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Purpose The Multicentre observational REgistry of patients hospitalized for heart failure and reAL-life adherence to international guidelines for the management of patients with acute and chronic Heart Failure (REAL-HF) aims to provide a comprehensive overview of hospital management of HF patients in Italy. Methods The registry involves 11 cardiology centers from seven Italian regions, including all adult patients hospitalized for HF in the period 2020-2026. Data are derived from hospital discharge letters and electronic records. Patients are included in the registry based on Diagnosis Related Groups codes. Results This preliminary analysis included 1600 patients hospitalized for HF in 2020 in two Italian tertiary university hospitals. Males were 851(53%) with a median age of 81(71-87) years. Less than one-third of the patients (n=461[29%]) was hospitalized in a cardiology unit, while almost half of the patients (n=783[49%]) was admitted to an internal medicine ward. Median hospital length of stay was 9(6-14) days. Readmission rates were 9% and 29% at 30 days and within the same year, respectively. In-hospital mortality was 9%, while 28% of the patients died within the same year. According to HF categories, 501(31%) patients were diagnosed as having HFrEF, 193(12%) mildly reduced ejection fraction (HFmrEF) and 689(43%) preserved ejection fraction (HFpEF). Median left ventricular EF was 49%(35-55%) and was significantly lower in patients with HFrEF (30%[25-35%]) compared to those with HFmrEF (45%[43-45%]) and HFpEF (55%[55-60%]) – p Conclusions Preliminary data from the multicentre REAL-HF registry confirm that HF constitutes a clinical issue. Adherence to the guidelines is still inadequate and this may impact on patients’ outcomes. Moreover, the significant differences in terms of patients’ profiles might further increase the gap between highly specialized cardiology units and internal medicine departments.

To date, very few studies focused their attention on efficacy and safety of recanalisation therapy in acute ischemic stroke (AIS) patients with cancer, reporting conflicting results. We retrospectively analysed data from our database of consecutive patients admitted to the Udine University Hospital with AIS that were treated with recanalisation therapy, i.e. intravenous thrombolysis (IVT), mechanical thrombectomy (MT), and bridging therapy, from January 2015 to December 2019. We compared 3-month dependency, 3-month mortality, and symptomatic intracranial haemorrhage (SICH) occurrence of patients with active cancer (AC) and remote cancer (RC) with that of patients without cancer (WC) undergoing recanalisation therapy for AIS. Patients were followed up for 3 months. Among the 613 AIS patients included in the study, 79 patients (12.9%) had either AC (n = 46; 7.5%) or RC (n = 33; 5.4%). Although AC patients, when treated with IVT, had a significantly increased risk of 3-month mortality [odds ratio (OR) 6.97, 95% confidence interval (CI) 2.42–20.07, p = 0.001] than WC patients, stroke-related deaths did not differ between AC and WC patients (30% vs. 28.8%, p = 0.939). There were no significant differences between AC and WC patients, when treated with MT ± IVT, regarding 3-month dependency, 3-month mortality and SICH. Functional independence, mortality, and SICH were similar between RC and WC patients. In conclusion, recanalisation therapy might be used in AIS patients with nonmetastatic AC and with RC. Further studies are needed to explore the outcome of AIS patients with metastatic cancer undergoing recanalisation therapy.

