Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid method of plane-wave and cylindrical-wave expansions for distributed Bragg-reflector pillars: formalism and its application to topological photonics

A hybrid computational method of plane-wave and cylindrical-wave expansions for distributed Bragg-reflector (DBR) pillars is proposed. The plane-wave expansion is employed to represent the one-dimensional periodic structure of the DBR. The cylindrical-wave expansion is employed to describe the scattering by circular pillars with the DBR structure inside. This formalism enables us to calculate the radiation fields, t matrices, scattering cross sections, photonic band structures, and quality factors of the DBR pillars. Furthermore, optical properties of arrayed DBR pillars are also investigated with the aid of the multiple-scattering method. Using this formalism, we demonstrate explicitly that high Q photonic band modes including the so-called bound states in continuum are obtained both in isolated and arrayed DBR pillars. We also present a novel formation of gapless Dirac-cone surface states in a three-dimensional photonic crystal composed of a two-dimensional periodic arrangement of core-shell DBR pillars.
etecting resting-state functional connectivity in the anguage system using functional near-infrared pectroscopy

u-Feng Zang an-Lin Peng hao-Zhe Zhu eijing Normal University tate Key Laboratory of Cognitive Neuroscience and Learning in Jie Kou Wai Street 19 eijing 100875 China Abstract. Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy fNIRS was demonstrated as a feasible method to study resting–state functional connectivity RSFC in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and highlevel neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach. © 2010 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.3462973
Smart Specialisation for Economic Change: The Case of Spain

Smart specialisation concept acquired a remarkable importance in the current regional policy as a model to understand the role of territories in international competitiveness. In fact, the definition of Smart Specialisation Strategies (RIS3) has become an ex ante conditionality for European regional policy in the period 2014-2020. Although the process of definition has been a good opportunity to rethink and improve the policymaking, it has not been out of difficulties and barriers since it is not always easy to translate academic concepts to real policies in the field. These difficulties are analysed from a threefold perspective: the definition, implementation and evaluation of RIS3. These three aspects are seen in the recently finished Spanish RIS3, with specific attention to: priority setting, policy instruments, and evaluation.
Quasiparticle energies and excitonic effects in dense solid hydrogen near metallization

We investigate the crucial metallization pressure of the $Cmca\text{\ensuremath{-}}12$ phase of solid hydrogen (H) using many-body perturbation theory within the $GW$ approximation. We consider the effects of self-consistency, plasmon-pole models, and the vertex correction on the quasiparticle band gap $({E}_{\mathrm{g}})$. Our calculations show that self-consistency leads to an increase in ${E}_{\mathrm{g}}$ by 0.33 eV over the one-shot ${G}_{0}{W}_{0}$ approach. Because of error cancellation between the effects of self-consistency and the vertex correction, the simplest ${G}_{0}{W}_{0}$ method underestimates ${E}_{\mathrm{g}}$ by only 0.16 eV compared with the prediction of the more accurate $GW\ensuremath{\Gamma}$ approach. Employing the plasmon-pole models underestimates ${E}_{\mathrm{g}}$ by 0.1\char21{}0.2 eV compared to the full-frequency numerical integration results. We thus predict a metallization pressure around 280 GPa, instead of 260 GPa predicted previously. Furthermore, we compute the optical absorption including the electron-hole interaction by solving the Bethe-Salpeter equation (BSE). The resulting absorption spectra demonstrate substantial redshifts and enhancement of absorption peaks compared to the calculated spectra neglecting excitonic effects. We find that the exciton binding energy decreases with increasing pressure from 66 meV at 100 GPa to 12 meV at 200 GPa due to the enhanced electronic screening as solid H approaches metallization. Because optical measurements are so important in identifying the structure of solid H, our BSE results should improve agreement between theory and experiment.
Examining Delay Discounting and Response to Incentive-Based Smoking-Cessation Treatment Among Pregnant Women

