Miracle-dz/UniFAR-FTUs huggingface dataset:
Marchenko equations for acoustic Green's function retrieval and imaging in dissipative media

We present a scheme for Marchenko imaging in a dissipative heterogeneous medium. The scheme requires measured reflection and transmission data at two sides of the dissipative medium. The effectual medium is the same as the dissipative medium, but with negative dissipation. We show how the measured double-sided data can be combined to obtain the single-sided reflection response of the effectual medium. Two sets of single-sided Marchenko equations follow that are used to compute to the focusing wavefield and the Green functions. Each uses single-sided reflection responses of the dissipative and effectual medium. To start the solution for these equations an initial estimate of the dissipation is required in addition to the estimate of the travel time of the first arrival. Avoiding the estimate of dissipation of the first arrival in a low-loss medium does not have a detrimental effects on the image quality. The numerical example shows the effectiveness of this strategy.
Naive Bayes Classification for Subset Selection in a Multi-label Setting

This article introduces a novel probabilistic formulation of multi-label classification based on the Bayes theorem. Under the naive hypothesis of conditional independence of features given the labels, a pseudo-bayesian inference approach is adopted, known as Naive Bayes. The prediction consists of two steps: the estimation of the size of the target label set and the selection of the elements of this set. This approach is implemented in the \nbx algorithm, an extension of naive Bayes into the multi-label domain. Its properties are discussed and evaluated on real-world data.
Density Estimation Using Non-Conventional Statistics

In this work the use of non-conventional statistics for estimating the probability density function of a given process is investigated. It is well known that the calculation of higher-order statistics, like skewness and kurtosis (which I call C-moments), is very sensitive to the presence of outliers and very dependent on sample size. Recently, the development of L-moments estimators (which are linear combinations of ordered statistics) had a significant impact on the use of sample statistics to infer probabilities. In contrast to C-moments, L-moments provide more robust and consistent sample estimators. I take advantage of this fact to obtain superior nonparametric pdf estimates via the principle of maximum entropy. The potential use of alternative skewness and kurtosis measures is also explored. The results obtained from simulation studies are discussed.
System analysis and expected performance of a high-contrast module for HARMONI

HARMONI is a first-light visible and near-IR integral field spectrograph of ESO’s Extremely Large Telescope (ELT) which will sit on top of Cerro Armazones, Chile. A Single Conjugate Adaptive Optics (SCAO) subsystem will provide diffraction-limited spectro-images in a Nyquist-sampled 0.61 x 0.86 arcsec field of view, with a R=3000-20000 spectral resolution. Inside the instrument, a High Contrast Module (HCM) could give HARMONI the ability to spectrally characterize young giant exoplanets (and disks) with flux ratio down to 10−6 as close as 100-200mas from their star. This would be achieved with an apodized pupil coronagraph to attenuate the diffracted light of the star and limit the dynamic range on the detector, and an internal ZELDA wavefront sensor to calibrate non-common path aberrations, assuming that the surface quality of the relay optics of HARMONI satisfy specific requirements. This communication presents (a) the system analysis that was conducted to converge towards these requirement, and the proposed HCM design, (b) an end-to-end simulation tool that has been built to produce realistic datacubes of hour-long observations, and (c) the estimated performance of the HCM, which has been derived by applying differential imaging techniques on the simulated data.
"Zero Cost" Majority Attacks on Permissionless Blockchains

The core premise of permissionless blockchains is their reliable and secure operation without the need to trust any individual agent. At the heart of blockchain consensus mechanisms is an explicit cost (whether work or stake) for participation in the network and the opportunity to add blocks to the blockchain. A key rationale for that cost is to make attacks on the network, which could be theoretically carried out if a majority of nodes were controlled by a single entity, too expensive to be worthwhile. We demonstrate that a majority attacker can successfully attack with a {\em negative cost}, which shows that the protocol mechanisms are insufficient to create a secure network, and emphasizes the importance of socially driven mechanisms external to the protocol. At the same time, negative cost enables a new type of majority attack that is more likely to elude external scrutiny.
Hotel Post Covid-19: How Preparedness Affects Guest Satisfaction In A Mid-Scales Hotel

