Miracle-dz/UniFAR-FTUs huggingface dataset:
The improvement of ICA with projection technique in multitask fMRI data analysis

The existence of the potential non-independency between task-related components in multi-task functional magnetic resonance imaging (fMRI) studies limits the general application of Independent Component Analysis (ICA) method. The ICA with projection (ICAp) method proposed by Long (2009, HBM) demonstrated its capacity to solve the interaction among task-related components of multi-task fMRI data. The basic idea of projection is to remove the influence of the uninteresting tasks through projection in order to extract one interesting task-related component. However, both the stimulus paradigm of each task and the homodynamic response function (HRF) are essential for the projection. Due to the noises in the data and the variability of the HRF across the voxels and subjects, the ideal time course of each task for projection would be deviant from the true value, which might worsen the ICAp results. In order to make the time courses for projection closer to the true value, the iterative ICAp is proposed in this study. The iterative ICAp is based on the assumption that the task-related time courses extracted from the fMRI data by ICAp is more approximate to the true value than the ideal reference function. Simulated experiment proved that both the spatial detection power and the temporal accuracy of time course were increased for each task-related component. Moreover, the results of the real two-task fMRI data were also improved by the iterative ICAp method.
Decay of ionization impulses in the D and E regions of the ionosphere

This paper extends an analysis by C.M. Grain and H.G. Booker of the decay of ionization impulses in the D and E regions of the ionosphere. They pointed out that, considering the ambient ionization in these regions, the lifetime of added ionization such as would result from nuclear bursts in space was greatest near 75 km during the day and 95 km at night. Their limited calculations are here extended to a wider range of altitudes, and detailed results are given for times up to several thousand seconds after the ionization impulsess.
Combining evidence on air pollution and daily mortality from the 20 largest US cities: a hierarchical modelling strategy

Reports over the last decade of association between levels of particles in outdoor air and daily mortality counts have raised concern that air pollution shortens life, even at concentrations within current regulatory limits. Criticisms of these reports have focused on the statistical techniques that are used to estimate the pollution–mortality relationship and the inconsistency in findings between cities. We have developed analytical methods that address these concerns and combine evidence from multiple locations to gain a unified analysis of the data. The paper presents log‐linear regression analyses of daily time series data from the largest 20 US cities and introduces hierarchical regression models for combining estimates of the pollution–mortality relationship across cities. We illustrate this method by focusing on mortality effects of PM10 (particulate matter less than 10 μm in aerodynamic diameter) and by performing univariate and bivariate analyses with PM10 and ozone (O3) level. In the first stage of the hierarchical model, we estimate the relative mortality rate associated with PM10 for each of the 20 cities by using semiparametric log‐linear models. The second stage of the model describes between‐city variation in the true relative rates as a function of selected city‐specific covariates. We also fit two variations of a spatial model with the goal of exploring the spatial correlation of the pollutant‐specific coefficients among cities. Finally, to explore the results of considering the two pollutants jointly, we fit and compare univariate and bivariate models. All posterior distributions from the second stage are estimated by using Markov chain Monte Carlo techniques. In univariate analyses using concurrent day pollution values to predict mortality, we find that an increase of 10 μg m‐3 in PM10 on average in the USA is associated with a 0.48% increase in mortality (95% interval: 0.05, 0.92). With adjustment for the O3 level the PM10‐coefficient is slightly higher. The results are largely insensitive to the specific choice of vague but proper prior distribution. The models and estimation methods are general and can be used for any number of locations and pollutant measurements and have potential applications to other environmental agents.
Theory of boron-vacancy complexes in silicon

The substitutional boron-vacancy ${\mathrm{B}}_{s}\mathrm{V}$ complex in silicon is investigated using the local density functional theory. These theoretical results give an explanation of the experimentally reported, well established metastability of the boron-related defect observed in $p$-type silicon irradiated at low temperature and of the two hole transitions that are observed to be associated with one of the configurations of the metastable defect. ${\mathrm{B}}_{s}\mathrm{V}$ is found to have several stable configurations, depending on charge state. In the positive charge state the second nearest neighbor configuration with ${C}_{1}$ symmetry is almost degenerate with the second nearest neighbor configuration that has ${C}_{1h}$ symmetry since the bond reconstruction is weakened by the removal of electrons from the center. A third nearest neighbor configuration of ${\mathrm{B}}_{s}\mathrm{V}$ has the lowest energy in the negative charge state. An assignment of the three energy levels associated with ${\mathrm{B}}_{s}\mathrm{V}$ is made. The experimentally observed ${E}_{v}+0.31\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$ and ${E}_{v}+0.37\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$ levels are related to the donor levels of second nearest neighbor ${\mathrm{B}}_{s}\mathrm{V}$ with ${C}_{1}$ and ${C}_{1h}$ symmetry respectively. The observed ${E}_{v}+0.11\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$ level is assigned to the vertical donor level of the third nearest neighbor configuration. The boron-divacancy complex ${\mathrm{B}}_{s}{\mathrm{V}}_{2}$ is also studied and is found to be stable with a binding energy between ${\mathrm{V}}_{2}$ and ${\mathrm{B}}_{s}$ of around $0.2\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$. Its energy levels lie close to those of the ${\mathrm{V}}_{2}$. However, the defect is likely to be an important defect only in heavily doped material.
MET-RODOS: A Comprehensive Atmospheric Dispersion Module

