Structure of magnetic poly(oxyethylene)-siloxane nanohybrids doped with Fe-II and Fe-III

Hybrid organic - inorganic nanocomposites doped with Fe-II and Fe-III ions and exhibiting interesting magnetic properties have been obtained by the sol - gel process. The hybrid matrix of these ormosils ( organically modified silicates), classed as di-ureasils and termed U( 2000), is composed of poly( oxyethylene) chains of variable length grafted to siloxane groups by means of urea crosslinkages. Iron perchlorate and iron nitrate were incorporated in the diureasil matrices, leading to compositions within the range 80 greater than or equal to n greater than or equal to 10, n being the molar ratio of ether-type O atoms per cation. The structure of the doped diureasils was investigated by small-angle X-ray scattering (SAXS). For Fe-II-doped samples, SAXS results suggest the existence of a two-level hierarchical structure. The primary level is composed of spatially correlated siloxane clusters embedded in the polymeric matrix and the secondary, coarser level consists of domains where the siloxane clusters are segregated. The structure of Fe-III-doped hybrids is different, revealing the existence of iron oxide based nanoclusters, identified as ferrihydrite by wide-angle X-ray diffraction, dispersed in the hybrid matrix. The magnetic susceptibility of these materials was determined by zero-field-cooling and field-cooling procedures as functions of both temperature and field. The different magnetic features between Fe-II- and Fe-III-doped samples are consistent with the structural differences revealed by SAXS. While Fe-II-doped composites exhibit a paramagnetic Curie-type behaviour, hybrids containing Fe-III ions show thermal and field irreversibilities.

Structure of luminescent mono and di-urethanesil nanocomposites doped with Eu3+ ions

A structure modeling of two families of sol-gel derived Eu3+-doped organic/inorganic hybrids based on the results of small-angle X-ray scattering experiments is reported. The materials are composed of poly(oxyethylene) chains grafted at one or both ends to siloxane groups and are called mono- and di-urethanesils, respectively. A theoretical function corresponding to a two-level hierarchical structure model fits well the experimental Scattering curves. The first level corresponds to small siloxane clusters embedded in a polymeric matrix. The secondary level is associated to the existence of siloxane cluster rich domains surrounded by a cluster-depleted polymeric matrix. Results show that increasing europium doping favors the growth of the secondary domains. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

The past and the future fate of the universe and the formation of structure in it

The history and the ultimate future fate of the universe as a whole depend on how much the expansion of the universe is decelerated by its own mass. In particular, whether the expansion of the universe will ever come to a halt can be determined from the past expansion. However, the mass density in the universe does not only govern the expansion history and the curvature of space, but in parallel also regulates the growth of hierarchical structure, including the collapse of material into the dense, virialized regions that we identify with galaxies. Hence, the formation of galaxies and their clustered distribution in space depend not only on the detailed physics of how stars are formed but also on the overall structure of the universe. Recent observational efforts, fueled by new large, ground-based telescopes and the Hubble Space Telescope, combined with theoretical progress, have brought us to the verge of determining the expansion history of the universe and space curvature from direct observation and to linking this to the formation history of galaxies.

A new perspective on service quality: A multi-dimensional, hierarchical scale

This study offers a new perspective on the nature, content and structure of perceived service quality. The Nordic and Gap schools of quality assessment are integrated with recent advances in the literature to develop and test a multidimensional, hierarchical scale. The scale provides a framework for assessing service quality within a high involvement, high contact, ongoing service environment. Empirical results indicated that service quality conforms to a multidimensional, hierarchical structure consisting of four primary dimensions, which in turn comprise nine sub-dimensions. The results obtained extend our understanding of service evaluation and have important implications for service providers seeking to improve the quality of the services they provide.

Template-free and eco-friendly synthesis of hierarchical Ag3PO4 microcrystals with sharp corners and edges for enhanced photocatalytic activity under visible light

Herein, we demonstrate a template-free and eco-friendly strategy to synthesize hierarchical Ag3PO4 microcrystals with sharp corners and edges via silver–ammine complex at room temperature. The as-synthesized hierarchical Ag3PO4 microcrystals were characterized by X-ray diffraction, field-emission scanning electron microscope (FESEM), UV–vis diffuse reflectance spectroscopy (UV–vis DRS), BET surface area analyzer, and photoluminescence analysis (PL). Our results clearly indicated that the as-synthesized Ag3PO4 microcrystals possess a hierarchical structure with sharp corners and edges. More attractively, the adsorption ability and visible light photocatalytic activity of the as-synthesized hierarchical Ag3PO4 is much higher than that of conventional Ag3PO4.

