Load Profiles Clustering and Knowledge Extraction to Assess Actual Usage of Telecommunication Sites

Deep awareness of a particular industry sector represents a fundamental starting point for its energy efficiency enhancement. In this perspective, a huge amount of industrial facilities' energy measurements are collected thanks to the widespread usage of monitoring systems and Internet-of-Things infrastructures. In this context, data mining techniques allows an effective exploitation of data for knowledge extraction to automatically analyse such enormous amount of data. This paper investigates a large data set including real telecommunication sites' aggregate electrical demand provided by the largest telecommunication service provider in Italy. The goal is the assessment of the actual usage category of telecommunication sites, aiming at supporting the facility management of the company and the energy knowledge discovery of each site category. A novel methodology is proposed that includes i) a proper normalisation method focused on energy Key Performance Indicators for telecommunication network energy management, ii) a time series decomposition tool to extract trends and periodical fluctuation of telecommunication sites' aggregated electric demand, and iii) the application of a k-Means clustering algorithm to assess sites' actual usage. The proposed methodology results in accurate outcomes, which witness the potential for practical application and discloses opportunities for further developments

A Low Rivaroxaban Plasma Level May Indicate Anticoagulation Undertreatment

Few reports have been published on the correlation between plasma concentrations of rivaroxaban and clinical outcome in patients who have experienced venous thromboembolism. This article describes the case of a 44-year-old woman who experienced deep vein thrombosis during anticoagulation therapy with rivaroxaban, with evidence of repeated low plasma levels of the drug. We postulate that the determination of plasma rivaroxaban anti-Xa activity can be useful in the evaluation of anticoagulation therapy in selected cases

Clinical Outcomes and Joint Stability after Lateralized Reverse Total Shoulder Arthroplasty with and without Subscapularis Repair: A Meta-Analysis

Introduction: Subscapularis tendon repair in reverse total shoulder arthroplasty represents a potentially modifiable risk factor for dislocation, and its role continues to be debated. The purpose of the present meta-analysis was to compare the outcomes of the primary lateralized RSAs with and without subscapularis repair in terms of range of motion, clinical outcomes, dislocations, and complications rate. Materials and Methods: A systematic literature search in MEDLINE (Pubmed), Embase, and the Cochrane Central Register of Controlled Trials database was carried up to December 2020. A data extraction form was developed to collect select data from the included studies. The methodological quality was assessed using a Methodological Index for Nonrandomized Studies (MINORS) score. Statistical analysis was performed with Review Manager (Version 5.4, The Cochrane Collaboration). Results: A total of four comparative studies involving 978 patients were included. In the pooled analysis, the reinsertion of the subscapularis yielded better functional outcomes in terms of the constant (P < 0.00001) and ASES (P = 0.002) scores. The forward elevation, external rotation at 0°, internal rotation, and dislocation rates were comparable between the two groups (P = n.s.), while statistically increased abduction was observed in those patients who did not have their subscapularis repaired (P < 0.00001). Conclusion: The results of the present findings suggest that it seems reasonable to reinsert the subscapularis whenever it is present, in good tissue conditions, and with no evidence of fatty degeneration of its muscle belly. Level of evidence: Level III meta-analysi

A Machine Learning Based Methodology for Load Profiles Clustering and Non-Residential Buildings Benchmarking

Buildings benchmarking based on their electric profiles is a fundamental step to identify, evaluate and then possibly implement energy efficiency oriented actions. Indeed, benchmarking enables comparison among peer buildings or industrial sites and the identification of reference cases, either efficient and inefficient ones. In this regard, temporal data clustering is an effective and widely applicable benchmarking tool. In this work, we propose a novel Machine Learning based methodology, taking advantage of two fundamental tools, namely a decomposition algorithm and a clustering one. Several clustering algorithms have been tested to identify k-Means as the most suitable one. The proposed methodology includes the evaluation of energy Key Performance Indicators for effective analysis and comparison of buildings. The proposed framework has been tested on a real-world case study including around 2000 non-residential buildings. The classification of buildings based on K-Means achieved an accuracy of 99.7% with respect to their usage category. Furthermore, reference Key Performance Indicator values for each cluster are obtained and discussed to understand buildings' energy behaviour and possible reasons for inefficiencies

Impact of acute changes of left ventricular contractility on the transvalvular impedance: validation study by pressure-volume loop analysis in healthy pigs

BACKGROUND: The real-time and continuous assessment of left ventricular (LV) myocardial contractility through an implanted device is a clinically relevant goal. Transvalvular impedance (TVI) is an impedentiometric signal detected in the right cardiac chambers that changes during stroke volume fluctuations in patients. However, the relationship between TVI signals and LV contractility has not been proven. We investigated whether TVI signals predict changes of LV inotropic state during clinically relevant loading and inotropic conditions in swine normal heart. METHODS: The assessment of RVTVI signals was performed in anesthetized adult healthy anesthetized pigs (n = 6) instrumented for measurement of aortic and LV pressure, dP/dtmax and LV volumes. Myocardial contractility was assessed with the slope (Ees) of the LV end systolic pressure-volume relationship. Effective arterial elastance (Ea) and stroke work (SW) were determined from the LV pressure-volume loops. Pigs were studied at rest (baseline), after transient mechanical preload reduction and afterload increase, after 10-min of low dose dobutamine infusion (LDDS, 10 ug/kg/min, i.v), and esmolol administration (ESMO, bolus of 500 µg and continuous infusion of 100 µg·kg-1·min-1). RESULTS: We detected a significant relationship between ESTVI and dP/dtmax during LDDS and ESMO administration. In addition, the fluctuations of ESTVI were significantly related to changes of the Ees during afterload increase, LDDS and ESMO infusion. CONCLUSIONS: ESTVI signal detected in right cardiac chamber is significantly affected by acute changes in cardiac mechanical activity and is able to predict acute changes of LV inotropic state in normal heart

