Interlocking directorates and different power forms: An explorative analysis in the Italian context

The purpose of the present paper is twofold. The first is to update the contribution by Drago et al. (2011) about cross-shareholdings and interlocking directorates in Italian listed companies (FTSE MIB) to 31 December 2016 and to reinforce theory of enlarged collusion. The second is to find how interlocking directorates can contribute to understanding the power structure. By using the social network analysis, we map the network structure of interlocking boards and employ centrality measures like degree, eigenvector and betweenness centrality along with the network density and average degree. We interpret eigenvector centrality as a measure of “effective power” of the connections because it can be seen as a weighted sum of not only direct connections but indirect connections, while betweenness centrality as a measure of “potential power” because it is a proxy of the volume of information that passes through the nodes. In this way, we provide a framework for selecting Italian firms with effective and potential power – around whom interactions and processes can be traced and analysed. In addition, we find that the position assumed by the controlling group of the Mediobanca Galaxy is definitely downsized

Social innovation practices: focus on success factors for crowdfunding

This article explores what are the success factor for interaction with platforms of crowdfunding in Italy. Through a Principal Component Analysis we outline three variables and through a multiple regression analysis we demonstrate that the interaction on crowdfunding is positive correlated with socio-economic propensity and cultural level. The analysis has been conducted on a sample of 316 of projects funded in the Crowdfunding platform Produzioni dal Basso, the first platform born in Italy. We draw on SD logic and relationship marketing to underscore the importance of networks of actors and integration to create a co-creation of value. This view emphasizes the social and economic factors that influence, and are influenced by, crowdfundin

An Analytical Model for Optimizing the Combination of Energy Sources in a Single Power Transmission Network

The increasing amount of renewable energy currently being added to distribution networks presents new challenges and opportunities to system operators. This situation further complicates the operators' tasks in dealing with changing net loads and balancing. The current work provides an analytical model to assist systems operators in stabilizing power generation and lowering total costs, through optimization of choices in the combination of programmable fossil sources and nonprogrammable renewable sources. The study first examines the various programmable and renewable energy sources that appear broadly suitable and economically appealing for combination. Next we identify the most important factors determining the potential integration of the sources in the system. Based on this introductory information we then develop the model for the selection of the appropriate mix of sources to achieve stable production. In developing the model we define indicators to evaluate and select the best configurations of the sources included in a particular combination. Next we apply the model to a specific case study and finally reexamine the interdependencies among all the variables of the model, to provide a better understanding of its dynamics and results

integrating capacity and logistics of large additive manufacturing networks

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An Analytical Model for Optimizing the Combination of Energy Sources in a Single Power Transmission Network

The increasing amount of renewable energy currently being added to distribution networks presents new challenges and opportunities to system operators. This situation further complicates the operators' tasks in dealing with changing net loads and balancing. The current work provides an analytical model to assist systems operators in stabilizing power generation and lowering total costs, through optimization of choices in the combination of programmable fossil sources and nonprogrammable renewable sources. The study first examines the various programmable and renewable energy sources that appear broadly suitable and economically appealing for combination. Next we identify the most important factors determining the potential integration of the sources in the system. Based on this introductory information we then develop the model for the selection of the appropriate mix of sources to achieve stable production. In developing the model we define indicators to evaluate and select the best configurations of the sources included in a particular combination. Next we apply the model to a specific case study and finally reexamine the interdependencies among all the variables of the model, to provide a better understanding of its dynamics and results. Variability in Energy Sources and Loads Electricity cannot be stored on a massive scale in an economical way; thus system operators must constantly balance power supply and demand to maintain overall stability and power quality. Serious mismatches could cause local power interruptions, blackouts, or breakdowns in the entire system. Conventional hydroelectricity and coal, oil, or gas thermal generation provide steady and predictable feeds to the energy grids, with precise scheduling of output. On the other hand, renewable energy sources such as wind and solar power are typically variable, meaning that they provide intermittent output that cannot be completely and accurately predicted. The increasing application of renewable energy technologies to feed into power grids is a challenge to the system operators, who must then deal with more unpredictable net loads and more complex balancing Possible solutions include (1) energy storage (e.g., pumped hydroelectric and compressed air energy storage, chemical batteries, and active load management) [3]; (2) geographic diversification of installation sites; (3) combination of energy sources. The option of energy storage as the solution to programming still presents important technical and financial limits. Diversification of renewable sources and installations can indeed reduce overall variability; however it does not eliminate the intrinsic variability of the sources. Thus one of the current challenges for network managers is the question of how to combine various energy sources in a manner that best controls variability over the entire distribution system. Possibilities and Advantages of Combining Energy Sources To combine energy sources means to integrate two or more power plants drawing on different sources. The aim of ou

