Miracle-dz/UniFAR-FTUs huggingface dataset:
Capture cross sections for the synthesis of new heavy nuclei using radioactive beams

This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Grant No. DE-SC0014380 (OSU), Australian Research Council Grants No. FL110100098, No. FT120100760, No. DP140101337, No. DP160101254, and No. DP170102318 (ANU) and the National Science Foundation under Cooperative Agreement No. PHY-110251(MSU). We gratefully acknowledge NCRIS for support of operations of the ANU Heavy Ion Accelerator Facility. One of us (K.S.) wishes to acknowledge support from the U.S. DOE NNSA through the Nuclear Science and Security consortium under Grant No. DE-NA0003180.
An effective medium ratio following miniaturized concentric meta‐atom for S‐ and C‐band applications

In this paper, a new effective medium ratio following miniaturized meta‐atom structure designed, fabricated and measured for dual‐band that has multiple circular concentric metal rings printed one inside the other. The each ring of meta‐atom structure delivers a magnetic resonance at different frequencies. The number of concentric ring resonator has created same number of resonances. A different analysis has been performed to verify distinct resonance frequencies, effective medium ratio and electromagnetic transmission properties simply by altering the design parameters. Computer simulation technology (CST) electromagnetic simulator which is commercially available is utilized to investigate the design of the meta‐atom. The dual‐band response has been displayed of the meta‐atom in conjunction with negative index material property over the certain span in the microwave regime. The proposed structure has become suitable for S‐ and C‐band applications and has achieved efficient electrically small microwave structure. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1233–1240, 2017
DEVELOPMENT OF A BIOINSPIRED APPROACH FOR THE DESIGN OF KINEMATIC CHAINS

In recent years, bioinspired lightweight design has become a high priority in technology. An important source is the musculoskeletal system, which achieves a light construction by the interplay of different effects, which have the aim of minimizing bending stresses. In this paper the potentials for technology and the challenges for a transfer are discussed using kinematic chains as an example. An iterative approach is presented, which represents a solution to integrate the simultaneous optimization process of the musculoskeletal system into the technical product development process.
On redundancy-modified NAND multiplexing

: In order to make systems that are based on unreliable components reliable, the design of fault tolerant architectures will be necessary. Inspired by von Neumann’s negative AND (NAND) multiplexing and William’s interwoven redundant logic, this paper presents a fault tolerant technique based on redundancy-modi ﬁ ed NAND gates for future nanocomputers. Bifurcation theory is used to analyze fault tolerant ability of the system and the simulation results show that the new system has a much higher fault tolerant ability than the conventional multiplexing based on NAND gates. According to the evaluation, the proposed architecture can tolerate a device error rate of up to 10 − 1 , with multiple redundant components. This fault tolerant technique is potentially useful for future nanoelectronics.
Simplified approach for tomographic diffractive microscopy of axisymmetric samples

Tomographic diffractive microscopy (TDM) is an imaging technique which allows for recording the complex optical index of unlabelled specimens. It is based on diffraction theory with a spatially coherent illumination and interference demodulation. Different methods have been developped like illumination rotation with fixed sample or sample rotation with fixed illumination. However this last technique is difficult to set up. Hence, we propose a novel reconstruction technique applicable to axisymmetric unlabelled specimens. It consists in a numerical rotation of the Ewald cap of sphere generated by a zero-degree illumination on the sample. Due to the specimen symmetry, we show that the Fourier space can be filled in the direction perpendicular to the axis of symmetry.
Focusing light through random photonic layers by four-element division algorithm

The propagation of waves in turbid media is a fundamental problem of optics with vast applications. Optical phase optimization approaches for focusing light through turbid media using phase control algorithm have been widely studied in recent years due to the rapid development of spatial light modulator. The existing approaches include element-based algorithms - stepwise sequential algorithm, continuous sequential algorithm and whole element optimization approaches - partitioning algorithm, transmission matrix approach and genetic algorithm. The advantage of element-based approaches is that the phase contribution of each element is very clear; however, because the intensity contribution of each element to the focal point is small especially for the case of large number of elements, the determination of the optimal phase for a single element would be difficult. In other words, the signal to noise ratio of the measurement is weak, leading to possibly local maximal during the optimization. As for whole element optimization approaches, all elements are employed for the optimization. Of course, signal to noise ratio during the optimization is improved. However, because more random processings are introduced into the processing, optimizations take more time to converge than the single element based approaches. Based on the advantages of both single element based approaches and whole element optimization approaches, we propose FEDA approach. Comparisons with the existing approaches show that FEDA only takes one third of measurement time to reach the optimization, which means that FEDA is promising in practical application such as for deep tissue imaging.
On Slowly Rotating Supercompact Schwarzschild Stars

