The Ligo-Virgo-KAGRA Computing Infrastructure for Gravitational-wave Research

The LIGO, VIRGO and KAGRA Gravitational-wave (GW) observatories are getting ready for their fourth observational period, O4, scheduled to begin in March 2023, with improved sensitivities and thus higher event rates. GW-related computing has both large commonalities with HEP computing, particularly in the domain of offline data processing and analysis, and important differences, for example in the fact that the amount of raw data doesn’t grow much with the instrument sensitivity, or the need to timely generate and distribute “event candidate alerts” to EM and neutrino observatories, thus making gravitational multi-messenger astronomy possible. Data from the interferometers are exchanged between collaborations both for low-latency and offline processing; in recent years, the three collaborations designed and built a common distributed computing infrastructure to prepare for a growing computing demand, and to reduce the maintenance burden of legacy custom-made tools, by increasingly adopting tools and architectures originally developed in the context of HEP computing. So, for example, HTCondor is used for workflow management, Rucio for many data management needs, CVMFS for code and data distribution, and more. We will present GW computing use cases and report about the architecture of the computing infrastructure as will be used during O4, as well as some planned upgrades for the subsequent observing run O5

Réadaptation sociale des patients psychiatriques dans la province de Parme, en Italie

Dans cet article, les auteurs soulignent les importants changements qui ont affecté la prestation des soins psychiatriques dispensés dans la province de Parme et, par ricochet, dans l'ensemble de l'Italie. Avant 1960, on notait une tendance centralisatrice caractéristique visant à regrouper les interventions thérapeutiques au sein d'une grande institution psychiatrique, l'Hôpital psychiatrique de Colorno. Par la suite, avec l'entrée en vigueur de la Loi de la réforme des soins psychiatriques, en 1978, toutes les activités ont été relocalisées sur le territoire. Les problèmes de réadaptation rencontrés lors de la mise en place de cet ambitieux projet sont analysés ici, et en particulier, les modèles d'intervention qui furent privilégiés pour le remplacement définitif de l'Hôpital psychiatrique de Colorno.In this article, the authors shed light on important changes that have affected psychiatric caragiving in the province of Parma and, by ricochet, in the whole of Italy. Up to 1960, there was a marked centralizing trend toward concentrating therapeutic interventions within a large psychiatric institution, namely Colorno Psychiatric Hospital. When the psychiatric care reform bill took effect, in 1978, all activities were relocated throughout the territory. As this ambitious project was being implemented, a number of rehabilitation problems were encountered. In addition to analyzing these problems, the authors examine specific intervention models that were used to definitively replace Colorno Psychiatric Hospital

Improved Cloud resource allocation: how INDIGO-Datacloud is overcoming the current limitations in Cloud schedulers

Trabajo presentado a: 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP2016) 10–14 October 2016, San Francisco.Performing efficient resource provisioning is a fundamental aspect for any resource provider. Local Resource Management Systems (LRMS) have been used in data centers for decades in order to obtain the best usage of the resources, providing their fair usage and partitioning for the users. In contrast, current cloud schedulers are normally based on the immediate allocation of resources on a first-come, first-served basis, meaning that a request will fail if there are no resources (e.g. OpenStack) or it will be trivially queued ordered by entry time (e.g. OpenNebula). Moreover, these scheduling strategies are based on a static partitioning of the resources, meaning that existing quotas cannot be exceeded, even if there are idle resources allocated to other projects. This is a consequence of the fact that cloud instances are not associated with a maximum execution time and leads to a situation where the resources are under-utilized. These facts have been identified by the INDIGO-DataCloud project as being too simplistic for accommodating scientific workloads in an efficient way, leading to an underutilization of the resources, a non desirable situation in scientific data centers. In this work, we will present the work done in the scheduling area during the first year of the INDIGO project and the foreseen evolutions.The authors want to acknowledge the support of the INDIGO-DataCloud (grant number 653549) project, funded by the European Commission’s Horizon 2020 Framework Programme.Peer Reviewe

Role of Acute Graft-Versus-Host Disease in the Risk of Bacteremia and Invasive Fungal Disease after Allogeneic Hemopoietic Stem Cell Transplantation in Children. Results from a Single-Center Observational Study

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Integrating multiple scientific computing needs via a Private Cloud infrastructure

In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit

Managing a tier-2 computer centre with a private cloud infrastructure

In a typical scientific computing centre, several applications coexist and share a single physical infrastructure. An underlying Private Cloud infrastructure eases the management and maintenance of such heterogeneous applications (such as multipurpose or application-specific batch farms, Grid sites, interactive data analysis facilities and others), allowing dynamic allocation resources to any application. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques. Such infrastructures are being deployed in some large centres (see e.g. the CERN Agile Infrastructure project), but with several open-source tools reaching maturity this is becoming viable also for smaller sites. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 centre, an Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The private cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem and the OpenWRT Linux distribution (used for network virtualization); a future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and OCCI

Minimal clinically important difference for asthma endpoints: an expert consensus report

Minimal clinically important difference (MCID) can be defined as the smallest change or difference in an outcome measure that is perceived as beneficial and would lead to a change in the patient's medical management.The aim of the current expert consensus report is to provide a "state-of-the-art" review of the currently available literature evidence about MCID for end-points to monitor asthma control, in order to facilitate optimal disease management and identify unmet needs in the field to guide future research.A series of MCID cut-offs are currently available in literature and validated among populations of asthmatic patients, with most of the evidence focusing on outcomes as patient reported outcomes, lung function and exercise tolerance. On the contrary, only scant and partial data are available for inflammatory biomarkers. These clearly represent the most interesting target for future development in diagnosis and clinical management of asthma, particularly in view of the several biologic drugs in the pipeline, for which regulatory agencies will soon require personalised proof of efficacy and treatment response predictors

Providing a nurse-led complex nursing INtervention FOcused on quality of life assessment on advanced cancer patients: The INFO-QoL pilot trial.

PURPOSE Unmet needs for advanced-disease cancer patients are fatigue, pain, and emotional support. Little information is available about the feasibility of interventions focused on patient-reported outcome measurement developed according to the Medical Research Council (MRC) Framework in advanced-disease cancer patients. We aimed to pilot a nurse-led complex intervention focused on QoL assessment in advanced-disease cancer patients. METHODS The INFO-QoL study was based on an exploratory, nonequivalent comparison group, pre-test-post-test design. Study sites received either the INFO-QoL intervention or usual care. Adult advanced-disease cancer patients admitted to hospice inpatient units that gave their informed consent were included in the study. Subjects were 187 patients and their families and 19 healthcare professionals. We evaluated feasibility, acceptability, and patients' outcomes using the Integrated Palliative Care Outcome Scale. RESULTS Nineteen healthcare professionals were included. The mean competence score increased significantly over time (p < 0.001) and the mean usefulness score was high 8.63 (±1.36). In the post-test phase, 54 patients were allocated to the experimental unit and 36 in the comparison unit. Compared to the comparison unit, in the experimental unit anxiety (R2 = 0.07; 95% CI = -0.06; 0.19), family anxiety (R2 = 0.22; 95% CI = -0.03; 0.41), depression (R2 = 0.31; 95% CI = -0.05; 0.56) and sharing feelings (R2 = 0.09; 95% CI = -0.05; 0.23), were improved between pre-test and post-test phase. CONCLUSIONS The INFO-QoL was feasible and potentially improved psychological outcomes. Despite the high attrition rate, the INFO-QoL improved the quality and safety culture for patients in palliative care settings