Simultaneous Extraction of Density of States Width, Carrier Mobility and Injection Barriers in Organic Semiconductors

The predictive accuracy of state–of–the–art continuum models for charge transport in organic semiconductors is highly dependent on the accurate tuning of a set of parameters whose values cannot be effectively estimated either by direct measurements or by first principles. Fitting the complete set of model parameters at once to experimental data requires to set up extremely complex multi–objective optimization problems whose solution is, on the one hand, overwhelmingly computationally expensive and, on the other, it provides no guarantee of the physical soundness of the value obtained for each individual parameter. In the present study we present a step–by–step procedure that enables to determine the most relevant model parameters, namely the density of states width, the carrier mobility and the injection barrier height, by fitting experimental data from a sequence of relatively simple and inexpensive measurements to suitably devised numerical simulations. At each step of the proposed procedure only one parameter value is sought for, thus highly simplifying the numerical fitting and enhancing its robustness, reliability and accuracy. As a case study we consider a prototypical n-type organic polymer. A very satisfactory fitting of experimental measurements is obtained, and physically meaningful values for the aforementioned parameters are extracted

Multiphysics simulation of corona discharge induced ionic wind

Ionic wind devices or electrostatic fluid accelerators are becoming of increasing interest as tools for thermal management, in particular for semiconductor devices. In this work, we present a numerical model for predicting the performance of such devices, whose main benefit is the ability to accurately predict the amount of charge injected at the corona electrode. Our multiphysics numerical model consists of a highly nonlinear strongly coupled set of PDEs including the Navier-Stokes equations for fluid flow, Poisson's equation for electrostatic potential, charge continuity and heat transfer equations. To solve this system we employ a staggered solution algorithm that generalizes Gummel's algorithm for charge transport in semiconductors. Predictions of our simulations are validated by comparison with experimental measurements and are shown to closely match. Finally, our simulation tool is used to estimate the effectiveness of the design of an electrohydrodynamic cooling apparatus for power electronics applications.Comment: 24 pages, 17 figure

Anti-angiogenic activity evaluation of secondary metabolites from Calycolpus moritzianus leaves.

Angiogenesis is a crucial step in many pathological conditions like cancer, inflammation and metastasis formation; on these basis the search for antiangiogenic agents has widened. In order to identify new compounds able to interfere in the Vascular Endothelial Growth Factor Receptor-1 (VEGFR-1, also known as Flt-1) recognition by VEGFs family members, we screened Calycolpus moritzianus (O. Berg) Burret leaves extracts by a competitive ELISA-based assay. MeOH and CHCl3 extracts and several their fractions demonstrated to be able to prevent VEGF or PlGF interaction with Flt-1, with an inhibition about 50% at concentration of 100 μg/mL. Phytochemical and pharmacological investigation of the active fractions led to the isolation of flavonoids, and terpenes

Retinoic Acid Specifically Enhances Embryonic Stem Cell Metastate Marked by Zscan4

Pluripotency confers Embryonic Stem Cells (ESCs) the ability to differentiate in ectoderm, endoderm, and mesoderm derivatives, producing the majority of cell types. Although the majority of ESCs divide without losing pluripotency, it has become evident that ESCs culture consists of multiple cell populations with different degrees of potency that are spontaneously induced in regular ESC culture conditions. Zscan4, a key pluripotency factor, marks ESC subpopulation that is referred to as high-level of pluripotency metastate. Here, we report that in ESC cultures treated with retinoic acid (RA), Zscan4 ESCs metastate is strongly enhanced. In particular, we found that induction of Zscan4 metastate is mediated via RA receptors (RAR-alpha, RAR-beta, and RAR-gamma), and it is dependent on phosphoinositide-3-kinase (PI3K) signaling. Remarkably, Zscan4 metastate induced by RA lacks canonical pluripotency genes Oct3/4 and Nanog but retained both self-renewal and pluripotency capabilities. Finally we demonstrated that the conditional ablation of Zscan4 subpopulation is dispensable for both endoderm and mesoderm but is required for ectoderm lineage. In conclusion, our research provides new insights about the role of RA signaling during ESCs high pluripotency metastate fluctuation