Miracle-dz/UniFAR-FTUs huggingface dataset:
Properties of luminous spheroids at redshifts z ~ 1 from Keck and HST

Abstract Three new and still on-going surveys that combine the power of spectroscopy or adaptive optics from the Keck Telescopes with HST images are DEEP, AEGIS, and CATS. The advantages of each for the study of distant bulges are accompanied by a few highlights. We find that the vast fraction of luminous distant bulges appear very red, independent of the bulge luminosity, bulge fraction, disk color, and environment. Yet early-type galaxies appear to be relatively young at redshifts z ~ 1, are less numerous then, host many X-ray AGN's with some that are highly obscured, and have low but increasing dry-dry and dry-wet merger rates over time.
Polarization mode preservation in elliptical index tailored optical fibers for apertureless scanning near-field optical microscopy

We report on the development of elliptical, index tailored optical fibers for higher-order mode preservation for fiber-based, apertureless, internally illuminated scanning near-field optical microscopy (ai-SNOM). The fiber structure is simulated by the finite element method, showing large spreads of the effective indices for neighboring first higher-order modes. We demonstrate experimentally that due to this spread, the first higher-order modes do not couple, hence, the polarization is maintained, when the fiber is bent down to 1 cm radius. Further, we discuss the implications for ai-SNOM applications.
Scaling laws of the Rayleigh–Taylor ablation front mixing zone evolution in inertial confinement fusion

A theoretical model for the ablatively driven Rayleigh–Taylor (RT) instability single-mode and multimode mixing fronts is presented. The effect of ablation is approximately included in a Layzer-type potential flow model, yielding the description of both the single-mode evolution and the two-bubble nonlinear competition. The reduction factor of the linear growth rate due to ablative stabilization obtained by the model is similar to the Takabe formula. The single-bubble terminal velocity is found to be similarly reduced by ablation, in good agreement with numerical simulations. Two-bubble competition is calculated, and a statistical mechanics model for multimode fronts is presented. The asymptotic ablation correction to the classical RT αgt2 mixing zone growth law is derived. The effect of ablative stabilization on the allowed in-flight aspect ratio of inertial confinement fusion pellets is estimated using the results of the statistical mechanics model.
Electro-Rheological Multi-layer Squeeze Film Damper and Its Application to Vibration Control of Rotor System

In this paper, a new electro-rheological multi-layer squeeze film damper (ERMSFD in short) is designed first and the constitutional Reynolds equation is established. Then the behavior of the rotor system is analyzed, the vibration around the first critical speed is suppressed and an on/off control is proposed to control the large amplitude around the first critical speed. A control method is used to suppress the sudden unbalance response. Finally, experiments are carried out to investigate the behavior of the rotor system to prove the effectiveness of the ER damper to suppress the vibration around the critical speed and the sudden unbalance response.
Nucleate Boiling in Large Arrays of Impinging Water Sprays

The nucleate boiling of subcooled water, under 100 cm2 square arrays of impinging sprays, was experimentally investigated. Three types of commercially available full cone pressure nozzles, of distinct flow capacities, allowed for runs where the average impinging coolant mass flux spanned the 0.3–7.2 kg/m2-s range. Array geometry was varied adjusting nozzle-to-nozzle and nozzle-to-impingement surface distances. Experimental construction allowed for good drainage of spent coolant and unrestricted air entrainment to spray cones. The average heat flux through the heated, upward-facing, copper impingement surface was found to be equal to the sum of single-phase and nucleate boiling heat flux components. The phase-change component was experimentally observed to depend upon wall excess temperature only. The proposed heat transfer correlation reproduces original experimental data with a mean absolute error of 10.6%. Non-critical-heat-flux (non-CHF) cooling capacity and efficiencies of up to, respectively, 2000 kJ/kg and 83% were observed.
Volume magnetic domain mirroring in magnetic shape memory crystals

From the magnetic domain patterns at adjacent crystal surfaces of NiMnGa shape memory crystals the internal domain configurations across a hidden twin-boundary are derived. The results proof the existence of domains extending from the sample surfaces into the nonvisible sample volume. Moreover, the structural twin boundary inside the material acts as a mirror for the basic domains. The analysis validates the relevance of surface magnetic response analysis for the understanding of the magnetoelastic behavior of magnetic shape memory alloys and is essential for the interpretation of magnetic domain images obtained from other surface-restricted observation techniques.
Globular Clusters and the Distance to the Galactic Center

The distance to the Galactic center is estimated from the space distribution of globular clusters. Simulations of the cluster distribution are constructed to account for the various biases in the observed sample due to extinction, sample incompleteness, geometric effects, and size-of-sample uncertainties. The resulting distance to the Galactic center is R(0) = 7.5 + or - 0.9 kpc, assuming M sub v (RR) = +0.6 + or - 0.2 at an Fe/H abundance ratio of -1.6. 77 refs.
The correlation functions of rbm and m/m/1

