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

Calculations of Hubbard U from first-principles

The Hubbard \emph{U} of the \emph{3d} transition metal series as well as SrVO$_{3}$, YTiO$_{3}$, Ce and Gd has been estimated using a recently proposed scheme based on the random-phase approximation. The values obtained are generally in good accord with the values often used in model calculations but for some cases the estimated values are somewhat smaller than those used in the literature. We have also calculated the frequency-dependent \emph{U} for some of the materials. The strong frequency dependence of \emph{U} in some of the cases considered in this paper suggests that the static value of \emph{U} may not be the most appropriate one to use in model calculations. We have also made comparison with the constrained LDA method and found some discrepancies in a number of cases. We emphasize that our scheme and the constrained LDA method theoretically ought to give similar results and the discrepancies may be attributed to technical difficulties in performing calculations based on currently implemented constrained LDA schemes.Comment: 24 pages, 13 figures; Submitted to Phys. Rev.

Microstructure of porous SiO2-Ta2O5-rich glass

Glasses composed of 60 wt% sodium borate and 40 wt% (SiO2 + Ta2O5) were melted, phase-separated by heat treatment and leached. The ratio SiO2 : Ta2O5 was varied between 4 : 1 and 1 : 14.7 (by wt). The microstructure of the glasses in the various stages of development was characterized by means of x-ray diffractometry and analytical electron microscopy. Substitution of SiO2 by Ta2O5 up to a ratio SiO2 : Ta2O5 = 1 : 5 (by wt) produced clear glasses whereas higher fractions of Ta2O5 produced opaque glasses which include a crystal-like phase. The specific surface area of the porous skeleton showed a strong dependence on composition in the leached state; a maximum of 352m2g-1 was measured for a composition with the ratio SiO2: Ta2O5 = 1 : 1. Transmission electron micrographs at high resolution show phase contrasts, indicating partial structural ordering in tantalum-rich, heat-treated and leached glasses, resembling lattice fringe Images of a crystalline structure. However, electron diffraction patterns show only one single and remarkably sharp diffraction ring, indicating a one-dimensionally ordered paracrystalline state of aggregation for the insoluble phase. This observation is in contradiction with existing models of glass structures. The presence of sodium in the porous insoluble skeleton with approximate composition Na2Ta6O15Si2 is confirmed by combined EDS and EELS analyses. The development of a fully ordered crystalline phase was monitored by means of a high-temperature x-ray camera; tetragonal crystal symmetry is proposed for this phase

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

Small Big Data: Using multiple data-sets to explore unfolding social and economic change

Bold approaches to data collection and large-scale quantitative advances have long been a preoccupation for social science researchers. In this commentary we further debate over the use of large-scale survey data and official statistics with ‘Big Data’ methodologists, and emphasise the ability of these resources to incorporate the essential social and cultural heredity that is intrinsic to the human sciences. In doing so, we introduce a series of new data-sets that integrate approximately 30 years of survey data on victimisation, fear of crime and disorder and social attitudes with indicators of socio-economic conditions and policy outcomes in Britain. The data-sets that we outline below do not conform to typical conceptions of ‘Big Data’. But, we would contend, they are ‘big’ in terms of the volume, variety and complexity of data which has been collated (and to which additional data can be linked) and ‘big’ also in that they allow us to explore key questions pertaining to how social and economic policy change at the national level alters the attitudes and experiences of citizens. Importantly, they are also ‘small’ in the sense that the task of rendering the data usable, linking it and decoding it, required both manual processing and tacit knowledge of the context of the data and intentions of its creators

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

Five sepharose-bound ligands for the chromatographic purification of Clostridium collagenase and clostripain

Social media data have provoked a mixed response from researchers. While there is great enthusiasm for this new source of social data – Twitter data in particular – concerns are also expressed about their biases and unknown provenance and, consequently, their credibility for social research. This article seeks a middle path, arguing that we must develop better understanding of the construction and circulation of social media data to evaluate their appropriate uses and the claims that might be made from them. Building on sociotechnical approaches, we propose a high-level abstraction of the ‘pipeline’ through which social media data are constructed and circulated. In turn, we explore how this shapes the populations and samples that are present in social media data and the methods that generate data about them. We conclude with some broad principles for supporting methodologically informed social media research in the future

Socially sensitive lactation: Exploring the social context of breastfeeding

Many women report difficulties with breastfeeding and do not maintain the practice for as long as intended. Although psychologists and other researchers have explored some of the difficulties they experience, fuller exploration of the relational contexts in which breastfeeding takes place is warranted to enable more in-depth analysis of the challenges these pose for breastfeeding women. The present paper is based on qualitative data collected from 22 first-time breastfeeding mothers through two phases of interviews and audio-diaries which explored how the participants experienced their relationships with significant others and the wider social context of breastfeeding in the first five weeks postpartum. Using a thematic analysis informed by symbolic interactionism, we develop the overarching theme of ‘Practising socially sensitive lactation’ which captures how participants felt the need to manage tensions between breastfeeding and their perceptions of the needs, expectations and comfort of others. We argue that breastfeeding remains a problematic social act, despite its agreed importance for child health. Whilst acknowledging the limitations of our sample and analytic approach, we suggest ways in which perinatal and public health interventions can take more effective account of the social challenges of breastfeeding in order to facilitate the health and psychological well-being of mothers and their infants