Post-pandemic health strategies will be critical to hotel success. Guests' expectations regarding sanitation, cleanliness, safety, and health continue to rise. As a mitigation plan, hotel preparedness is essential to ensure guest satisfaction. Still, few studies examine the relationship between preparedness and guest satisfaction during the COVID-19 pandemic. This study aims to determine the effect of preparedness on guest satisfaction and assess the preparedness’s importance and performance on guest satisfaction in Bandung. The mid-scale hotel category was chosen as the unit of study since it contains the majority of hotels in Bandung. This quantitative cross-sectional study was undertaken. The data was gathered using a questionnaire survey of respondents who had stayed in the mid-scale hotel in Bandung during the pandemic. The data was analyzed using Structural Equation Modeling (SEM) PLS and Importance-Performance Map Analysis (IPMA). According to the research findings, hotel preparedness has a synergic effect on guest satisfaction. Preparedness is a process, not a product, and each practice cannot be attained separately but must be integrated to ensure guest satisfaction. This research contributes that implementing crisis management through preparedness has an essential role in guest satisfaction; practically, hotels are expected to focus on cleanliness quality and strengthen human resources by enhancing employee competencies since they have the highest level of importance in reducing the risk of COVID-19. Keywords— COVID-19, Guest Satisfaction, Mid-Scale Hotel, Preparedness
Magnetocaloric effect in single-crystal HoNi with a canted magnetic structure

We have studied the magnetocaloric effect (MCE) of single-crystal HoNi, which shows a ferromagnetic transition at TC = 35 K and a spin-reorientation transition at TSR = 13 K. Below TC, HoNi has ferromagnetic and antiferromagnetic components along the a- and c-axes, respectively. We find that the MCE in HoNi is highly anisotropic owing to the canted magnetic structure of this material. When a magnetic field is applied along the a- (B ∥ a) and b-axes (B ∥ b), the maximum isothermal magnetic-entropy change reaches 22.8 J K−1 kg−1 at 35 K and 18.8 J K−1 kg−1 at 13 K, respectively, when the magnetic field is increased from 0 to 5 T. On the other hand, for B ∥ c, is approximately three times smaller than those for B ∥ a and B ∥ b. In addition, the sign of depends on the temperature owing to the antiferromagnetic component along the c-axis and the existence of a metamagnetic transition.
The conceptual basis of addiction memory, allostasis and dual processes, and the classical therapy of addiction

Purpose In recent years, research has yielded new information regarding the impact of intense, long-term alcohol consumption on the development of permanent changes in the central nervous system. The present study examines the mechanisms related to the existence of addiction memory, sensitization and allostasis. A dual-process model was also created, which analyses the role of conscious and automatic mechanisms in the functioning of addicts. The aim of the article is to present these mechanisms and to consider the implications of their existence for the course of therapy. Views The mechanisms analysed shed new light on some of the negative phenomena occurring during and after therapy, such as frequent abstinence after treatment, switching addictions, and returning to drinking after a long period of abstinence. The existence of these mechanisms should also change the character of addiction therapy, which has so far focused mainly on conscious aspects and ignored the existence of automatic ones. Attempts are already being made to implement the dual-process model in addiction therapy. Conclusions A better understanding of the mechanisms resulting from the dual-process model can significantly influence perspectives regarding functioning in addiction and the course of therapy. These processes merit further research, as do possible therapeutic interventions based on them.
Non-autonomous Eigenvalue Problems with Variable (p1,p2)-Growth

Abstract We are concerned with the study of a class of non-autonomous eigenvalue problems driven by two non-homogeneous differential operators with variable (p1,p2){(p_{1},p_{2})}-growth. The main result of this paper establishes the existence of a continuous spectrum consisting in an unbounded interval and the nonexistence of eigenvalues in a neighbourhood of the origin. The abstract results of this paper are described by two Rayleigh-type quotients and the proofs rely on variational arguments.
A Modeling Study of Stacked Cu-CNT TSV on Electrical, Thermal, and Reliability Analysis