This paper describes the (auto) correlation functions of regulated or reflecting Brownian motion (RBM) and several processes associated with the M/M/1 queue. For RBM and the M/M/1 continuous-time queue-length process, the correlation function of the stationary process coincides with the complementary stationary-excess cdf (cumulative distribution function) associated with a previously studied first-moment cdf. The first-moment cdf is the mean as a function of time given that the process starts at the origin, normalized by dividing by the steady-state limit. The M/M/1 first-moment cdf in turn is the stationary-excess cdf associated with the M/M/1 busy-period cdf. In fact, all the moment cdfs and correlation functions can be expressed directly in terms of the busy-period cdf. This structure provides the basis for simple approximations of the correlation functions and the moments as functions of time by hyperexponentials.
A multiplicative mixed model when the variances are heterogeneous

Abstract When animals are compared across environments, adjustment for differences among the environments is important. Not only are some environments more favorable than others, but the amount of variability may differ. A number of methods exist to account for heterogeneous variances. However, current methods have several potential disadvantages. A multiplicative mixed model that incorporates scaling factors is presented along with estimation procedures based on the model. A multiplicative mixed model differs from the usual mixed models in that the fixed and random effects are scaled by the scaling factor of each environment. A prior distribution, based on the chi-squared distribution, for the scaling factors is used. Marginal posterior mode estimators are given for estimation of the unknown parameters. An example data set is used to illustrate the procedure.
ε factor of representations of classical groups

Abstract We let G be the isometry group of a nondegenerate symmetric or skew-symmetric form h on a space V over some local or global field K [i.e., G = U(V, h)]. We let LG be the L group of Go = the identity component of G and r be the natural representation of this group. We develop here a theory of L functions and e factors attached to this r. In particular we develop a theory of local and global zeta integrals for such G. We use very special intertwining operators; therein we require an analysis of the proper normalization of such operators. With such techniques we determine the correct e factors associated to local representations. The issue of the correct local L factor is discussed.
Roles of solvent additive in organic photovoltaic cells through intensity dependence of current-voltage characteristics and charge recombination

In this research, the enhanced power conversion efficiency of PBnDT-FTAZ:PC70BM bulk-heterojunction (BHJ) solar cells (over 7%), fabricated with a solvent additive (1,8-diiodooctane, 3%), was demonstrated. The appropriate ratio of solvent additive leads to a device with increased JSC, fill factor, and favorably controlled nanomorphology phase separation. Furthermore, the device with BHJ film fabricated with the solvent additive exhibited improved charge collection and simultaneously reduced charge recombination from a systematic light intensity analysis. The lack of Shockley-Read-Hall recombination at open circuit, the dominance of bimolecular recombination only when approaching open circuit, and an improved charge collection probability (95.5%) at short circuit contribute to high performance organic photovoltaic cells.
Fleet management models and algorithms for an oil-tanker routing and scheduling problem

This paper explores models and algorithms for routing and scheduling ships in a maritime transportation system. The principal thrust of this research effort is focused on the Kuwait Petroleum Corporation (KPC) Problem. This problem is of great economic significance to the State of Kuwait, whose economy has been traditionally dominated to a large extent by the oil sector, and any enhancement in the existing ad-hoc scheduling procedure has the potential for significant savings. A mixed-integer programming model for the KPC problem is constructed in this paper. The resulting mathematical formulation is rather complex to solve due to the integrality conditions and the overwhelming size of the problem for a typical demand contract scenario. Consequently, an alternate aggregate model that retains the principal features of the KPC problem is formulated. The latter model is computationally far more tractable than the initial model, and a specialized rolling horizon heuristic is developed to solve it. The proposed heuristic procedure enables us to derive solutions for practical sized problems that could not be handled by directly solving even the aggregate model. The initial formulation is solved using CPLEX-4.0-MIP capabilities for a number of relatively small-sized test cases, whereas for larger problem instances, the aggregate formulation is solved using CPLEX-4.0-MIP in concert with the developed rolling horizon heuristic, and related results are reported. An ad-hoc routing procedure that is intended to simulate the current KPC scheduling practice is also described and implemented. The results demonstrate that the proposed approach substantially improves upon the results obtained using the current scheduling practice at KPC.
The log-periodic array at the Clark Lake Radio Observatory

A log-periodic array, three km in length, is operating at Clark Lake Radio Observatory. It makes one-dimensional sweeps of the solar brightness distribution in the frequency range 20 to 65 MHz once per sec. The phasing of the array and the receiving system are described, as well as how the dynamic spectra are analyzed for the positions of solar radio sources. Simultaneous measurements at many frequencies enable the observer to remove the effects of ionospheric refraction and to obtain fundamental positions to an accuracy of about one arc min at decametric wavelengths. Fundamental positions are given for Cassiopeia A. (auth)
Extending the assessment of complex problem solving to finite state automata: Embracing heterogeneity.

