Selection of features based on electric power quantities for non-intrusive load monitoring

Non-intrusive load monitoring (NILM) is a process of determining the operating states and the energy consumption of single electric devices using a single energy meter providing aggregate load measurements. Due to the large spread of power electronic-based and nonlinear devices connected to the network, the time signals of both voltage and current are typically non-sinusoidal. The effectiveness of a NILM algorithm strongly depends on determining a set of discriminative features. In this paper, voltage and current signals were combined to define, according to the definitions provided in Standard IEEE 1459, different power quantities, that can be used to distinguish different types of appliance. Multi-layer perceptron (MLP) classifiers were trained to solve the appliance detection problem as a multi-class event classification problem, varying the electric features in input. This allowed to select an optimal set of features guarantying good classification performance in identifying typical electric loads

Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation

Computational Fluid Dynamics (CFD) simulations of blood flow are widely used to compute a variety of hemodynamic indicators such as velocity, time-varying wall shear stress, pressure drop, and energy losses. One of the major advances of this approach is that it is non-invasive. The accuracy of the cardiovascular simulations depends directly on the level of certainty on input parameters due to the modelling assumptions or computational settings. Physiologically suitable boundary conditions at the inlet and outlet of the computational domain are needed to perform a patient-specific CFD analysis. These conditions are often affected by uncertainties, whose impact can be quantified through a stochastic approach. A methodology based on a full propagation of the uncertainty from clinical data to model results is proposed here. It was possible to estimate the confidence associated with model predictions, differently than by deterministic simulations. We evaluated the effect of using three-element Windkessel models as the outflow boundary conditions of a patient-specific aortic coarctation model. A parameter was introduced to calibrate the resistances of the Windkessel model at the outlets. The generalized Polynomial Chaos method was adopted to perform the stochastic analysis, starting from a few deterministic simulations. Our results show that the uncertainty of the input parameter gave a remarkable variability on the volume flow rate waveform at the systolic peak simulating the conditions before the treatment. The same uncertain parameter had a slighter effect on other quantities of interest, such as the pressure gradient. Furthermore, the results highlight that the fine-tuning of Windkessel resistances is not necessary to simulate the post-stenting scenario

A Proof of Concept of a Non-Invasive Image-Based Material Characterization Method for Enhanced Patient-Specific Computational Modeling

PURPOSE: Computational models of cardiovascular structures rely on their accurate mechanical characterization. A validated method able to infer the material properties of patient-specific large vessels is currently lacking. The aim of the present study is to present a technique starting from the flow-area (QA) method to retrieve basic material properties from magnetic resonance (MR) imaging. METHODS: The proposed method was developed and tested, first, in silico and then in vitro. In silico, fluid-structure interaction (FSI) simulations of flow within a deformable pipe were run with varying elastic modules (E) between 0.5 and 32 MPa. The proposed QA-based formulation was assessed and modified based on the FSI results to retrieve E values. In vitro, a compliant phantom connected to a mock circulatory system was tested within MR scanning. Images of the phantom were acquired and post-processed according to the modified formulation to infer E of the phantom. Results of in vitro imaging assessment were verified against standard tensile test. RESULTS: In silico results from FSI simulations were used to derive the correction factor to the original formulation based on the geometrical and material characteristics. In vitro, the modified QA-based equation estimated an average E = 0.51 MPa, 2% different from the E derived from tensile tests (i.e. E = 0.50 MPa). CONCLUSION: This study presented promising results of an indirect and non-invasive method to establish elastic properties from solely MR images data, suggesting a potential image-based mechanical characterization of large blood vessels

Cytokeratin 20-positive hepatocellular carcinoma

The differential diagnosis between hepatocellular carcinoma (HCC), cholangiocarcinoma (CC) and metastatic colorectal adenocarcinoma (MCA) may be difficult when only based on morphology. For this purpose immunohistochemical analyses are often required, utilizing antibodies directed against CK8-18, Hep-Par1, glypican 3, CK7, CK19, CK20. Here we report a case of a 65-year-old man who presented with a clinical picture of decompensated cirrhosis. Ultrasonography revealed two nodular areas in the right liver lobe. Liver needle biopsy revealed micro-macronodular cirrhosis associated with HCC with trabecular and pseudoglandular patterns. Immunohistochemically, tumour cells were diffusely positive for CK8-18 and also diffusely immunostained by glypican 3 and Hep-Par1. Interestingly, a diffuse and strong staining for CK20 was detected in the vast majority of tumor cells, particularly in the areas showing a pseudo-glandular pattern. No immunostaining for CK7 and CK19 was found in the tumor cells. The tumor behaved aggressively, with a rapid diffusion to the whole liver. The patient died from the disease few months after presentation. These findings underline that the interpretation of the expression of CK20 alone in the differential diagnosis among HCC, CC and MCA should be done with caution because a diffuse immunoreactivity for CK20 alone may not rule out the diagnosis of HCC

