Good teaching inputs do not correspond to desired responses in ecological neural networks

In this paper we analyze how supervised learning occurs in ecological neural networks, i.e. networks that interact with an autonomous external environment and, therefore, at least partially determine with their behavior their own input. Using an evolutionary method for selecting good teaching inputs we surprisingly find that to obtain a desired outputX it is better to use a teaching input different fromX. To explain this fact we claim that teaching inputs in ecological networks have two different effects: (a) to reduce the discrepancy between the actual output of the network and the teaching input, (b) to modify the network's behavior and, as a consequence, the network's learning experiences. Evolved teaching inputs appear to represent a compromise between these two needs. We finally show that evolved teaching inputs that are allowed to change during the learning process function differently at different stages of learning, first giving more weight to (b) and, later on, to (a).     

Techniques for the mechanical characterisation of civil structures

Broadly speaking, structural defects include all those changes affecting a structure so that its behaviour is no longer in keeping with its intended use characteristics or differs from the behaviour it was originally designed for. In recent years, damage recognition and location methods, relying on the measurement of parameters that are indicative of a structure's mechanical behaviour, have benefitted from the introduction of innovative approaches, which make it possible to process and correlate an unprecedented wealth of measurble data. The aim of this work is to illustrate the basic problems associated with the different methods used for structural identification (parametric and non-parametric, linear and non-linear, with known and unknown inputs, etc.) and to report on some interesting applications for civil structural diagnosis.     

Cyclic Nigerosyl-Nigerose as Oxygen Nanocarrier to Protect Cellular Models from Hypoxia/Reoxygenation Injury: Implications from an In Vitro Model

Heart failure (HF) prevalence is increasing among the aging population, and the mortality rate remains unacceptably high despite improvements in therapy. Myocardial ischemia (MI) and, consequently, ischemia/reperfusion injury (IRI), are frequently the basis of HF development. Therefore, cardioprotective strategies to limit IRI are mandatory. Nanocarriers have been proposed as alternative therapy for cardiovascular disease. Controlled reoxygenation may be a promising strategy. Novel nanocarriers, such as cyclic nigerosyl-nigerose (CNN), can be innovative tools for oxygen delivery in a controlled manner. In this study we analyzed new CNN-based formulations as oxygen nanocarriers (O₂-CNN), and compared them with nitrogen CNN (N₂-CNN). These different CNN-based formulations were tested using two cellular models, namely, cardiomyoblasts (H9c2), and endothelial (HMEC) cell lines, at different concentrations. The effects on the growth curve during normoxia (21% O₂, 5% CO₂ and 74% N₂) and their protective effects during hypoxia (1% O₂, 5% CO₂ and 94% N₂) and reoxygenation (21% O₂, 5% CO₂ and 74% N₂) were studied. Neither O₂-CNN nor N₂-CNN has any effect on the growth curve during normoxia. However, O₂-CNN applied before hypoxia induces a 15–30% reduction in cell mortality after hypoxia/re-oxygenation when compared to N₂-CNN. O₂-CNN showed a marked efficacy in controlled oxygenation, which suggests an interesting potential for the future medical application of soluble nanocarrier systems for MI treatment.     

Focal Ischemic Injury to the Early Neonatal Rat Brain Models Cognitive and Motor Deficits with Associated Histopathological Outcomes Relevant to Human Neonatal Brain Injury

Neonatal arterial ischemic stroke is one of the more severe birth complications. The injury can result in extensive neurological damage and is robustly associated with later diagnoses of cerebral palsy (CP). An important part of efforts to develop new therapies include the on-going refinement and understanding of animal models that capture relevant clinical features of neonatal brain injury leading to CP. The potent vasoconstrictor peptide, Endothelin-1 (ET-1), has previously been utilised in animal models to reduce local blood flow to levels that mimic ischemic stroke. Our previous work in this area has shown that it is an effective and technically simple approach for modelling ischemic injury at very early neonatal ages, resulting in stable deficits in motor function. Here, we aimed to extend this model to also examine the impact on cognitive function. We show that focal delivery of ET-1 to the cortex of Sprague Dawley rats on postnatal day 0 (P0) resulted in impaired learning in a touchscreen-based test of visual discrimination and correlated with important clinical features of CP including damage to large white matter structures.     

