Towards a predictive multi-phase model for alpine mass movements and process cascades

Alpine mass movements can generate process cascades involving different materials including rock, ice, snow, and water. Numerical modelling is an essential tool for the quantification of natural hazards, but state-of-the-art operational models reach their limits when facing unprecedented or complex events. Here, we advance our predictive capabilities for process cascades on the basis of a three-dimensional numerical model, coupling fundamental conservation laws to finite strain elastoplasticity. Through its hybrid Eulerian-Lagrangian character, our approach naturally reproduces fractures and collisions, erosion/deposition phenomena, and multi-phase interactions, which finally grant very accurate simulations of complex dynamics. Four benchmark simulations demonstrate the physical detail of the model and its applicability to real-world full-scale events, including various materials and ranging through four orders of magnitude in volume. In the future, our model can support risk-management strategies through predictions of the impact of potentially catastrophic cascading mass movements at vulnerable sites.

Data Lives

How can we begin to grasp the scope and scale of our new data-rich world, and can we truly comprehend what is at stake? This book explores the intricacies of data creation and charts how data-driven technologies have become essential to how society, government and the economy work. Creatively blending scholarly analysis, biography and fiction, the book demonstrates how data are shaped by social and political forces, and the extent to which they influence our daily lives. The book begins with an overview of the sociality of data. Data-driven endeavours are as much a result of human values, desires, and social relations as they are scientific principles and technologies. The data revolution has been transforming work and the economy, the nature of consumption, the management and governance of society, how we communicate and interact with media and each other, and forms of play and leisure. Indeed, our lives are saturated with digital devices and services that generate, process, and share vast quantities of data. The book reveals the many, complex, contested ways in which data are produced and circulated, as well as the consequences of living in a data-driven world. The book concludes with an exploration as to what kind of data future we want to create and strategies for realizing our visions. It highlights the need to enact 'a digital ethics of care', and to claim and assert 'data sovereignty'. Ultimately, the book reveals our data world to be one of potential danger, but also of hope.

Data Stories

This chapter provides an overview of the sociality of data. Data-driven endeavours are not simply technical systems, but are socio-technical systems. That is, they are as much a result of human values, desires, and social relations as they are scientific principles and technologies. The sociality of data is also evident with respect to how we have come to live with data. The data revolution has been transforming work and the economy, the nature of consumption, the management and governance of society, how we communicate and interact with media and each other, and forms of play and leisure. Indeed, our lives are saturated with digital devices and services that generate, process, and share vast quantities of data. This book reveals the myriad, complex, contested ways in which data are produced and circulated, as well as the consequences of living in a data-driven world.

Quantitative and Algorithmic aspects of Barrier Synchronization in Concurrency

International audience In this paper we address the problem of understanding Concurrency Theory from a combinatorial point of view. We are interested in quantitative results and algorithmic tools to refine our understanding of the classical combinatorial explosion phenomenon arising in concurrency. This paper is essentially focusing on the the notion of synchronization from the point of view of combinatorics. As a first step, we address the quantitative problem of counting the number of executions of simple processes interacting with synchronization barriers. We elaborate a systematic decomposition of processes that produces a symbolic integral formula to solve the problem. Based on this procedure, we develop a generic algorithm to generate process executions uniformly at random. For some interesting sub-classes of processes we propose very efficient counting and random sampling algorithms. All these algorithms have one important characteristic in common: they work on the control graph of processes and thus do not require the explicit construction of the state-space.

Autopoietic Knowledge Management Systems

Knowledge management in an organisation is a key activity that aims to improve the organisation's competitiveness through gathering, processing, storing, and sharing of organisational knowledge. Socio-technical solutions designed to support knowledge management are systems for managing knowledge in an organisation. IT systems can support employees in their knowledge processes as well as independently generate, process, and codify knowledge, thus supporting the processes of organisational learning and development of knowledge bases. The cyclical and recurrent character of activities, both in terms of the interactions between process participants in organisations and actions of IT systems themselves, can be perceived in terms of autopoiesis, which explains the significance of knowledge management systems in organisational knowledge processing. The aim of this chapter is to analyse a knowledge management system through the lens of autopoietic perception of the activities taking place in an organisation, which are performed in poietic space.