Abstract. Recent advancements in the assessment of Complex Problem Solving (CPS) build on the use of homogeneous tasks that enable the reliable estimation of CPS skills. The range of problems featured in established instruments such as MicroDYN is consequently limited to a specific subset of homogeneous complex problems. This restriction is problematic when looking at domain-specific examples of complex problems, which feature characteristics absent from current assessment instruments (e.g., threshold states). We propose to utilize the formal framework of Finite State Automata (FSA) to extend the range of problems included in CPS assessment. An approach based on FSA, called MicroFIN, is presented, translated into specific tasks, and empirically investigated. We conducted an empirical study (N = 576), (1) inspecting the psychometric features of MicroFIN, (2) relating it to MicroDYN, and (3) investigating the relations to a measure of reasoning (i.e., CogAT). MicroFIN (1) exhibited adequate measurement char.
An improved model of a pneumatic vibration isolator : Theory and experiment

Abstract The design of an active controller for a vibration isolation table employing pneumatic vibration isolators requires an accurate mathematical model of the isolator. An experimental investigation of the validity of available models has been performed and indicates significant errors between predicted and observed behavior. An analysis of the model and the data suggested that a previously ignored component of the isolator, the diaphragm, plays a significant role in isolator response. This paper develops the modification to the standard isolator model that incorporates the effects of the diaphragm. When the diaphragm is included in the isolator model, the modified model predicts time-domain and frequency-domain behavior quite closely. We conclude that the modified model of the pneumatic isolator improves markedly the accuracy of the predictions provided by the model.
{sup 129}Xe-Cs (D{sub 1},D{sub 2}) versus {sup 129}Xe-Rb (D{sub 1}) spin-exchange optical pumping at high xenon densities using high-power laser diode arrays

We investigate {sup 129}Xe-Cs (D{sub 1},D{sub 2}) spin exchange optical pumping (SEOP) at high Xe densities ({approx}0.12-2.44 amagat) using newly available high-power (>40 W) laser diode arrays and compare with {sup 129}Xe-Rb D{sub 1} SEOP under similar conditions. At elevated Xe densities, the spin-exchange rate (per alkali-metal atom, {gamma}{sup '}) for Cs-{sup 129}Xe is {approx}1.5-fold greater than that for Rb-{sup 129}Xe. Higher spin-exchange rates and lower {sup 129}Xe spin-destruction rates for Cs-{sup 129}Xe versus Rb-{sup 129}Xe contribute to {approx}twofold improvement in {sup 129}Xe nuclear spin polarization measured at 9.4 T - with the largest gains observed at the highest Xe densities.
Thermal decomposition of sputtered thin PtOx layers used in super-resolution optical disks

Decomposition of sputtered PtOx layers has been studied by x-ray absorption spectroscopy. X-ray absorption fine structure measurements demonstrated that as-deposited films possess a composition of PtOx (x=1.1–1.7). Upon annealing, the metallic platinum phase is formed. The formation of the metallic Pt phase starts at very early stages of the decomposition process. The decomposition is not monotonic and slows down at the final stage. The structure at intermediate stages of decomposition is a mixture of the starting phase and metallic Pt.
Manipulability of Robotic Mechanisms

This paper discusses the manipulating ability of robotic mechanisms in positioning and orienting end-effectors and proposes a measure of manipulability. Some properties of this measure are obtained, the best postures of various types of manipulators are given, and a four-degree-of-freedom finger is considered from the viewpoint of the measure. The pos tures somewhat resemble those of human arms and fingers.
Face recognition using sparse representation classifier with Volterra kernels

Sparse representation based classification (SRC) could not well classify the sample belonging to different classes distribute on the same direction. To solve the problem, a Volterra kernel sparse representation based classification (Volterra-SRC) algorithm is proposed in this paper. Firstly, the original face images are divided into non overlapped patches and then mapped into a high dimensional space by utilizing the Volterra kernels. During the training stage, following by the Fisher criteria, the objective function is defined to obtain the optimal Volterra kernels via maximizing inter-class distances and minimizing intra-class distances simultaneously. During the testing stage, a voting procedure is introduced in conjunction with a sparse representation based classification to decide to which class each individual patch belongs. Finally, the aggregate classification results of all patches in a face are used to determine the overall recognition outcome for the given face image. We demonstrate the experiments on ORL and Extended Yale B benchmark face databases and show that our proposed Volterra-SRC algorithm consistently outperforms the original SRC and the proposed has some advantages and robustness in case of small train number samples.
Differential spatial activity patterns of acupuncture by a machine learning based analysis