In this Ph.D thesis, I will present results concerning to my doctoral research project submitted to the Department of Physics and Astronomy at the University of South Carolina. The thesis belongs to the area of Theoretical Physics, particularly, in the framework of Einstein’s Theory of General Relativity. The project is the study of integral and surface properties of slowly rotating homogeneous masses in the gravastar limit R → Rs, where Rs is the Schwarzschild radius. For this purpose we followed the perturbative method proposed by Hartle in 1967. In this model, the relativistic equations of structure for a slowly rotating star were derived at second order in the angular velocity Ω. An interesting, and educational, application of this model was investigated by Chandrasekhar and Miller. In their approach, they solved numerically the structure equations of a homogeneous star (constant energy density) up to the Buchdahl bound (9/8)Rs. Based on this work, our objective was to investigate the interesting region below the Buchdahl bound Rs < R < (9/8)Rs, which has not been studied previously in the literature. Our results were astonishing. We found that the surface properties and quadrupole mass moment approach the values corresponding to those of the Kerr metric when expanded at second order in angular momentum. This remarkable result provides a long sought solution to the problem of the source of rotation in the Kerr spacetime.
Fault-tolerance and diagnosability of hierarchical star networks

ABSTRACT The hierarchical star networks , proposed by Shi and Srimani, is a new level network topology and uses the star graphs as building blocks. Given a graph G, the h-extra connectivity of G is the minimum cardinality of a set of vertices in G, if exists, whose deletion disconnects G and leaves every remaining component with more than h vertices. There is no known polynomial-time algorithm for finding for a given graph G. In this paper, by exploring the combinatorial properties and fault-tolerance of , we show that the largest component of a survival graph contains almost all of the remaining vertices after removing at most 4n−8 vertices and obtain the h-extra connectivity for of , where . As applications, the conditional diagnosability and the h-extra conditional diagnosability for of under the PMC model and the MM* model, respectively, are obtained.
Advances in finite-difference methods for electromagnetic modeling /

Stability issues involved with using a time domain formulation of the perfectly matched layer (PML) absorbers are considered. One time domain formulation of the anisotropic PML is considered and it is shown that this formulation is dynamically unstable. Numerical stability of Berenger’s formulation is next considered. This formulation is shown to be conditionally stable. The stability condition is shown to be independent of the coordinate stretch variables cTx, cry, and a^. The numerical phase error of classical methods is considered. This phase error is related to the spatial resolution and thus limits the maximum grid size for a desired accuracy. Greater accuracy is typically achieved by defining finer resolutions or im­ plementing higher order methods. Both these techniques require more memory and longer computation times. In this dissertation, new modified methods are presented which are optimized to problems of electromagnetics. Simple methods are presented that reduce numerical phase error without additional processing time or memory re­ quirements. Furthermore, these methods are apphed to both the Helmholtz equation and the finite difference time domain (FDTD) method. Both analytical and numerical results are presented to demonstrate the accuracy of these new methods. Sub-gridding methods are presented. A systematic method is presented for op­ timally choosing weights required for interpolation between meshes. These weights are optimized for plane waves. Numerical verifications are presented. This concept 11 is desirable for resolving electrically small objects, approximating curvatures more accurately, and modeling dense materials more efficiently.
Etude de la consanguinité des bisons d'Europe avec un modèle de Markov caché à multiples classes autozygotes

