Entropy-Based Logic Explanations of Neural Networks

Explainable artificial intelligence has rapidly emerged since lawmakers have started requiring interpretable models for safety-critical domains. Concept-based neural networks have arisen as explainable-by-design methods as they leverage human-understandable symbols (i.e. concepts) to predict class memberships. However, most of these approaches focus on the identification of the most relevant concepts but do not provide concise, formal explanations of how such concepts are leveraged by the classifier to make predictions. In this paper, we propose a novel end-to-end differentiable approach enabling the extraction of logic explanations from neural networks using the formalism of First-Order Logic. The method relies on an entropy-based criterion which automatically identifies the most relevant concepts. We consider four different case studies to demonstrate that: (i) this entropy-based criterion enables the distillation of concise logic explanations in safety-critical domains from clinical data to computer vision; (ii) the proposed approach outperforms state-of-the-art white-box models in terms of classification accuracy and matches black box performances

Entropy-based Logic Explanations of Neural Networks

Explainable artificial intelligence has rapidly emerged since lawmakers have started requiring interpretable models for safety-critical domains. Concept-based neural networks have arisen as explainable-by-design methods as they leverage human-understandable symbols (i.e. concepts) to predict class memberships. However, most of these approaches focus on the identification of the most relevant concepts but do not provide concise, formal explanations of how such concepts are leveraged by the classifier to make predictions. In this paper, we propose a novel end-to-end differentiable approach enabling the extraction of logic explanations from neural networks using the formalism of First-Order Logic. The method relies on an entropy-based criterion which automatically identifies the most relevant concepts. We consider four different case studies to demonstrate that: (i) this entropy-based criterion enables the distillation of concise logic explanations in safety-critical domains from clinical data to computer vision; (ii) the proposed approach outperforms state-of-the-art white-box models in terms of classification accuracy

Entropy-Based Logic Explanations of Neural Networks

Explainable artificial intelligence has rapidly emerged since lawmakers have started requiring interpretable models for safety-critical domains. Concept-based neural networks have arisen as explainable-by-design methods as they leverage human-understandable symbols (i.e. concepts) to predict class memberships. However, most of these approaches focus on the identification of the most relevant concepts but do not provide concise, formal explanations of how such concepts are leveraged by the classifier to make predictions. In this paper, we propose a novel end-to-end differentiable approach enabling the extraction of logic explanations from neural networks using the formalism of First-Order Logic. The method relies on an entropy-based criterion which automatically identifies the most relevant concepts. We consider four different case studies to demonstrate that: (i) this entropy-based criterion enables the distillation of concise logic explanations in safety-critical domains from clinical data to computer vision; (ii) the proposed approach outperforms state-of-the-art white-box models in terms of classification accuracy and matches black box performances

Neuromuscular magnetic stimulation counteracts muscle decline in ALS patients: results of a randomized, double-blind, controlled study

The aim of the study was to verify whether neuromuscular magnetic stimulation (NMMS) improves muscle function in spinal-onset amyotrophic lateral sclerosis (ALS) patients. Twenty-two ALS patients were randomized in two groups to receive, daily for two weeks, NMMS in right or left arm (referred to as real-NMMS, rNMMS), and sham NMMS (sNMMS) in the opposite arm. All the patients underwent a median nerve conduction (compound muscle action potential, CMAP) study and a clinical examination that included a handgrip strength test and an evaluation of upper limb muscle strength by means of the Medical Research Council Muscle Scale (MRC). Muscle biopsy was then performed bilaterally on the flexor carpi radialis muscle to monitor morpho-functional parameters and molecular changes. Patients and physicians who performed examinations were blinded to the side of real intervention. The primary outcome was the change in the muscle strength in upper arms. The secondary outcomes were the change from baseline in the CMAP amplitudes, in the nicotinic ACh currents, in the expression levels of a selected panel of genes involved in muscle growth and atrophy, and in histomorphometric parameters of ALS muscle fibers. The Repeated Measures (RM) ANOVA with a Greenhouse-Geisser correction (sphericity not assumed) showed a significant effect [F(3, 63) = 5.907, p < 0.01] of rNMMS on MRC scale at the flexor carpi radialis muscle, thus demonstrating that the rNMMS significantly improves muscle strength in flexor muscles in the forearm. Secondary outcomes showed that the improvement observed in rNMMS-treated muscles was associated to counteracting muscle atrophy, down-modulating the proteolysis, and increasing the efficacy of nicotinic ACh receptors (AChRs). We did not observe any significant difference in pre- and post-stimulation CMAP amplitudes, evoked by median nerve stimulation. This suggests that the improvement in muscle strength observed in the stimulated arm is unlikely related to reinnervation. The real and sham treatments were well tolerated without evident side effects. Although promising, this is a proof of concept study, without an immediate clinical translation, that requires further clinical validation

