Orbital photogalvanic effects in quantum-confined structures

We report on the circular and linear photogalvanic effects caused by free-carrier absorption of terahertz radiation in electron channels on (001)-oriented and miscut silicon surfaces. The photocurrent behavior upon variation of the radiation polarization state, wavelength, gate voltage and temperature is studied. We present the microscopical and phenomenological theory of the photogalvanic effects, which describes well the experimental results. In particular, it is demonstrated that the circular (photon-helicity sensitive) photocurrent in silicon-based structures is of pure orbital nature originating from the quantum interference of different pathways contributing to the absorption of monochromatic radiation.Comment: 8 pages, 5 figures, two culumne

Photo editing: Enhancing social media images to reflect appearance ideals

Many of the images used in traditional forms of mass media have been modified to portray unrealistic and idealised beauty characteristics. Further to this, members of the general public have now begun to digitally enhance their own pictures for social media posts, in order to fulfil these often unattainable standards. Ella Guest explores the impact exposure to idealised images of peers may have on health and wellbein

Forecasting in the light of Big Data

Predicting the future state of a system has always been a natural motivation for science and practical applications. Such a topic, beyond its obvious technical and societal relevance, is also interesting from a conceptual point of view. This owes to the fact that forecasting lends itself to two equally radical, yet opposite methodologies. A reductionist one, based on the first principles, and the naive inductivist one, based only on data. This latter view has recently gained some attention in response to the availability of unprecedented amounts of data and increasingly sophisticated algorithmic analytic techniques. The purpose of this note is to assess critically the role of big data in reshaping the key aspects of forecasting and in particular the claim that bigger data leads to better predictions. Drawing on the representative example of weather forecasts we argue that this is not generally the case. We conclude by suggesting that a clever and context-dependent compromise between modelling and quantitative analysis stands out as the best forecasting strategy, as anticipated nearly a century ago by Richardson and von Neumann

Gab2 deficiency prevents Flt3-ITD driven acute myeloid leukemia in vivo

Internal tandem duplications (ITD) of the FMS-like tyrosine kinase 3 (FLT3) predict poor prognosis in acute myeloid leukemia (AML) and often co-exist with inactivating DNMT3A mutations. In vitro studies implicated Grb2-associated binder 2 (GAB2) as FLT3-ITD effector. Utilizing a Flt3-ITD knock-in, Dnmt3a haploinsufficient mouse model, we demonstrate that Gab2 is essential for the development of Flt3-ITD driven AML in vivo, as Gab2 deficient mice displayed prolonged survival, presented with attenuated liver and spleen pathology and reduced blast counts. Furthermore, leukemic bone marrow from Gab2 deficient mice exhibited reduced colony-forming unit capacity and increased FLT3 inhibitor sensitivity. Using transcriptomics, we identify the genes encoding for Axl and the Ret co-receptor Gfra2 as targets of the Flt3-ITD/Gab2/Stat5 axis. We propose a pathomechanism in which Gab2 increases signaling of these receptors by inducing their expression and by serving as downstream effector. Thereby, Gab2 promotes AML aggressiveness and drug resistance as it incorporates these receptor tyrosine kinases into the Flt3-ITD signaling network. Consequently, our data identify GAB2 as a promising biomarker and therapeutic target in human AML

Direct Image to Point Cloud Descriptors Matching for 6-DOF Camera Localization in Dense 3D Point Cloud

We propose a novel concept to directly match feature descriptors extracted from RGB images, with feature descriptors extracted from 3D point clouds. We use this concept to localize the position and orientation (pose) of the camera of a query image in dense point clouds. We generate a dataset of matching 2D and 3D descriptors, and use it to train a proposed Descriptor-Matcher algorithm. To localize a query image in a point cloud, we extract 2D keypoints and descriptors from the query image. Then the Descriptor-Matcher is used to find the corresponding pairs 2D and 3D keypoints by matching the 2D descriptors with the pre-extracted 3D descriptors of the point cloud. This information is used in a robust pose estimation algorithm to localize the query image in the 3D point cloud. Experiments demonstrate that directly matching 2D and 3D descriptors is not only a viable idea but also achieves competitive accuracy compared to other state-of-the-art approaches for camera pose localization

Learning and Matching Multi-View Descriptors for Registration of Point Clouds

Critical to the registration of point clouds is the establishment of a set of accurate correspondences between points in 3D space. The correspondence problem is generally addressed by the design of discriminative 3D local descriptors on the one hand, and the development of robust matching strategies on the other hand. In this work, we first propose a multi-view local descriptor, which is learned from the images of multiple views, for the description of 3D keypoints. Then, we develop a robust matching approach, aiming at rejecting outlier matches based on the efficient inference via belief propagation on the defined graphical model. We have demonstrated the boost of our approaches to registration on the public scanning and multi-view stereo datasets. The superior performance has been verified by the intensive comparisons against a variety of descriptors and matching methods

Are the dead taking over Facebook? A Big Data approach to the future of death online

We project the future accumulation of profiles belonging to deceased Facebook users. Our analysis suggests that a minimum of 1.4 billion users will pass away before 2100 if Facebook ceases to attract new users as of 2018. If the network continues expanding at current rates, however, this number will exceed 4.9 billion. In both cases, a majority of the profiles will belong to non-Western users. In discussing our findings, we draw on the emerging scholarship on digital preservation and stress the challenges arising from curating the profiles of the deceased. We argue that an exclusively commercial approach to data preservation poses important ethical and political risks that demand urgent consideration. We call for a scalable, sustainable, and dignified curation model that incorporates the interests of multiple stakeholders

Data, ideology, and the developing critical program of social informatics

The rapidly shifting ideological terrain of computing has a profound impact on Social Informatics's critical and empirical analysis of computerization movements. As these movements incorporate many of the past critiques concerning social fit and situational context leveled against them by Social Informatics research, more subtle and more deeply ingrained modes of ideological practice have risen to support movements of computerization. Among these, the current emphasis on the promises of data and data analytics presents the most obvious ideological challenge. In order to reorient Social Informatics in relation to these new ideological challenges, Louis Althusser's theory of ideology is discussed, with its implications for Social Informatics considered. Among these implications, a changed relationship between Social Informatics's critical stance and its reliance on empirical methods is advanced. Addressed at a fundamental level, the practice of Social Informatics comes to be reoriented in a more distinctly reflective and ethical direction

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

Modeling the impact of amino acid substitution in a monoclonal antibody on cation exchange chromatography

A vital part of biopharmaceutical research is decision making around which lead candidate should be progressed in early-phase development. When multiple antibody candidates show similar biological activity, developability aspects are taken into account to ease the challenges of manufacturing the potential drug candidate. While current strategies for developability assessment mainly focus on drug product stability, only limited information is available on how antibody candidates with minimal differences in their primary structure behave during downstream processing. With increasing time-to-market pressure and an abundance of monoclonal antibodies (mAbs) in development pipelines, developability assessments should also consider the ability of mAbs to integrate into the downstream platform. This study investigates the influence of amino acid substitutions in the complementarity-determining region (CDR) of a full-length IgG1 mAb on the elution behavior in preparative cation exchange chromatography. Single amino acid substitutions within the investigated mAb resulted in an additional positive charge in the light chain (L) and heavy chain (H) CDR, respectively. The mAb variants showed an increased retention volume in linear gradient elution compared with the wild-type antibody. Furthermore, the substitution of tryptophan with lysine in the H-CDR3 increased charge heterogeneity of the product. A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. The results reveal the potential effects of lead optimization during antibody drug discovery on downstream processing