A Linear Network Code Construction for General Integer Connections Based on the Constraint Satisfaction Problem

The problem of finding network codes for general connections is inherently difficult in capacity constrained networks. Resource minimization for general connections with network coding is further complicated. Existing methods for identifying solutions mainly rely on highly restricted classes of network codes, and are almost all centralized. In this paper, we introduce linear network mixing coefficients for code constructions of general connections that generalize random linear network coding (RLNC) for multicast connections. For such code constructions, we pose the problem of cost minimization for the subgraph involved in the coding solution and relate this minimization to a path-based Constraint Satisfaction Problem (CSP) and an edge-based CSP. While CSPs are NP-complete in general, we present a path-based probabilistic distributed algorithm and an edge-based probabilistic distributed algorithm with almost sure convergence in finite time by applying Communication Free Learning (CFL). Our approach allows fairly general coding across flows, guarantees no greater cost than routing, and shows a possible distributed implementation. Numerical results illustrate the performance improvement of our approach over existing methods.Comment: submitted to TON (conference version published at IEEE GLOBECOM 2015

Information and Design: Book Symposium on Luciano Floridi’s The Logic of Information

Purpose – To review and discuss Luciano Floridi’s 2019 book The Logic of Information: A Theory of Philosophy as Conceptual Design, the latest instalment in his philosophy of information (PI) tetralogy, particularly with respect to its implications for library and information studies (LIS). Design/methodology/approach – Nine scholars with research interests in philosophy and LIS read and responded to the book, raising critical and heuristic questions in the spirit of scholarly dialogue. Floridi responded to these questions. Findings – Floridi’s PI, including this latest publication, is of interest to LIS scholars, and much insight can be gained by exploring this connection. It seems also that LIS has the potential to contribute to PI’s further development in some respects. Research implications – Floridi’s PI work is technical philosophy for which many LIS scholars do not have the training or patience to engage with, yet doing so is rewarding. This suggests a role for translational work between philosophy and LIS. Originality/value – The book symposium format, not yet seen in LIS, provides forum for sustained, multifaceted and generative dialogue around ideas

Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models

The demand for psychological counseling has grown significantly in recent years, particularly with the global outbreak of COVID-19, which has heightened the need for timely and professional mental health support. Online psychological counseling has emerged as the predominant mode of providing services in response to this demand. In this study, we propose the Psy-LLM framework, an AI-based system leveraging Large Language Models (LLMs) for question-answering in online psychological consultation. Our framework combines pre-trained LLMs with real-world professional Q&A from psychologists and extensively crawled psychological articles. The Psy-LLM framework serves as a front-end tool for healthcare professionals, allowing them to provide immediate responses and mindfulness activities to alleviate patient stress. Additionally, it functions as a screening tool to identify urgent cases requiring further assistance. We evaluated the framework using intrinsic metrics, such as perplexity, and extrinsic evaluation metrics, with human participant assessments of response helpfulness, fluency, relevance, and logic. The results demonstrate the effectiveness of the Psy-LLM framework in generating coherent and relevant answers to psychological questions. This article concludes by discussing the potential of large language models to enhance mental health support through AI technologies in online psychological consultation

Effective fertility counselling for transgender adolescents : a qualitative study of clinician attitudes and practices

OBJECTIVE: Fertility counselling for trans and gender diverse (TGD) adolescents has many complexities, but there is currently little guidance for clinicians working in this area. This study aimed to identify effective strategies for-and qualities of-fertility counselling for TGD adolescents based on clinicians' experiences. DESIGN: We conducted qualitative semi-structured individual interviews in 2019 which explored clinician experiences and fertility counselling practices, perspectives of the young person's experience and barriers and facilitators to fertility preservation access. Data were analysed using thematic analysis. SETTING: This qualitative study examined experiences of clinicians at the Royal Children's Hospital-a tertiary, hospital-based, referral centre and the main provider of paediatric TGD healthcare in Victoria, Australia. PARTICIPANTS: We interviewed 12 clinicians from a range of disciplines (paediatrics, psychology, psychiatry and gynaecology), all of whom were involved with fertility counselling for TGD adolescents. RESULTS: Based on clinician experiences, we identified five elements that can contribute to an effective approach for fertility counselling for TGD adolescents: a multidisciplinary team approach; shared decision-making between adolescents, their parents and clinicians; specific efforts to facilitate patient engagement; flexible personalised care; and reflective practice. CONCLUSIONS: Identification of these different elements can inform and hopefully improve future fertility counselling practices for TGD adolescents, but further studies examining TGD adolescents' experiences of fertility counselling are also required

Technology Gap Navigator: Emerging Design of Biometric-Enabled Risk Assessment Machines

This paper reports the Technology Gap (TG) navigator, a novel tool for individual risk assessment in the layered security infrastructure. It is motivated by the practical need of the biometricenabled security systems design. The tool helps specify the conditions for bridging the identified TGs. The input data for the TG navigator includes 1) a causal description of the TG, 2) statistics regarding the available resources and performances, and 3) the required performance. The output includes generated probabilistic conditions, and the corresponding technology requirements for bridging the targeted TG

Selective Loss of Wild-Type p16INK4a Expression in Human Nevi

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