Increased homocysteine and lipoprotein(a) levels highlight systemic atherosclerotic burden in patients with a history of acute coronary syndromes

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insights into bedrock paleomorphology and linear dynamic soil properties of the cassino intermontane basin central italy

Abstract Seismic amplifications are dictated by the depth of the bedrock and the stratigraphy and dynamic properties of the soil deposits. Quantifying these properties, together with their uncertainty, is a necessary task to perform a reliable assessment of the seismic risk at an urban scale. In this paper, a multidisciplinary analysis is presented, where information of different nature is combined. Borehole logs, geophysical, geological and geotechnical surveys are interpreted with the aid of analytical, numerical and geostatistical techniques to characterise the complex shape of the bedrock and the linear dynamic properties of the sedimentary deposits filling the Cassino basin, a Quaternary intermontane basin located in central Italy. The regional and local seismic hazard is firstly identified with geological surveys that reveal an active seismogenic fault capable of producing earthquakes with estimated magnitudes up to 6.5. Boreholes reaching depths variable up to a maximum of 180 meters and microtremor measurements, revealing the sharp impedance contrast at the transition between the sedimentary/arenaceous bedrock and the soft Quaternary infilling, are combined to identify the depth of the bedrock and the linear dynamic properties of soil deposits. These are one of the key factors governing the propagation to the ground level of seismic waves, and their assessment represents the first step for the seismic hazard characterisation of the plain

A New Method of Technical Analysis to Optimise the Design of Low Impact Energy Systems for Buildings

Energy consumption for civil constructions represents about 40% of total energy requirements, so it is necessary to achieve the goal of energy savings and the consequent reduction of greenhouse gases emissions. The study in content aims to provide a design methodology enables to identify the best plant configuration for buildings from a technical, economic and environmental point of view. To assess validity of the calculation model, an analysis of an historical building was carried out in combination with two softwares of proven reliability: TRNSYS, used to evaluate the thermal demand of users, and RETScreen, used to estimate the validity of the chosen energy model

31% European InGaP/GaAs/InGaAs Solar Cells for Space Application

We report a triple junction InGaP/GaAs/InGaNAs solar cell with efficiency of ~31% at AM0, 25 °C fabricated using a combined molecular beam epitaxy (MBE) and metal-organic chemical vapour deposition (MOCVD) processes. The prototype cells comprise of InGaNAs (Indium Gallium Nitride Arsenide) bottom junction grown on a GaAs (Gallium Arsenide) substrate by MBE and middle and top junctions deposited by MOCVD. Repeatable cell characteristics and uniform efficiency pattern over 4-inch wafers were obtained. Combining the advantages offered by MBE and MOCVD opens a new perspective for fabrication of high-efficiency space tandem solar cells with three or more junctions. Results of radiation resistance of the sub-cells are also presented and critically evaluated to achieve high efficiency in EOL conditions

Osservatorio Territoriale Droga e Tossicodipendenze. Il fenomeno delle dipendenze nel territorio della ASL MI 2. Anno 2010 - XI Rapporto

Report on the state of legal and illegal substances use in the territory of the Local Healthcare Service-MI 2, Province of Milan.Il Report analizza il fenomeno delle dipendenze nella ASL Milano 2. La descrizione del fenomeno si sviluppa intorno all\u27analisi degli indicatori individuati dall\u27Osservatorio Europeo delle Dipendenze di Lisbona (OEDT): 1-uso di sostanze nella popolazione generale (questo indicatore va a rilevare i comportamenti nei confronti di alcol e sostanze psicoattive da parte della popolazione generale); 2-prevalenza d\u27uso problematico delle sostanze psicoattive; 3-domanda di trattamento degli utilizzatori di sostanze; 4-mortalit? degli utilizzatori di sostanze; 5-malattie infettive. Altri due importanti indicatori che si stanno sviluppando, e che vengono qui illustrati, sono l\u27analisi delle Schede di Dimissione Ospedaliera (SDO) e gli indicatori relativi alle conseguenza sociali dell\u27uso di droghe (criminalit? droga correlata). Inoltre sono state applicate diverse metodologie standard di stima sia per quantificare la quota parte sconosciuta di utilizzatori di sostanze che non afferiscono ai servizi, sia per identificarne alcune caratteristiche