A comprehensive meteorological dispersion module called MET-RODOS is being developed to serve the real-time RODOS (1-3) decision support system with an integrated prediction capability for airborne radioactive spread, deposition and gamma radiation exposure on all scales. Deposition, ground level air concentrations, and ground level gamma dose rates from up to 15 simultaneous released nuclides are calculated using a nested system of local and long range atmospheric dispersion models, driven by real-time available on-line meteorological information. The MET-RODOS module uses concurrently the available source term and weather information in the RODOS data base system, and returns, up to +36 h forecasts of nuclei-specific air and deposited concentrations including gamma dose rate estimations for display and subsequent processing within the RODOS framework. Weather and meteorology is available to the system via on-line connections to on-site local meteorological observations (met-towers and sodars) and via network (either public domain Internet or user-owned point-to-point ISDN) connections to remote national or international meteorological forecasting services. In its final form, scheduled for operational use in 1999, the MET-RODOS meteorological module is intended to service the RODOS system with actual and forecast (+36 h) nuclei-specific air concentrations, deposition values, and gamma radiation estimates on the local, national, and European scale. Provisions are furthermore being made for accommodating on-line available radiological monitoring data in the meteorological model chains in order for the module to assist with source term determination based on real-time data assimilation and back-fitting procedures.
A review of survival trees

This paper presents a non–technical account of the developments in tree–based methods for the analysis of survival data with censoring. This review describes the initial developments, which mainly extended the existing basic tree methodologies to censored data as well as to more recent work. We also cover more complex models, more specialized methods, and more specific problems such as multivariate data, the use of time–varying covariates, discrete–scale survival data, and ensemble methods applied to survival trees. A data example is used to illustrate some methods that are implemented in R.
ESPRESSO instrument control electronics: a PLC based distributed layout for a second generation instrument at ESO VLT

ESPRESSO is an ultra-stable fiber-fed spectrograph designed to combine incoherently the light coming from up to 4 Unit Telescopes of the ESO VLT. From the Nasmyth focus of each telescope the light, through an optical path, is fed by the Coudé Train subsystems to the Front End Unit placed in the Combined Coudé Laboratory. The Front End is composed by one arm for each telescope and its task is to convey the incoming light, after a calibration process, into the spectrograph fibers. To perform these operations a large number of functions are foreseen, like motorized stages, lamps, digital and analog sensors that, coupled with dedicated Technical CCDs (two per arms), allow to stabilize the incoming beam up to the level needed to exploit the ESPRESSO scientific requirements. The Instrument Control Electronics goal is to properly control all the functions in the Combined Coudé Laboratory and the spectrograph itself. It is fully based on a distributed PLC architecture, abandoning in this way the VME-based technology previously adopted for the ESO VLT instruments. In this paper we will describe the ESPRESSO Instrument Control Electronics architecture, focusing on the distributed layout and its interfaces with the other ESPRESSO subsystems.
Thermal Stress Development Due to Laser Step Input Pulse Heating

The closed form solution for the thermal stress distribution inside the substrate material is obtained for a stress-free boundary condition at the surface, which is the most practical situation in laser material processing. Since the molecules in the liquid and gas phases are free to move, the thermal strains in these phases are significantly small, so that the thermal stress field is formulated for the solid phase and the heat conduction equation for solid heating, therefore, considered only. It is found that the temperature in the region next to the surface vicinity drops sharply while the temperature reduces gradually in the surface vicinity due to the high amount of energy absorption from the irradiated field in this region. The variation in the temperature gradient in the surface region results in thermal stress waves propagating into the substrate material at a constant speed. Thermal stress below the surface is compressive due to high thermal strain developing in this region.
NONPARAMETRIC TESTS FOR TREND DETECTION IN WATER QUALITY TIME SERIES

