Miracle-dz/UniFAR-FTUs huggingface dataset:
CREDIT SCORING MODELING WITH STATE-DEPENDENT SAMPLE SELECTION: A COMPARISON STUDY WITH THE USUAL LOGISTIC MODELING

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model, a logistic regression with state-dependent sample selection model and a bounded logistic regression model via a large simulation study. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian retail bank portfolio. Our simulation results so far revealed that there is nostatistically significant difference in terms of predictive capacity among the naive logistic regression models, the logistic regression with state-dependent sample selection models and the bounded logistic regression models. However, there is difference between the distributions of the estimated default probabilities from these three statistical modeling techniques, with the naive logistic regression models and the boundedlogistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. Which are common in practice.
Financial Assistance and Environmental Compliance: Evidence from the Clean Water Act and the Clean Water State Revolving Fund

ABSTRACT:Using data from the National Pollution Discharge Elimination System compliance and the Clean Water State Revolving Funds (CWSRF) for wastewater treatment plants in nine states between 2010 and 2018, we examine (1) the effect of noncompliance on the distribution and size of awarded CWSRF loans, and (2) the effects of the CWSRF provision and award size on postfunding compliance. We observe that funded facilities have poorer compliance records than the unfunded ones and that funded facilities decrease violations within two years after receiving financial support. On average, a $50 million CWSRF loan decreases violations by one count within two postfunding years.
Wind-induced instability of structures

Forms of wind-induced instability of structures are described, and two of these, typical of long bodies with bluff cross-sections, are selected for more detailed consideration. The first is vortex-induced bending oscillation, a type of resonant response to the periodic surface pressure loading caused by the discrete wake vortex street formed from the shear layers separating from the bluff cross-section. Oscillation phenomena are described, including capture of the vortex frequency by the structural response frequency over a discrete wind speed range and amplification and phase shift of the loading over this range. The second form is transverse galloping, arising from aerodynamic instability of the bluff cross-sectional shape, so that small-amplitude oscillations generate forces which increase the amplitudes to large values. Oscillation phenomena are described, including the occurrence at very nearly natural frequencies, and the relatively large amplitudes (compared to vortex-induced oscillations) increasing with wind speed beyond a critical wind speed dependent on the level o fstructural damping. Effects of body and wind parameters on both forms of oscillation are considered, and methods of analysis and suppression for susceptible structures are described. Some probable future requirements and prospects are considered.
Calendar Year Reserves in the Multivariate Additive Model

For the multivariate additive model proposed by Hess et al. [2006] which provides an extension of the additive (or incremental loss ratio) method to correlated lines of business, we determine the Gauss{Markov predictors of the calendar year reserves and their mean squared error of prediction. We also show that the mean squared errors of prediction can be estimated by using moment estimators for the parameters which determine the correlation structure. The result is of interest with regard to Solvency II, and it is new even in the univariate case considered by Mack [1991].
Negative trion emission spectrum in stacked quantum dots: External electric field and valence band mixing

We study the negatively charged exciton trion in stacked quantum dots by the configuration interaction method. We discuss the trion recombination spectrum in an external electric field ($F$) and look for the effects of the valence band mixing leading to the antibonding-hole ground-state formation in the quantum dot molecule. We find that the antibonding-hole ground state produces a distinct modification of the trion emission for strongly coupled dots inverting the intensities of recombination lines in the principal avoided crossing appearing in the spectrum within the range of low $F$. This avoided crossing is very similar to the one observed for the neutral exciton only with a shift of the anticrossing centra on the scale of $F$. The exciton and trion emission spectra are distinctly different for weak interdot tunnel coupling, for which the effects of the antibonding-hole ground state are less evident for both the exciton and the trion. In particular for both the bonding and the antibonding-hole ground states the dissociation of the negative trion ground state appears as a two-stage process with a characteristic shape of the recombination line as observed experimentally.
Greedy Algorithm: Huffman Algorithm

This paper presents a survey on Greedy Algorithm. This discussion is centered on overview of huffman code, huffman algorithm and applications of greedy algorithm. A greedy algorithm is an algorithm that follows the problem solving heuristic of making the locally optimal choice at each stage with the hope of finding a global optimum. In many problems, a greedy strategy does not in general produce an optimal solution, but nonetheless a greedy heuristic may yield locally optimal solutions that approximate a global optimal solution in a reasonable time.Greedy algorithms determine the minimum number of coins to give while making change. These are the steps a human would take to emulate a greedy algorithm to represent 36 cents using only coins with values {1, 5, 10, 20}. The coin of the highest value, less than the remaining change owed, is the local optimum. (Note that in general the change-making problem requires dynamic programming or integer programming to find an optimal solution; However, most currency systems, including the Euro and US Dollar, are special cases where the greedy strategy does find an optimum solution.)
Operators on C(! ) which do not preserve C(! )

