crs: A package for nonparametric spline estimation in R

crs is a library for R written by Jeffrey S. Racine (Maintainer) and Zhenghua Nie. This add-on package provides a collection of functions for spline-based nonparametric estimation of regression functions with both continuous and categorical regressors. Currently, the crs package integrates data-driven methods for selecting the spline degree, the number of knots and the necessary bandwidths for nonparametric conditional mean, IV and quantile regression. A function for multivariate density spline estimation with mixed data is also currently in the works. As a bonus, the authors have also provided the first simple R interface to the NOMAD (‘nonsmooth mesh adaptive direct search’) optimization solver which can be applied to solve other mixed integer optimization problems that future users might find useful in other settings. Although the crs package shares some of the same functionalities as its kernel-based counterpart—the np package by the same author—it currently lacks some of the features the np package provides, such as hypothesis testing and semiparametric estimation. However, what it lacks in breadth, crs makes up in speed. A Monte Carlo experiment in this review uncovers sizable speed gains compared to its np counterpart, with a marginal loss in terms of goodness of fit. Therefore, the package will be extremely useful for applied econometricians interested in employing nonparametric techniques using large amounts of data with a small number of discrete covariates

The value of express delivery services for cross-border e-commerce in European Union markets

Further growth of cross-border e-commerce in the European Union markets requires improved express delivery services. The framework presented in this paper identifies relevant contextual factors that affect express delivery adoption rates in European cross-border e-commerce. This framework leads to a set of hypotheses, both on the effects of express deliveries on financial performance indicators (order incidence, order size, and repurchase rate) and on the factors that drive demand for express deliveries (consumer income, logistic costs, and lead-time benefits). A case study provides empirical tests of the hypotheses, using data on about forty thousand sales transactions from a consumer electronics manufacturer’s cross-border online shop. The findings are that express delivery has positive effects on financial performance, as it leads to higher order incidence, larger order size, and higher repurchase rates in cross-border transactions. Demand for express delivery services increases with higher income, larger lead-time benefits, and lower logistic costs. Managers can employ the presented framework to formulate and analyse their own targets for performance and express delivery services

Neutron beam test of CsI crystal for dark matter search

We have studied the response of Tl-doped and Na-doped CsI crystals to nuclear recoils and $\gamma$'s below 10 keV. The response of CsI crystals to nuclear recoil was studied with mono-energetic neutrons produced by the $^3$H(p,n)$^3$He reaction. This was compared to the response to Compton electrons scattered by 662 keV $\gamma$-ray. Pulse shape discrimination between the response to these $\gamma$'s and nuclear recoils was studied, and quality factors were estimated. The quenching factors for nuclear recoils were derived for both CsI(Na) and CsI(Tl) crystals.Comment: 21pages, 14figures, submitted to NIM

Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions

Introduction to Holographic Superconductors

These lectures give an introduction to the theory of holographic superconductors. These are superconductors that have a dual gravitational description using gauge/gravity duality. After introducing a suitable gravitational theory, we discuss its properties in various regimes: the probe limit, the effects of backreaction, the zero temperature limit, and the addition of magnetic fields. Using the gauge/gravity dictionary, these properties reproduce many of the standard features of superconductors. Some familiarity with gauge/gravity duality is assumed. A list of open problems is included at the end.Comment: 34 pages, 10 figures, to appear in the proceedings of the 5th Aegean Summer School, "From Gravity to Thermal Gauge Theories: the AdS/CFT Correspondence"; v2: references adde

CFD Simulation of Liquid-solid Multiphase Flow in Mud Mixer

In the present study, a computational fluid dynamics (CFD) simulation was performed to analyze the mixing phenomena associated with multi-phase flow in a mud mixing system. For the validation of CFD simulation, firstly a liquid-solid multiphase flow inside horizontal pipe was simulated and compared with the experiments and other numerical simulations. And then, the multiphase flow simulation was carried out for the mud mixer in the drilling handling system in order to understand mixing phenomena and predict the mixing efficiency. For the modeling and simulation, a commercial software, STAR-CCM+, based on a finite-volume method (FVM) was adopted. The simulation results for liquid-solid flow inside the pipe shows a good agreement with the experimental data. With the same multiphase model, the simulation for mud mixer is performed under the generalized boundary condition and then pressure drop through the mud mixer will be discussed

