Exact Hybrid Covariance Thresholding for Joint Graphical Lasso

This paper considers the problem of estimating multiple related Gaussian graphical models from a $p$-dimensional dataset consisting of different classes. Our work is based upon the formulation of this problem as group graphical lasso. This paper proposes a novel hybrid covariance thresholding algorithm that can effectively identify zero entries in the precision matrices and split a large joint graphical lasso problem into small subproblems. Our hybrid covariance thresholding method is superior to existing uniform thresholding methods in that our method can split the precision matrix of each individual class using different partition schemes and thus split group graphical lasso into much smaller subproblems, each of which can be solved very fast. In addition, this paper establishes necessary and sufficient conditions for our hybrid covariance thresholding algorithm. The superior performance of our thresholding method is thoroughly analyzed and illustrated by a few experiments on simulated data and real gene expression data

Sex doll ownership: an agenda for research

Purpose of review: The topic of sex doll ownership is becoming an increasingly discussed issue from both a social and legal perspective. This review aims to examine the veracity of the existing psychological, sexological, and legal literature in relation to doll ownership. Recent findings: Strong views exist across the spectrum of potential socio-legal positions on sex doll ownership. However, there is an almost total lack of empirical analyses of the psychological characteristics or behavioral implications of doll ownership. As such, existing arguments appear to represent the philosophical positions of those scholars expressing them, rather than being rooted in any objective evidence base. Summary: Despite an absence of empirical data on the characteristics and subsequent effects of doll ownership, discussions about the ethical and legal status of doll ownership continue. This highlights a real and urgent need for a coherent research agenda to be advanced in this area of work

Temporary migration programmes: the cause or antidote for migrant worker exploitation in UK agriculture

The referendum result in Britain in 2016 and the potential loss of EU labour in the advent of a “hard Brexit” has raised pressing questions for sectors that rely on EU labour, such as agriculture. Coupled with the closure of the long-standing Seasonal Agricultural Scheme in 2013, policymakers are grappling with how to satisfy one the one hand employer demands for mobility schemes, and on the other public demands for restrictive immigration policies. Labour shortages in agriculture transcend the immigration debate, raising questions for food security, the future of automation and ultimately what labour market the UK hopes to build. Temporary Migration programmes have been heralded as achieving a triple win, yet they are rightly criticized for breeding bonded labour and exploitation. In lieu of a dedicated EU labour force agricultural employers are calling for the establishment of a new seasonal scheme. In this paper we explore whether the absence of a temporary migration programme resolves the potential exploitation of migrant workers. We argue that the absence of a TMP is not an antidote to migrant exploitation, and that a socially just TMP which is built around migrant agency may be the most palpable solution

The computational therapeutic: exploring Weizenbaum's ELIZA as a history of the present

This paper explores the history of ELIZA, a computer programme approximating a Rogerian therapist, developed by Jospeh Weizenbaum at MIT in the 1970s, as an early AI experiment. ELIZA’s reception provoked Weizenbaum to re-appraise the relationship between ‘computer power and human reason’ and to attack the ‘powerful delusional thinking’ about computers and their intelligence that he understood to be widespread in the general public and also amongst experts. The root issue for Weizenbaum was whether human thought could be ‘entirely computable’ (reducible to logical formalism). This also provoked him to re-consider the nature of machine intelligence and to question the instantiation of its logics in the social world, which would come to operate, he said, as a ‘slow acting poison’. Exploring Weizenbaum’s 20th Century apostasy, in the light of ELIZA, illustrates ways in which contemporary anxieties and debates over machine smartness connect to earlier formations. In particular, this article argues that it is in its designation as a computational therapist that ELIZA is most significant today. ELIZA points towards a form of human–machine relationship now pervasive, a precursor of the ‘machinic therapeutic’ condition we find ourselves in, and thus speaks very directly to questions concerning modulation, autonomy, and the new behaviorism that are currently arising

Marketing Actions and the Value of Customer Assets: A Framework for Customer Asset Management

This article develops a framework for assessing how marketing actions affect customers’lifetime value to the firm. The framework is organized around four critical actions that firms must take to effectively manage the asset value of the customer base: database creation, market segmentation, forecasting customer purchase behavior, and resource allocation. In this framework, customer lifetime value is treated as a dynamic construct, that is, it influences the eventual allocation of marketing resources but is also influenced by that allocation. By viewing customers as assets and systematically managing these assets, a firm can identify the most appropriate marketing actions to acquire, maintain, and enhance customer assets and thereby maximize financial returns. The article discusses in detail how to assess customer lifetime value and manage customers as assets. Then, it identifies key research challenges in studying customer asset management and the managerial challenges associated with implementing effective customer asset management practices.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