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.
Boundary value problems to first-order complex partial differential equations in a ring domain

Four basic boundary value problems, namely, Schwarz, Dirichlet, Neumann, Robin problems for analytic functions and more generally for the inhomogeneous Cauchy–Riemann equation are investigated in a concentric ring domain (concentric annulus). The representations to the solutions and solvability conditions are given in an explicit form.
Reverberation mapping by regularized linear inversion

Reverberation mapping of active galactic nucleus (AGN) emission-line regions requires the numerical deconvolution of two time series. We suggest the application of a new method, regularized linear inversion, to the solution of this problem. This method possesses many good features; it imposes no restrictions on the sign of the response function; it can provide clearly defined uncertainty estimates; it involves no guesswork about unmeasured data; it can give a clear indication of when the underlying convolution model is inadequate; and it is computationally very efficient. Using simulated data, we find the minimum S/N and length of the time series in order for this method to work satisfactorily. We also define guidelines for choosing the principal tunable parameter of the method and for interpreting the results. Finally, we reanalyze published data from the 1989 NGC 5548 campaign using this new method and compare the results to those previously obtained by maximum entropy analysis. For some lines we find good agreement, but for others, especially C III lambda(1909) and Si IV lambda(1400), we find significant differences. These can be attributed to the inability of the maximum entropy method to find negative values of the response function, but also illustrate the nonuniqueness of any deconvolution technique. We also find evidence that certain line light curves (e.g., C IV lambda(1549)) cannot be fully described by the simple linear convolution model.
Implementation of A Geometric Constraint Regularization For Multibody System Models

Redundant constraints in MBS models severely deteriorate the computational performance and accuracy of any numerical MBS dynamics simulation method. Classically this problem has been addressed by means of numerical decompositions of the constraint Jacobian within numerical integration steps. Such decompositions are computationally expensive. In this paper an elimination method is discussed that only requires a single numerical decomposition within the model preprocessing step rather than during the time integration. It is based on the determination of motion spaces making use of Lie group concepts. The method is able to reduce the set of loop constraints for a large class of technical systems. In any case it always retains a sufficient number of constraints. It is derived for single kinematic loops.
Adaptive composite filters for pattern recognition in linearly degraded and noisy scenes

New adaptive correlation filters for reliable recognition of geometrically distorted objects in blurred and noisy scenes are proposed. The filters are based on modified synthetic discriminant functions. The information about objects to be recognized, false objects, disjoint background, additive noise, and expected degradations of targets and input scenes are utilized in an iterative training algorithm. The algorithm is used to design a correlation filter with a specified discrimination capability. Computer simulation results obtained with the proposed adaptive filters in test scenes are discussed and compared with those of various correlation filters in terms of discrimination capability and location errors.
Dependence of emission of terahertz radiation on geometrical parameters of dipole photoconductive antennas

The dependence of the emission spectrum of terahertz (THz) radiation on the geometrical parameters of the dipole antenna, and the relationship between these parameters and the temporal characteristics of the transient current that generate THz radiation, is reported. The emission intensity and the peak frequency strongly depend on these geometrical parameters. This dependence varies significantly with changes in the temporal characteristics of the transient current. We have also found that the emission efficiency can be increased by increasing the aspect ratio for the dipole.
Missing covariates in generalized linear models when the missing data mechanism is non‐ignorable

We propose a method for estimating parameters in generalized linear models with missing covariates and a non‐ignorable missing data mechanism. We use a multinomial model for the missing data indicators and propose a joint distribution for them which can be written as a sequence of one‐dimensional conditional distributions, with each one‐dimensional conditional distribution consisting of a logistic regression. We allow the covariates to be either categorical or continuous. The joint covariate distribution is also modelled via a sequence of one‐dimensional conditional distributions, and the response variable is assumed to be completely observed. We derive the E‐ and M‐steps of the EM algorithm with non‐ignorable missing covariate data. For categorical covariates, we derive a closed form expression for the E‐ and M‐steps of the EM algorithm for obtaining the maximum likelihood estimates (MLEs). For continuous covariates, we use a Monte Carlo version of the EM algorithm to obtain the MLEs via the Gibbs sampler. Computational techniques for Gibbs sampling are proposed and implemented. The parametric form of the assumed missing data mechanism itself is not `testable' from the data, and thus the non‐ignorable modelling considered here can be viewed as a sensitivity analysis concerning a more complicated model. Therefore, although a model may have `passed' the tests for a certain missing data mechanism, this does not mean that we have captured, even approximately, the correct missing data mechanism. Hence, model checking for the missing data mechanism and sensitivity analyses play an important role in this problem and are discussed in detail. Several simulations are given to demonstrate the methodology. In addition, a real data set from a melanoma cancer clinical trial is presented to illustrate the methods proposed.