Modelling of strain effects in manganite films

Thickness dependence and strain effects in films of $La_{1-x}A_xMnO_3$ perovskites are analyzed in the colossal magnetoresistance regime. The calculations are based on a generalization of a variational approach previously proposed for the study of manganite bulk. It is found that a reduction in the thickness of the film causes a decrease of critical temperature and magnetization, and an increase of resistivity at low temperatures. The strain is introduced through the modifications of in-plane and out-of-plane electron hopping amplitudes due to substrate-induced distortions of the film unit cell. The strain effects on the transition temperature and transport properties are in good agreement with experimental data only if the dependence of the hopping matrix elements on the $Mn-O-Mn$ bond angle is properly taken into account. Finally variations of the electron-phonon coupling linked to the presence of strain turn out important in influencing the balance of coexisting phases in the filmComment: 7 figures. To be published on Physical Review

Data-driven Warehouse Management in Global Supply Chains

Warehouse management has emerged as a determinant for success of global supply chain management. This thesis focuses on how to solve warehouse challenges in global supply chain management (SCM) that is characterized by large volume uncertainty, great responsiveness needs and complex order-fulfilment collaboration with other functionalities. We employ data analytic methods to exploit the rich data information obtained from detailed registration of daily warehouse operations to address these challenges. By providing actual application examples in real-world situations we showcase the potency of such data-driven warehouse management. In this dissertation, data-driven warehouse management is presented by four-steps in the time horizon of warehouse operations: Long-term opportunities (for the coming years) are examined by predictive analytics for expanding cross-border e-commerce in the European Union. Mid-term demand for spare parts during the end-of-life phase (of several months) are forecasted by means of data-driven modelling for installed base. Short-term operational opportunity (weekly or daily) are presented by employing detailed productivity data to sustain effective operation of variable warehouse resources. Real-time (hourly or shorter) data applications are introduced for job priority allocation to improve daily responsiveness in warehouse order fulfilment. All these data analytic methods can be incorporated in warehouse management systems where practitioners can tune the specific strategies according to their warehouse constraints, including location cost, labour cost, time criticality, and freight company flexibility. In this way, data analytics at the warehouse level offers great opportunities for managing increasing uncertainties and performance requirements in global SCM

Average Lattice Symmetry and Nanoscale Structural Correlations in Magnetoresistive Manganites

We report x-ray scattering studies of nanoscale structural correlations in the paramagnetic phases of the perovskite manganites La$_{0.75}$(Ca$_{0.45}$Sr$_{0.55}$)$_{0.25}$MnO$_3$, La$_{0.625}$Sr$_{0.375}$MnO$_3$, and Nd$_{0.45}$Sr$_{0.55}$MnO$_3$. We find that these correlations are present in the orthorhombic $O$ phase in La$_{0.75}$(Ca$_{0.45}$Sr$_{0.55}$)$_{0.25}$MnO$_3$, but they disappear abruptly at the orthorhombic-to-rhombohedral transition in this compound. The orthorhombic phase exhibits increased electrical resistivity and reduced ferromagnetic coupling, in agreement with the association of the nanoscale correlations with insulating regions. In contrast, the correlations were not detected in the two other compounds, which exhibit rhombohedral and tetragonal phases. Based on these results, as well as on previously published work, we propose that the local structure of the paramagnetic phase correlates strongly with the average lattice symmetry, and that the nanoscale correlations are an important factor distinguishing the insulating and the metallic phases in these compounds.Comment: a note on recent experimental work, and a new reference adde

Improving warehouse responsiveness by job priority management

Warehouses employ order cut-off times to ensure sufficient time for fulfilment. To satisfy higher consumer expectations, these cut-off times are gradually postponed to improve order responsiveness. Warehouses therefore have to allocate jobs more efficiently to meet compressed response times. Priority job management by means of flow-shop models has been used mainly for manufacturing systems but can also be applied for warehouse job scheduling to accommodate tighter cut-off times. This study investigates which priority rule performs best under which circumstances. The performance of each rule is evaluated in terms of a common cost criterion that integrates the objectives of low earliness, low tardiness, low labour idleness, and low work-in-process stocks. A real-world case study for a warehouse distribution centre of an original equipment manufacturer in consumer electronics provides the input parameters for a simulation study. The simulation outcomes validate several strategies for improved responsiveness. In particular, the critical ratio rule has the fastest flow-time and performs best for warehouse scenarios with expensive products and high labour costs