Study of inbreeding in the European bison with a multiple autozygous classes hidden Markov model European bison (Bison bonasus) disappeared in the wild at the end of the First World War. They survived in several zoos and were subsequently reintroduced into the forest of Białowieża, Poland. In order to study the consequences of this bottleneck and to study the present state of conservation of the species, a characterization of inbreeding was carried out. The use of a genomic approach makes it possible to be free from the use of the genealogy. The multiclass HMM model used (ZooRoH) estimates the realized global and local inbreeding. It also evaluates the age of the ancestors (ie, which generation of the past they belonged to) at the origin of the inbreeding. The aim of this work was to bring ZooRoH under the R environment by improving its properties (including parameter estimation) before characterizing inbreeding in European bison. First, the method of estimating the original parameters (EM) was replaced by the L-BFGS-B method of the optim function. This requires fewer iterations to converge and has, in addition, a more appropriate stop criterion. Reparametrization was also carried out, making it possible to obtain parameters with the desired properties, as well as to make the results more easily interpretable and readable. These modifications were evaluated on simulated and real data sets by comparing the estimated likelihoods, parameters and coefficients of inbreeding via 4 models (2e, 4p, 4e, 10p). It has been shown that the 4p and 10p models are more stable than the 4e model. Thus, in the subsequent study of the inbreeding of wisent with this program, the 10p model was used to combine two advantages : ease of comparison of individuals and broad view of the past with its 9 autozygous classes (IBD). Prior to the estimation of the global consanguinity of wisent with ZooRoH under R (ZooRoH/R), the structure of their population was analyzed (MDS with PLINK, PCA with GCTA then ADMIXTURE) to conclude that it is homogeneous. An overall consanguinity of 40% on average in the population was estimated, which is very high both compared to Belgian Blue Beef, considered already highly inbred, and compared to an expected inbreeding between father and daugther (25%). By removing markers in linkage disequilibrium, older inbreeding is difficult to detect. However, inbreeding remains fairly recent and seems to be stabilizing : more recently born animals see their inbreeding moving slightly towards older classes. Thus, this work is a first step towards the creation of a R package for ZooRoH which can be applied to a population with an unknown demographic past. It also confirmed a successful reintroduction of wisent and suspected a past purge event. iii Table des matières
A quantitative method for choosing optimal Daubechies wavelets

We develop a new method for calculating specific values of Daubechies wavelets in one dimension. The novelty of this approach is its ability to calculate exact values of the Daubechies scaling functions and, by extension, wavelets, without calculating values of the scaling function at other unnecessary dyadic rationals. We then provide a new quantitative method for choosing the best wavelet for applications by giving a rigorous error analysis of the wavelet transform for functions of various smoothness.
An optimized direction statistics for detecting and removing random-valued impulse noise

In this paper, we propose a robust local image statistic based on optimized direction, by which we can distinguish image details and edges from impulse noise effectively. Therefore it can identify noisy pixels more accurately. Meanwhile, we combine it with the edge-preserving regularization to remove random-valued impulse noise in the cause of precise estimated value. Simulation results show that our method can preserve edges and details efficiently even at high noise levels.
Microscopic description of fission properties for r-process nuclei

Fission properties of 886 even-even nuclei in the region 84 ≤ Z ≤ 120 and 118 ≤ Z ≤ 250 were computed using the Barcelona-Catania-Paris-Madrid energy density functional. An extensive study of both the potential energy surfaces and collectives inertias was performed. Spontaneous fission half-lives are computed using the semiclassical Wentzel-Kramers-Brillouin formalism. By comparing these three quantities we found that the stability of the nucleus against the fission process is driven by the interplay between both the potential energy and the collective inertias. In our calculations, nuclei with relative long half-lives were found in two regions around Z = 120, N = 182 and Z = 104, N = 222.
Growth Curve Cognitive Diagnosis Models for Longitudinal Assessment

Author(s): Lee, Seung Yeon | Advisor(s): Rabe-Hesketh, Sophia | Abstract: This dissertation proposes longitudinal growth curve cognitive diagnosis models (GC-CDM) to incorporate learning over time into the cognitive assessment framework. The approach was motivated by higher-order latent trait models (de la Torre a Douglas, 2004), which define a higher-order continuous latent trait that affects all the latent skills. The higher-order latent trait can be viewed as the more broadly defined general ability; and the skills can be viewed as the specific knowledge arising from the higher-order latent trait. GC-CDMs trace changes in the higher-order latent traits over time by using latent growth curve model with respondent-specific random intercept and random slope of time, and simultaneously trace students' skill mastery through the CDM measurement model.GC-CDMs are estimated using marginal maximum likelihood (MML) estimation in Mplus. Relevant issues for estimating GC-CDMs are addressed, e.g., the high-dimensional computation problem, model specification for the relationship between the higher-order latent trait and the multiple skills, and model identification. In simulation studies, we use the DINA measurement model, and examine parameter recovery of the GC-DINA model under differing conditions. Particularly, the effects of the design of the Q-matrix, the number of respondents and the number of time points are discussed. Overall, MML estimation in Mplus shows good parameter recovery; especially, the average growth, which is the parameter of most interest, is well estimated in all conditions. We also illustrate the application of the GC-DINA model to real data using two datasets from multi-wave experiments designed to assess the effects of the Enhanced Anchored Instruction (EAI; Bottge et al., 2003) on mathematics achievement. In addition, the GC-DINA model is compared to the latent transition analysis DINA model (LTA-DINA) (Li et al., 2016; Kaya a Leite, 2016) and a longitudinal item response theory (IRT) model (Andersen, 1985) using a simulated data. The results suggest that the GC-DINA model and the LTA-DINA model are similar in terms of the predicted skill mastery; and the GC-DINA model and the longitudinal IRT model are similar in terms of the predicted higher-order latent trait.
An Euler-Euler Multiphysics Solver for the Analysis of the Helium Bubbling System in the MSFR

