Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Two-step sinter-crystallization of K2O–CaO–P2O5–SiO2 (45S5-K) bioactive glass

Bioactive glasses and glass-ceramics (GCs) effectively regenerate bone tissue, however most GCs show improved mechanical properties. In this work, we developed and tested a rarely studied bioactive glass composition (24.4K₂O-26.9CaO-46.1SiO₂-2.6P₂O₅ mol%, identified as 45S5-K) with different particle sizes and heating rates to obtain a sintered GC that combines good fracture strength, low elastic modulus, and bioactivity. We analyzed the influence of the sintering processing conditions in the elastic modulus, Vickers microhardness, density, and crystal phase formation in the GC. The best GC shows improved properties compared with its parent glass. This glass achieves a good densification degree with a two-step viscous flow sintering approach and the resulting GC shows as high bioactivity as that of the standard 45S5 Bioglass®. Furthermore, the GC elastic modulus (56 GPa) is relatively low, minimizing stress shielding. Therefore, we unveiled the glass sintering behavior with concurrent crystallization of this complex bioactive glass composition and developed a potential GC for bone regeneration.     

Microscopic simulation of electronic noise in semiconductormaterials and devices

We present a microscopic interpretation of electronic noise in semiconductor materials and two-terminal devices. The theory is based on Monte Carlo simulations of the carrier motion self-consistently coupled with a Poisson solver. Current and voltage noise operations are applied and their respective representations discussed. As application we consider the cases of homogeneous materials, resistors, n⁺nn ⁺ structures, and Schottky-barrier diodes. Phenomena associated with coupling between fluctuations in carrier velocity and self-consistent electric field are quantitatively investigated for the first time. At increasing applied fields hot-carrier effects are found to be of relevant importance in all the cases considered here. As a general result, noise spectroscopy is found to be a source of valuable information to investigate and characterize transport properties of semiconductor materials and devices     

Entities,identities, identifiers and credentials — what does it all mean?

This paper looks at the concepts of entities, identities, identifiers and credentials, their definitions, and how they combine to authenticate an identity to an account, or function, within a service. Credentials can be divided into several different types on the basis of their use, origin and characteristics. In particular, types such as composite, dynamic and derived credentials will be considered, and their applicability within an identity management system. Each credential must be managed through its entire life cycle from initial registration, general use and suspension, to deletion. The notion of public (i.e. freely distributable) and private (i.e. known only to you) aspects of a credential is explored. The bindings, by trusted third parties, of identifiers and public credentials into permits and instruments of proof is explained along with the convenience, but greater exposure, of local information. Several scenarios are analysed in terms of how different types of credentials are employed during the authentication process.     

An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet.

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.     

Perceived stress management skill mediates the relationship between optimism and positive mood following radical prostatectomy.

This study evaluated relations among optimism, perceived stress management skills (PSMS), and positive mood in 46 men who had surgical treatment for localized prostate cancer. The authors found that optimism, PSMS, and positive mood scores were positively correlated. Positive mood was unrelated to demographic and disease-related control variables. In a hierarchical regression model controlling for PSMS, the relationship between optimism and positive mood became nonsignificant, whereas PSMS remained a correlate of positive mood. Results suggest that the relationship between optimism and positive mood may be mediated by belief in being able to use stress management techniques effectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effect of beam voltage on the properties of aluminium nitride prepared by ion beam assisted deposition

The effects of nitrogen-beam voltage on the structure, stress, energy band gap and hardness of AIN thin films deposited on Si (111), Si (100) and sapphire (0001) by ion beam assisted deposition (IBAD) are reported. As the nitrogen-beam voltage was increased from 50 to 200 V, the stress and disorder in the AIN films increased as determined by X-ray diffraction, FTIR and Raman spectroscopy. The preferred orientation of the film's c-axis changed from completely normal to the film at 100 V, to a mixture of normal and in the plane of the film at 200 V. For AIN films deposited under the same conditions, the films were more highly oriented on sapphire (0001) than in Si (111). The hardness of the films increased from 18.2 to 23.7 GPa with the nitrogen-beam voltage, and possible reasons for this change in hardness are considered.     

Executing algorithms with hypercube topology on torusmulticomputers

Many parallel algorithms use hypercubes as the communication topology among their processes. When such algorithms are executed on hypercube multicomputers the communication cost is kept minimum since processes can be allocated to processors in such a way that only communication between neighbor processors is required. However, the scalability of hypercube multicomputers is constrained by the fact that the interconnection cost-per-node increases with the total number of nodes. From scalability point of view, meshes and toruses are more interesting classes of interconnection topologies. This paper focuses on the execution of algorithms with hypercube communication topology on multicomputers with mesh or torus interconnection topologies. The proposed approach is based on looking at different embeddings of hypercube graphs onto mesh or torus graphs. The paper concentrates on toruses since an already known embedding, which is called standard embedding, is optimal for meshes. In this paper, an embedding of hypercubes onto toruses of any given dimension is proposed. This novel embedding is called xor embedding. The paper presents a set of performance figures for both the standard and the xor embeddings and shows that the latter outperforms the former for any torus. In addition, it is proven that for a one-dimensional torus (a ring) the xor embedding is optimal in the sense that it minimizes the execution time of a class of parallel algorithms with hypercube topology. This class of algorithms is frequently found in real applications, such as FFT and some class of sorting algorithms