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Religion and innovation
No full textIn earlier work (Bénabou, Ticchi and Vindigni 2013) we uncovered a robust negative
association between religiosity and patents per capita, holding across countries as well as
US states, with and without controls. In this paper we turn to the individual level, examining
the relationship between religiosity and a broad set of pro‐ or anti‐innovation attitudes in all
five waves of the World Values Survey (1980 to 2005). We thus relate eleven indicators of
individual openness to innovation, broadly defined (e.g., attitudes toward science and
technology, new versus old ideas, change, risk taking, personal agency, imagination and
independence in children) to five different measures of religiosity, including beliefs and
attendance. We control for all standard socio‐demographics as well as country, year and
denomination fixed effects. Across the fifty‐two estimated specifications, greater religiosity
is almost uniformly and very significantly associated to less favorable views of innovation
DebtRank: A microscopic foundation for shock propagation
No full textThe DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical "microscopic" theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of leverages the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least a bank will default. We apply this results to a network of roughly 200 among the largest European banks in the period 2008 - 2013. We show that network effects generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis), when we stress the system with a 0.5% shock on external (i.e. non-interbank) assets for all banks
Dictionary learning for unsupervised identification of ischemic territories in CP-BOLD Cardiac MRI at rest
No full textA power and energy procedure in operating photovoltaic systems to quantify the losses according to the causes
No full textRecently, after high feed-in tariffs in Italy, retroactive cuts in the energy payments have generated economic concern about several grid-connected photovoltaic (PV) systems with poor performance. In this paper the proposed procedure suggests some rules for determining the sources of losses and thus minimizing poor performance in the energy production. The on-site
field inspection, the identification of the irradiance sensors, as close as possible the PV system, and the assessment of energy production are three preliminary steps which do not require experimental tests. The fourth step is to test the arrays of PV modules on-site. The fifth step is to test only the PV strings or single modules belonging to arrays with poor performance (e.g., I-V mismatch). The sixth step is to use the thermo-graphic camera and the electroluminescence at the PV-module level. The seventh step is to monitor the DC racks of each inverter or the individual inverter, if equipped with only one Maximum Power Point Tracker (MPPT). Experimental results on real PV systems show the effectiveness of this procedure
Ownership, Taxes and Default
No full textThis paper determines ownership and leverage of two units facing a tax-
bankruptcy trade-o�. Connected units have higher leverage and lower tax burden,
because of internal support through both bailouts and corporate dividends. Owner-
ship adjusts to additional tax provisions. A hierarchical group with a wholly-owned
subsidiary results from Thin Capitalization rules. The presence of corporate divi-
dend taxes generates horizontal groups, or a Special Purpose Vehicle, or a private
equity fund. Combinations of tax provisions contain tax savings, debt and default
in connected units. No bailout provisions, such as the Volcker rule, succeed in
reducing leverage and default
Optimization algorithms for the solution of the frictionless normal contact between rough surfaces
No full textThis paper revisits the fundamental equations for the solution of the frictionless unilateral normal contact problem between a rough rigid surface and a linear elastic half-plane using the boundary element method (BEM). After recasting the resulting Linear Complementarity Problem (LCP) as a convex quadratic program (QP) with nonnegative constraints, different optimization algorithms are compared for its solution: (i) a Greedy method, based on different solvers for the unconstrained linear system (Conjugate Gradient CG, Gauss–Seidel, Cholesky factorization), (ii) a constrained CG algorithm, (iii) the Alternating Direction Method of Multipliers (ADMM), and (iv) the Non-Negative Least Squares (NNLS) algorithm, possibly warm-started by accelerated gradient projection steps or taking advantage of a loading history. The latter method is two orders of magnitude faster than the Greedy CG method and one order of magnitude faster than the constrained CG algorithm. Finally, we propose another type of warm start based on a refined criterion for the identification of the initial trial contact domain that can be used in conjunction with all the previous optimization algorithms. This method, called cascade multi-resolution (CMR), takes advantage of physical considerations regarding the scaling of the contact predictions by changing the surface resolution. The method is very efficient and accurate when applied to real or numerically generated rough surfaces, provided that their power spectral density function is of power-law type, as in case of self-affine fractal surfaces
Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets
No full textThe increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data
Generalized Erdos Numbers for network analysis
No full textIn this paper we consider the concept of `closeness' between nodes in a weighted network that can be defined topologically even in the absence of a metric. The Generalized Erd\H{o}s Numbers (GENs) satisfy a number of desirable properties as a measure of topological closeness when nodes share a finite resource between nodes as they are real-valued and non-local, and can be used to create an asymmetric matrix of connectivities. We show that they can be used to define a personalized measure of the importance of nodes in a network with a natural interpretation that leads to a new global measure of centrality and is highly correlated with Page Rank. The relative asymmetry of the GENs (due to their non-metric definition) is linked also to the asymmetry in the mean first passage time between nodes in a random walk, and we use a linearized form of the GENs to develop a continuum model for `closeness' in spatial networks. As an example of their practicality, we deploy them to characterize the structure of static networks and show how it relates to dynamics on networks in such situations as the spread of an epidemic
Codon Bias Patterns of E.coli's Interacting Proteins
No full textSynonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, CompAI, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for E.coli, comparing CompAI with other widely used indices: tAI, CAI, and Nc. We show that CompAI and tAI capture similar information by being positively correlated with gene conservation, measured by ERI, and essentiality, whereas, CAI and Nc appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of tAI and CompAI with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs). We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in E.coli. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by CompAI and tAI). Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, CompAI turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation
Domain-specific queries and Web search personalization: some investigations
No full textMajor search engines deploy personalized Web results to enhance users’ experience, by showing
them data supposed to be relevant to their interests. Even if this process may bring benefits to
users while browsing, it also raises concerns on the selection of the search results. In particular,
users may be unknowingly trapped by search engines in protective information bubbles, called “filter
bubbles”, which can have the undesired effect of separating users from information that does not
fit their preferences. This paper moves from early results on quantification of personalization over
Google search query results. Inspired by previous works, we have carried out some experiments
consisting of search queries performed by a battery of Google accounts with differently prepared
profiles. Matching query results, we quantify the level of personalization, according to topics of the
queries and the profile of the accounts. This work reports initial results and it is a first step a for more
extensive investigation to measure Web search personalization