Enabling technology for maintenance in a smart factory: A literature review

Industry 4.0 technologies are transforming the factory in an "intelligent" or "smart" factory. In a such context, a greater efficiency and innovative relationship is basically demanded within the whole production chain, including suppliers, producers, and customers. To be more competitive, companies are becoming increasingly aware that maintenance plays a key role during the digital transformation from the perspective of both technology and management. In this work, we perform a literature review of published cases to investigate how maintenance is changing through technologies of Industry 4.0 currently used in maintenance. We found 34 papers in literature involved in analyzing relations between maintenance and Industry 4.0 technology. The analysis of such studies let us to establish the current technology state-of-art and identify the most suited technology that today is employed in maintenance tasks. In particular Industrial Internet of Things and Cloud Computing are more common in the analyzed studies, confirming how these concepts and technologies are at the basis of Industry 4.0

A data-mining approach for wind turbine fault detection based on scada data analysis using artificial neural networks

Wind energy has shown significant growth in terms of installed power in the last decade. However, one of the most critical problems for a wind farm is represented by Operation and Maintenance (O&M) costs, which can represent 20-30% of the total costs related to power generation. Various monitoring methodologies targeted to the identification of faults, such as vibration analysis or analysis of oils, are often used. However, they have the main disadvantage of involving additional costs as they usually entail the installation of other sensors to provide real-time control of the system. In this paper, we propose a methodology based on machine learning techniques using data from SCADA systems (Supervisory Control and Data Acquisition). Since these systems are generally already implemented on most wind turbines, they provide a large amount of data without requiring extra sensors. In particular, we developed models using Artificial Neural Networks (ANN) to characterize the behavior of some of the main components of the wind turbine, such as gearbox and generator, and predict operating anomalies. The proposed method is tested on real wind turbines in Italy to verify its effectiveness and applicability, and it was demonstrated to be able to provide significant help for the maintenance of a wind farm

Endothelial cell regulation of leukocyte infiltration in inflammatory tissues

Endothelial cells play an important, active role in the onset and regulation of inflammatory and immune reactions. Through the production of chemokines they attract leukocytes and activate their adhesive receptors. This leads to the anchorage of leukocytes to the adhesive molecules expressed on the endothelial surface. Leukocyte adhesion to endothelial cells is frequently followed by their extravasation. The mechanisms which regulate the passage of leukocytes through endothelial clefts remain to be clarified. Many indirect data suggest that leukocytes might transfer signals to endothelial cells both through the release of active agents and adhesion to the endothelial cell surface. Adhesive molecules (such as PECAM) on the endothelial cell surface might also ‘direct’ leukocytes through the intercellular junction by haptotaxis. The information available on the molecular structure and functional properties of endothelial chemokines, adhesive molecules or junction organization is still fragmentary. Further work is needed to clarify how they interplay in regulating leukocyte infiltration into tissues

Private hospital energy performance benchmarking using energy audit data: an Italian case study

The increased focus on energy efficiency, both at the national and international levels, has fostered the diffusion and development of specific energy consumption benchmarks for most relevant economic sectors. In this context, energy-intensive facilities, such as hospitals and health structures, represent a unique case. Indeed, despite the high energy consumption of these structures, scientific literature lacks the presence of adequate energy performance benchmarks, especially in regard to the European context. Thus, this study aimed at defining energy benchmark indicators for the Italian private healthcare sector using data collected from the Italian mandatory energy audits according to Art.8 EU Directive 27/2012. The benchmark indicators’ definition was made using a methodology proposed by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA). This methodology provided the calculation of specific energy performance indicators (EnPIs) by considering the global energy consumption of the different sites and the sector’s relevant variables. The results obtained were compared with those obtained from a consolidated but more complex methodology: the one envisaged by the Environmental Protection Agency. The results obtained allowed us to validate the reliability of the proposed methodology, as well as the validity and future usability of the calculated indicators. Relying on a significant database containing actual data from recent energy audits, this study was thus able to provide an up-to-date and reliable benchmark for the private healthcare sector

Is cerebrospinal fluid amyloid-β42 a promising biomarker of response to nusinersen in adult spinal muscular atrophy patients?

