Hewlett-Packard (Italy)

Analyzing cultural heritage (CH) materials, particularly organic substances, is challenging due to their complex chemical composition. A key requirement in such analyses is the use of analytical techniques that cause minimal damage to the artifact while providing the maximum amount of chemical information about the materials. Chromatographic and mass spectrometric (MS) techniques give valuable information about components of the organic materials, but these typically require a microsample from the object, along with specific preparation and instrumental conditions. For CH artifacts, techniques that work directly on the surface, thereby causing minimal damage, are far more desirable. We have developed a 355 nm optical fiber-coupled laser ablation (LA) atmospheric pressure chemical ionization (APCI)-MS system that enables the analysis of organic material directly from the solid surface of the artifact under ambient conditions with minimal surface damage. In this study, we coupled LA with APCI-Fourier transform ion cyclotron resonance (FT-ICR)-MS. The main aim was to evaluate the effectiveness of the developed LA-APCI high-resolution (HR)MS system for the analysis of five handmade mock-up materials of different paint and varnish layers and one real-life sample. The results demonstrate the analytical potential of the LA-APCI-HRMS technique, as high-quality and identifiable mass spectra were obtained for most of the analyzed materials. In the future, the developed LA-APCI-HRMS technique could be applied not only to cultural heritage but also to other fields (e.g., forensics, material science, etc.).

One of the main DevOps practices is the automation of resource provisioning and deployment of complex software. This automation is enabled by the explicit definition of Infrastructure-as-Code (IaC), i.e., a set of scripts, often written in different modeling languages, which defines the infrastructure to be provisioned and applications to be deployed.We introduce the DevOps Modeling Language (DOML), a new Cloud modeling language for infrastructure deployments. DOML is a modeling approach that can be mapped into multiple IaC languages, addressing infrastructure provisioning, application deployment and configuration.The idea behind DOML is to use a single modeling paradigm which can help to reduce the need of deep technical expertise in using different specialized IaC languages.We present the DOML’s principles and discuss the related work on IaC languages. Furthermore, the advantages of the DOML for the end-user are demonstrated in comparison with some state-of-the-art IaC languages such as Ansible, Terraform, and Cloudify, and an evaluation of its effectiveness through several examples and a case study is provided.

Abstract PurposeThere have been large geographical differences in the infection and death rates of COVID-19. Foods and beverages containing high amounts of phytochemicals with bioactive properties were suggested to prevent contracting, to limit the severity of, and to facilitate recovery from COVID-19. The goal of our study was to determine the correlation of the type of foods/beverages people consumed and the risk reduction of contracting COVID-19 and the recovery from COVID-19.MethodsWe developed an online survey that asked the participants whether they contracted COVID-19, their symptoms, time to recover, and their frequency of eating various types of foods/beverages. The survey was first developed in English and then translated into 10 different languages.ResultsThe participants who did not contract COVID-19 consumed vegetables, herbs/spices, and fermented foods/beverages significantly more than the participants who contracted COVID-19 and those who were not tested but became sick most likely from COVID-19. The geographic location of participants corresponded with the language of the survey, except for the English version, thus, nine out of the 10 language versions represented a country. Among the six countries (India, Iran, Italy, Japan, Russia, Spain) with over one hundred participants, we found that in India and Japan the people who contracted COVID-19 showed significantly shorter recovery time, and greater daily intake of vegetables, herbs/spices, and fermented foods/beverages was associated with faster recovery.ConclusionOur results suggest that phytochemical compounds included in the vegetables may have contributed in not only preventing contraction of COVID-19, but also accelerating their recovery. (249 words; EJN limit is 250 words)

Abstract One of the main DevOps practices is the automation of resource provisioning and deployment of complex software. This automation is enabled by the explicit definition of Infrastructure-as-Code (IaC), i.e., a set of scripts, often written in different modelling languages, which defines the infrastructure and applications to be deployed. We introduce the DevOps Modelling Language (DOML), a new Cloud modelling language for infrastructure deployments. DOML is a modelling approach that can be mapped into multiple IaC languages, addressing infrastructure provisioning, application deployment and configuration at once. The idea behind DOML is to use a single modelling paradigm which can help to reduce the need of deep technical expertise in using different specialised IaC languages. We present the DOML’s principles and discuss the related work on IaC languages. We demonstrate the DOML advantages for the end-user in comparison with state-of-the-art IaC languages such as Ansible, Terraform, and Cloudify, and show its effectiveness through an example.

The aim of this registry study in patients with Parkinson's Disease (PD) in treatment, was to evaluate the effects of Pycnogenol® supplementation on some accessory symptoms and cognitive functions (COFU). The registry included 43 PD patients who had been diagnosed at least one year before the start of the study. The PD condition was considered mild, with minimal progression. The management for these patients was a monotherapy using carbidopa/levodopa (standard management; SM). Supplementary Pycnogenol® was used at 150 mg/day for 4 weeks. The neurological management was not affected. Tolerability and safety were very good; the two registry groups were comparable with comparable symptoms at baseline. The most disabling symptoms were considered tremor, bradychinesia, alterations in COFU, rigidity and speech changes. All symptoms were rated as mild-to-moderate. After 4 weeks, these target symptoms were significantly attenuated with the supplement in comparison with the SM only (P<0.05). Particularly the COFU score was significantly higher (P<0.05) with the supplement. No interference between the main neurological management and the supplement was observed. Oxidative stress (plasma free radicals), high in both registry groups at inclusion, was significantly lower in the supplement group at 4 weeks (P<0.05). The main PD-associated items (cognitive aspects, motory and postural aspects) considered the most common and disturbing problems were evaluated and scored (0 to 4) with a visual scale line. At 4 weeks, the scores for all items were lower in the supplement group in comparison with the control, SM group. Peripheral edema was present in all patients at inclusion. The edema was minimal at inclusion (at the ankle-foot level with pretibial extension) and present in all subjects. It changed in two SM subjects and was still present at 4 weeks in 19 out 22 of the SM patients. In the supplemented patients, edema (present at inclusion in all subjects), was visible in 4 subjects out of 21 (19%) at 4 weeks. Pycnogenol® supplementation may help in selected patients with PD - under stable neurological treatment - to improve some signs and symptoms and some aspects associated with COFU. Studies are in progress on a larger population sample and with new evaluation methods.

As critical infrastructures become more complex, sophisticated and digitally interconnected they are also more susceptible to cyber and physical security attacks. In order to mitigate the risks of such attacks, there is a need for securing them in an integrated way, which considers the simultaneous protection of their cyber and physical assets. In this paper we introduce a BigData platform that implements an integrated approach to securing and protecting critical infrastructures for the financial sector, by treating them as large scale cyber-physical systems. The main building blocks of the platform include an integrated security model that covers cyber and physical assets, an architecture for security monitoring and control based on appropriate probes, as well as a range of data analytics algorithms for detecting risks, vulnerabilities and threats. These building blocks are outlined in the paper, along with their deployment and use in a number of representative critical infrastructure protection use cases for the financial sector. One of the merits of our work is its reference character i.e. it can serve as a blueprint for developing and deploying systems for integrated cyber/physical security in various application areas.

Building the Environment for Things as a Service (BETaaS) is a novel platform for the deployment and execution of contentcentric Machine-to-Machine (M2M) applications, which relies on a local cloud of gateways. BETaaS platform provides a uniform interface and services to map content with things in a