pinecone/core-2020-05-10-deduplication huggingface dataset:
Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation

Generalized linear mixed models are a widely used tool for modeling longitudinal data. However, their use is typically restricted to few covariates, because the presence of many predictors yields unstable estimates. The presented approach to the fitting of generalized linear mixed
models includes an L1-penalty term that enforces variable selection and shrinkage simultaneously. A gradient ascent algorithm is proposed that allows to maximize the penalized loglikelihood yielding models with reduced complexity. In contrast to common procedures it can be used in high-dimensional settings where a large number of  otentially influential explanatory variables is available. The method is investigated in simulation studies and illustrated by use of real data sets.
Conformational transitions of a semiflexible polymer in nematic solvents

Conformations of a single semiflexible polymer chain dissolved in a low-molecular-weight liquid crystalline solvent (nematogen) are examined by using a mean field theory. We take into account a stiffness and partial orientational ordering of the polymer. As a result of an anisotropic coupling between the polymer and nematogen, we predict a discontinuous (or continuous) phase transition from a condensed-rodlike conformation to a swollen one of the polymer chain, depending on the stiffness of the polymer. We also discuss the effects of the nematic interaction between polymer segments
The α particle based on modern nuclear forces

The Faddeev-Yakubovsky equations for the α particle are solved. Accurate results are obtained for several modern nucleon-nucleon (NN) interaction models, which include charge-symmetry breaking effects in the NN force, nucleon mass dependences as well as the Coulomb interaction. These models are augmented by three-nucleon forces of different types and adjusted to the 3N binding energy. Our results are close to the experimental binding energy with a slight overbinding. Thus there is only little room left for the contribution of possible 4N interactions to the α-particle binding energy. We also discuss model dependences of the binding energies and the wave functions
Delayed-Choice Experiments and the Metaphysics of Entanglement

Delayed-choice experiments in quantum mechanics are often taken to undermine a realistic interpretation of the quantum state. More specifically, Healey has recently argued that the phenomenon of delayed-choice entanglement swapping is incompatible with the view that entanglement is a physical relation between quantum systems. This paper argues against these claims. It first reviews two paradigmatic delayed-choice experiments and analyzes their metaphysical implications. It then applies the results of this analysis to the case of entanglement swapping, showing that such experiments pose no threat to realism about entanglement
Estimation of Triticum aestivum in pasta flour: interspecific limits for sitosteryl palmitate content

Sitosteryl palmitate (SP) content of flour was shown to be not significantly affected by normal variations in milling yield. Since the distribution of fat in a wheat kernel does not follow the same pattern as does SP, it is preferable to consider SP content on the basis of DM content of the flour. A survey of 46 Triticum aestivum and 24 T. durum flours showed that the latter contained SP, but its level did not exceed 1.5 mg/100 g. T. aestivum varieties show a two-peak distribution, with the maxima at approximately 4 mg/100 g and at 12 mg/100 g, respectively. Three T. aestivum flours were within the T. durum range and three others were close to it. Limits for sitosteryl palmitate content in T. aestivum and T. durum were tentatively established at 16.5 mg/100 g and 1.5 mg/100 g respectively. Based on these limits, a method is proposed for the estimation of the minimum amount of T. Aestivum in a mixture
Improvement of Takagi-Sugeno Fuzzy Model for the Estimation of Nonlinear Functions

Two new and efficient approaches are presented to improve the local and global estimation of the Takagi-Sugeno (T-S) fuzzy model. The main aim is to obtain high function approximation accuracy and fast convergence. The main problem is that the T-S identification method can not be applied when the membership functions are overlapped by pairs. The approaches developed here can be considered as generalized versions of T-S method with optimized performance. The first uses the minimum norm approach to search for an exact optimum solution at the expense of increasing complexity and computational cost. The second is a simple and less computational method, based on weighting of parameters. Illustrative examples are chosen to evaluate the potential, simplicity and remarkable performance of the proposed methods and the high accuracy obtained in comparison with the original T-S model
Analysis of global manufacturing virtual networks in the aeronautical industry