Delay discounting is considered by many to be a risk factor for substance use disorders and other health-related behavior problems. While these health-related behavior problems are often treated with incentive-based interventions, little is known about whether delay discounting (DD) moderates response to that treatment approach. The present study examined how response to incentive-based smoking-cessation treatment varied as a function of baseline DD scores among pregnant women participating in randomized controlled clinical trials examining the efficacy of financial incentives. Women were assigned to a condition wherein they earned vouchers exchangeable for retail items contingent on abstinence from recent smoking or to a control condition wherein they received vouchers of comparable value but independent of smoking status. Individual differences in DD of hypothetical monetary rewards were measured at the study intake and follow-up assessments. We examined whether individual differences in baseline scores on that instrument predict antepartum and postpartum smoking status using logistic regression, and if sustaining abstinence caused changes in DD scores from intake to 24-weeks postpartum. We did not see any significant main effects of DD or interactions of DD with treatment on antepartum or postpartum smoking status. Treatment condition, baseline smoking rate (cigs/day), a history of quit attempts pre-pregnancy, and educational attainment were all associated with increased odds of abstaining from smoking at the late-pregnancy antepartum assessment, and treatment condition was the only significant predictor of abstaining from smoking at 24-weeks postpartum, three months after the treatment formally ended. We saw no discernible evidence that sustained abstinence from smoking was associated with post-treatment decreases in DD. Overall, we saw no evidence that being a steeper discounter is associated with a lack of success in quitting smoking in either treatment condition. Being assigned to the incentives condition was the only predictor of antepartum and postpartum abstinence. The observed associations of a lower baseline smoking rate, higher educational attainment, and a history of having attempted to quit smoking previously with increased odds of success in achieving antepartum smoking abstinence is consistent with results from previous reports on predictors of response to this treatment underscoring the reliability of these relationships.
2 Random Walk Framework 2 . 1 Graphs , Random Search Strategies and their Analysis

We investigate hide-and-seek games on complex networks using a random walk framework. Specifically, we investigate the efficiency of various degree-biased random walk search strategies to locate items that are randomly hidden on a subset of vertices of a random graph. Vertices at which items are hidden in the network are chosen at random as well, though with probabilities that may depend on degree. We pitch various hide and seek strategies against each other, and determine the efficiency of search strategies by computing the average number of hidden items that a searcher will uncover in a random walk of n steps. Our analysis is based on the cavity method for finite single instances of the problem, and generalises previous work of De Bacco et al. [1] so as to cover degree-biased random walks. We also extend the analysis to deal with the thermodynamic limit of infinite system size. We study a broad spectrum of functional forms for the degree bias of both the hiding and the search strategy and investigate the efficiency of families of search strategies for cases where their functional form is either matched or unmatched to that of the hiding strategy. Our results are in excellent agreement with those of numerical simulations. We propose two simple approximations for predicting efficient search strategies. One is based on an equilibrium analysis of the random walk search strategy. While not exact, it produces correct orders of magnitude for parameters characterising optimal search strategies. The second exploits the existence of an effective drift in random walks on networks, and is expected to be efficient in systems with low concentration of small degree nodes.
Comparative mapping of Cucurbita moschata and C. pepo using SSR markers.

The first SSR-based genetic linkage map of C. moschata was created by integrating the maps of two F2 populations with one common parent developed from the crosses Waltham Butternut (WB) × Nigerian Local (NL) and ZHOU (a hull-less type) × WB. This integrated C. moschata map comprises 205 SSR markers and 2 morphological traits (Gr and n). The map is composed of 27 linkage groups with a marker density of 7 cM. Comparison of the C. moschata map and the published C. pepo map revealed a high level of macro-synteny. Seventy-one common SSR markers between C. moschata and C. pepo are located in homologous linkage groups. These markers representing orthologous loci in general have conserved orders and similar genetic distances. Four SSR markers were mapped in non-homologous linkage groups. They may represent different members of multi-gene families, chromosomal rearrangements and paralogs. The comparative mapping of C. moschata and C. pepo reported here will be useful for further studies on Cucurbit evolution, gene isolation, and breeding. INTRODUCTION C. pepo (2n=2x=40) and C. moschata (2n=2x=40), two species of the genus Cucurbita, are economically important crops worldwide (Robinson and DeckerWalters 1997, Loy 2004). Genetic mapping in the genus Cucurbita was hampered by the lack of available sequence specific markers. Based on anonymous RAPD and AFLP markers, two maps using inter-specific crosses between C. pepo and C. moschata (Lee et al. 1995; Brown and Myers 2002) and one map of C. pepo (Zraidi et al. 2007) were developed, which did not allow comparative analysis between species. This, however, became possible after the development of a large number of SSR markers specific for Cucurbita (Gong et al. 2008), which allowed updating the C. pepo map published by Zraidi et al. (2007). Well developed SSR maps are of great value for comparative genetics and to accelerate marker-assisted selection (MAS). Genome sequence information in Cucurbita is very limited yet; the comparative mapping of C. moschata and C. pepo may contribute to future Cucurbita genomic studies. MATERIALS AND METHODS Cucurbitaceae 2008, Proceedings of the IX EUCARPIA meeting on genetics and breeding of Cucurbitaceae (Pitrat M, ed), INRA, Avignon (France), May 21-24, 2008
Forecasting Global Equity Indices Using Large Bayesian VARs