A review of nonparametric tests for trend leads to the conclusion that Mann-Whitney, Spearman, and Kendall tests are the best choice for trend detection in water quality time series. Recently these tests have been adapted to account for dependence and seasonality in such series. For monotonic trends, a procedure allowing to select the pertinent tests considering the characteristics of time series is proposed and the practical limitations of the tests are also brought out. This procedure has been applied to identify the appropriate trend detection test for the time series of nine water quality parameters at Lake Laflamme (Quebec). When a time series can be tested with the Mann-Whitney, Kendall, Spearman, or Lettenmaier (1976) test, the number of observations required to detect trends of a given magnitude, for selected significance and power levels can be calculated with the power function of the t test. When the test proposed by Hirsch, et al., Hirsch and Slack, or Farrell need to be used, the number of observations can only be estimated approximately from the results of empirical power studies.
Vacuum entanglement and black hole entropy of gauge fields

Black holes in general relativity carry an entropy whose value is given by the Bekenstein-Hawking formula, but whose statistical origin remains obscure. Such horizons also possess an entanglement entropy, which has a clear statistical meaning but no a priori relation to the dynamics of gravity. For free minimally-coupled scalar and spinor fields, these two quantities are intimately related: the entanglement entropy is the one-loop correction to the black hole entropy due to renormalization of Newton's constant. For gauge fields, the entanglement entropy and the one-loop correction to the black hole entropy differ. This dissertation addresses two issues concerning the entanglement entropy of gauge fields, and its relation black hole entropy. First, for abelian gauge fields Kabat identified a negative divergent contribution to the black hole entropy that is not part of the entanglement entropy, known as a ``contact term''. We show that the contact term can be attributed to an ambiguous expression for the gauge field's contribution to the Wald entropy. Moreover, in two-dimensional de Sitter space, the contact term arises from an incorrect treatment of zero modes and is therefore unphysical. In a manifestly gauge-invariant reduced phase space quantization of two-dimensional gauge theory, the gauge field contribution to the entropy is positive, finite, and equal to the entanglement entropy. This suggests that the contact term in more than two dimensions may also be unphysical. Second, we consider lattice gauge theory and point out that the Hilbert space corresponding to a region of space includes edge states that transform nontrivially under gauge transformations. By decomposing these edge states in irreducible representations of the gauge group, the entanglement entropy of an arbitrary state is shown to be a sum of a bulk entropy and a boundary entropy associated to the edge states. This entropy formula agrees with the two-dimensional results from the reduced phase space quantization. These results are applied to several examples, including the ground state in the strong coupling expansion of Kogut and Susskind, and the entropy of the edge states is found to be the dominant contribution to the entanglement entropy.
An efficient analysis of frequency selective surface in spectral domain with RWG basis functions

In this article, the spectral domain method of moment is utilized to analyze frequency selective surface with RWG basis functions for arbitrarily shaped metal geometry. The Fourier transform of the RWG basis function can be expressed in the analytical form and the fast convergence characteristic can reduce the computation time of impedance matrix. Some examples are calculated to demonstrate the efficiency of the proposed method. © 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 2567–2570, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24674
Simplicity out of complexity in environmental modelling: Occam's razor revisited.

While large models based on a deterministic-reductionist philosophy have an important part to play in environmental research, it is advantageous to consider alternative modelling methodologies which overtly acknowledge the poorly defined and uncertain nature of most environmental systems. The paper discusses this topic and presents an integrated statistical modelling procedure which involves three main methodological tools: uncertainty and sensitivity studies based on Monte Carlo simulation techniques; dominant mode analysis using a new method of combined linearization and model-order reduction; and data-based mechanistic modelling. This novel approach is illustrated by two practical examples: modelling the global carbon cycle in relation to possible climate change; and modelling a horticultural glasshouse for the purposes of automatic climate control system design.
Finite horizon robust Kalman filter design

In this paper, we study the problem of finite horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters which can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. Also proposed is a recursive design method which can be applied to real-time applications.
Statistical Mechanics of Two-Dimensional Vortices and Collisionless Stellar Systems

In this article, we stress the analogy between two-dimensional vortices and collisionless stellar systems. This analogy is based on the similar morphology of the Euler and Vlasov equations. These equations develop finer and finer filaments, and a statistical description is appropriate to smooth out the fluctuations and describe the macroscopic evolution of the system. We show here that the two descriptions are similar and apply the methods obtained in two-dimensional turbulence to the case of stellar systems. In particular, we propose a new evolution equation for the coarse grained distribution function f̄ based on a general maximum entropy production principle. This equation (of a generalized Fokker-Planck type) takes into account the “incompleteness” and the “statistical degeneracy” of the violent relaxation and should be able to model the evolution of collisionless stellar systems.
Discussion of Some Problems About Nonlinear Time Series Prediction Using ν-Support Vector Machine