In this article, we propose a position-oriented carbon nanotube (CNT) sampling method based on the Monte Carlo (MC) concept, which obtains the relative positional distribution and concentration of CNTs, providing an accurate modeling basis. The copper-CNT (Cu-CNT) through-silicon via (TSV) model is established through the transition from the unit level to the circuit level, and the circuit analysis is performed with the TSV pair. We find that Cu-CNT TSVs have better resistivity than Cu TSVs in long-distance transport under the premise of ensuring variability. But CNT does not optimize the crosstalk performance of the composite material, as expected, due to the inhibition of CNTs by Cu in the composite. Cu-CNT well reduces the negative impact of interfacial resistance on delay (< 0.146%) and exhibits excellent heat dissipation and reliability. Under ideal conditions, its median time to failure (MTTF) can be as high as Cu ten times with a small current capacity loss. Moreover, we also intersperse discussions of changes in the filling ratio, CNT diameter, and aspect ratio (AR) throughout the analysis to further study the effect of CNT variability.
Non-Linear Regularized Attenuation Compensation for Microwave Breast Imaging

We develop non-linear optimization algorithms for attenuation compensation of rapidly time-varying microwave signals in the context of breast imaging. The breast tissues attenuate the energy of the scattered wavefield as it travels within the medium. Compensating the attenuation effect is a challenging and typically unstable task. To address this issue, we develop inversion-based algorithms that take advantage of prior knowledge about the system. We formulate the attenuation compensation as a regularized non-linear cost function and introduce two efficient algorithms. The first algorithm assumes that the reflectivity series is smooth and follows a Gaussian distribution, i.e., <inline-formula><tex-math notation="LaTeX">$\ell _{2}$</tex-math></inline-formula> norm, and the second algorithm assumes that it can be cast as a sparse series, i.e., <inline-formula><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula> norm. Also, both algorithms force the inverted quality factor to be close to an expected value based on previous evaluations of different models and datasets. Through testing of the algorithms on simulated and experimental datasets, we show that the proposed algorithms successfully compensate for attenuation. The images after attenuation compensation provide more accurate localization of the tumors and superior resolution when compared with conventional imaging practice.
Internet-Based Treatment of Body Dysmorphic Disorder

Abstract Initial findings indicate the effectiveness of internet-based interventions for body dysmorphic disorder (BDD). In order to substantiate these findings, a seven-module guided internet-based intervention was created and examined. We report the mixed data of participants with clinical and subclinical BDD of the treatment group (n = 18). We investigated the feasibility, the quality of the program content, the design and usability, and its effects on symptom severity and related psychopathology. Adherence to the intervention was low and dropout rate high (55.6%). The program content, perceived website usability, and visual aesthetic were rated high. Credibility and expectancy were on a medium level. Satisfaction with appearance improved significantly in the intention-to-treat analysis (d = 0.58). In sum, symptom-related outcomes and program evaluation showed a positive trend albeit the study conduction was difficult. Future programs should investigate the role of additional motivation strategies and more flexible support addressing the known treatment barriers.
Dimensionless design model for biaxial Cartwheel flexure hinges

ABSTRACT Flexure hinges have been widely used in space-borne telescopes for mounting reflective optics with high surface figure requirements. To realize the three-point flexural mount of a Φ750 mm primary mirror, a Cartwheel biaxial flexural hinge composed by filleted short beams is proposed and the dimensionless design graph method for the flexural hinge is presented. The finite element analysis is performed on the flexure model to validate the proposed method. We also demonstrate the feasibility of the proposed method experimentally. The maximum relative error of the rotational stiffness between analysis, testing result, and design value is 5.0%. The proposed dimensionless design graph can be used as a design tool to determine the optimal geometry of a spatial flexure hinge rapidly.
Quantum Matrices Using Quantum Gates

Quantum mechanics explains the behavior of matter and its movement with energy in the scale of atoms and subatomic particles. In quantum circuits there are many gates such as Hadamard Gate, Pauli Gates, many more gates for half turns, quarter turns, eighth turns, sixteenth turns and so on, rest for spinning, parametrized etc. Linear operators in general and quantum mechanics can be represented in the form of vectors and in turn can be viewed as matrices format because linear operators are totally equivalent with the matrices view point. This paper discloses creation of various quantum matrices using Quantum bits. Square, Identity and Transposition of matrices are performed considering whole process in entanglement. Angle, phase, coordinates, magnitude, complex numbers and amplitude has been noted and documented in this paper for further research.
Statistical aspects of credit scoring