This paper proposes a large Bayesian Vector Autoregressive (BVAR) model with common stochastic volatility to forecast global equity indices. Using a dataset consisting of monthly data on global stock indices the BVAR model inherently incorporates co-movements in the stock markets. The time-varying specification of the covariance structure moreover accounts for sudden shifts in the level of volatility. In an out-of-sample forecasting application we show that the BVAR model with stochastic volatility significantly outperforms the random walk both in terms of root mean squared errors as well as Bayesian log predictive scores. The BVAR model without stochastic volatility, on the other hand, underperforms relative to the random walk. In a portfolio allocation exercise we moreover show that it is possible to use the forecasts obtained from our BVAR model with common stochastic volatility to set up simple investment strategies. Our results indicate that these simple investment schemes outperform a naive buy-and-hold strategy.
Memory as an Elephant: How prior Events Determine User Attitudes in ERP Implementation

Assimilation of a standard ERP system to an organization is difficult. User involvement seems to be the crux of the matter. However, even the best intentions for user involvement may come to nothing. A case study of a five year ERP implementation process reveals that a main reason for this miss may be that the perception of usefulness in any given phase of the implementation is heavily dependant on preceding events – the process. A process model analysis identifies eight episodes and nine encounters in the case showing that users attitude towards an ERP system change between acceptance, equivocation, resistance and rejection depending on three things: (1) Dynamic between user and consultants, (2) Dynamic between different user groups, and (3) Understanding of technical, organizational and socio-technical options.
Coupled Fluid-Thermal-Structural Simulations In Microvalves And Microchannels

This paper presents the results of high-fidelity, 3-D simulations of coupled flow, heat-transfer and structural mechanics simulations of microchannels, micropumps, microvalves, and time-accurate simulations of a microoscillator. In each of these cases, the simulated results were compared with experimental and/or other published data, with excellent agreement. These results demonstrate the capabilities, accuracy and speed of the simulation tools for predictions of coupled, complex multi-physics processes in MEMS devices and their utility during the design phases of these devices for optimization and performance prediction.
On Identification of Parallel Cascade Serial Systems

Abstract We consider identification of systems with a parallel serial (cascade) structure with multiple-input and multiple-output signals. The statistical properties of estimated models are studied with respect to input signals and possible sensor locations. The quality of the estimates are analyzed by means of the asymptotic covariance matrix of the estimated parameters. This is an extension of previous work on identification of cascaded linear systems. The key result concerns systems where the sub-systems have common dynamics. An interesting observation is that for this case the variance for the parameters belonging to the unmeasured subsystem always is larger than for the other sub-systems. This is not true for general parameters. The variance results can be used for optimal input and sensor location design. The results are illustrated by some simple FIR examples and numerical evaluations.
Vacant parking area estimation through background subtraction and transience map analysis

A method for estimating the dimensions of non-delimited free parking areas by using a static surveillance camera is proposed. The proposed method is specially designed to tackle the main challenges of urban scenarios (multiple moving objects, outdoor illumination conditions and occlusions between vehicles) with no training. The core of this work is the temporal analysis of the video frames to detect the occupancy variation of the parking areas. Two techniques are combined: background subtraction using a mixture of Gaussians to detect and track vehicles and the creation of a transience map to detect the parking and leaving of vehicles. The authors demonstrate that the proposed method yields satisfactory estimates on three real scenarios while being a low computational cost solution that can be applied in any kind of parking area covered by a single camera.
Tensile Properties of Bamboo Fiber-reinforced Polypropylene Composites Modified by Impregnation with Calcium Carbonate Nanoparticles

Tensile properties of bamboo fiber (BF)/polypropylene (PP) composites were investigated for different impregnation modification processes. The surface morphology of BF and the fracture morphology of the BF/PP composites were examined by scanning electron microscopy (SEM). Images showed that CaCO3 nanoparticles (nano-CaCO3) adhered to the fiber surfaces. Tension tests of individual bamboo fibers (IBFs) and the BF/PP composites were conducted. The results indicated that the tensile strength (TS), modulus of elasticity (MOE), and elongation at break (EAB) of IBFs increased by 16.0%, 22.2%, and 5.2%, respectively, while those of the BF/PP composites increased by 3.0%, 7.0%, and 15.8%, respectively, compared to the control samples. Various process parameters during the impregnation with nano-CaCO3 had marked effects on the tensile properties of the composites. The optimal conditions for BF-reinforced PP composites by impregnation modification were determined to be a nano-CaCO3 concentration of 1.0×10-2 g/mL, an ethylenediamine tetraacetic acid disodium salt (EDTA-2Na) additive concentration of 8.5×10-4 g/mL, and an impregnation time of 25 min.
Optimal sizing of PV-FC-Battery hybrid system with Energy Based Approach and PSO

