A Comprehensive Review on Time Sensitive Networks with a Special Focus on Its Applicability to Industrial Smart and Distributed Measurement Systems

The groundbreaking transformations triggered by the Industry 4.0 paradigm have dramati-cally reshaped the requirements for control and communication systems within the factory systems of the future. The aforementioned technological revolution strongly affects industrial smart and distributed measurement systems as well, pointing to ever more integrated and intelligent equipment devoted to derive accurate measurements. Moreover, as factory automation uses ever wider and complex smart distributed measurement systems, the well-known Internet of Things (IoT) paradigm finds its viability also in the industrial context, namely Industrial IoT (IIoT). In this context, communication networks and protocols play a key role, directly impacting on the measurement accuracy, causality, reliability and safety. The requirements coming both from Industry 4.0 and the IIoT, such as the coexistence of time-sensitive and best effort traffic, the need for enhanced horizontal and vertical integration, and interoperability between Information Technology (IT) and Operational Technology (OT), fostered the development of enhanced communication subsystems. Indeed, established tech-nologies, such as Ethernet and Wi-Fi, widespread in the consumer and office fields, are intrinsically non-deterministic and unable to support critical traffic. In the last years, the IEEE 802.1 Working Group defined an extensive set of standards, comprehensively known as Time Sensitive Networking (TSN), aiming at reshaping the Ethernet standard to support for time-, mission-and safety-critical traffic. In this paper, a comprehensive overview of the TSN Working Group standardization activity is provided, while contextualizing TSN within the complex existing industrial technological panorama, particularly focusing on industrial distributed measurement systems. In particular, this paper has to be considered a technical review of the most important features of TSN, while underlining its applicability to the measurement field. Furthermore, the adoption of TSN within the Wi-Fi technology is addressed in the last part of the survey, since wireless communication represents an appealing opportunity in the industrial measurement context. In this respect, a test case is presented, to point out the need for wirelessly connected sensors networks. In particular, by reviewing some literature contributions it has been possible to show how wireless technologies offer the flexibility necessary to support advanced mobile IIoT applications

A learning model for battery lifetime prediction of LoRa sensors in additive manufacturing

Today, an innovative leap for wireless sensor networks, leading to the realization of novel and intelligent industrial measurement systems, is represented by the requirements arising from the Industry 4.0 and Industrial Internet of Things (IIoT) paradigms. In fact, unprecedented challenges to measurement capabilities are being faced, with the ever-increasing need to collect reliable yet accurate data from mobile, battery-powered nodes over potentially large areas. Therefore, optimizing energy consumption and predicting battery life are key issues that need to be accurately addressed in such IoT-based measurement systems. This is the case for the additive manufacturing application considered in this work, where smart battery-powered sensors embedded in manufactured artifacts need to reliably transmit their measured data to better control production and final use, despite being physically inaccessible. A Low Power Wide Area Network (LPWAN), and in particular LoRaWAN (Long Range WAN), represents a promising solution to ensure sensor connectivity in the aforementioned scenario, being optimized to minimize energy consumption while guaranteeing long-range operation and low-cost deployment. In the presented application, LoRa equipped sensors are embedded in artifacts to monitor a set of meaningful parameters throughout their lifetime. In this context, once the sensors are embedded, they are inaccessible, and their only power source is the originally installed battery. Therefore, in this paper, the battery lifetime prediction and estimation problems are thoroughly investigated. For this purpose, an innovative model based on an Artificial Neural Network (ANN) is proposed, developed starting from the discharge curve of lithium-thionyl chloride batteries used in the additive manufacturing application. The results of experimental campaigns carried out on real sensors were compared with those of the model and used to tune it appropriately. The results obtained are encouraging and pave the way for interesting future developments

An IoT Measurement System Based on LoRaWAN for Additive Manufacturing

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible

A road map for defining Good Environmental Status in the deep-sea

The development of tools to assess the Good Environmental Status (GES) in the Deep Sea (DS) is one of the aspects that ATLAS WP3 is addressing. GES assessment in the DS is challenging due to 1) the lack of baseline data, 2) the remoteness of the DS ecosystems, and 3) the limitations of the sampling methods currently available. Throughout the duration of the project, ATLAS will develop a suitable approach to address GES in the DS. During the 2nd General Assembly, we will present a draft for a “road map” to address GES in the DS as well some of the aspects discussed during the 2017 ICES WG on Deep Sea Ecosystems. The temporal and spatial scale at which GES should be assessed in the deep-sea is an important aspect to be considered. Due to the data limited situation and challenges posed to monitoring, it may well be the case that GES will have to be assessed at large spatial and temporal scales when comparing the shallower waters of the European Seas. For similar reasons, the type of indicators to be used may have to be simplified and likely be based on high-level analyses related to traits, pressures/risks, and habitat /ecosystem resilience. Ultimately, the results of the combined analyses of GES descriptors might bring to a potential refining or redefinition of the GES concept for the deep-sea