Process Models to Understand Resident-to-Resident Aggression Among Residents With Dementia in Long-Term Care

Background/Objectives: Resident-to-resident aggression (RRA) is a prevalent form of interpersonal violence in long-term care (LTC) settings. Research to guide preventive interventions is limited. Using social-ecological and need-driven dementia-compromised behavior perspectives, we sought to generate process models representing common RRA pathways in dementia-specific LTC units. Research Methods: We used qualitative focus group methodology involving staff ( n = 36) exposed to everyday resident interactions at two urban LTC facilities in Toronto, Canada. Semistructured interviews were audio-recorded and transcribed. Two independent raters coded the transcripts using iterative, constant comparison analytic processes. Results: Two distinct RRA process models in dementia-specific LTC units were developed. Models reflect sequential pathways driven by residents’ benign or responsive behaviors and cognitive processing limitations, with escalation points within resident dyads or groups. Implications: This study furthers RRA conceptualization as a process rather than an aggressive event. Models capture unique RRA manifestations in dementia-specific LTC units and entrypoints for prevention or management.

Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics

Clinical genetics has an important role in the healthcare system to provide a definitive diagnosis for many rare syndromes. It also can have an influence over genetics prevention, disease prognosis and assisting the selection of the best options of care/treatment for patients. Next-generation sequencing (NGS) has transformed clinical genetics making possible to analyze hundreds of genes at an unprecedented speed and at a lower price when comparing to conventional Sanger sequencing. Despite the growing literature concerning NGS in a clinical setting, this review aims to fill the gap that exists among (bio)informaticians, molecular geneticists and clinicians, by presenting a general overview of the NGS technology and workflow. First, we will review the current NGS platforms, focusing on the two main platforms Illumina and Ion Torrent, and discussing the major strong points and weaknesses intrinsic to each platform. Next, the NGS analytical bioinformatic pipelines are dissected, giving some emphasis to the algorithms commonly used to generate process data and to analyze sequence variants. Finally, the main challenges around NGS bioinformatics are placed in perspective for future developments. Even with the huge achievements made in NGS technology and bioinformatics, further improvements in bioinformatic algorithms are still required to deal with complex and genetically heterogeneous disorders.

Gossip, Internet-Based Reputation Systems, and Governance

Internet-based reputation systems allow to generate, process, and publish reputationally relevant information. They sustain practices that at first sight might appear to be an incarnation of traditional gossip, where a subject, “ego,” transmits evaluative information to others, “alter,” about an absent “tertius.” This chapter argues that such identification is inappropriate, and it proposes a characterization of gossip that is suited for the Internet Age. While being different in several ways, gossip and Internet-based reputation systems display a functional similarity: they both generate reputationally relevant information, which reverberates on the distribution of resources, hence of power. In generating such information, Internet-based reputation systems level the playing field and, in a sense, “democratize” gossip. Deliberate engineering could enhance this interesting characteristic of Internet-based reputation systems, particularly so in applications to public governance, which is an explicit focus of this chapter.

Public Personnel Management Process Capability Assessment

Personnel management plays a critical role in the success of public organizations. Our literature review shows that there is a lack of systematic guidance on how to improve Public Personnel Management Process (PPMP) quality. Software Process Improvement and Capability Determination (SPICE) is a process assessment framework that is successfully used by software organizations during the past two decades. The framework can also be used as a baseline to generate process capability models for different specific domains/sectors. We have utilized this approach for the government domain and we developed the process definition of PPMP. To observe the benefits and usability of the model, we have performed a multiple case study, including the assessments of three organizations’ PPMP capability levels and the development of action plans for PPMP improvement. The findings show that the proposed approach is applicable for identifying the PPMP capability levels and is capable of providing a roadmap for moving to the next level.

Recent Progress in Laboratory Astrophysics Achieved with NASA Ames’ COSmIC Facility

We describe the characteristics and the capabilities of the laboratory facility, COSmIC, that was developed at NASA Ames to generate, process and analyze interstellar, circumstellar and planetary analogs in the laboratory. COSmIC stands for ’Cosmic Simulation Chamber’ and is dedicated to the study of neutral and ionized molecules and nanoparticles under the low temperature and high vacuum conditions that are required to simulate various space environments such as diffuse interstellar clouds, circumstellar outflows and planetary atmospheres. Recent results obtained using COSmIC will be highlighted. In particular, the progress that has been achieved in the domain of the diffuse interstellar bands (DIBs) and in monitoring, in the laboratory, the formation of circumstellar dust grains and planetary atmosphere aerosols from their gas-phase molecular precursors. Plans for future laboratory experiments on interstellar and planetary molecules and grains will also be addressed, as well as the implications of the studies underway for astronomical observations and past and future space mission data analysis.