IoT-Aware Architecture to Guarantee Safety of Maintenance Operators in Industrial Plants

One of the most important factors that influence people’s daily lives and their well-being at work is the so-called “worker safety”. Different literature works demonstrated the positive effects on worker mood and well-being brought by the awareness of being in a safe environment and, consequently, less prone to accidents. Every working environment should guarantee safety protection to employees and operators both in normal operations and extraordinary duties (e.g., maintenance operations), however, the industrial domain is the one that is more exposed to risks for workers. Different technologies already accomplished such requirements in “normal” operations, nonetheless, the literature still lacks solutions to also monitor and guide operators during exceptional and dangerous operations (e.g., maintenance). The combination of IoT and Industry 4.0 can guide the research toward the resolution of the maintenance-related exposed problems. This paper proposes an IoT-aware architecture for the industrial domain to support maintenance operators. It was designed to guide them step by step while real-time monitoring plant, machinery, and other employees working in the same area. During the maintenance procedure, the operator is guided in the proper execution of every single step required by maintenance and an autonomous IoT system monitors the status of the different parts of the plants and machinery to, then, authorize and show, the next steps foreseen in the maintenance process. To test the feasibility and usefulness of the proposed system, a prototype was developed and functionally tested through the exploitation of a machinery simulator and a real lathe machine

WEARABLE MIXED REALITY SOLUTIONS FOR INDUSTRIAL PLANTS AND PRODUCTION LINES

In the present research project, the authors developed wearable and portable solutions capable to improve safety in production lines by taking advantages of availability of exhaustive and reliable data in modern industrial plants. Indeed, the synergy between Industry 4.0 and cutting edge devices, such as smartphones and headsets for Mixed Reality demonstrated to be potentially used to assist personnel on the shop floor, especially during critical and most dangerous operations. In this paper it is presented an ongoing project devoted to develop such support systems and to evaluate their efficiency in multiple industrial environments

AUTONOMOUS SYSTEMS & SAFETY ISSUES: THE ROADMAP TO ENABLE NEW ADVANCES IN INDUSTRIAL APPLICATIONS

The paper addresses the safety issues related to the development of new solutions based on autonomous systems for industrial applications and the necessity to develop experimental environments for investigating these cases; a set of examples is proposed in order to provide cases and challenges as well as to suggest approaches to address these problems

Digital twin reference model development to prevent operators' risk in process plants

In the literature, many applications of Digital Twin methodologies in the manufacturing, construction and oil and gas sectors have been proposed, but there is still no reference model specifically developed for risk control and prevention. In this context, this work develops a Digital Twin reference model in order to define conceptual guidelines to support the implementation of Digital Twin for risk prediction and prevention. The reference model proposed in this paper is made up of four main layers (Process industry physical space, Communication system, Digital Twin and User space), while the implementation steps of the reference model have been divided into five phases (Development of the risk assessment plan, Development of the communication and control system, Development of Digital Twin tools, Tools integration in a Digital Twin perspective and models and Platform validation). During the design and implementation phases of a Digital Twin, different criticalities must be taken into consideration concerning the need for deterministic transactions, a large number of pervasive devices, and standardization issues. Practical implications of the proposed reference model regard the possibility to detect, identify and develop corrective actions that can affect the safety of operators, the reduction of maintenance and operating costs, and more general improvements of the company business by intervening both in strictly technological and organizational terms

QUBIC: The Q & U Bolometric Interferometer for Cosmology

The Q & U Bolometric Interferometer for Cosmology, QUBIC, is an innovative experiment designed to measure the polarization of the cosmic microwave background and in particular the signature left therein by the inflationary expansion of the Universe. The expected signal is extremely faint; thus, extreme sensitivity and systematic control are necessary in order to attempt this measurement. QUBIC addresses these requirements using an innovative approach combining the sensitivity of transition-edge sensor cryogenic bolometers, with the deep control of systematics characteristic of interferometers. This makes QUBIC unique with respect to others´ classical imagers experiments devoted to the CMB polarization. In this contribution, we report a description of the QUBIC instrument including recent achievements and the demonstration of the bolometric interferometry performed in laboratory. QUBIC will be deployed at the observation site in Alto Chorrillos, in Argentina, at the end of 2019.Fil: Battistelli, E. S.. Universita di Roma La Sapienza; ItaliaFil: Ade, P.. Cardiff University; Reino UnidoFil: Alberro, José Gabriel. Universidad Nacional de La Plata; ArgentinaFil: Almela, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Amico, G.. Universita di Roma La Sapienza; ItaliaFil: Arnaldi, L. H.. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Auguste, D.. Laboratoire de l’Accelerateur Lineaire; FranciaFil: Bonaparte, J.. Comisión Nacional de Energía Atómica; ArgentinaFil: Bottani, A.. Universidad Nacional de La Plata; ArgentinaFil: Di Donato, A.. Comisión Nacional de Energía Atómica; ArgentinaFil: Etchegoyen, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Fasciszewski, A.. Comisión Nacional de Energía Atómica; ArgentinaFil: Ferreyro, Luciano Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Fracchia, D.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Gamboa Lerena, Martín Miguel. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Garcia, Beatriz Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: García Redondo, Manuel Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Gomez Berisso, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Gonzalez, M.. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Harari, Diego Dario. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Kristukat, C.. Comisión Nacional de Energía Atómica; ArgentinaFil: Medina, Maria Clementina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; ArgentinaFil: Mundo, L. M.. Universidad Nacional de La Plata; ArgentinaFil: Pastoriza, Hernan. Comisión Nacional de Energía Atómica; ArgentinaFil: Platino, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Ringegni, P.. Universidad Nacional de La Plata; ArgentinaFil: Romero, Gustavo Esteban. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; ArgentinaFil: Salatino, M.. Kavli Institute for Particle Astrophysics and Cosmology; Estados UnidosFil: Salum, J. M.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Scoccola, Claudia Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Suarez, F.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: The QUBIC Collaboration. No especifíca

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications

The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches and in applications to real-world problems. Complex networks have fared extremely well in both of these aspects, with their sound theoretical basis developed over the years and with a variety of applications. In this survey, we analyze the applications of complex networks to real-world problems and data, with emphasis in representation, analysis and modeling, after an introduction to the main concepts and models. A diversity of phenomena are surveyed, which may be classified into no less than 22 areas, providing a clear indication of the impact of the field of complex networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions are welcome