In this work, a multi-physics OpenFOAM solver for the study of the Molten Salt Fast Reactor (MSFR) is presented. A particular focus is devoted to the analysis of the helium bubbling system of the MSFR and of its effect on the reactor dynamic behaviour. Neutronics is modelled with the multi-group diffusion equation, while thermal-hydraulics is described with an Eulerian-Eulerian approach. The void reactivity feedback coefficient is evaluated on the basis the bubble spatial distribution, pointing out differences with respect to simulations carried out with uniform void fractions. The outcomes of this analysis constitute the starting point for further research on the MSFR dynamics and transient analysis, with a particular focus on the design of the reactivity control systems and the optimization of the reactor as well.
Elevation beam profile control with bias polarity patterns applied to microfabricated ultrasound transducers

In contrast to PZT probes, capacitive microfabricated ultrasonic transducers (cMUTs) require a DC bias. We investigate elevation beam profile shaping by spatially varying this bias polarity. Such a scheme introduces a 180/spl deg/ phase shift in the device's impulse response. A Fresnel zone plate is realized which is capable of generating tight elevation foci using a large aperture. This paper presents measurements from a prototype Fresnel cMUT probe, and matching simulation results. The Fresnel probe is capable of improved slice thickness compared with both a conventionally lensed probe and a multi-row design. Also, combinations of bias polarity control and multiple firings can enable harmonic imaging without pre-distortion of the transmit signal. Multiple firing schemes further optimize slice thickness, and allow beam steering in elevation.
A Stochastic Information Diffusion Model in Social Networks Based on SIR Epidemic Model

Social networks are an important infrastructure for information, the paper present a information diffusion model with random perturbation in social networks, which is based on SIR deterministic epidemic diseases. We prove that there exists a unique nonnegative solution to the stochastic information diffusion model for any positive initial value, investigate the stochastic asymptotic behavior of the information diffusion model, give the stability condition by the construction of the Lyapunov function, i.e. the conditions of the information diffusion will die out and be persistent in social networks.
A Gaussian semi-parametric implied volatility model

Modeling the implied volatility has received extensive attention, as the implied volatility is an important parameter in option pricing. Usually the implied volatility can be approximated by fitting a polynomial about the strike and the maturity or by stochastic methods. In this article, a Gaussian semi-parametric model is proposed based on the quadratic polynomial semi-parametric model suggested by Borovkova. In the new model, the Gaussian function is used to construct a smooth term substituting the quadratic term in the polynomial model, and the arbitrage-free constraints are used to calibrate the model. The empirical tests show that the Gaussian semi-parametric model has a better performance in fitting and forecasting.
Méthodes élémentaires en vue du théorème de Sylvester

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Notes on misspecifying the random effects distribution regarding analysis under the AB/BA crossover trial in dichotomous data – a Monte Carlo evaluation

Abstract When patient responses are dichotomous under an AB/BA design, we commonly assume the normal random effects logistic regression model. This normality assumption for random effects is, however, unlikely to hold. Based on the maximum likelihood estimator, we apply Monte Carlo simulations to investigate the impact of misspecification on hypothesis testing and estimation because of the incorrect normal assumption for random effects. We find that Type I error is not affected by misspecifying the normal random effects distributions. We further find that the influence due to misspecifying distributions of random effects on power, bias and mean-squared-error, the coverage probability and the average length of the confidence interval is generally minimal when the variation of responses between patients is small and the number of patients per group is large. This influence can be substantial when the variation of responses between patients is large and the number of patients per group is small. Thus, the estimate of the required sample size or the accuracy of an interval estimator under the normal random effects assumption can be liberal. We use the data comparing a drug with placebo in treating cerebrovascular deficiency to illustrate the potential difference in inference between various random effects distributions considered here.
Inverse Optimal Adaptive H ∞ Consensus Control of Multi-Agent Systems on Directed Network Graphs

: Design methods of inverse optimal adaptive H ∞ consensus control of multi-agent systems denoted by the ﬁrst-order and the second-order regression models on directed network graphs are presented in this paper. The proposed control schemes are derived as solutions of certain H ∞ control problems, where estimation errors of tuning parameters are regarded as external disturbances to the process. It is shown that the resulting control systems are robust to uncertain system parameters and that the desirable consensus tracking is achieved approximately via adaptation schemes and design parameters.