The evolution of organizations that work in multinational environments has considerably altered their production strategies. One of the consequences has been the appearance of Global Manufacturing Virtual Networks (GMVNs), which include all kinds of enterprises and production centres and establish a new type of horizontal collaboration and relations between independent companies and even competitors who establish occasional collaborations on projects they could not take on individually. This paper analyses the causes behind the formation of such networks, their strategy, structure, dynamics and evolution, taking into account areas such as strategic intercompany alliances, synchronization of their value and supply chains, their information systems, the cultural aspects of the organizations in question and, finally, their convergence with another of the more relevant future trends in production: mass customization. The proposed model shall be applied to the aeronautical industry which is one of the industries which has developed the GMVN concept. The case study of the engine manufacturer Rolls Royce will provide a better understanding of the evolution of its strategic positioning, as well as the dynamic and fluent nature of its virtual relations. This will demonstrate its effectiveness by clarifying and putting these organizations in perspective and analyzing their evolution over the next few year
Extreme ultraviolet detection using AlGaN-on-Si inverted Schottky photodiodes

We report on the fabrication of aluminum gallium nitride (AlGaN) Schottky diodes for extreme ultraviolet (EUV) detection. AlGaN layers were grown on silicon wafers by molecular beam epitaxy with the conventional and inverted Schottky structure, where the undoped, active layer was grown before or after the n-doped layer, respectively. Different current mechanisms were observed in the two structures. The inverted Schottky diode was designed for the optimized backside sensitivity in the hybrid imagers. A cut-off wavelength of 280 nm was observed with three orders of magnitude intrinsic rejection ratio of the visible radiation. Furthermore, the inverted structure was characterized using a EUV source based on helium discharge and an open electrode design was used to improve the sensitivity. The characteristic He I and He II emission lines were observed at the wavelengths of 58.4 nm and 30.4 nm, respectively, proving the feasibility of using the inverted layer stack for EUV detectio
Design and evaluation of acceleration strategies for speeding up the development of dialog applications

In this paper, we describe a complete development platform that features different innovative acceleration strategies, not included in any other current platform, that simplify and speed up the definition of the different elements required to design a spoken dialog service. The proposed accelerations are mainly based on using the information from the backend database schema and contents, as well as cumulative information produced throughout the different steps in the design. Thanks to these accelerations, the interaction between the designer and the platform is improved, and in most cases the design is reduced to simple confirmations of the “proposals” that the platform dynamically provides at each step.\ud
In addition, the platform provides several other accelerations such as configurable templates that can be used to define the different tasks in the service or the dialogs to obtain or show information to the user, automatic proposals for the best way to request slot contents from the user (i.e. using mixed-initiative forms or directed forms), an assistant that offers the set of more probable actions required to complete the definition of the different tasks in the application, or another assistant for solving specific modality details such as confirmations of user answers or how to present them the lists of retrieved results after querying the backend database. Additionally, the platform also allows the creation of speech grammars and prompts, database access functions, and the possibility of using mixed initiative and over-answering dialogs. In the paper we also describe in detail each assistant in the platform, emphasizing the different kind of methodologies followed to facilitate the design process at each one.\ud
Finally, we describe the results obtained in both a subjective and an objective evaluation with different designers that confirm the viability, usefulness, and functionality of the proposed accelerations. Thanks to the accelerations, the design time is reduced in more than 56% and the number of keystrokes by 84%
LED bulbs technical specification and testing procedure for solar home systems

The definition of technical specifications and the corresponding laboratory procedures are necessary steps in order to assure the quality of the devices prior to be installed in Solar Home Systems (SHS). To clarify and unify criteria a European project supported the development of the Universal Technical Standard for Solar Home Systems (UTSfSHS). Its principles were to generate simple and affordable technical requirements to be optimized in order to facilitate the implementation of tests with basic and simple laboratory tools even on the same SHS electrification program countries. These requirements cover the main aspects of this type of installations and its lighting chapter was developed based on the most used technology at that time: fluorescent tubes and CFLs. However, with the consolidation of the new LED solid state lighting devices, particular attention is being given to this matter and new procedures are required. In this work we develop a complete set of technical specifications and test procedures that have been designed within the frame of the UTSfSHS, based on an intense review of the scientific and technical publications related to LED lighting and their practical application. They apply to lamp reliability, performance and safety under normal, extreme and abnormal operating conditions as a simple but complete quality meter tool for any LED bulb
Conditional density approximations with mixtures of polynomials

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated basis functions (MoTBFs). The empirical results show that the proposed methods generally yield models that are comparable to or significantly better than those found using the MoTBF-based method
A Cooperative Decison Support System for Children's Neurodevelopment Monitoring.

