Optimization of electron microscopy for human brains with long-term fixation and fixed-frozen sections.

BackgroundAbnormal connectivity across brain regions underlies many neurological disorders including multiple sclerosis, schizophrenia and autism, possibly due to atypical axonal organization within white matter. Attempts at investigating axonal organization on post-mortem human brains have been hindered by the availability of high-quality, morphologically preserved tissue, particularly for neurodevelopmental disorders such as autism. Brains are generally stored in a fixative for long periods of time (often greater than 10 years) and in many cases, already frozen and sectioned on a microtome for histology and immunohistochemistry. Here we present a method to assess the quality and quantity of axons from long-term fixed and frozen-sectioned human brain samples to demonstrate their use for electron microscopy (EM) measures of axonal ultrastructure.ResultsSix samples were collected from white matter below the superior temporal cortex of three typically developing human brains and prepared for EM analyses. Five samples were stored in fixative for over 10 years, two of which were also flash frozen and sectioned on a freezing microtome, and one additional case was fixed for 3 years and sectioned on a freezing microtome. In all six samples, ultrastructural qualitative and quantitative analyses demonstrate that myelinated axons can be identified and counted on the EM images. Although axon density differed between brains, axonal ultrastructure and density was well preserved and did not differ within cases for fixed and frozen tissue. There was no significant difference between cases in axon myelin sheath thickness (g-ratio) or axon diameter; approximately 70% of axons were in the small (0.25 μm) to medium (0.75 μm) range. Axon diameter and g-ratio were positively correlated, indicating that larger axons may have thinner myelin sheaths.ConclusionThe current study demonstrates that long term formalin fixed and frozen-sectioned human brain tissue can be used for ultrastructural analyses. Axon integrity is well preserved and can be quantified using the methods presented here. The ability to carry out EM on frozen sections allows for investigation of axonal organization in conjunction with other cellular and histological methods, such as immunohistochemistry and stereology, within the same brain and even within the same frozen cut section

Empirical extinction coefficients for the GALEX, SDSS, 2MASS and WISE passbands

Using the "standard pair" technique of paring stars of almost nil and high extinction but otherwise of almost identical stellar parameters from the SDSS, and combing the SDSS, GALEX, 2MASS and WISE photometry ranging from the far UV to the mid-IR, we have measured dust reddening in the FUV-NUV, NUV-u, u-g, g-r, r-i, i-z, z-J, J-H, H-Ks, Ks-W1 and W1-W2 colors for thousands of Galactic stars. The measurements, together with the E(B-V) values given by Schlegel et al. (1998), allow us to derive the observed, model-free reddening coefficients for those colors. The results are compared with previous measurements and the predictions of a variety of Galactic reddening laws. We find that 1) The dust reddening map of Schlegel et al. (1998) over-estimates E(B-V) by about 14 per cent, consistent with the recent work of Schlafly et al. (2010) and Schlafly & Finkbeiner (2011); 2) All the new reddening coefficients, except those for NUV-u and u-g, prefer the R(V) = 3.1 Fitzpatrick reddening law rather than the R(V) = 3.1 CCM and O'Donnell (O'Donnell 1994) reddening laws. Using the Ks-band extinction coefficient predicted by the R(V) = 3.1 Fitzpatrick law and the observed reddening coefficients, we have deduced new extinction coefficients for the FUV, NUV, u, g, r, i, z, J, H, W1 and W2 passbands. We recommend that the new reddening and extinction coefficients should be used in the future and an update of the Fitzpatrick reddening law in the UV is probably necessary. We stress however that the FUV- and NUV-band coefficients should be used with caution given their relatively large measurement uncertainties. Finally, potential applications of the "standard pair" technique with the LAMOST Galactic surveys are discussed.Comment: 13 pages, 9 figures, accepted to MNRA

Van der Waals-like phase transition from holographic entanglement entropy in Lorentz breaking massive gravity

In this paper, phase transition of AdS black holes in lorentz breaking massive gravity has been studied in the framework of holography. We find that there is a first order phase transition(FPT) and second order phase transition(SPT) both in Bekenstein-Hawking entropy(BHE)-temperature plane and holographic entanglement entropy(HEE)-temperature plane. Furthermore, for the FPT, the equal area law is checked and for the SPT, the critical exponent of the heat capacity is also computed. Our results confirm that the phase structure of HEE is similar to that of BHE in lorentz breaking massive gravity, which implies that HEE and BHE have some potential underlying relationship.Comment: 10 pages, 10 figure

A Theoretical Model and Empirical Investigation of Social Networking Site Users’ Switching Intention

Customers’ post-adoption switching behavior among competing service providers, particularly among different online Social Network Sites (SNSs), is gaining increasing attention from both information system researchers and practitioners, as the size of user base is both a selling point and a source of revenue of SNS service providers. In this study, we draw on the uses and gratification theory to identify factors motivating an individual to switch SNSs. In addition, informed by social identity theory, we explore how individuals’ social identities on their current SNSs moderate the effects of the motivating factors on their intention to switch to a more attractive SNS. The results of our survey study reveal that the perceived relative values of a competing SNS (when compared with the user’s current SNS) positively influence his/her intention to switch to the competing SNS. However, the positive impact of perceived relative values on switching intention is mitigated by the user’s perception of his/her salient social identity on his/her current SNS. This study has significant implications for both academics and practitioners

MeshAdv: Adversarial Meshes for Visual Recognition

Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial examples, which are carefully crafted inputs aiming to mislead the predictions. Currently, the majority of these studies have focused on perturbation added to image pixels, while such manipulation is not physically realistic. Some works have tried to overcome this limitation by attaching printable 2D patches or painting patterns onto surfaces, but can be potentially defended because 3D shape features are intact. In this paper, we propose meshAdv to generate "adversarial 3D meshes" from objects that have rich shape features but minimal textural variation. To manipulate the shape or texture of the objects, we make use of a differentiable renderer to compute accurate shading on the shape and propagate the gradient. Extensive experiments show that the generated 3D meshes are effective in attacking both classifiers and object detectors. We evaluate the attack under different viewpoints. In addition, we design a pipeline to perform black-box attack on a photorealistic renderer with unknown rendering parameters.Comment: Published in IEEE CVPR201