An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization

Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results.Comment: mail: [email protected]

Solving the scalarization issues of Advantage-based Reinforcement Learning algorithms

In this research, some of the issues that arise from the scalarization of the multi-objective optimization problem in the Advantage Actor–Critic (A2C) reinforcement learning algorithm are investigated. The paper shows how a naive scalarization can lead to gradients overlapping. Furthermore, the possibility that the entropy regularization term can be a source of uncontrolled noise is discussed. With respect to the above issues, a technique to avoid gradient overlapping is proposed, while keeping the same loss formulation. Moreover, a method to avoid the uncontrolled noise, by sampling the actions from distributions with a desired minimum entropy, is investigated. Pilot experiments have been carried out to show how the proposed method speeds up the training. The proposed approach can be applied to any Advantage-based Reinforcement Learning algorithm

Formal Derivation of Mesh Neural Networks with Their Forward-Only Gradient Propagation

This paper proposes the Mesh Neural Network (MNN), a novel architecture which allows neurons to be connected in any topology, to efficiently route information. In MNNs, information is propagated between neurons throughout a state transition function. State and error gradients are then directly computed from state updates without backward computation. The MNN architecture and the error propagation schema is formalized and derived in tensor algebra. The proposed computational model can fully supply a gradient descent process, and is potentially suitable for very large scale sparse NNs, due to its expressivity and training efficiency, with respect to NNs based on back-propagation and computational graphs

Fostering Distributed Business Logic in Open Collaborative Networks: an integrated approach based on semantic and swarm coordination

Given the great opportunities provided by Open Collaborative Networks (OCNs), their success depends on the effective integration of composite business logic at all stages. However, a dilemma between cooperation and competition is often found in environments where the access to business knowledge can provide absolute advantages over the competition. Indeed, although it is apparent that business logic should be automated for an effective integration, chain participants at all segments are often highly protective of their own knowledge. In this paper, we propose a solution to this problem by outlining a novel approach with a supporting architectural view. In our approach, business rules are modeled via semantic web and their execution is coordinated by a workflow model. Each company’s rule can be kept as private, and the business rules can be combined together to achieve goals with defined interdependencies and responsibilities in the workflow. The use of a workflow model allows assembling business facts together while protecting data source. We propose a privacy-preserving perturbation technique which is based on digital stigmergy. Stigmergy is a processing schema based on the principle of self-aggregation of marks produced by data. Stigmergy allows protecting data privacy, because only marks are involved in aggregation, in place of actual data values, without explicit data modeling. This paper discusses the proposed approach and examines its characteristics through actual scenarios

Cytochrome P450 and Parkinson's disease: protective role of neuronal CYP 2E1 from MPTP toxicity

Summary. Elucidation of the biochemical steps leading to the 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine (MPTP)-induced degeneration of the nigro-striatal dopamine (DA) pathway has provided new clues to the pathophysiology of Parkinson's Disease (PD). In line with the enhancement of MPTP toxicity by diethyldithiocarbamate (DDC), here we demonstrate how other CYP450 (2E1) inhibitors, such as diallyl sulfide (DAS) or phenylethylisothiocyanate (PIC), also potentiate the selective DA neuron degeneration in C57=bl mice. In order to provide direct evidence for this isozyme involvement, CYP 2E1 knockout mice were challenged with MPTP or the combined treatment. Here we show that these transgenic mice have a low sensitivity to MPTP alone, similarly to the wild type SVI, suggesting that it is likely that transgenic mice compensate for the missing enzyme. However, in these CYP 2E1 knockout mice, DDC pretreatment completely fails to enhance MPTP toxicity; this enhancement is instead regularly present in the SVI control animals. This study indicates that the occurrence of CYP 2E1 in C57=bl mouse brain is relevant for MPTP toxicity, and suggests that this isozyme may have a detoxificant role related to the efflux transporter of the toxin. Abbreviations DA dopamine; PD Parkinson's Disease; DDC diethyldithiocarbamate; PIC phenylethylisothiocyanate; DAS diallyl sulfide; MPTP 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine; MPP þ 1-methyl-4-phenylpyridinium; SN substantia nigra; TH tyrosine hydroxylase; SVI Cyp 2e1þ=þ (129S1=SvImJ); GONZ Cyp 2e1À=À (129=SV-Cyp 2e1 tm1Gonz )

Connexin 26 Expression in Mammalian Cardiomyocytes

Connexins are a family of membrane-spanning proteins named according to their molecular weight. They are known to form membrane channels mediating cell-cell communication, which play an essential role in the propagation of electrical activity in the heart. Cx26 has been described in a number of tissues but not in the heart, and its mutations are frequently associated with deafness and skin diseases. The aim of this study was to assess the possible Cx26 expression in heart tissues of different mammalian species and to demonstrate its localization at level of cardiomyocytes. Samples of pig, human and rat heart and H9c2 cells were used for our research. Immunohistochemical and molecular biology techniques were employed to test the expression of Cx26. Interestingly, this connexin was found in cardiomyocytes, at level of clusters scattered over the cell cytoplasm but not at level of the intercalated discs where the other cardiac connexins are usually located. Furthermore, the expression of Cx26 in H9c2 myoblast cells increased when they were differentiated into cardiac-like phenotype. To our knowledge, the expression of Cx26 in pig, human and rat has been demonstrated for the first time in the present paper

High availability using virtualization - 3RC

High availability has always been one of the main problems for a data center. Till now high availability was achieved by host per host redundancy, a highly expensive method in terms of hardware and human costs. A new approach to the problem can be offered by virtualization. Using virtualization, it is possible to achieve a redundancy system for all the services running on a data center. This new approach to high availability allows the running virtual machines to be distributed over a small number of servers, by exploiting the features of the virtualization layer: start, stop and move virtual machines between physical hosts. The 3RC system is based on a finite state machine, providing the possibility to restart each virtual machine over any physical host, or reinstall it from scratch. A complete infrastructure has been developed to install operating system and middleware in a few minutes. To virtualize the main servers of a data center, a new procedure has been developed to migrate physical to virtual hosts. The whole Grid data center SNS-PISA is running at the moment in virtual environment under the high availability system.Comment: 10 page

Aggregation of human neutrophils induced by phytohemagglutinin

Phytohemagglutinin-induced aggregation of circulating neutrophils was studied in 13 normal subjects. The interference caused by various drugs (vinblastine, cytochalasin B, indomethacin, nicardipine and flunarizine) was tested. The modifications in the aggregation values induced by these drugs are in favour of an evident dependence of the phenomenon upon the trans-membrane flow of calcium ions and the calmodulin function and of a limited dependence upon the microtubular function