Objective To report clinical and electroneuromyographic (ENMG) characteristics of patients affected by severe COVID-19 infection, evaluated for muscular weakness. Materials and methods ENMGs performed for evaluation of diffuse weakness in patients who could not be discharged from semi-intensive care COVID unit because of difficulties in ventilation weaning were reviewed. Patients with severe COVID-19 infection who had undergone endotracheal intubation and able to co-operate were considered. ENMG protocol was focused on neurophysiological items that excluded or confirmed critical illness polyneuropathy (CIP), myopathy (CIM), or polyneuromyopathy (CIPM). Standardized clinical evaluation was performed using Medical Research Council (MRC) sum score. Results Eight patients were included in the study. All presented known risk factors for intensive care unit-acquired weakness (ICU-AW), and none of them had history of underlying neuromuscular disorders. ENMG findings were normal in two patients, while only two patients had an altered MRC sum score (< 48). Neuromuscular involvement was diagnosed in 6/8 patients (75%): 2 had CIP, 1 had possible CIM, 1 had CIPM, while 1 patient, with clinically evident weakness but equivocal ENMG findings, was classified as ICU-AW. Finally, 1 patient was diagnosed with acute demyelinating neuropathy. Patients with neuromuscular involvement were those with longer intubation duration and higher levels of IL-6 at admission. Conclusion Neuromuscular complications are frequent in severe COVID-19 and cannot be excluded by MRC sum scores above 48. Standardized ENMG is helpful in guiding diagnosis when clinical evaluation is not reliable or possible. Elevated IL-6 at admission may be a predictor biomarker of ICU-AW in COVID-19.

VDD pacemakers are regarded as a second choice in patients with atrio-ventricular blocks mainly due to the potential failure of atrial sensing, leading to a loss of atrio-ventricular synchrony. This single-centre study aimed to evaluate the prevalence of loss of atrial sensing and its potential determinants in patients with VDD pacemakers.142 patients with an implanted VDD device underwent long-term follow-up with clinical evaluation, electrocardiogram, device interrogation and echocardiogram.Over a long follow-up period [median 110 (68-156) months], 17 patients (12%) in sinus rhythm presented loss of atrial sensing. This was most often intermittent, but three patients required a permanent switch to VVI mode. ECG showed higher prevalence of interatrial blocks (50% vs 26.6%, p = 0.057) and longer P wave duration (116 ± 19 vs 105 ± 15 ms, p = 0.019) in patients with loss of atrial sensing. Echocardiography revealed larger left atrial (LA) volumes (p 0.05) in patients with loss of atrial sensing, and lower LA ejection fraction (0.40 vs 0.47, p = 0.0037) and expansion index (0.63 ± 0.26 vs 0.90 ± 0.31, p = 0.003). P wave duration on ECG proved to be independently associated with loss of atrial sensing on multivariable analysis (OR 1.062, 95% CI 1.015-1.110; p = 0.008). The prevalence of atrial fibrillation and subsequent switch to VVI mode was high (16%).In the long-term follow-up, the loss of atrial sensing is present in 12% of patients with implanted VDD pacemakers. ECG and echocardiographic parameters may serve as screening tools for the detection of atrial myopathy which is associated with the loss of atrial sensing.

ObjectiveTo evaluate the prevalence of hyposmia and dysgeusia in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their temporal relationship with the onset of other symptoms.MethodsWe performed a retrospective analysis of patients admitted during the month of March 2020 to the nonintensive COVID unit of Udine University Hospital on the basis of a positive swab test and/or of clinical-radiologic signs of SARS-CoV-2 infection. Patients were interviewed with a standardized questionnaire. Clinical and laboratory data were collected. Data were analyzed with descriptive statistics, and results expressed as point estimates and 95% confidence intervals (CIs).ResultsOf 141 patients admitted, 93 were interviewed. Hyposmia and dysgeusia were present in 58 cases (62.4%). In 22.4% of them, olfactory and gustatory impairment clearly preceded systemic symptoms. The presence of active smoking was very limited in both groups: 8.6% in hyposmic vs 2.9% in normosmic patients (odds ratio 3.2; 95% CI 0.3–28.6). Moreover, total leukocytes and neutrophils count were respectively 23% (effect estimate 1.23; 95% CI 1.06–1.42) and 29% (effect estimate 1.29; 95% CI 1.07–1.54) lower in the hyposmic cohort. No difference was found for other inflammatory biomarkers.ConclusionsHyposmia and dysgeusia are common in SARS-CoV-2 infection and can precede systemic symptoms. They should be actively searched and prompt close monitoring and isolation until infection is confirmed or disproven. The lower number of total leukocytes and neutrophils in hyposmic patients might indicate an early-phase virus-induced cytopenia.