The intermittent nature of renewable energy sources is a major challenge in designing standalone hybrid systems. Over sizing of system components increases the cost of the system and under sizing causes a lack of reliability. In this paper optimal hybrid system sizing method has been proposed using particle swarm optimization algorithm. The optimal system size has been determined for a photovoltaic-fuel cell-battery hybrid system considering annualized cost of the system and reliability constraint. The hybrid system is simulated to determine the size of all system components and to test the effectiveness of the proposed algorithm over the energy based system sizing method. Simulation results show that optimal system configuration is able to supply the stand alone load throughout the year and system cost is also less with the proposed algorithm. KeywordsEnergy Management, Hybrid System, Optimization, PSO, Sizing.
A Note On The Defininiton of An Orlicz Space

The Orlicz spaces were introduced by Z.W. Birnbaum and W. Orlicz in 1931 as a natural generalization of the classical Lebesgue spaces. For this generalization the function �ݔ ௣ � entering in the definition of Lebesgue's space is replaced by a more general convex function Ф. Until today, Orlicz spaces have been studied by many authors from a different aspects. But, most of these studies used different definitions for the convex function Ф to define the Orlicz spaces. In this paper we will investigate the exact relationships between these different definitions of convex functions Ф and obtain the differences between the corresponding Orlicz spaces.
The triple system HD 150136: From periastron passage to actual masses

Context. The triple system HD 150136 is composed of an O3 V((f*))–O3.5 V((f+)) primary, of an O5.5–6 V((f)) secondary, and of a more distant O6.5–7 V((f)) tertiary. The latter component went through periastron in 2015–2016, an event that will not occur again within the next eight years. Aims. We aim to analyse the tertiary periastron passage to determine the orbital properties of the outer system, to constrain its inclination and its eccentricity, and to determine the actual masses of the three components of the system. Methods. We conducted an intensive spectroscopic monitoring of the periastron passage of the tertiary component and combined the outcoming data with new interferometric measurements. This allows us to derive the orbital solution of the outer orbit in three-dimensional space. We also obtained the light curve of the system to further constrain the inclination of the inner binary. Results. We determine an orbital period of 8.61 ± 0.02 years, an eccentricity of 0.682 ± 0.002, and an inclination of 106.18 ± 0.14° for the outer orbit. The actual masses of the inner system and of the tertiary object are 72.32−8.49+8.45 M⊙ and 15.54−4.97+4.96 M⊙, respectively. From the mass of the inner system and accounting for the known mass ratio between the primary and the secondary, we determine actual masses of 42.81 M⊙ and 29.51 M⊙ for the primary and the secondary components, respectively. We infer, from the different mass ratios and the inclination of the outer orbit, an inclination of 62.4° for the inner system. This value is confirmed by photometry. Grazing eclipses and ellipsoidal variations are detected in the light curve of HD 150136. We also compute the distance of the system to 1.096 ± 0.274 kpc. Conclusions. By combining spectroscopy, interferometry, and photometry, HD 150136 offers us a unique chance to compare theory and observations. The masses estimated through our analysis are smaller than those constrained by evolutionary models. The formation of this triple system suggests similar ages for the three components within the errorbars. Finally, we show that Lidov–Kozai cycles have no effect on the evolution of the inner binary, which suggests that the latter will experience mass transfer leading to a merger of the two stars.
A multiresolution approach for image morphing

A new multiresolution approach for image morphing is proposed in this research. By exploring the fact that the human visual system recognizes primarily global features of objects in a fast changing image sequence, we use mainly the low frequency information of images in morphing. Besides, we consider the morphing process in the wavelet domain rather than in the spatial domain and, as a consequence, both spatial and frequency characteristics of the initial and final images in a range of resolution scales can be effectively used. Experimental results of morphing of two face images are given 20 illustrate the performance of the proposed method. <<ETX>>
Classification of kidney and liver tissue using ultrasound backscatter data

Ultrasound (US) tissue characterization provides valuable information for the initialization of automatic segmentation algorithms, and can further provide complementary information for diagnosis of pathologies. US tissue characterization is challenging due to the presence of various types of image artifacts and dependence on the sonographer’s skills. One way of overcoming this challenge is by characterizing images based on the distribution of the backscatter data derived from the interaction between US waves and tissue. The goal of this work is to classify liver versus kidney tissue in 3D volumetric US data using the distribution of backscatter US data recovered from end-user displayed Bmode image available in clinical systems. To this end, we first propose the computation of a large set of features based on the homodyned-K distribution of the speckle as well as the correlation coefficients between small patches in 3D images. We then utilize the random forests framework to select the most important features for classification. Experiments on in-vivo 3D US data from nine pediatric patients with hydronephrosis showed an average accuracy of 94% for the classification of liver and kidney tissues showing a good potential of this work to assist in the classification and segmentation of abdominal soft tissue.