Effect of intraoperative HES 6% 130/0.4 on the need for blood transfusion after major oncologic surgery: a propensity-matched analysis

OBJECTIVES: To evaluate the effect of the intraoperative use of hydroxyethyl starch on the need for blood products in the perioperative period of oncologic surgery. The secondary end-points included the need for other blood products, the clotting profile, the intensive care unit mortality and length of stay. METHODS: Retrospective observational analysis in a tertiary oncologic ICU in Brazil including 894 patients submitted to oncologic surgery for a two-year period from September 2007. Patients were grouped according to whether hydroxyethyl starch was used during surgery (hydroxyethyl starch and No-hydroxyethyl starch groups) and compared using a propensity score analysis. A total of 385 propensity-matched patients remained in the analysis (97 in the No-hydroxyethyl starch group and 288 in the hydroxyethyl starch group). RESULTS: A higher percentage of patients in the hydroxyethyl starch group required red blood cell transfusion during surgery (26% vs. 14%; p = 0.016) and in the first 24 hours after surgery (5% vs. 0%; p = 0.015) but not in the 24- to 48-hour period after the procedure. There was no difference regarding the transfusion of other blood products, intensive care unit mortality or length of stay. CONCLUSION: Hydroxyethyl starch use in the intraoperative period of major oncologic surgery is associated with an increase in red blood cell transfusions. There are no differences in the need for other blood products, intensive care unit length of stay or mortality

Tuna Longline Fishing around West and Central Pacific Seamounts

BACKGROUND: Seamounts have been identified as aggregating locations for pelagic biodiversity including tuna; however the topography and prevailing oceanography differ between seamounts and not all are important for tuna. Although a relatively common feature in oceanic ecosystems, little information is available that identifies those that are biologically important. Improved knowledge offers opportunities for unique management of these areas, which may advance the sustainable management of oceanic resources. In this study, we evaluate the existence of an association between seamounts and tuna longline fisheries at the ocean basin scale, identify significant seamounts for tuna in the western and central Pacific Ocean, and quantify the seamount contribution to the tuna longline catch. METHODOLOGY/PRINCIPAL FINDINGS: We use data collected for the Western and Central Pacific Ocean for bigeye, yellowfin, and albacore tuna at the ocean basin scale. GLMs were applied to a coupled dataset of longline fisheries catch and effort, and seamount location information. The analyses show that seamounts may be associated with an annual longline combined catch of 35 thousand tonnes, with higher catch apparent for yellowfin, bigeye, and albacore tuna on 17%, 14%, and 14% of seamounts respectively. In contrast 14%, 18%, and 20% of seamounts had significantly lower catches for yellowfin, bigeye and albacore tuna respectively. Studying catch data in relation to seamount positions presents several challenges such as bias in location of seamounts, or lack of spatial resolution of fisheries data. Whilst we recognize these limitations the criteria used for detecting significant seamounts were conservative and the error in identification is likely to be low albeit unknown. CONCLUSIONS/SIGNIFICANCE: Seamounts throughout the study area were found to either enhance or reduce tuna catch. This indicates that management of seamounts is important Pacific-wide, but management approaches must take account of local conditions. Management of tuna and biodiversity resources in the region would benefit from considering such effects

The impact of deep-sea fisheries and implementation of the UNGA Resolutions 61/105 and 64/72. Report of an international scientific workshop

The scientific workshop to review fisheries management, held in Lisbon in May 2011, brought together 22 scientists and fisheries experts from around the world to consider the United Nations General Assembly (UNGA) resolutions on high seas bottom fisheries: what progress has been made and what the outstanding issues are. This report summarises the workshop conclusions, identifying examples of good practice and making recommendations in areas where it was agreed that the current management measures fall short of their target

Longer duration of obesity is associated with a reduction in urinary angiotensinogen in prepubertal children