Thermoacoustic characterization of gas turbine combustion systems is of primary importance for successful development of gas turbine technology, to meet the stringent targets on pollutant emissions. In this context, it becomes more and more necessary to develop reliable tools to be used in the industrial design process. The dynamics of a lean-premixed full-annular combustor for heavy-duty applications has been numerically studied in this work. The well-established CFD-SI method has been used to investigate the flame response varying operational parameters such as the flame temperature (global equivalence ratio) and the fuel split between premixed and pilot fuel injections: such a wide range experimental characterization represents an opportunity to validate the employed numerical methods and to give a deeper insight into the flame dynamics. URANS simulations have been performed, due to their affordable computational costs from the industrial perspective, after validating their accuracy through the comparison against LES results. Furthermore, an approach where the pilot and the premixed flame responses are analyzed separately is proposed, exploiting the independence of their evolution. The calculated FTFs have been implemented in a 3D FEM model of the chamber, in order to perform linear stability analysis and to validate the numerical approach. A boundary condition for rotational periodicity based on Bloch-Wave theory has been implemented into the Helmholtz solver and validated against full-annular chamber simulations, allowing a significant reduction in computational time. The reliability of the numerical procedure has been assessed through the comparison against full-annular experimental results.

The epidemiology of paraneoplastic neurological syndromes (PNS) remains to be defined. We present here the first population-based incidence study and report the clinical spectrum and antibody profile of PNS in a large area in Northeastern Italy. We performed a 9-year (2009–2017) population-based epidemiological study of PNS in the provinces of Udine, Pordenone and Gorizia, in the Friuli-Venezia Giulia region (983,190 people as of January 1, 2017). PNS diagnosis and subgroups were defined by the 2004 diagnostic criteria. Age- and sex-adjusted incidence rates were calculated. We identified 89 patients with a diagnosis of definite PNS. Median age was 68 years (range 26–90), 52% were female. The incidence of PNS was 0.89/100,000 person-years. PNS incidence rates increased over time from 0.62/100,000 person-years (2009–2011), 0.81/100,000 person-years (2012–2014) to 1.22/100,000 person-years (2015–2017). The prevalence of PNS was 4.37 per 100,000. Most common PNS were limbic encephalitis (31%), cerebellar degeneration (28%) and encephalomyelitis (20%). Among antibody (Ab)-positive cases, most frequent specificities included: Yo (30%), Hu (26%), and Ma2 (22%), while the most frequent associated tumors were lung (17%) and breast cancer (16%), followed by lymphoma (12%). PNS developed in 1 in every 334 cancers in our region. Statistically significant associations were observed between cancer type and Ab-specificity (P

As a consequence of the fourth industrial revolution, the data produced by companies’ day-by-day activities and the rate at which the transactions occur are growing exponentially. In order to extract business value from those data, they need to be organised under a reference conceptual model facilitating data analysis and decision making. Since no sound reference model for organising digital factory production data has been proposed in the literature, this paper aims at developing and testing a conceptual multidimensional model to support a broad range of data analytics activities for the management and optimisation of production in a smart factory. The testing of the model in a case study company of the printing sector provides insights into the applicability of the model and the connected benefits.

