side distance 646 mm), confined by the polytetrafluoroethylene (PTFE) reflective wall, and a vertical drift distance of 600 mm defined by the cathode mesh and gate grid located at the bottom and top. For each physical event, the prompt scintillation photons (S1) and the delayed electroluminescence photons (S2) from the ionized electrons are collected by two arrays of 55 Hamamatsu R11410-arXiv:1607.07400v3 [hep-ex] Hamamatsu R8520-406 1-inch PMTs serving as an active veto. The γ background, which produces electron recoil (ER) events, can be distinguished from the dark matter nuclear recoil (NR) using the S2-to-S1 ratio. During the data taking period in Run 9, a few diffe...