It is shown that if , are ordinals such that 1 < < ! , then there is an operator from C(! ) onto itself such that if Y is a subspace of C(! ) which is isomorphic to C(! ), then the operator is not an isomorphism on Y. This contrasts with a result of J. Bourgain that implies that there are uncountably many ordinals for which for any operator from C(! ) onto itself there is a subspace of C(! ) which is isomorphic to C(! ) on which the operator is an isomorphism.
Image Inpainting using Nonlinear Partial Differential Equations

Based on some geometrical considerations, we propose a two-step method to do digital image inpainting. In the first step, we try to propagate the isophote directions into the inpainting domain. An energy minimization model combined with the zero divergence condition is used to get a nonlinear Stokes equation. Once the isophote directions are constructed, an image is restored to fit the constructed directions. Both steps reduce to the solving of some nonlinear partial differential equations. Details about the discretization and implementation are explained. The algorithms have been intensively tested on synthetic and real images. The advantages of the proposed methods are demonstrated by these experiments.
Energy minimization of redundant manipulators using Generalized Pattern Search

Optimal motion planning is very important in the operation of robot manipulators. Its main target is the generation of a trajectory from start to goal that satisfies objectives, such as minimizing path traveling distance or time interval, lowest energy consumption or obstacle avoidance and satisfying the robot's kinematics and dynamics. Due to increasing demand on fuel consumption and the uprising political crisis, there is a need to optimize the energy consumption for stable and durable operation. In this paper, an optimal trajectory is designed for a three degree–of–freedom planar redundant manipulator under the criterion of minimum energy consumption. Each joint trajectory is assumed as a fourth order polynomial and the proposed algorithms are required to optimize the coefficients in such away the actuator torque will be minimized. Two optimization algorithms are presented here the Genetic Algorithm (GAs) and the Generalized Pattern Search (GPS). A simulation study to identify the optimal performance parameters is carried out using MATLAB. Comparison between the proposed two algorithms is carried out using the energy consumption per cycle, E, for validation.
Hate Speech on Campus: How Student Leaders of Color Respond

Abstract:The spike of hate speech incidents on college campuses since the 2016 U.S. presidential election has compounded the racial hostility students of color face on historically White campuses. These ongoing incidents require institutions to respond purposively to address the harm students of color experience in their aftermath. Using an "inclusive freedom" framework that connects freedom of expression with goals of inclusion, we employ an embedded single-case study of 28 student leaders of color to examine how they responded to hate speech in light of insufficient institutional action. Findings illustrate how student leaders of color bolster inclusion by leveraging their freedom of expression following hate speech incidents. Through efforts that were taxing and left them feeling drained, students generated affinity spaces and fostered dialogue about the negative impacts of hate speech on campus. Their experiences illuminate how institutions can more deliberately promote principles of inclusion and freedom of expression in their responses to hate speech within legal boundaries. These intentional efforts require an antiracist approach to inclusion that attends to the systemic factors that foster hate speech in the first place and to the deleterious consequences for students of color when they encounter hate speech on campus.
Spectral Test via Discrete Tchebichef Transform for Randomness

Random key plays essential roles in cryptography. NIST statistical test suite for randomness is the most comprehensive set of random tests. It has been popular and used as a benchmark test for randomness. One of the random tests is spectral test. There has been some serious problem in spectral test as pointed out by few researchers. In this paper, an alternative test shall be proposed to replace the spectral test. The distribution of discrete orthonormal Tchebichef transform has been obtained based on computational observation being made on random noise. A recommendation on the new random test setting for short cryptographic keys shall also be made.
Mathematical Model of Sulphomethylation Process of Nonylphenol

This paper concerns the development of the mat mathematical model of sulphomethylation process of nonylphenol based on planning of the experiment While developing the mathematical model of the process. a method of gross factor experiment (GFE). realizing all possible combinations of the factors chosen. was used by us. By varying four factors on two (minimum and maximum) levels. the experimental values of yields of the product required (sodium sulphate of hydroxynonylbenzyl sulphonic acid). were obtained The coefficients of regression equations Bi are calculated by scalar products Then the adequacy of the mathematical model was checked Thus. a mathematical model of the sulphomethylation process l)f nonylphenol in the full scale of coordinates was obtained.
Stabilisation of switched positive systems with actuator saturation

