On the resolution of extremal and constant scalar curvature Kaehler orbifolds

In this paper we give sufficient conditions on a compact orbifold with an extremal Kaehler metric to admit a resolution with an extremal Kaehler metric. We also complete the Kaehler constant scalar curvature case.Comment: This paper, together with the next one by the same authors, contains more general results than arxiv.org/abs/1402.5919 (by the same authors), which will then be withdraw

Corporate Social Responsibility Disclosure in Italy: An Analysis of the Last Years

Corporate Social Responsibility Disclosure (CSRD) is the process of communicating the social, ethical and environmental effects of organizations’ economic actions. It is a formal commitment to inform and involve stakeholders with an adequate flow of communication through suitable channels, focusing on relevant content. The aim is to study voluntary disclosure implemented by Italian listed companies in the last 9 years (2008-2016). The empirical survey covers data and information on 165 companies. We have analysed: 1) the extent of CSRD in Italy; 2) the characteristics of voluntary disclosure in terms of type of report published and guidelines or standards followed; 3) the main differences between the industrial sectors about the publication of non-financial reports and the types of report used. Our findings show a significant improvement in the practice of voluntary disclosure of Italian listed companies and a key role of industry in decisions regarding the quantity and quality of non-financial disclosure. The value of this research concern in the wide (in time, through the last nine years, and in space, through the different industries) point of view through which is investigated the phenomenon of CSRD in Italy before the shift from a voluntary to a legislative perspective

Multiparametric flow cytometry to characterize vaccine-induced polyfunctional T cell responses and T cell/NK cell exhaustion and memory phenotypes in mouse immuno-oncology models

Suitable methods to assess in vivo immunogenicity and therapeutic efficacy of cancer vaccines in preclinical cancer models are critical to overcome current limitations of cancer vaccines and enhance the clinical applicability of this promising immunotherapeutic strategy. In particular, availability of methods allowing the characterization of T cell responses to endogenous tumor antigens is required to assess vaccine potency and improve the antigen formulation. Moreover, multiparametric assays to deeply characterize tumor-induced and therapy-induced immune modulation are relevant to design mechanism-based combination immunotherapies. Here we describe a versatile multiparametric flow cytometry method to assess the polyfunctionality of tumor antigen-specific CD4+ and CD8+ T cell responses based on their production of multiple cytokines after short-term ex vivo restimulation with relevant tumor epitopes of the most common mouse strains. We also report the development and application of two 21-color flow cytometry panels allowing a comprehensive characterization of T cell and natural killer cell exhaustion and memory phenotypes in mice with a particular focus on preclinical cancer models

Towards Explainability in Knowledge Enhanced Neural Networks

Research on Deep Learning has achieved remarkable results in recent years, mainly thanks to the computing power of modern computers and the increasing availability of large data sets. However, deep neural models are universally considered black boxes: they employ sub-symbolic representations of knowledge, which are inherently opaque to human beings trying to derive explanations. In this work, we first give a survey on the research field of Explainable AI, providing more rigorous definitions of the concepts of interpretability and explainability. We then delve deeper in the research field of Neural Symbolic Integration, which tackles the task of integrating the statistical learning power of machine learning with the symbolic and abstract world of logic. Specifically, we analyze Knowledge Enhanced Neural Networks, a special kind of residual layer for neural architectures which makes it possible to inject symbolic logical knowledge inside a neural network. We describe and analyze experimental results on relational data on the task of collective classification, and study how KENN is able to automatically learn the importance of logical rules from the training data. We finally review explainability methods for KENN, proposing ways to extract explanations for the predictions provided by the model

Tecniche di machine learning per la diagnosi della malaria

La malaria importata è ancora un grave problema anche in paesi non endemici. La prima difficoltà da affrontare nella diagnosi della malaria è la distinzione tra malaria severa e non severa. Questa tesi analizza il problema della diagnosi della malaria a partire dai dati forniti dall'Ospedale Lazzaro Spallanzani di Roma, relativi a 259 pazienti diagnosticati con malaria. L'obiettivo primario di questo studio è la costruzione di classificatori tramite tecniche di machine learning, che siano in grado di diagnosticare correttamente futuri pazienti con malaria. Per rendere possibile un'interpretazione medica dei risultati, sono anche state applicate tecniche di feature selection e clustering. Così facendo, sono stati selezionati i fattori medici più rilevanti sia ai fini della diagnosi, che per la prevenzione dei casi più gravi

Plasticity of type I interferon-mediated responses in cancer therapy: from anti-tumor immunity to resistance

The efficacy of several therapeutic strategies against cancer, including cytotoxic drugs, radiotherapy, targeted immunotherapies and oncolytic viruses, depend on intact type I interferon (IFN) signaling for the promotion of both direct (tumor cell inhibition) and indirect (anti-tumor immune responses) effects. Malfunctions of this pathway in tumor cells or in immune cells may be responsible for the lack of response or resistance. Although type I IFN signaling is required to trigger anti-tumor immunity, emerging evidence indicates that chronic activation of type I IFN pathway may be involved in mediating resistance to different cancer treatments. The plastic and dynamic features of type I IFN responses should be carefully considered to fully exploit the therapeutic potential of strategies targeting IFN signaling. Here, we review available evidence supporting the involvement of type I IFN signaling in mediating resistance to various cancer therapies and highlight the most promising modalities that are being tested to overcome resistance

On the Resolution of Extremal and Constant Scalar Curvature Kähler Orbifolds

Given a compact Kähler orbifold with an extremal metric, whose singularities admit a local ALE Kähler scalar-flat resolution, we prove that there exists a Kähler desingularization with an extremal metric. Moreover we study the same problem for constant scalar curvature metrics and prove some partial results

On the Kummer construction for Kcsc metrics

Given a compact constant scalar curvature Kähler orbifold, with nontrivial holomorphic vector fields, whose singularities admit a local ALE Kähler Ricci-flat resolution, we find sufficient conditions on the position of the singular points to ensure the existence of a global constant scalar curvature Kähler desingularization. We also give complete proofs of a number of analytic results which have been used in this context by various authors. A series of explicit examples is discussed

Corporate Social Responsibility Disclosure in Italy: An Analysis of the Last Years

Corporate Social Responsibility Disclosure (CSRD) is the process of communicating the social, ethical and environmental effects of organizations’ economic actions. It is a formal commitment to inform and involve stakeholders with an adequate flow of communication through suitable channels, focusing on relevant content. The aim is to study voluntary disclosure implemented by Italian listed companies in the last 9 years (2008-2016). The empirical survey covers data and information on 165 companies. We have analysed: 1) the extent of CSRD in Italy; 2) the characteristics of voluntary disclosure in terms of type of report published and guidelines or standards followed; 3) the main differences between the industrial sectors about the publication of non-financial reports and the types of report used. Our findings show a significant improvement in the practice of voluntary disclosure of Italian listed companies and a key role of industry in decisions regarding the quantity and quality of non-financial disclosure. The value of this research concern in the wide (in time, through the last nine years, and in space, through the different industries) point of view through which is investigated the phenomenon of CSRD in Italy before the shift from a voluntary to a legislative perspective