Processing of hierarchical syntactic strusture in music

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

Processing of hierarchical syntactic strusture in music

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

Electrospun hierarchical artificial muscle for soft robotics applications

Nowadays, one of the most ambitious challenges in soft robotics is the development of actuators capable to achieve performance comparable to skeletal muscles. Scientists have been working for decades, inspired by Nature, to mimic both their complex structure and their perfectly balanced features in terms of linear contraction, force-to-weight ratio, scalability and flexibility. The present Thesis, contextualized within the FET open Horizon 2020 project MAGNIFY, aims to develop a new family of innovative flexible actuators in the field of soft-robotics. For the realization of this actuator, a biomimetic approach has been chosen, drawing inspiration from skeletal muscle. Their hierarchical fibrous structure was mimicked employing the electrospinning technique, while the contraction of sarcomeres was designed employing chains of molecular machines, supramolecular systems capable of performing movements useful to execute specific tasks. The first part deals with the design and production of the basic unit of the artificial muscle, the artificial myofibril, consisting in a novel electrospun core-shell nanofiber, with elastomeric shell and electrically conductive core, coupled with a conductive coating, for the realization of which numerous strategies have been investigated. The second part deals instead with the integration of molecular machines (provided by the project partners) inside these artificial myofibrils, preceded by the study of several model molecules, aimed at simulating the presence of these molecular machines during the initial phases of the project. The last part concerns the realization of an electrospun multiscale hierarchical structure, aimed at reproducing the entire muscle morphology and fibrous organization. These research will be joined together in the near future like the pieces of a puzzle, recreating the artificial actuator most similar to biological muscle ever made, composed of millions of artificial myofibrils, electrically activated in which the nano-scale movement of molecular machines will be incrementally amplified to the macro-scale contraction of the artificial muscle.

Hierarchical Multi-Label Text Classification in a Low-Resource Setting

In this thesis we address a multi-label hierarchical text classification problem in a low-resource setting and explore different approaches to identify the best one for our case. The goal is to train a model that classifies English school exercises according to a hierarchical taxonomy with few labeled data. The experiments made in this work employ different machine learning models and text representation techniques: CatBoost with tf-idf features, classifiers based on pre-trained models (mBERT, LASER), and SetFit, a framework for few-shot text classification. SetFit proved to be the most promising approach, achieving better performance when during training only a few labeled examples per class are available. However, this thesis does not consider all the hierarchical taxonomy, but only the first two levels: to address classification with the classes at the third level further experiments should be carried out, exploring methods for zero-shot text classification, data augmentation, and strategies to exploit the hierarchical structure of the taxonomy during training.

A incubação das micro, pequenas e médias empresas (MPMEs) em Portugal : uma discussão sobre custos de transacção, dimensão competitiva e a cadeia de valor

RESUMO: Este trabalho tem por objectivo discutir as formas como as incubadoras de empresas contribuem para a criação da cadeia de valores de Micros, Pequenas e Médias Empresas (MPMEs) permitindo a redução dos seus custos de transacção. Para melhor compreender a forma como se reduzem os custos de transacção é importante conhecer os pressupostos comportamentais que provocam a existência de tais custos: a racionalidade limitada, porque a nossa forma de pensar tem limitações; e o oportunismo, porque há pessoas com comportamentos desonestos envolvidas no negócio. O verdadeiro poder explicativo da teoria dos custos de transacção está, no entanto, na análise de três variáveis que determinam se esses custos serão mais baixos numa estrutura hierárquica ou num mercado. Estas três variáveis são: a especificidade de activos - se uma transacção envolve ou não activos específicos à actividade da empresa; a incerteza - qual o grau de incerteza em encontrar um produto ou serviço externo à empresa; e a frequência - e se um bem ou serviço é frequentemente utilizado ou não. As incubadoras de empresas são actualmente consideradas como uma iniciativa essencial ao desenvolvimento socioeconómico regional, e nacional. Estas instituições contribuem para corrigir ineficiências no mercado, conferindo às empresas uma capacidade de inovação tecnológica que garante empregos e a criação de riquezas, aumentando o bem-estar da sociedade. O sucesso da sua actuação resume-se à capacidade para gerar dimensões virtuais que contribuem para a cadeia de valores, permitindo as MPMEs, a redução dos seus custos de transacção. ABSTRACT: This work aims to discuss the relevant forms how incubators contribute to the value chain of a in micro, small and medium enterprises (MSME´s) reducing their transaction costs. To better understand how transaction costs can be reduced one must recognize the behavioral assumptions that are behind there existence; bounded rationality - because our way of thinking has limitations and opportunism - because there are dishonest people involved in the business. The true cost theory´s explanatory power comes from the analyses of the three variables that determine whether those costs will be lower in a hierarchical structure or a market structure. These three variables are: specificity of assets - if the transaction involves or not specific assets in for the firm´s activity; the uncertainty - what is the degree of uncertainty in finding a product or service external to the firm; and the frequency - what is the frequency of the good or service use. Business incubators are currently regarded as a key initiative for the national or regional economic development. The institutions contribute to correct market inefficiencies, improving the capacity of firms to produce technological innovations that guaranty jobs and wealth creation increasing welfare. The success of this all boils down to the capacity to create virtual dimensions that contributes to the MSME´s value chain reducing transaction costs.