This study focuses on the stabilisation problem of switched positive systems with actuator saturation. Through multiple linear co-positive Lyapunov functions, the two cases of time-dependent switching and state-dependent switching are investigated for the first time. Sufficient conditions for stabilisation of the system are proposed under the state feedback controllers. In addition, the convex hull technique is employed to deal with actuator saturation. Finally, an application of the obtained results to the control of aero engines is proposed to demonstrate the validity.
Sampled-Data Control for Linear Systems with Time Delays

This paper investigates the sampled-data control of linear systems with time delays.Based on a novel time-dependent Lyapunov-krasovskii functional,the conditions for the exponential stability anylisis and state-feedback controller design of sampled-data systems are derived in terms of linear matrix inequalities(LMIs) via the descriptor and free-weighting matrix approaches.Finally,the simulation examples illustrate the feasibility and correctness of the conclusions.
Birth of a Theorem: A Mathematical Adventure

In 2009, the Wall Street Journal published the results of a survey designed to find out what is the best job to have based on a range of criteria including job satisfaction, stress level and salary. Perhaps just a little surprisingly the job of mathematician came top. Since then, the survey has been carried out regularly and although the job of mathematician has not completely monopolised first place, it has always been in the top handful and occasionally first. So what is it about mathematics that makes the job of mathematician so attractive? Cédric Villani makes a fascinating attempt to answer this question.
SEARCHING FOR LIGHT ECHOES DUE TO CIRCUMSTELLAR MATTER IN SNe Ia SPECTRA

We present an analytical model for light echoes (LEs) coming from circumstellar material (CSM) around Type Ia Supernovae (SNe Ia). Using this model we find two spectral signatures at 4100 Å and 6200 Å that are useful to identify LEs during the Lira law phase (between 35 and 80 days after maximum light) coming from nearby CSM at distances of 0.01–0.25 pc. We analyze a sample of 89 SNe Ia divided into two groups according to their B − V ? > decline rate during the Lira law phase, and search for LEs from CSM interaction in the group of SNe with steeper slopes by comparing their spectra with our LE model. We find that a model with LEs + pure extinction from interstellar material (ISM) fits the observed spectra better than a pure ISM extinction model that is constant in time, but we find that a decreasing extinction alone explains the observations better without the need of LEs, possibly implying dust sublimation due to the radiation from the SN.
Theoretical Methods of Infrared Image Signal Processing under Sea and Sky Background

Aiming at the needs of a given project design and the system application characteristics,theoretical methods of small and weak infrared target detection and position computation under the sea and sky background are discussed.Based on the project research practically,the theoretical methods of small and weak infrared target detection and position computation under the sea and sky are proposed in order to realize target detection and position computation rapidly.
Analogous Hawking radiation from gapped excitations in a transonic flow of binary Bose-Einstein condensates

We have studied analytically the approximate solutions to the gapped mode equations in the hydrodynamic regime for a class of binary Bose-Einstein condensate acoustic black holes. The horizon from the transonic flow is formed by manipulating the phonon sound speed and the flow velocity with the experimentally accessible parameters. The asymptotic modes of various scattering processes are constructed from which to obtain scattering coefficients and then to further decompose the field operator in terms of the asymptotic states. Also, the Unruh state is introduced to be the appropriate state for the description of gravitational collapse of the black hole. The particle densities of the outgoing modes are computed. The effective energy gap term in the dispersion relation of the gapped excitations introduces the threshold frequency $\omega_r$ in the subsonic regime, below which the propagating modes do not exist. Thus, the particle spectrum of the analogous Hawking modes in the exterior of the horizon of the subsonic region significantly deviates from that of the gapless cases near the threshold frequency due to the modified graybody factor, which vanishes as the mode frequency is below $\omega_r$. However, in the interior region of the horizon of the supersonic region, the spectrum of the particle production of the Hawking partner has the nonthermal feature. The correlators between the analog Hawking mode and its partner of relevance to the experimental observations are also investigated and show some peaks near the threshold frequency $\omega_r$ resulting from the gap energy term to be seen in future experiments.
G2T: A SIMPLE BUT VERSATILE FRAMEWORK FOR TOPIC MODELING BASED ON PRETRAINED LANGUAGE MODEL AND COMMUNITY DETECTION

