The layered structure of company share networks

We present a framework for the analysis of corporate governance problems using network science and graph algorithms on ownership networks. In such networks, nodes model companies/shareholders and edges model shares owned. Inspired by the widespread pyramidal organization of corporate groups of companies, we model ownership networks as layered graphs, and exploit the layered structure to design feasible and efficient solutions to three key problems of corporate governance. The first one is the long-standing problem of computing direct and indirect ownership (integrated ownership problem). The other two problems are introduced here: computing direct and indirect dividends (dividend problem), and computing the group of companies controlled by a parent shareholder (corporate group problem). We conduct an extensive empirical analysis of the Italian ownership network, which, with its 3.9M nodes, is 30× the largest network studied so far

Rib Cage Deformities Alter Respiratory Muscle Action and Chest Wall Function in Patients with Severe Osteogenesis Imperfecta

Osteogenesis imperfecta (OI) is an inherited connective tissue disorder characterized by bone fragility, multiple fractures and significant chest wall deformities. Cardiopulmonary insufficiency is the leading cause of death in these patients.Seven patients with severe OI type III, 15 with moderate OI type IV and 26 healthy subjects were studied. In addition to standard spirometry, rib cage geometry, breathing pattern and regional chest wall volume changes at rest in seated and supine position were assessed by opto-electronic plethysmography to investigate if structural modifications of the rib cage in OI have consequences on ventilatory pattern. One-way or two-way analysis of variance was performed to compare the results between the three groups and the two postures. compared to predicted values, on condition that updated reference equations are considered. In both positions, ventilation was lower in OI patients than control because of lower tidal volume (p<0.01). In contrast to OI type IV patients, whose chest wall geometry and function was normal, OI type III patients were characterized by reduced (p<0.01) angle at the sternum (pectus carinatum), paradoxical inspiratory inward motion of the pulmonary rib cage, significant thoraco-abdominal asynchronies and rib cage distortions in supine position (p<0.001).In conclusion, the restrictive respiratory pattern of Osteogenesis Imperfecta is closely related to the severity of the disease and to the sternal deformities. Pectus carinatum characterizes OI type III patients and alters respiratory muscles coordination, leading to chest wall and rib cage distortions and an inefficient ventilator pattern. OI type IV is characterized by lower alterations in the respiratory function. These findings suggest that functional assessment and treatment of OI should be differentiated in these two forms of the disease

Structured reporting for fibrosing lung disease: a model shared by radiologist and pulmonologist

Objectives: To apply the Delphi exercise with iterative involvement of radiologists and pulmonologists with the aim of defining a structured reporting template for high-resolution computed tomography (HRCT) of patients with fibrosing lung disease (FLD). Methods: The writing committee selected the HRCT criteria\ue2\u80\u94the Delphi items\ue2\u80\u94for rating from both radiology panelists (RP) and pulmonology panelists (PP). The Delphi items were first rated by RPs as \ue2\u80\u9cessential\ue2\u80\u9d, \ue2\u80\u9coptional\ue2\u80\u9d, or \ue2\u80\u9cnot relevant\ue2\u80\u9d. The items rated \ue2\u80\u9cessential\ue2\u80\u9d by &lt; 80% of the RP were selected for the PP rating. The format of reporting was rated by both RP and PP. Results: A total of 42 RPs and 12 PPs participated to the survey. In both Delphi round 1 and 2, 10/27 (37.7%) items were rated \ue2\u80\u9cessential\ue2\u80\u9d by more than 80% of RP. The remaining 17/27 (63.3%) items were rated by the PP in round 3, with 2/17 items (11.7%) rated \ue2\u80\u9cessential\ue2\u80\u9d by the PP. PP proposed additional items for conclusion domain, which were rated by RPs in the fourth round. Poor consensus was observed for the format of reporting. Conclusions: This study provides a template for structured report of FLD that features essential items as agreed by expert thoracic radiologists and pulmonologists

Preliminary Evidence of “Other-Race Effect”-Like Behavior Induced by Cathodal-tDCS over the Right Occipital Cortex, in the Absence of Overall Effects on Face/Object Processing

Neuromodulation techniques such as tDCS have provided important insight into the neurophysiological mechanisms that mediate cognition. Albeit anodal tDCS (a-tDCS) often enhances cognitive skills, the role of cathodal tDCS (c-tDCS) in visual cognition is largely unexplored and inconclusive. Here, in a single-blind, sham-controlled study, we investigated the offline effects of 1.5 mA c-tDCS over the right occipital cortex of 86 participants on four tasks assessing perception and memory of both faces and objects. Results demonstrated that c-tDCS does not overall affect performance on the four tasks. However, post-hoc exploratory analysis on participants' race (Caucasian vs. non-Caucasians), showed a “face-specific” performance decrease (≈10%) in non-Caucasian participants only. This preliminary evidence suggests that c-tDCS can induce “other-race effect (ORE)-like” behavior in non-Caucasian participants that did not show any ORE before stimulation (and in case of sham stimulation). Our results add relevant information about the breadth of cognitive processes and visual stimuli that can be modulated by c-tDCS, about the design of effective neuromodulation protocols, and have important implications for the potential neurophysiological bases of ORE

XQuake: an XML-based Knowledge Discovery Environment

Data mining is the analysis of large volumes of data to find unsuspected relationships and to summarize the data in novel ways, that are both understandable and useful to the data owner. Nowadays, the rapid growth of semi-structured sources raises the need of designing and implementing environments for data mining out of XML data. On the basis of the principles of the inductive database theory, this dissertation presents a flexible data mining system with capabilities of obtaining, maintaining, representing and querying induced, deduced and prior knowledge, stored inside native XML databases. In particular, it summarizes our three-years experience in the design and development of XQuake, a query language that extends XQuery to support mining primitives. Features of the language are an intuitive syntax, a good expressiveness, and the capability of dealing uniformly with data mining entities. A detail of its implementation and the evaluation of its performance are also given

Discrimination data analysis: A multi-disciplinary bibliography

Discrimination data analysis has been investigated for the last fifty years in a large body of social, legal, and economic studies. Recently, discrimination discovery and prevention has become a blooming research topic in the knowledge discovery community. This chapter provides a multi-disciplinary annotated bibliography of the literature on discrimination data analysis, with the intended objective to provide a common basis to researchers from a multi-disciplinary perspective.We cover legal, sociological, economic and computer science references

Programming the KDD process using XQuery

XQuake is a language and system for programming data mining processes over native XML databases in the spirit of inductive databases. It extends XQuery to support KDD tasks. This paper focuses on the features required in the definition of the steps of the mining process. The main objective is to show the expressiveness of the language in handling mining operations as an extension of basic XQuery expressions. To this purpose, the paper offers an extended application in the field of analyzing web logs.<br /

XML Data Mining

XML is the standard language for representing semi-structured data. With the spreading of XML sources, mining XML data can be an important objective in the near future. This paper presents a project focussed on designing a general-purpose query language in support of mining XML data. In our framework, raw data, mining models and domain knowledge are represented by way of XML documents and stored inside XML native databases. Data mining tasks are expressed in an extension of XQuery. Special attention is given to the frequent pattern discovery problem, and a way of exploiting domain-dependent optimizations and efficient data structures as deeper as possible in the extraction process is presented. We report the results of a first bunch of experiments, showing that a good trade-off between expressiveness and efficiency in XML data mining is not a chimera