Estudo empírico da caracterização da selecção de fornecedores

O problema de selecção de fornecedores/parceiros é uma parte integrante e importante nas empresas que se propõem a um desempenho competitivo e lucrativo na sua área de actividade. A escolha do melhor fornecedor/parceiro passa na maior parte da vezes por fazer uma análise cuidada dos factores que podem influenciar positiva ou negativamente essa escolha. Desde cedo este problema tem vindo a ser alvo de inúmeros estudos, estudos esses que se focam essencialmente nos critérios a considerar e nas metodologias a adoptar para optimizar a escolha dos parceiros. De entre os vários estudos efectuados, muitos são os que consideram como critérios chave o custo do produto, a qualidade, a entrega e a reputação da empresa fornecedora. Ainda assim, há muitos outros que são referidos e que na sua maioria se apresentam como subcritérios. No âmbito deste trabalho, foram identificados cinco grandes critérios, Qualidade, Sistema Financeiro, Sinergias, Custo e Sistema Produtivo. Dentro desses critérios, sentiu-se a necessidade de incluir alguns subcritérios pelo que, cada um dos critérios chave apresenta cinco subcritérios. Identificados os critérios, foi necessário perceber de que forma são aplicados e que modelos são utilizados para se poder tirar o melhor partido das informações. Sabendo que existem modelos que privilegiam a programação matemática e outros que fazem uso de ponderações lineares para se identificar o melhor fornecedor, foi realizado um inquérito e contactadas empresas por forma a perceber quais os factores que mais peso tinham nas suas decisões de escolha de parceiros. Interpretados os resultados e tratados os dados foi adoptado um modelo de ponderação linear para traduzir a importância de cada um dos factores. O modelo proposto apresenta uma estrutura hierárquica e pode ser aplicado com o método AHP de Saaty ou o método de Análise de Valor. Este modelo permite escolher a ou as alternativas que melhor se adequam aos requisitos das empresas.

Fractional order control on a wind turbine benchmark

This paper is about a hierarchical structure with an event-based supervisor in a higher level and a fractional-order proportional integral (FOPI) in a lower level applied to a wind turbine. The event-based supervisor analyzes the operation conditions to determine the state of the wind turbine. This controller operate in the full load region and the main objective is to capture maximum power generation while ensuring the performance and reliability required for a wind turbine to be integrated into an electric grid. The main contribution focus on the use of fractional-order proportional integral controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. Comparisons between fractional-order pitch control and a default proportional integral pitch controller applied to a wind turbine benchmark are given and simulation results by Matlab/Simulink are shown in order to prove the effectiveness of the proposed approach.

Supplier's selection model based on an empirical study

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

Fractional order control on a wind turbine benchmark

This paper is about a hierarchical structure with an event-based supervisor in a higher level and a fractional-order proportional integral (FOPI) in a lower level applied to a wind turbine. The event-based supervisor analyzes the operation conditions to determine the state of the wind turbine. This controller operate in the full load region and the main objective is to capture maximum power generation while ensuring the performance and reliability required for a wind turbine to be integrated into an electric grid. The main contribution focus on the use of fractional-order proportional integral controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. Comparisons between fractional-order pitch control and a default proportional integral pitch controller applied to a wind turbine benchmark are given and simulation results by Matlab/Simulink are shown in order to prove the effectiveness of the proposed approach.