No study investigated the possible detrimental effect of stress hyperglycemia on patients affected acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT). A new index, the glucose-to-glycated hemoglobin ratio (GAR), has been developed for assessing stress hyperglycemia. We retrospectively analyzed data from a prospectively collected database of consecutive patients admitted to the Udine University Hospital with AIS that were treated with IVT from January 2015 to December 2019. Four hundred and fourteen consecutive patients with AIS undergoing IVT entered the study. The patients were then stratified into four groups by quartiles of GAR (Q1–Q4). The higher GAR index was, the more severe stress hyperglycemia was considered. Prevalence of 3 months poor outcome (37.7% for Q1, 34% for Q2, 46.9% for Q3, and 66.7% for Q4, p for trend = 0.001), 3 months mortality (10.5% for Q1, 7.5% for Q2, 11.2% for Q3, and 27.1% for Q4, p for trend = 0.001), and symptomatic intracranial hemorrhage (0.9% for Q1, 0.9% for Q2, 5.1% for Q3, and 17.7% for Q4, p for trend = 0.001) was significant different among the four groups. AIS patients with severe stress hyperglycemia had a significantly increased risk of 3 months poor outcome (OR 2.43, 95% CI 1.14–5.22, p = 0.02), 3 months mortality (OR 2.38, 95% CI 1.01–5.60, p = 0.04), and symptomatic intracranial hemorrhage (OR 16.76, 95% CI 2.09–134.58, p = 0.008) after IVT. In conclusion, we demonstrated that stress hyperglycemia, as measured by the GAR index, is associated to worse outcome in AIS patients undergoing IVT.

ObjectiveTo define the clinical characteristics, management, and outcome of neurologic immune-related adverse events (n-irAEs) of immune checkpoint inhibitors (ICIs).MethodsSystematic review of the literature following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.ResultsA total of 694 articles were identified. Two hundred fifty-six articles, with 428 individual patients, met the inclusion criteria. Reports regarding neuromuscular disorders (319/428, 75%) were more frequent than those on CNS disorders (109/428, 25%). The most common n-irAEs reports were myositis (136/428, 32%), Guillain-Barré syndrome and other peripheral neuropathies (94/428, 22%), myasthenic syndromes (58/428, 14%), encephalitis (56/428, 13%), cranial neuropathies (31/428, 7%), meningitis (13/428, 3%), CNS demyelinating diseases (8/428, 2%), and myelitis (7/428, 2%). Other CNS disorders were detected in 25/428 (6%) patients. Compared with the whole sample, myasthenic syndromes were significantly more Ab positive (33/56, 59%; p < 0.001). Anti–programmed cell death protein 1/programmed cell death ligand 1 was more frequent in myasthenic syndromes (50/58, 86%; p = 0.005) and less common in meningitis (2/13, 15%; p < 0.001) and cranial neuropathies (13/31, 42%; p = 0.005). Anti–cytotoxic T-lymphocyte antigen-4 ICIs were more frequent in meningitis (8/13, 62%; p < 0.001) and less common in encephalitis (2/56, 4%; p = 0.009) and myositis (12/136, 9%; p = 0.01). Combination of different ICIs was more frequent in cranial neuropathies (12/31, 39%; p = 0.005). Melanoma was more frequent in patients with peripheral neuropathies (64/94, 68%; p = 0.003) and less common in encephalitis (19/56, 34%; p = 0.001). The highest mortality rate was reached in myasthenic syndromes (28%).ConclusionConsidering the increasing use of ICI therapy in the forthcoming future, this information can be valuable in assisting neurologists and oncologists in early n-irAEs diagnosis and treatment.