It has been reported that clustering-based topic models, which cluster high-quality sentence embeddings with an appropriate word selection method, can generate better topics than generative probabilistic topic models. However, these approaches suffer from the inability to select appropriate parameters and incomplete models that overlook the quantitative relation between words with topics and topics with text. To solve these issues, we propose graph to topic (G2T), a simple but effective framework for topic modelling. The framework is composed of four modules. First, document representation is acquired using pretrained language models. Second, a semantic graph is constructed according to the similarity between document representations. Third, communities in document semantic graphs are identiﬁed, and the relationship between topics and documents is quantiﬁed accordingly. Fourth, the word–topic distribution is computed based on a variant of TFIDF. Automatic evaluation suggests that G2T achieved state-of-the-art performance on both English and Chinese documents with different lengths. Human judgements demonstrate that G2T can produce topics with better interpretability and coverage than baselines. In addition, G2T can not only determine the topic number automatically but also give the probabilistic distribution of words in topics and topics in documents. Finally, G2T is publicly available, and the distillation experiments provide instruction on how it works.
Magnon squeezing in conical spin spirals

We investigate squeezing of magnons in a conical spin spiral configuration. We find that while the energy of magnons propagating along the $\boldsymbol{k}$ and the $-\boldsymbol{k}$ directions can be different due to the non-reciprocal dispersion, these two modes are connected by the squeezing, hence can be described by the same squeezing parameter. The squeezing parameter diverges at the center of the Brillouin zone due to the translational Goldstone mode of the system, but the squeezing also vanishes for certain wave vectors. We discuss possible ways of detecting the squeezing.
Sequential importance sampling for

There are two generations of Gibbs sampling methods for semiparametric models involving the Dirichlet process. The first generation suffered from a severe drawback: the locations of the clusters, or groups of parameters, could essentially become fixed, moving only rarely. Two strategies that have been proposed to create the second generation of Gibbs samplers are integration and appending a second stage to the Gibbs sampler wherein the cluster locations are moved. We show that these same strategies are easily implemented for the sequential importance sampler, and that the first strategy dramatically improves results. As in the case of Gibbs sampling, these strategies are applicable to a much wider class of models. They are shown to provide more uniform importance sampling weights and lead to additional Rao-Blackwellization of estimators.
Computing Weak Distance between the 2-Sphere and Its Nonsmooth Approximations

A novel algorithm is proposed for quantitative comparisons between compact surfaces embedded in the three-dimensional Euclidian space. The key idea is to identify those objects with the associated surface measures and compute a weak distance between them using the Fourier transform on the ambient space. In particular, the inhomogeneous Sobolev norm of negative order for a difference between two surface measures is evaluated via the Plancherel theorem, which amounts to approximating a weighted integral norm of smooth data on the frequency space. This approach allows several advantages including high accuracy due to fast-converging numerical quadrature rules, acceleration by the nonuniform fast Fourier transform, and parallelization on many-core processors. In numerical experiments, the 2-sphere, which is an example whose Fourier transform is explicitly known, is compared with its icosahedral discretization, and it is observed that the piecewise linear approximations converge to the smooth object at the quadratic rate up to small truncation.
Incoherent mode division multiplexing for high-security information encryption

In the age of information explosion, the conventional optical communication protocols are rapidly reaching the limits of their capacity, as almost all available degrees of freedom (e.g., wavelength, polarization) for division multiplexing have been explored to date. Recent advances in coherent mode division multiplexing have greatly facilitated high-speed optical communications and secure, high-capacity information storage and transfer. However, coherent mode division multiplexing is quite vulnerable to even minute environmental disturbances which can cause significant information loss. Here, we propose and experimentally demonstrate a paradigm shift to incoherent mode division multiplexing for high-security optical information encryption by harnessing the degree of coherence of structured random light beams. In contrast to the conventional techniques, our approach does not require mode orthogonality to circumnavigate unwanted mode crosstalk. In addition, our protocol has, in principle, no upper bound on its capacity. Thanks to the extreme robustness of structured random light to external perturbations, we are able to achieve highly accurate information encryption and decryption in the adverse environment. The proposed protocol opens new horizons in an array of fields, such as optical communications and cryptography, and it can be relevant for information processing with acoustical, matter as well as other types of waves.