A Search Algorithm for Subshift Attractors of Cellular Automata

We describe a heuristic algorithm which searches for spreading clopen sets of a cellular automaton. Then the algorithms searches for the corresponding subshift attractors (which are omega-limits of spreading sets found) as forward images of joins of signal subshifts.     

LAS glass–ceramic scaffolds by three-dimensional printing

Highly porous (>60% open porosity) glass–ceramic scaffolds with remarkable mechanical properties (compression strength of ～15 MPa) were produced by indirect 3D printing. Precursor glass powders were printed into 3D ordered structures and then heat treated to sinter and develop crystalline phases. The final glass–ceramic contained a β-spodumene solid solution together with a secondary phase of lithium disilicate.The precision of the printed geometry and the density of the struts in the scaffold depended on several processing parameters (e.g. powder size and flowability, layer thickness) and were improved by increasing the binder saturation and drying time. Two types of powders with different particle size distribution (PSD) and flowability were used. Powders with a larger PSD, could be processed within a wider range of printing parameters due to their good flowability; however, the printing precision and the struts density were lower compared to the scaffolds printed using the powder in a smaller average PSD.     

Process simulation of a hybrid SOFC/mGT and enriched air/steam fluidized bed gasifier power plant

The aim of this work is to experimentally and numerically analyze the performance of a integrated power plant composed by a steam oxygen fluidized bed biomass gasifier fed by woods, a Solid Oxide Fuel Cell (SOFC) and a micro Gas Turbine (mGT). The numerical analysis is carried out by using ChemCAD software. In particular, SOFC and gasifier were modeled using proper developed Fortran subroutines interfaced to the basic software. The adopted SOFC model was already validated by the authors in previous works, while the gasifier model was here developed and validated by means of experimental activities carried out by using a bench scale gasifier. Different compounds (Benzene, Toluene, Naphthalene, Phenols) were chosen to analyze the tar evolution in the gaseous stream during the gasification process. Hot gas cleaning (based on catalytic ceramic filter candles inserted in the freeboard of the gasifier – UNIQUE concept) was adopted to remove tar and particulates from the fuel hot gas stream. Different moisture contents in the range between 10 and 30% (i.e. in a deviation of 10% around the usual wood moisture content of 20%) were numerically simulated as well as the degree of purity of the oxygen utilized in the power plant (between 25% and 95%, the rest being N₂). The power requirement for pure oxygen production leads to a reduction of the electrical efficiency of the whole power plant. For this reason, a sensitivity analysis was conducted to find the optimal operation conditions in order to maximise the syngas (H₂, CO) content in the produced gas, while maintaining a high overall electrical efficiency.     

What the 2007 TAC Market Design Game tells us about effective auction mechanisms

This paper analyzes the entrants to the 2007 tac Market Design Game. We present a classification of the entries to the competition, and use this classification to compare these entries. The paper also attempts to relate market dynamics to the auction rules adopted by these entries and their adaptive strategies via a set of post-tournament experiments. Based on this analysis, the paper speculates about the design of effective auction mechanisms, both in the setting of this competition and in the more general case.     

Operators for transforming kernels into quasi-local kernels that improve SVM accuracy

Motivated by the crucial role that locality plays in various learning approaches, we present, in the framework of kernel machines for classification, a novel family of operators on kernels able to integrate local information into any kernel obtaining quasi-local kernels. The quasi-local kernels maintain the possibly global properties of the input kernel and they increase the kernel value as the points get closer in the feature space of the input kernel, mixing the effect of the input kernel with a kernel which is local in the feature space of the input one. If applied on a local kernel the operators introduce an additional level of locality equivalent to use a local kernel with non-stationary kernel width. The operators accept two parameters that regulate the width of the exponential influence of points in the locality-dependent component and the balancing between the feature-space local component and the input kernel. We address the choice of these parameters with a data-dependent strategy. Experiments carried out with SVM applying the operators on traditional kernel functions on a total of 43 datasets with different characteristics and application domains, achieve very good results supported by statistical significance.     

A 2D Full-Band Monte Carlo Study of HgCdTe-Based Avalanche Photodiodes

This work presents a numerical simulation study of HgCdTe-based avalanche photodetectors (APDs). The two-dimensional model used is based on a full-band Monte Carlo approach in which the electronic structure is computed using a nonlocal empirical pseudopotential model with spin–orbit corrections. The carrier–phonon scattering rates have been computed from first principles using a rigid pseudo-ion model. The most attractive feature of these devices is the potential for single-carrier ionization when electrons are used as the primary injection carrier. For this reason, this work focuses on two front-illuminated (electron-injection) device structures: a planar diffused PIN structure and a planar diffused PN photodiode with guard rings. To predict the performance of these APDs, the electron multiplication gain has been studied as a function of the position where photogenerated carriers are injected and as a function of the curvature of the p-type diffusion region. We find that, in the diffused PIN structure, the limited lateral spatial extent of the high-electric-field region leads to a reduction of the multiplication gain from the center of the device to the periphery. Furthermore, the higher the curvature, the more abruptly the gain decreases. For the simple PN structure, we find that the presence of the guard rings removes the high electric field from the surface and induces a more gradual roll-off of the gain from the center of the device to the periphery.     