Background: Admission hyperglycemia impairs outcome in acute ischemic stroke (AIS) patients undergoing mechanical thrombectomy (MT). Since hyperglycemia in AIS represents a dynamic condition, we tested whether the dynamic patterns of hyperglycemia, defined as blood glucose levels &gt, 140 mg/dl, affect outcomes in these patients. Methods: We retrospectively analyzed data of 200 consecutive patients with prospective follow-up. Based on blood glucose level, patients were distinguished into 4 groups: (1) persistent normoglycemia, (2) hyperglycemia at baseline only, (3) hyperglycemia at 24-h only, and (4) persistent (at baseline plus at 24-h following MT) hyperglycemia. Results: AIS patients with persistent hyperglycemia have a significantly increased risk of poor functional outcome (OR 6.89, 95% CI 1.98&ndash, 23.94, p = 0.002, for three-month poor outcome, OR 11.15, 95% CI 2.99&ndash, 41.52, p = 0.001, for no major neurological improvement), mortality (OR 5.37, 95% CI 1.61&ndash, 17.96, p = 0.006, for in-hospital mortality, OR 4.43, 95% CI 1.40&ndash, 13.97, p = 0.01, for three-month mortality), and hemorrhagic transformation (OR 6.89, 95% CI 2.35&ndash, 20.21, p = 0.001, for intracranial hemorrhage, OR 5.42, 95% CI 1.54&ndash, 19.15, p = 0.009, for symptomatic intracranial hemorrhage) after endovascular treatment. These detrimental effects were partially confirmed after also excluding diabetic patients. The AUC-ROC showed a very good performance for predicting three-month poor outcome (0.76) in-hospital mortality (0.79) and three-month mortality (0.79). Conclusions: Our study suggests that it is useful to perform the prolonged monitoring of glucose levels lasting 24-h after MT.

The coronavirus disease 2019 (COVID-19) pandemic is a major worldwide health disorder. There is an increasing number of neurological complications recognized with COVID-19 including patients with GBS and its variants.A review of the clinical cases of GBS associated to COVID-19 infection published in the last months has been developed. We included 48 patients (31 men, mean age 56.4 years). The most common COVID-19 symptoms were cough (60.4%) and fever (56.3%). Mean time from COVID-19 symptoms to neurologic manifestations was 12.1 days, but in nine patients (18.8%) developed GBS within seven days. Eleven patients (22.9%) presented cranial nerve involvement in the absence of muscle weakness; 36 presented the classic sensory motor variant (75%) and one had a pure motor variant (2.1%). The electrodiagnostic pattern was considered demyelinating in 82.4% of the generalized variants. The presence of hyposmia/dysgeusia was associated with a latency shorter than seven days to GBS onset of symptoms (30% vs 15.6%), and cranial nerve involvement in the absence of weakness (30.8% vs 17.1%). Most patients (87.5%) were treated with intravenous immunoglobulin. Neurological outcome was favorable in 64.6%; 29.2% had respiratory failure and 4.2% died shortly after being admitted.GBS in patients with SARS-CoV-2 infection resembles clinically and electrophysiology the classical forms. Further studies are necessary to understand whether GBS frequency is actually increased due to SARS-CoV-2 infection and explore pathogenic mechanisms.Síndrome de Guillain-Barré asociado a infección por COVID-19: revisión de casos publicados.Introducción. La pandemia por la enfermedad por coronavirus 2019 (COVID-19) es un importante problema para la salud mundial. Hay un incremento en las complicaciones neurológicas reconocidas por la COVID-19, incluyendo el síndrome de Guillain-Barré (SGB) y sus variantes. Desarrollo. Se realizó una revisión de los casos publicados en los últimos meses de SGB asociado a infección por COVID-19. Incluimos a 48 pacientes (31 hombres; edad media: 56,4 años). Los síntomas de COVID-19 más comunes fueron tos (60,4%) y fiebre (56,3%). El tiempo promedio entre los síntomas de COVID-19 y el SGB fue de 12,1 días, pero nueve pacientes (18,8%) desarrollaron SGB en menos de siete días. Once pacientes (22,9%) presentaron afectación de los nervios craneales en ausencia de debilidad muscular, 36 presentaron la variante clásica sensitivomotora (75%) y uno tuvo una variante motora pura (2,1%). El patrón electrofisiológico se consideró desmielinizante en el 82,4% de las variantes generalizadas. La presencia de hiposmia/disgeusia estuvo asociada con una latencia menor a los siete días hasta el inicio de los síntomas del SGB (30 frente a 15,6%) y a la afectación de los nervios craneales en ausencia de debilidad (30,8 frente a 17,1%). La mayoría de los pacientes (87,5%) fueron tratados con inmunoglobulina endovenosa. La evolución neurológica fue favorable en el 64,6%, el 29,2% tuvo insuficiencia respiratoria y hubo un 4,2% de muertes. Conclusiones. El SGB en pacientes con infección por SARS-CoV-2 es similar clínica y electrofisiológicamente a las formas clásicas. Se requieren más estudios para comprender si la frecuencia del SGB realmente aumentó debido a la pandemia por COVID-19 y explorar los mecanismos patógenos involucrados.