Infectious agents including COVID-19 and the involvement of blood coagulation and fibrinolysis. A narrative review

Platelets, blood coagulation along with fibrinolysis are greatly involved in the pathophysiology of infectious diseases induced by bacteria, parasites and virus. This phenomenon is not surprising since both the innate immunity and the hemostatic systems are two ancestral mechanisms which closely cooperate favoring host's defense against foreign invaders. However, the excessive response of these systems may be dangerous for the host itself

Immunoreactivity of thymosin beta 4 in human foetal and adult genitourinary tract

Thymosin beta 4 (Tβ4) is a member of the beta-thymosins family, a family of peptides playing essential roles in many cellular functions. Our recent studies suggested Tβ4 plays a key role in the development of human salivary glands and the gastrointestinal tract. The aim of this study was to analyse the presence of Tβ4 in the human adult and foetal genitourinary tract. Immunolocalization of Tβ4 was studied in autoptic samples of kidney, bladder, uterus, ovary, testicle and prostate obtained from four human foetuses and four adults. Presence of the peptide was observed in cells of different origin: in surface epithelium, in gland epithelial cells and in the interstitial cells. Tβ4 was mainly found in adult and foetal bladder in the transitional epithelial cells; in the adult endometrium, glands and stromal cells were immunoreactive for the peptide; Tβ4 was mainly localized in the glands of foetal prostate while, in the adults a weak Tβ4 reactivity was restricted to the stroma. In adult and foetal kidney, Tβ4 reactivity was restricted to ducts and tubules with completely spared glomeruli; a weak positivity was observed in adult and foetal oocytes; immunoreactivity was mainly localized in the interstitial cells of foetal and adult testis. In this study, we confirm that Tβ4 could play a relevant role during human development, even in the genitourinary tract, and reveal that immunoreactivity for this peptide may change during postnatal and adult life

Pathology of autoimmune hepatitis

Autoimmune hepatitis (AIH) is a relatively rare non-resolving chronic liver disease, which mainly affects women. It is characterized by hypergammaglobulinemia, circulating autoantibodies, interface hepatitis on liver histology and a favourable response to immunosuppression. The putative mechanism for the development of autoimmune hepatitis is thought to be the interaction between genetic predisposition, environmental triggers and failure of the native immune system. AIH still remains a major diagnostic and therapeutic challenge, mainly because it is a very heterogeneous disease. Prompt and timely diagnosis is crucial since, if left untreated, AIH has a high mortality rate. Histological demonstration of hepatitis is required for the diagnosis of AIH and, therefore, liver biopsy is mandatory in the initial diagnostic work-up, before treatment. In this review, we summarize the histological features of AIH with the main aim of highlighting the most important clinical-pathological hallmarks useful in the routine diagnostic practice

eXplainable artificial intelligence applied to algorithms for disruption prediction in tokamak devices

Introduction: This work explores the use of eXplainable artificial intelligence (XAI) to analyze a convolutional neural network (CNN) trained for disruption prediction in tokamak devices and fed with inputs composed of different physical quantities.Methods: This work focuses on a reduced dataset containing disruptions that follow patterns which are distinguishable based on their impact on the electron temperature profile. Our objective is to demonstrate that the CNN, without explicit training for these specific mechanisms, has implicitly learned to differentiate between these two disruption paths. With this purpose, two XAI algorithms have been implemented: occlusion and saliency maps.Results: The main outcome of this paper comes from the temperature profile analysis, which evaluates whether the CNN prioritizes the outer and inner regions.Discussion: The result of this investigation reveals a consistent shift in the CNN's output sensitivity depending on whether the inner or outer part of the temperature profile is perturbed, reflecting the underlying physical phenomena occurring in the plasma