Some problems in using ν-support vector machine (ν-SVM) for the prediction of nonlinear time series are discussed. The problems include selection of various net parameters, which affect the performance of prediction, mixture of kernels, and decomposition cooperation linear programming ν-SVM regression, which result in improvements of the algorithm. Computer simulations in the prediction of nonlinear time series produced by Mackey–Glass equation and Lorenz equation provide some improved results.
Tracking in clutter with strongest neighbor measurements. I. Theoretical analysis

When tracking a target in clutter, a measurement may have originated from either the target, clutter, or some other source. The measurement with the strongest intensity (amplitude) in the neighborhood of the predicted target measurement is known as the "strongest neighbor" (SN) measurement. A simple and commonly used method for tracking in clutter is the so-called strongest neighbor filter (SNF), which uses the SN measurement at each time as if it were the true one. The paper deals with tracking in clutter with the SN measurements. It presents analytic results, along with useful comments, for the SN measurement and the SNF, including the a priori and a posteriori probabilities of data association events, the conditional probability density functions and the covariance matrices of the SN measurement, and various mean-square-error matrices of state prediction and state update. These results provide valuable insight into the problem of tracking in clutter and theoretical foundation for the development of improved tracking algorithms, for performance analysis, prediction, and comparison of tracking with the SN measurements, and for solving some important detection-tracking problems, such as the optimal determination of the detection threshold and gate size.
Generalized multiple-point Metropolis algorithms for approximate Bayesian computation

It is well known that the approximate Bayesian computation algorithm based on Markov chain Monte Carlo methods suffers from the sensitivity to the choice of starting values, inefficiency and a low acceptance rate. To overcome these problems, this study proposes a generalization of the multiple-point Metropolis algorithm, which proceeds by generating multiple-dependent proposals and then by selecting a candidate among the set of proposals on the basis of weights that can be chosen arbitrarily. The performance of the proposed algorithm is illustrated by using both simulated and real data.
On a mixture vector autoregressive model

The authors show how to extend univariate mixture autoregressive models to a multivariate time series context. Similar to the univariate case, the multivariate model consists of a mixture of stationary or nonstationary autoregressive components. The authors give the first and second order stationarity conditions for a multivariate case up to order 2. They also derive the second order stationarity condition for the univariate mixture model up to arbitrary order. They describe an EM algorithm for estimation, as well as a diagnostic checking procedure. They study the performance of their method via simulations and include a real application.
A numerical study of the regions of validity of the Kirchhoff and small‐perturbation rough surface scattering models

The regions of validity of the Kirchhoff and the first-order small-perturbation models in rough surface scattering are examined by numerical simulation. The procedure is to generate a one dimensional perfectly conducting random surface on the digital computer, compute the induced current on the surface due to an impinging plane wave by the moment method, and then calculate the far zone backscattered field and power. This procedure is repeated at least forty times and the results averaged to obtain the average scattered power. It is important to note that many so called Kirchhoff models in the literature involve simplifying assumptions in addition to the Kirchhoff approximation. To avoid confusion the Kirchhoff model in this study uses only the Kirchhoff approximation for the surface current. The far zone scattered field and power are evaluated numerically without further simplifying assumptions. Comparisons between the numerical calculations and the models are made for various values of the surface rms height and correlation length both normalized to the incident wave number (denoted by kσ and kL, respectively). By using these two parameters to form a two-dimensional space the approximate regions of validity are then established. It is found that due to the inclusion of the coherent scattering component the Kirchhoff model continues to provide good agreement with numerical calculations over small angles of incidence when kσ is less than 0.2 and kL < 2.0, a region where the Kirchhoff method was expected to fail. It is also found that the usual requirements of small height and small slope are inadequate to guarantee the validity of the first-order perturbation model. It is necessary that kL also be small.
Direct writing of silver conductive patterns: Improvement of film morphology and conductance by controlling solvent compositions

The authors have investigated the influence of conductive ink compositions on the quality of ink-jet printed patterns. Controlling the solvent compositions plays an important role of reducing the so-called coffee ring effect. The use of a higher boiling point solvent with lower surface tension such as ethylene glycol enables the formation of a uniform deposit of silver nanoparticles due to surface tension gradient-induced inward Marangoni flow, which can compensate outward convective flow. It is demonstrated that the ink-jet printed film quality is directly related to the resistance difference in the conductive patterns.