Study and development of morphological analysis guidelines for point cloud management: The “decisional cube”

When talking about reverse engineering, it is necessary to focus on the management of point clouds. Generally speaking, every 3D scanner device codifies simple and complex geometries providing different point cloud densities as an output. Point cloud density is usually more correlated with the technical specifications of the device employed rather than with the morphology of the object acquired. This situation is due to the frequent use of structured grids by a large quantity of devices. In order to solve this problem, we therefore need to integrate the classical structured grid acquisition with a smart selective one, which is able to identify different point cloud densities in accordance with the morphological complexity of the object regions acquired.Currently, we can reach the destination in many different ways. Each of them is able to provide different performances depending on the object morphology and the performances of 3D scanner devices. Unfortunately, there does not yet exist one universal approach able to be employed in all cases. For this reason, the present paper aims to propose a first analysis of the available methodologies and parameters, in order to provide final users with some guidelines for supporting their decisions according to the specific application they are facing. Moreover, the developed guidelines have been illustrated and validated by a series of case studies of the proposed method.     

On the hierarchy of conservation laws in a cellular automaton

Conservation laws in cellular automata (CA) are studied as an abstraction of the conservation laws observed in nature. In addition to the usual real-valued conservation laws we also consider more general group-valued and semigroup-valued conservation laws. The (algebraic) conservation laws in a CA form a hierarchy, based on the range of the interactions they take into account. The conservation laws with smaller interaction ranges are the homomorphic images of those with larger interaction ranges, and for each specific range there is a most general law that incorporates all those with that range. For one-dimensional CA, such a most general conservation law has—even in the semigroup-valued case—an effectively constructible finite presentation, while for higher-dimensional CA such effective construction exists only in the group-valued case. It is even undecidable whether a given two-dimensional CA conserves a given semigroup-valued energy assignment. Although the local properties of this hierarchy are tractable in the one-dimensional case, its global properties turn out to be undecidable. In particular, we prove that it is undecidable whether this hierarchy is trivial or unbounded. We point out some interconnections between the structure of this hierarchy and the dynamical properties of the CA. In particular, we show that positively expansive CA do not have non-trivial real-valued conservation laws.     

Bracciolini新区的圣新玛丽亚教堂

我们可以在历史中心的旁边辨认出新的城市中心广场。简单的北向双拱线形建筑定义了一个被纵向天窗一分为二的室内空间。该项目旨在突出拱顶并弱化通     

Rapid and Simultaneous Analysis of Xanthines and Polyphenols as Bitter Taste Markers in Bakery Products by FT-NIR Spectroscopy

The food industry has a direct interest into bitter-tasting substances either for the identification of negative off-flavors or for the monitoring of a desired organoleptic quality. A rapid technique, based on Fourier transform-near infrared (FT-NIR) spectroscopy and able to detect taste molecular markers in bakery commodities, was developed, focusing the attention on biscuits category. Xanthines (caffeine, theobromine, and theophylline) and polyphenols (catechins and epicathechins), considered as mainly responsible for the bitter-taste of coffee\cocoa\chocolate based products, were firstly checked using a confirmatory liquid chromatography (LC)-ESI\mass spectrometry (MS)-MS procedure after hot methanol–water extraction. Correspondent data were used for the calibration of the FT-NIR through PLS regression. Values of the standard errors of prediction (lower than 10 %) were comparable to the values of the standard errors of cross-validation. Coefficients of determination indicated a good predictive power in the calibration model (R ² xanthines?=?0.97, R ² polyphenols?=?0.96) and a satisfying discriminating power among different contents in the validation models (R ² xanthines?=?0.96, R ² polyphenols?=?0.96). A testing phase on the generated model was executed by a comparison of LC-MS and sensory panel data with FT-NIR responses recorded on unknown biscuits: differences between found and predicted levels were generally below 5 % and the best predictability was achievable in chocolate-based biscuits. This methodology is able to work directly on solid products, has the potential to be expanded on other categories of gustative molecular markers (like sugars) and can be conceived as applicable for a routine control of a standardized bitter taste quality in a real industrial production.