In the contemporary Italian scenario, Garrone’s work undoubtedly represents one of the best examples of cinema that bravely confronts reality. The social/political commitment takes shape, in Primo Amore, in different ways if compared to the usual cinematic procedure Garrone adopts in his other works. In Gomorra and Reality the denunciation of society is intense. Saviano’s novel is sectioned in order to highlight the basic issues (the assimilation of camorra with capitalism, the false ‘respectability’ of the establishment). The focus in Reality is a harsh critique of remunerative gratification, an instrument to control the masses. The plot of Primo Amore, a tragic love story centred on an obsession with feminine thinness, is a metaphor for the rejection of abundance, perceived as unsatisfactory and limiting. This article explores Garrone’s critical approach, focusing on the author’s figurative and stylistic choices, while highlighting the complexity of the entire representation.

Paraneoplastic cerebellar degeneration (PCD) is usually thought to have a subacute progression over several weeks. We report herein incidence and clinical features of hyperacute onset PCD, a vertebrobasilar stroke mimic. We performed a retrospective analysis of all suspected PCD cases referred to the Udine University Hospital between 2009 and 2017. Our center provides the only neuroimmunology laboratory for three provinces of the Friuli-Venezia Giulia region, Italy (983,190 people as of January 1, 2017). Inclusion criteria were (1) abrupt onset of neurological symptoms; (2) initial consideration of a vascular etiology; (3) final diagnosis of “definite PCD.” We also carried out a systematic review of the literature in order to identify previous stroke-like PCD cases. Between 2009 and 2017, 24 patients received a final diagnosis of PCD. The age-standardized incidence rate of PCD was 0.22/100,000 person-years. Two cases (8.3%) had a stroke-like onset, with an incidence of 0.02/100,000 person-years. Additionally, 10 previously reported stroke-like PCD cases were identified. Among all cases (n = 12), 67% were female; median age was 51 years (range, 22–69). An associated cancer was discovered in all cases. Brain imaging was normal in most (75%) of the patients. Cerebrospinal fluid (CSF) analysis showed inflammatory alterations in 73% of the cases. Cancer treatment was more effective than immunotherapy in improving the neurological syndrome. Typical patients with hyperacute PCD are middle-aged women with normal brain imaging, inflammatory markers in CSF, and cancer. Surgery of the underlying cancer is probably the best treatment. PCD must be considered in the differential diagnosis of acute-onset ataxia and/or vertigo.

This paper describes the development phases of a damping system for combustion instability reduction in an annular type combustor for heavy-duty gas turbine applications. As reported by the authors in a previous paper, the full scale annular test rig allowed for an extensive characterization of the combustor with realistic acoustic boundaries at engine-relevant conditions. Emissions and operability assessment over a wide range of load conditions was performed, allowing the evaluation of the response of the system near the thermo-acoustic instability onset. The instability is quantified by its acoustic growth rate. This quantity is a crucial input in the design process of dampers. A methodology has been used to extract these growth rates form measured pulsation data. Experimentally determined growth rates have been evaluated for different fuel flow rate split between the main and the pilot injections, providing input to dampers preliminary design. Given current combustor architecture constraints, a first attempt configuration has been proposed and performances evaluated in the full annular rig. Dampers have been equipped with dynamic sensors and thermocouples with the purpose of measuring the growth rate abatement and the consequent NOx emissions reduction. A dedicated numerical toolbox, in-house developed by GE Power, has been used for both dampers preliminary design and growth rate reduction evaluation. Fine tuning of dampers elements as well as design assumptions adjustments required additional experimental evaluations and design iterations. Encouraged by the successful test in the concept phase, an optimized design for engine implementation was defined, that featured a significant increased damper volume, involving combustor parts re-design. The optimized configuration was finally tested in full annular rig and results demonstrated an important enhancement of operability while maintaining NOx emissions below the target levels.