The effect of timing and frequency of push notifications on usage of a smartphone-based stress management intervention: An exploratory trial

Push notifications offer a promising strategy for enhancing engagement with smartphone-based health interventions. Intelligent sensor-driven machine learning models may improve the timeliness of notifications by adapting delivery to a user's current context (e.g. location). This exploratory mixed-methods study examined the potential impact of timing and frequency on notification response and usage of Healthy Mind, a smartphone-based stress management intervention. 77 participants were randomised to use one of three versions of Healthy Mind that provided: intelligent notifications; daily notifications within pre-defined time frames; or occasional notifications within pre-defined time frames. Notification response and Healthy Mind usage were automatically recorded. Telephone interviews explored participants' experiences of using Healthy Mind. Participants in the intelligent and daily conditions viewed (d = .47, .44 respectively) and actioned (d = .50, .43 respectively) more notifications compared to the occasional group. Notification group had no meaningful effects on percentage of notifications viewed or usage of Healthy Mind. No meaningful differences were indicated between the intelligent and non-intelligent groups. Our findings suggest that frequent notifications may encourage greater exposure to intervention content without deterring engagement, but adaptive tailoring of notification timing does not always enhance their use. Hypotheses generated from this study require testing in future work. Trial registration number: ISRCTN67177737 © 2017 Morrison et al

ELSA in industrial robotics

Purpose of ReviewIndustry is changing; converging technologies allow a fourth Industrial Revolution, where it is envisaged that robots will work alongside humans. We investigate how the research community is responding to the ethical, legal, and social aspects of industrial robots, with a primary focus on manufacturing industry.Recent FindingsThe literature shows considerable interest in the impact of robotics and automation on industry. This interest spans many disciplines, which is to be expected given that the ELS impacts of industrial robotics may be profound in their depth and far-reaching in their scope.SummaryWe suggest that the increasing importance of human-robot interaction (HRI) reduces the differentiation between industrial robotics and other robotic domains and that the main challenges to successful adoption for the benefit of human life are above all political and economic. Emerging standards and legal frameworks may scaffold this success, but it is apparent that getting it wrong might have repercussions that last for generations

A randomized controlled pilot study of a brief web-based mindfulness training

Background: Mindfulness has been shown to be effective in treating various medical and mental problems. Especially its incorporation in cognitive-behavioural interventions has improved long-term outcomes of those treatments. It has also been shown, that brief mindfulness-based trainings are effective in reducing distress. There have been few web-based interventions incorporating mindfulness techniques in their manual and it remains unclear whether a brief web-based mindfulness intervention is feasible. Methods: Out of 50 adults (different distress levels; exclusion criteria: < 18 years, indication of psychotic or suicidal ideation in screening) who were recruited via e-mail and screened online, 49 were randomized into an immediate 2-weeks-treatment group (N = 28) or a waitlist-control group (N = 21), starting with a 2-week delay. Distress (BSI), perceived stress (PSQ), mindfulness (FMI), as well as mood and emotion regulation (PANAS/SEK-27) were measured at pre-, post- and 3-month follow-up (3MFU). Intention-to-treat analyses using MI for missing data and per-protocol analyses (≥ 50% attendance) were performed. Results: 26 participants of the treatment group completed post-measures. Most measures under ITT-analysis revealed no significant improvement for the treatment group, but trends with medium effect sizes for PSQ (d = 0.46) and PANASneg (d = 0.50) and a small, non-significant effect for FMI (d = 0.29). Per-protocol analyses for persons who participated over 50% of the time revealed significant treatment effects for PSQ (d = 0.72) and PANASneg (d = 0.77). Comparing higher distressed participants with lower distressed participants, highly distressed participants seemed to profit more of the training in terms of distress reduction (GSI, d = 0.85). Real change (RCI) occurred for PSQ in the treatment condition (OR = 9). Results also suggest that participants continued to benefit from the training at 3MFU. Conclusion: This study of a brief web-based mindfulness training indicates that mindfulness can be taught online and may improve distress, perceived stress and negative affect for regular users. Although there were no significant improvements, but trends, for most measures under ITT, feasibility of such a program was demonstrated and also that persons continued to use techniques of the training in daily life