Background: We aimed to study the impact of obesity on urinary excretion of angiotensinogen (U-AGT) in prepubertal children, focusing on the duration of obesity and gender. Also, we aimed to evaluate whether plasma angiotensinogen (P-AGT) and hydrogen peroxide (H2O2) play a role in the putative association. Methods: Cross-sectional evaluation of 305 children aged 8–9 years (160 normal weight, 86 overweight, and 59 obese). Anthropometric measurements and 24-h ambulatory blood pressure monitoring were performed. Angiotensinogen (AGT) was determined by a commercial enzyme-linked immunosorbent assay (ELISA) kit and H2O2 by a microplate fluorometric assay. Results: U-AGT and P-AGT levels were similar across body mass index (BMI) groups and between sexes. However, boys who were overweight/obese since the age of 4 years presented lower levels of U-AGT compared with those of normal weight at the same age. In children who were overweight/obese since the age of 4, urinary H2O2 decreased with P-AGT. Conclusions: A higher duration of obesity was associated with decreased U-AGT in boys, thus reflecting decreased intrarenal activity of the renin–angiotensin system. Also, children with a longer duration of obesity showed an inverse association between urinary H2O2 and P-AGT. Future studies should address whether these results reflect an early compensatory mechanism to limit obesity-triggered renal dysfunction.This project was supported by funds from Fundo Europeu de Desenvolvimento Regional (FEDER) from Programa Operacional Factores de Competitividade – COMPETE (FCOMP-01-0124-FEDER-028751), by national funds from the Portuguese Foundation for Science and Technology (FCT) (PTDC/DTP-PIC/0239/2012) and by Calouste Gulbenkian Foundation, that granted the study design and data collection and analysis. Liane Correia-Costa was supported by FCT (grant SFRH/SINTD/95898/2013), Teresa Sousa was supported by FCT and POPH/FSE (EC) (Ciência 2008 and SFRH/BPD/112005) and Franz Schaefer was supported by the ERA-EDTA Research Programme and the KfH Foundation for Preventive Medicine. The Epidemiology Research Unit (EPIUnit) is funded by FCT (UID/DTP/04750/2013)

Impact of physical activity on redox status and nitric oxide bioavailability in nonoverweight and overweight/obese prepubertal children

Nutritional status might contribute to variations induced by physical activity (PA) in redox status biomarkers. We investigated the influence of PA on redox status and nitric oxide (NO) production/metabolism biomarkers in nonoverweight and overweight/obese prepubertal children. We performed a cross-sectional evaluation of 313 children aged 8-9 years (163 nonoverweight, 150 overweight/obese) followed since birth in a cohort study (Generation XXI, Porto, Portugal). Plasma total antioxidant status (P-TAS), plasma and urinary isoprostanes (P-Isop, U-Isop), urinary hydrogen peroxide (U-H2O2), myeloperoxidase (MPO) and plasma and urinary nitrates and nitrites (P-NOx, U-NOx) were assessed, as well as their association with variables of reported PA quantification (categories of PA frequency (>1x/week and ≤1x/week)and continuous PA index (obtained by the sum of points)) in a questionnaire with increasing ranks from sedentary to vigorous activity levels. U-NOx was significantly higher in children who presented higher PA index scores and higher PA frequency. Separately by BMI classes, U-NOx was significantly higher only in nonoverweight children who practiced PA more frequently (p = 0.037). In overweight/obese children, but not in nonoverweight, P-TAS was higher among children with higher PA frequency (p = 0.007). Homeostasis model assessment index (HOMA-IR) was significantly lower in more active overweight/obese children, but no differences were observed in nonoverweight children. In the fully adjusted multivariate linear regression models for P-TAS, in the overweight/obese group, children with higher PA frequency presented higher P-TAS. In the U-NOx models, U-NOx significantly increased with PA index, only in nonoverweight children. Our results provide additional evidence in support of a protective effect of physical activity, in nonoverweight by increasing NO bioavailability and in overweight/obese children by enhancing systemic antioxidant capacity and insulin sensitivity. These results highlight the importance of engaging in regular physical exercise, particularly among overweight/obese children, in which a positive association between oxidant status and cardiometabolic risk markers has been described.This project was supported by FEDER funds from Programa Operacional Factores de Competitividade – COMPETE [FCOMP-01-0124-FEDER-028751], by national funds from the Portuguese Foundation for Science and Technology (FCT), Lisbon, Portugal [PTDC/DTP-PIC/0239/2012] and by Calouste Gulbenkian Foundation. Liane Correia-Costa was supported by FCT [SFRH/SINTD/95898/2013] and Teresa Sousa was supported by FCT and POPH/FSE (EC) [Ciência 2008 and SFRH/BPD/112005]

An Augmented Interface to Display Industrial Robot Faults

Technology advancement is changing the way industrial factories have to face an increasingly complex and competitive market. The fourth industrial revolution (known as industry 4.0) is also changing how human workers have to carry out tasks and actions. In fact, it is no longer impossible to think of a scenario in which human operators and industrial robots work side-by-side, sharing the same environment and tools. To realize a safe work environment, workers should trust robots as well as they trust human operators. Such goal is indeed complex to achieve, especially when workers are under stress conditions, such as when a fault occurs and the human operators are no longer able to understand what is happening in the industrial manipulator. Indeed, Augmented Reality (AR) can help workers to visualize in real-time robots’ faults. This paper proposes an augmented system that assists human workers to recognize and visualize errors, improving their awareness of the system. The system has been tested using both an AR see-through device and a smartphone