Introduction: Nusinersen was approved as the first treatment for all types of spinal muscular atrophy (SMA), including adults with SMA types 2 and 3. Robust biomarkers of treatment response in SMA adults are lacking. Our aim was to examine cerebrospinal fluid (CSF) amyloid-β40 (Aβ40) and amyloid-β42 (Aβ42) peptides as biomarkers of treatment response. Methods: Eight patients with SMA types 2 and 3 were recruited consecutively in a single-center study. CSF was sampled at baseline, after a loading dose, and after three maintenance doses. Levels of Aβ42 and Aβ40 were evaluated for each CSF sampling. Wilcoxon matched-pairs signed-rank test was used to detect longitudinal changes. Results: CSF levels of Aβ42 increased from baseline to day 420 (95% confidence interval, P =.018), with a significant increase at days 180 and 420 compared with days 0 and 300, respectively (95% confidence interval, P =.012 and P =.018). Discussion: The maintenance and promotion of wellness of residual motor neurons mediated by the restored level of SMN protein due to nusinersen could result in an increased level of amyloid peptides

Catching the flu: Syndromic surveillance, algorithmic governmentality and global health security

How do algorithms shape the imaginary and practice of security? Does their proliferation point to a shift in the political rationality of security? If so, what is the nature and extent of that shift? This article explores these questions in relation to global health security. Prompted by an epidemic of new infectious disease outbreaks – from HIV, SARS and pandemic flu, through to MERS and Ebola – many governments are making health security an integral part of their national security strategies. Algorithms are central to these developments because they underpin a number of nextgeneration syndromic surveillance systems now routinely used by governments and international organizations to rapidly detect new outbreaks globally. This article traces the origins, design and evolution of three such internet-based surveillance systems: 1) the Program for Monitoring Emerging Diseases, 2) the Global Public Health Intelligence Network, and 3) HealthMap. The article shows how the successive introduction of those three syndromic surveillance systems has propelled algorithmic technologies into the heart of global outbreak detection. This growing recourse to algorithms for the purposes of strengthening global health security, the article argues, signals a significant shift in the underlying problem, nature, and role of knowledge in contemporary security practices

Convexal subarachnoid hemorrhage and acute ischemic stroke: a border zone matter?

Background Convexal subarachnoid hemorrhage (c-SAH) is an infrequent condition with variable causes. c-SAH concomitant to acute ischemic stroke (AIS) is even less frequent, and the relationship between the two conditions remains unclear. Methods Between January 2016 and January 2018, we treated four patients who were referred to our stroke unit with ischemic stroke and concomitant nontraumatic c-SAH. The patients underwent an extensive diagnostic workup, including digital subtraction angiography (DSA). Results All four patients developed acute focal neurological symptoms with restricted MRI diffusion in congruent areas. In three of the patients, infarcts were in a border zone between the main cerebral arteries and c-SAH was nearby. The fourth patient showed a small cortical infarct, and c-SAH was in a border zone territory of the contralateral hemisphere. An embolic source was discovered or strongly suspected in all cases. One patient was treated with intravenous thrombolysis, but this treatment was not related to c-SAH. None of the four patients showed microbleeds or further cortical siderosis, thus excluding cerebral amyloid angiopathy. In addition, DSA did not show signs of vasculitis, reversible cerebral vasoconstriction syndrome, or intracranial arterial dissection. Conclusions We proposed the embolism or hemodynamic changes of the border zone arterioles as a unifying pathogenetic hypothesis of coexisting c-SAH and AIS

TDP-43 promotes the formation of neuromuscular synapses through the regulation of Disc-large expression in Drosophila skeletal muscles

Background: The ribonuclear protein TDP-43 has been implicated in the pathophysiology of amyotrophic lateral sclerosis (ALS), with genetic mutations being linked to the neurological symptoms of the disease. Though alterations in the intracellular distribution of TDP-43 have been observed in skeletal muscles of patients suffering from ALS, it is not clear whether such modifications play an active role in the disease or merely represent an expression of muscle homeostatic mechanisms. Also, the molecular and metabolic pathways regulated by TDP-43 in the skeletal muscle remain largely unknown. Here, we analyze the function of TBPH, the Drosophila melanogaster ortholog of TDP-43, in skeletal muscles. Results: We modulated the activity of TDP-43 in Drosophila muscles by means of RNA interference and observed that it is required to promote the formation and growth of neuromuscular synapses. TDP-43 regulated the expression levels of Disc-large (Dlg), and restoring Dlg expression either in skeletal muscles or in motoneurons was sufficient to suppress the locomotive and synaptic defects of TDP-43-null flies. These results were validated by the observation of a decrease in Dlg levels in human neuroblastoma cells and iPSC-differentiated motoneurons derived from ALS patients, suggesting similar mechanisms may potentially be involved in the pathophysiology of the disease. Conclusions: Our results help to unveil the physiological role of TDP-43 in skeletal muscles as well as the mechanisms responsible for the autonomous and non-autonomous behavior of this protein concerning the organization of neuromuscular synapses