Quantification of secondary structure prediction improvement using multiple alignments

The use of multiple sequence alignments for secondary structurepredictions is analysed. Seven different protein families, containingonly sequences of known structure, were considered to providea range of alignment and prediction conditions. Using alignmentsobtained by spatial superposition of main chain atoms in knowntertiary protein structures allowed a mean of 8% in secondarystructure prediction accuracy, when compared to those obtainedfrom the individual sequences. Substitution of these alignmentsby those determined directly from an automated sequence alignmentalgorithm showed variations in the prediction accuracy whichcorrelated with the quality of the multiple alignments and distanceof the primary sequence. Secondary structure predictions canbe reliably improved using alignments from an automatic alignmentprocedure with a mean increase of 6.87percnt;, giving an overallprediction accuracy of 68.5%, if there is a minimum of 25% sequenceidentity between all sequences in a family.     

Two-Grid Methods for Hermitian positive definite linear systems connected with an order relation

Given a multigrid procedure for linear systems with coefficient matrices $A_n,$ we discuss the optimality of a related multigrid procedure with the same smoother and the same projector, when applied to properly related algebraic problems with coefficient matrices $B_n$ : we assume that both $A_n$ and $B_n$ are Hermitian positive definite with $A_n\le \vartheta B_n,$ for some positive $\vartheta $ independent of $n.$ In this context we prove the Two-Grid Method optimality. We apply this elementary strategy for designing a multigrid solution for modifications of multilevel structured linear systems, in which the Hermitian positive definite coefficient matrix is banded in a multilevel sense. As structured matrices, Toeplitz, circulants, Hartley, sine ( $\tau $ class) and cosine algebras are considered. In such a way, several linear systems arising from the approximation of integro–differential equations with various boundary conditions can be efficiently solved in linear time (with respect to the size of the algebraic problem). Some numerical experiments are presented and discussed, both with respect to Two-Grid and multigrid procedures.     

<Superscript>1</Superscript>H NMR characterization of milk lipids: A comparison between cow and buffalo milk

Characterization of the lipid fraction of raw cow and buffalo milk samples, collected in different breeding areas in Apulia, a region of southern Italy, were performed by means of ¹H NMR. The aim of this work was to establish whether FA composition data obtained by ¹H NMR can be used in the differentiation of buffalo and cow milk samples according to species. A complete assignment of the signals present in the spectrum was attempted by COSY, heteronuclear coherence spectra. Quantification of FA was carried out by inserting the integrals of particular peaks in suitable calculations. Multivariate statistical analysis, conducted on the results of the quantification, permitted buffalo and cow milks to be distinguished.     

Network Externalities,Incumbent’s Competitive Advantage and the Degree of Openness of Software Start-Ups

This paper proposes a formal model that analyzes the degree of openness chosen by start-ups when entering the software industry. In line with the literature, we label as degree of openness the extent to which software start-ups mix open source (OS) and proprietary solutions in the portfolio of software products they offer. We relate the choice of the degree of openness to two key characteristics of the market segments in which software start-ups operate: the strength of the network externalities and the competitive advantage of the incumbent. Specifically, by modelling (price) competition between an incumbent and an entrant in two ways, i.e., the entrant is price-setter or price-taker, we derive the necessary condition(s) in terms of the strength of network externalities for observing the adoption of a business model that comprises the offering of both proprietary and OS solutions by the entrant (i.e., hybrid business model). Then, we highlight that, if a hybrid business model is the choice, the degree of openness chosen in equilibrium increases along with both the strength of the network externalities and the competitive advantage of the incumbent. This result holds indifferently whether the software start-up is modelled as a price-setter or a price-taker. An empirical test run on a sample of European start-ups in the software industry supports these theoretical predictions.     

Nanoindentation Characterization of Submicro- and Nano-Sized Liquid-Phase-Sintered SiC Ceramics

Submicro- and nano-sized liquid-phase-sintered SiC ceramics were mechanically tested by nanoindentation in the peak load range 5–400 mN. The submicro-sized sample showed a marked indentation size effect which the nano-sized samples did not exhibit. The relevance of indentation depth with respect to the microstructural scale has been outlined. In the investigated grain-size range, the hardness dependence on the grain size could be described by a load-dependent inverse Hall–Petch relation. Young's modulus was less microstructure- and load-dependent. Because of the very fine microstructure, the nano-sized SiC materials gave lower elastic values than the submicro-sized SiC ceramic.