Decision Support Systems can enhance e-Health monitoring and IoT scenarios on the early detection of neurodevelopmental disorders in children. Thus, Ambient Intelligence could support innovative application domains like motor or cognitive impairments? detection at the home environment. The paper describes the design of an innovative cooperative system (Galatea) that supports the refinement process of a Knowledge Base expressed as an OWL ontology. The ontology supports decision-making process and is the core of: (1) a Web-Based Smart System aimed to enhance the screening of language disorders at medical centers and schools by fostering the identification of a developmental disorders before 4 years old of age; (2) a set of child smart care services that use Ambient Intelligent paradigm for early attention of motor impairments in children who are often not diagnosed or treated by health care entities
Intraday empirical analysis and modeling of diversified world stock indices

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)This paper proposes an approach to the intraday analysis of diversified world stock accumulation indices. The growth optimal portfolio (GOP) is used as reference unit or benchmark in a continuous financial market model. Diversified portfolios, covering the world stock market, are constructed and shown to approximate the GOP, providing the basis for a range of financial applications. The normalized GOP is modeled as a time transformed square root process of dimension four. Its dynamics are empirically verified for several world stock indices. Furthermore, the evolution of the transformed time is modeled as the integral over a rapidly evolving mean-reverting market activity process with deterministic volatility. The empirical findings suggest a rather simple and robust model for a world stock index that reflects the historical evolution, by using only a few readily observable parameters
Determination of the mechanical properties of amorphous materials through instrumented nanoindentation

A novel methodology based on instrumented indentation is developed to determine the mechanical properties of amorphous materials which present cohesive-frictional behaviour. The approach is based on the concept of a universal hardness equation, which results from\ud
the assumption of a characteristic indentation pressure proportional to the hardness. The actual universal hardness equation is obtained from a detailed finite element analysis of the process of sharp indentation for a very wide range of material properties, and the inverse\ud
problem (i.e. how to extract the elastic modulus, the compressive yield strength and the friction angle) from instrumented indentation is solved. The applicability and limitations of the novel approach are highlighted. Finally, the model is validated against experimental data\ud
in metallic and ceramic glasses as well as polymers, covering a wide range of amorphous materials in terms of elastic modulus, yield strength and friction angle
Can chemical and molecular biomarkers help discriminate between industrial, rural and urban environments?

Air samples from four contrasting outdoor environments including a park, an arable farm, a waste water treatment plant and a composting facility were analysed during the summer and winter months. The aim of the research was to study the feasibility of differentiating microbial communities from urban, rural and industrial areas between seasons with chemical and molecular markers such as microbial volatile organic compounds (MVOCs) and phospholipid fatty acids (PLFAs). Air samples (3 l) were collected every 2 h for a total of 6 h in order to assess the temporal variations of MVOCs and PLFAs along the day. MVOCs and VOCs concentrations varied over the day, especially in the composting facility which was the site where more human activities were carried out. At this site, total VOC concentration varied between 80 and 170 μg m−3 in summer and 20–250 μg m−3 in winter. The composition of MVOCs varied between sites due to the different biological substrates including crops, waste water, green waste or grass. MVOCs composition also differed between seasons as in summer they are more likely to get modified by oxidation processes in the atmosphere and in winter by reduction processes. The composition of microbial communities identified by the analysis of PLFAs also varied among the different locations and between seasons. The location with higher concentrations of PLFAs in summer was the farm (7297 ng m−3) and in winter the park (11,724 ng m−3). A specific set of MVOCs and PLFAs that most represent each one of the locations was identified by principal component analyses (PCA) and canonical analyses. Further to this, concentrations of both total VOCs and PLFAs were at least three times higher in winter than in summer. The difference in concentrations between summer and winter suggest that seasonal variations should be considered when assessing the risk of exposure to these compounds
Evidence for Quark Gluon Plasma from Hadron Production in High Energy
  Nuclear Collisions