Multiple Sclerosis disease: a computational approach for investigating its drug interactions

Multiple Sclerosis (MS) is a chronic and potentially highly disabling disease that can cause permanent damage and deterioration of the central nervous system. In Europe it is the leading cause of non-traumatic disabilities in young adults, since more than 700,000 EU people suffer from MS. Although recent studies on MS pathophysiology have been provided, MS remains a challenging disease. In this context, thanks to recent advances in software and hardware technologies, computational models and computer simulations are becoming appealing research tools to support scientists in the study of such disease. Thus, motivated by this consideration we propose in this paper a new model to study the evolution of MS in silico, and the effects of the administration of Daclizumab drug, taking into account also spatiality and temporality of the involved phenomena. Moreover, we show how the intrinsic symmetries of the system can be exploited to drastically reduce the complexity of its analysis.Comment: Submitted to CIBB 2019 post proceedings - LNC

Preoperative Fibrinogen-to-Albumin Ratio as Potential Predictor of Bladder Cancer: A Monocentric Retrospective Study

: Background and objective: Fibrinogen and albumin are two proteins widely used, singularly and in combination, in cancer patients as biomarkers of nutritional status, inflammation and disease prognosis. The aim of our study was to investigate the preoperative fibrinogen-to-albumin ratio (FAR) as a preoperative predictor of malignancy as well as advanced grade in patients with bladder cancer. Materials and Methods: A retrospective analysis of patients who underwent TURBT at our institution between 2017 and 2021 was conducted. FAR was obtained from preoperative venous blood samples performed within 30 days from scheduled surgery and was analyzed in relation to histopathological reports, as was the presence of malignancy. Statistical analysis was performed using a Kruskal−Wallis Test, and univariate and multivariate logistic regression analysis, assuming p < 0.05 to be statistically significant. Results: A total of 510 patients were included in the study (81% male, 19% female), with a mean age of 71.66 ± 11.64 years. The mean FAR was significantly higher in patients with low-grade and high-grade bladder cancer, with values of 80.71 ± 23.15 and 84.93 ± 29.96, respectively, compared to patients without cancer (75.50 ± 24.81) (p = 0.006). Univariate regression analysis reported FAR to be irrelevant when considered as a continuous variable (OR = 1.013, 95% CI = 1.004−1.022; p = 0.004), while when considered as a categorical variable, utilizing a cut-off set at 76, OR was 2.062 (95% CI = 1.378−3.084; p < 0.0001). Nevertheless, the data were not confirmed in the multivariate analysis. Conclusions: Elevated preoperative FAR is a potential predictor of malignancy as well as advanced grade in patients with bladder cancer. Further data are required to suggest a promising role of the fibrinogen-to-albumin ratio as a diagnostic biomarker for bladder tumors

DIGITAL INVESTIGATION OF LAMNIFORM SHARK VERTEBRAE FROM THE SIBILLINI MTS. (NORTHERN APENNINES, ITALY)

During the sampling of a stratigraphic section along the shore of the Fiastra Lake (Carg Project - Sheet 313 “Camerino” of the Geological Map of Italy at 1:50 000 scale), a small rock boulder with partially exposed bony material was discovered at the base of a small cliff at the northern termination of the Sibillini Mts. In this area, the classical facies of Umbria-Marche stratigraphic succession are well exposed. The Oligocene-Miocene portion of the succession is represented by the ~200 m-thick Scaglia Cinerea Formation, passing upwards to the ~100 m-thick Bisciaro Formation. The microfossil assemblage has allowed the specimen to be constrained to the lower Burdigalian. The skeletal remains were examined using a CT-SCAN, a non-invasive method that has proven to be highly performing. The analysis revealed some articulated vertebrae, deformed by lithostatic compaction, which are attributed to a shark of the Order Lamniformes. Subsequently, the vertebrae were digitally isolated, extracted from the surrounding matrix, and rendered into three-dimensional prints. Through digital retro-deformation, the body length of the lamniform shark was estimated to be approximately 4 metres. Further considerations on the vertebrae allowed us to infer that the studied shark had similarities to either Isurus oxyrinchus Rafinesque, 1810 or Carcharodon carcharias Linnaeus, 1758. The development of a dead-fall microbial community likely facilitated the preservation of the vertebrae. The studied specimen represents the first occurrence of a lamniform shark in the Lower Miocene of the Umbria-Marche Domain and represents one of the very rare recorded occurrences of lamniforms from the Lower Miocene of Italy