The collection, organisation and analysis of large amount of data (Big Data) in different application domains still require the involvement of experts for the identification of relevant data only, without being overwhelmed by volume, velocity and variety of collected data. According to the “Human-In-the-Loop Data Analysis” vision, experts explore data to take decisions in unexpected situations, based on their long-term experience. In this paper, the IDEAaS (Interactive Data Exploration As-a-Service) approach is presented, apt to enable Big Data Exploration (BDE) according to data relevance. In the approach, novel techniques have been developed: (i) an incremental clustering algorithm, to provide summarised representation of collected data streams; (ii) multi-dimensional organisation of summarised data, for data exploration according to different analysis dimensions; (iii) data relevance evaluation techniques, to attract the experts’ attention on relevant data only during exploration. The approach has been experimented to apply BDE for state detection in the Industry 4.0 domain, given the strategic importance of Big Data management as enabling technology in this field. In particular, a stream of numeric features is collected from a Cyber Physical System and is explored to monitor the system health status, supporting the identification of unknown anomalous conditions. Results of an extensive experimentation in the Industry 4.0 domain are presented in the paper and demonstrated the effectiveness of developed techniques to attract the attention of experts on relevant data, also beyond the considered domain, in presence of disruptive characteristics of Big Data, namely volume (millions of collected records), velocity (measured in milliseconds) and variety (number and heterogeneity of analysis dimensions).

Tacrolimus-induced encephalopathy presents with acute neurological symptoms such as headache, seizures, visual disturbances, hemiplegia, and altered mental status. A 60-year-old woman, presented to our clinic with a 4-month history of severe headache. She recently underwent kidney transplantation and was taking tacrolimus. MRI scan showed diffuse and symmetric alterations involving both supratentorial and infratentorial white matter. Cerebral spinal fluid assessment for infectious diseases were negative but elevated total protein level and oligoclonal bands positivity were reported. Treatment with steroid bolus, along with tacrolimus tapering, provided clinico-radiological improvement. This is the first case of tacrolimus-induced neurotoxicity strongly suggestive of an immune-mediated pathogenesis.

Recent advances in the smart factory created new opportunities in industrial support, specifically in anomaly detection and asset management for maintenance purposes. Data collected from machines in operation is integrated in cyberspace with advanced cockpit and dashboard visualisation tools, as well as computerised maintenance management systems (CMMS). This paves the way to collaborative environments for Cyber Physical Systems, that assist maintenance operators in making better decisions while dealing with real time data in a dynamic context of interconnected systems. To this aim, models and techniques for data representation and treatment are highly required. In this paper, we propose a state detection service for Cyber Physical Systems, able to identify anomalies based on large amounts of data incrementally collected, organized and analysed on-the-fly. The service combines in a novel way data summarisation and data relevance techniques, to focus the computation on relevant data only, as well as a multi-dimensional model, that organises summarised data according to multiple dimensions, for flexible anomaly detection according to different analysis requirements. A pilot case study in the smart factory is also described, to demonstrate the applicability of the approach.

The increasing connections of systems that produce high volumes of real time data have raised the importance of addressing data abundance research challenges. In the Industry 4.0 application domain, for example, high volumes and velocity of data collected from machines, as well as value of data that declines very quickly, put Big Data issues among the new challenges also for the factory of the future. While many approaches have been developed to investigate data analysis, data visualisation, data collection and management, the impact of Big Data exploration is still under-estimated. In this paper, we propose an approach to support and ease exploration of real time data in a dynamic context of interconnected systems, such as the Industry 4.0 domain, where large amounts of data must be incrementally collected, organized and analysed on-the-fly. The approach relies on: (i) a multi-dimensional model, that is suited for supporting the iterative and multi-step exploration of Big Data; (ii) novel data summarisation techniques, based on clustering; (iii) a model of relevance, aimed at focusing the attention of the user only on relevant data that are being explored. We describe the application of the approach in the smart factory as a case study.