The experimental results on the pion, strangeness and J/psi production in
high energy nuclear collisions are discussed. The anomalous energy dependence
of pion and strangeness production is consistent with the hypothesis that a
transition to a deconfined phase takes place between the top AGS (15 AGeV) and
the SPS (200 AGeV) energies. The J/psi production systematics at the SPS can be
understood assuming that the J/psi mesons are created at hadronization
according to the available hadronic phase space. This new interpretation of the
J/psi data allows one to establish a coherent picture of high energy nuclear
collisions based on the statistical approaches of the collision early stage and
hadronization. Surprisingly, the statistical model of strong interactions is
successful even in the region reserved up to now for pQCD based models
Simple currents versus orbifolds with discrete torsion -- a complete
  classification

We give a complete classification of all simple current modular invariants,
extending previous results for $(\Zbf_p)^k$ to arbitrary centers. We obtain a
simple explicit formula for the most general case. Using orbifold techniques to
this end, we find a one-to-one correspondence between simple current invariants
and subgroups of the center with discrete torsions. As a by-product, we prove
the conjectured monodromy independence of the total number of such invariants.
The orbifold approach works in a straightforward way for symmetries of odd
order, but some modifications are required to deal with symmetries of even
order. With these modifications the orbifold construction with discrete torsion
is complete within the class of simple current invariants. Surprisingly, there
are cases where discrete torsion is a necessity rather than a possibility.Comment: 28 page
The dynamics of narrative writing in primary grade children: Writing process factors predict story quality

In this study of third grade school children, we investigated the association between writing process measures recorded with key stroke logging and the final written product. Moreover, we examined the cognitive predictors of writing process and product measures. Analyses of key strokes showed that while most children spontaneously made local online revisions while writing, few revised previously written text. Children with good reading and spelling abilities made more online revisions than their peers. Two process factors, transcription fluency and online revision activity, contributed to explaining variance in narrative macrostructural quality and story length. As for cognitive predictors, spelling was the only factor that gave a unique contribution to explaining variance in writing process factors. Better spelling was associated with more revisions and faster transcription. The results show that developing writers’ ability to make online revisions in creative writing tasks is related to both the quality of the final written product and to individual literacy skills. More generally, the findings indicate that investigations of the dynamics of the writing process may provide insights into the factors that contribute to creative writing during early stages of literacy
Network assisted content protection architectures for a connected world

Content protection is a key component for the success of a multimedia services platform, as proven by the plethora of solutions currently on the market. In this paper we analyze a new network scenario where permanent bidirectional connectivity and video-aware encryption technologies allow a trustful operation of ubiquitous end devices. We propose new scalable models for a content protection architecture that may achieve dramatic improvement in robustness, reliability, and scalability. Selective ciphering and countermeasures are included in those models, together with several examples of their application
Numerical simulation of group combustion of pulverized coal

A mathematical model for the group combustion of pulverized coal particles was developed in a previous work. It includes the Lagrangian description of the dehumidification, devolatilization and char gasification reactions of the coal particles in the homogenized gaseous environment resulting from the three fuels, CO, H2 and volatiles, supplied by the gasification of the particles and their simultaneous group combustion by the gas phase oxidation reactions, which are considered to be very fast. This model is complemented here with an analysis of the particle dynamics, determined principally by the effects of aerodynamic drag and gravity, and its dispersion based on a stochastic model. It is also extended to include two other simpler models for the gasification of the particles: the first one for particles small enough to extinguish the surrounding diffusion flames, and a second one for particles with small ash content when the porous shell of ashes remaining after gasification of the char, non structurally stable, is disrupted.\ud
\ud
As an example of the applicability of the models, they are used in the numerical simulation of an experiment of a non-swirling pulverized coal jet with a nearly stagnant air at ambient temperature, with an initial region of interaction with a small annular methane flame. Computational algorithms for solving the different stages undergone by a coal particle during its combustion are proposed. For the partial differential equations modeling the gas phase, a second order finite element method combined with a semi-Lagrangian characteristics method are used. The results obtained with the three versions of the model are compared among them and show how the first of the simpler models fits better the experimental results