Normal edge-colorings of cubic graphs

A normal $k$-edge-coloring of a cubic graph is an edge-coloring with $k$ colors having the additional property that when looking at the set of colors assigned to any edge $e$ and the four edges adjacent it, we have either exactly five distinct colors or exactly three distinct colors. We denote by $\chi'_{N}(G)$ the smallest $k$, for which $G$ admits a normal $k$-edge-coloring. Normal $k$-edge-colorings were introduced by Jaeger in order to study his well-known Petersen Coloring Conjecture. More precisely, it is known that proving $\chi'_{N}(G)\leq 5$ for every bridgeless cubic graph is equivalent to proving Petersen Coloring Conjecture and then, among others, Cycle Double Cover Conjecture and Berge-Fulkerson Conjecture. Considering the larger class of all simple cubic graphs (not necessarily bridgeless), some interesting questions naturally arise. For instance, there exist simple cubic graphs, not bridgeless, with $\chi'_{N}(G)=7$. On the other hand, the known best general upper bound for $\chi'_{N}(G)$ was $9$. Here, we improve it by proving that $\chi'_{N}(G)\leq7$ for any simple cubic graph $G$, which is best possible. We obtain this result by proving the existence of specific no-where zero $\mathbb{Z}_2^2$-flows in $4$-edge-connected graphs.Comment: 17 pages, 6 figure

Catching the flu: Syndromic surveillance, algorithmic governmentality and global health security

How do algorithms shape the imaginary and practice of security? Does their proliferation point to a shift in the political rationality of security? If so, what is the nature and extent of that shift? This article explores these questions in relation to global health security. Prompted by an epidemic of new infectious disease outbreaks – from HIV, SARS and pandemic flu, through to MERS and Ebola – many governments are making health security an integral part of their national security strategies. Algorithms are central to these developments because they underpin a number of nextgeneration syndromic surveillance systems now routinely used by governments and international organizations to rapidly detect new outbreaks globally. This article traces the origins, design and evolution of three such internet-based surveillance systems: 1) the Program for Monitoring Emerging Diseases, 2) the Global Public Health Intelligence Network, and 3) HealthMap. The article shows how the successive introduction of those three syndromic surveillance systems has propelled algorithmic technologies into the heart of global outbreak detection. This growing recourse to algorithms for the purposes of strengthening global health security, the article argues, signals a significant shift in the underlying problem, nature, and role of knowledge in contemporary security practices

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

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

Electronic Structure and Valence Band Spectra of Bi4Ti3O12

The x-ray photoelectron valence band spectrum and x-ray emission valence-band spectra (Ti K _beta_5, Ti L_alpha, O K_alpha) of Bi4Ti3O12 are presented (analyzed in the common energy scale) and interpreted on the basis of a band-structure calculation for an idealized I4/mmm structure of this material.Comment: 6 pages + 7 PostScript figures, RevTex3.0, to be published in Phys.Rev.B52 (Oct.95). Figures also available via anonymous ftp at ftp://ftp.physik.uni-osnabrueck.de/pub/apostnik/BiTiO

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

Problem-solving for problem-solving: Data analytics to identify families for service intervention

The article draws on Bacchi’s ideas about problematisation (2020) and links to technological solutionism as governing logics of our age, to explore the double-faceted problem-solving logic operating in the UK family policy and early intervention field. Families with certain characteristics are identified as problematic, and local authorities are tasked with intervening to fix that social problem. Local authorities thus need to identify these families for problem-solving intervention, and data analytics companies will solve that problem for them. In the article, we identify discourses of transmitted deprivation and anti-social behaviour in families and the accompanying costly public sector burden as characteristics that produce families as social problems, and discursive themes around delivering powerful knowledge, timeliness and economic efficiently in data analytic companies’ problem solving claims for their data linkage and predictive analytics systems. These discursive rationales undergird the double-faceted problem-solving for problem-solving logic that directs attention away from complex structural causes

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

Mobile, wearable and ingestible health technologies : towards a critical research agenda

In this article, we review critical research on mobile and wearable health technologies focused on the promotion of ‘healthy lifestyles’. We begin by discussing key governmental and policy interests which indicate a shift towards greater digital integration in health care. Subsequently, we review relevant research literature, which highlights concerns about inclusion, social justice, and ownership of mobile health data, which we argue, provoke a series of key sociological questions that are in need of additional investigation. We examine the expansion of what counts as health data, as a basis for advocating the need for greater research into this area. Finally, we consider how digital devices raise questions about the reconfiguration of relationships, behaviours, and concepts of individuality

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