Combustor liner of present gas turbine engines is subjected to high thermal loads as it surrounds high temperature combustion reactants and is hence facing the related radiative load. This generally produces high thermal stress levels on the liner, strongly limiting its life expectations and making it one of the most critical components of the entire engine. The reliable prediction of such thermal loads is hence a crucial aspect to increase the flame tube life span and to ensure safe operations. The present study aims at investigating the aerothermal behavior of a GE Dry Low NOx (DLN1) class flame tube and in particular at evaluating working metal temperatures of the liner in relation to the flow and heat transfer state inside and outside the combustion chamber. Three different operating conditions have been accounted for (i.e., lean–lean partial load, premixed full load, and primary load) to determine the amount of heat transfer from the gas to the liner by means of computational fluid dynamics (CFD). The numerical predictions have been compared to experimental measurements of metal temperature showing a good agreement between CFD and experiments.

Combustor liner of present gas turbine engines is subjected to high thermal loads as it surrounds high temperature combustion reactants and is hence facing the related radiative load. This generally produces high thermal stress levels on the liner, strongly limiting its life expectations and making it one of the most critical components of the entire engine. The reliable prediction of such thermal loads is hence a crucial aspect to increase the flame tube life span and to ensure safe operations. The present study aims at investigating the aero-thermal behavior of a GE DLN1 (Dry Low NOx) class flame tube and in particular at evaluating working metal temperatures of the liner in relation to the flow and heat transfer state inside and outside the combustion chamber. Three different operating conditions have been accounted for (i.e. Lean-Lean partial load, Premixed full load and Primary load) to determine the amount of heat transfer from the gas to the liner by means of CFD. The numerical predictions have been compared to experimental measurements of metal temperature showing a good agreement between CFD and experiments.

The transition-piece of a gas turbine engine is subjected to high thermal loads as it collects high temperature combustion products from the gas generator to a turbine. This generally produces high thermal stress levels in the casing of the transition piece, strongly limiting its life expectations and making it one of the most critical components of the entire engine. The reliable prediction of such thermal loads is hence a crucial aspect to increase the transition-piece life span and to assure safe operations. The present study aims to investigate the aerothermal behavior of a gas turbine engine transition-piece and in particular to evaluate working temperatures of the casing in relation to the flow and heat transfer situation inside and outside the transition-piece. Typical operating conditions are considered to determine the amount of heat transfer from the gas to the casing by means of computational fluid dynamics (CFD). Both conjugate approach and wall fixed temperature have been considered to compute the heat transfer coefficient (HTC), and more in general, the transition-piece thermal loads. Finally a discussion on the most convenient HTC expression is provided.

The transition-piece of a gas turbine engine is subjected to high thermal loads as it collects high temperature combustion products from the gas generator to a turbine. This generally produces high thermal stress levels in the casing of the transition piece, strongly limiting its life expectations and making it one of the most critical components of the entire engine. The reliable prediction of such thermal loads is hence a crucial aspect to increase the transition-piece life span and to assure safe operations. The present study aims to investigate the aero-thermal behaviour of a gas turbine engine transition-piece and in particular to evaluate working temperatures of the casing in relation to the flow and heat transfer situation inside and outside the transition-piece. Typical operating conditions are considered to determine the amount of heat transfer from the gas to the casing by means of CFD. Both conjugate approach and wall fixed temperature have been considered to compute the heat transfer coefficient, and more in general, the transition-piece thermal loads. Finally a discussion on the most convenient heat transfer coefficient expression is provided.