This thesis is concerned with statistical aspects of credit scoring, the process of determining how likely an applicant for credit is to default with repayments. In Chapters 1-4 a detailed introduction to credit scoring methodology is presented, including evaluation of previous published work on credit scoring and a review of discrimination and classification techniques. In Chapter 5 we describe different approaches to measuring the absolute and relative performance of credit scoring models. Two significance tests are proposed for comparing the bad rate amongst the accepts (or the error rate) from two classifiers. In Chapter 6 we consider different approaches to reject inference, the procedure of allocating class membership probabilities to the rejects. One reason for needing reject inference is to reduce the sample selection bias that results from using a sample consisting only of accepted applicants to build new scorecards. We show that the characteristic vectors for the rejects do not contain information about the parameters of the observed data likelihood, unless extra information or assumptions are included. Methods of reject inference which incorporate additional information are proposed. In Chapter 7 we make comparisons of a range of different parametric and nonparametric classification techniques for credit scoring: linear regression, logistic regression, projection pursuit regression, Poisson regression, decision trees and decision graphs. We conclude that classifier performance is fairly insensitive to the particular technique adopted. In Chapter 8 we describe the application of the k-NN method to credit scoring. We propose using an adjusted version of the Eucidean distance metric, which is designed to incorporate knowledge of class separation contained in the data. We evaluate properties of the k-NN classifier through empirical studies and make comparisons with existing techniques.
Extended Target Fast Labeled Multi-Bernoulli Filter

Focusing on the real-time tracking of the extended target labeled multi-Bernoulli (ET-LMB) filter, this paper proposes an extended target fast labeled multi-Bernoulli (ET-FLMB) filter based on beta gamma box particle (BGBP) and Gaussian process (GP), called ET-BGBP-GP-FLMB filter. First, a new ET-FLMB filter is derived to reduce the computational complexity of the ET-LMB filter. Then, by modeling the target state as an augmented state including detection probability, measurement rate, kinematic state and extension state, the BGBP-GP implementation of the ET-FLMB filter is presented. Compared with the traditional sequential Monte Carlo (SMC) implementation, the proposed implementation can not only greatly reduce the number of particles and the amount of computation, but also estimate the detection probabilities, measurement rates and extension states while estimating the number and kinematic states of extended targets. Finally, the simulation results show that the proposed filter can significantly reduce the computational burden and improve the real-time performance.
Design of FRM-based MDFT filter banks in the canonic signed digit space using modified meta-heuristic algorithms

An optimal totally multiplier-less sharp transition width Modified Discrete Fourier Transform (MDFT) filter bank is proposed in this work. Since, here, the aim is to design a low complexity sharp transition width MDFT filter bank, the filters of the filter bank are designed using Frequency Response Masking technique to reduce the number of multipliers and hence the complexity. To replace multipliers with adders and shifters, the filter coefficients are converted into the Canonic Signed Digit space. In order to reduce the number of adders and shifters in the multiplier-less implementation, restricted number of non-zero bits is used in the conversion. This may degrade the performances of the MDFT filter bank. The performances are improved using modified meta-heuristic algorithms. A new hybrid algorithm which combines the qualities of Harmony Search Algorithm and Gravitational Search Algorithm is proposed in this work to optimise the performance of the MDFT filter bank.
Confinement effects on Brillouin scattering in semiconductor nanowire photonic crystal

Scattering of photons by phonons, or Brillouin scattering, enables manipulation and control of light and has led to revolutionary applications, from slow light to saser and cooling of micromechanical resonators. Recently, enhanced light and sound interaction has been demonstrated in waveguides. However, the design of the waveguide geometry tunes and alters the phonon and photon dispersion simultaneously. Here we investigate, through femtosecond pump-probe spectroscopy and theoretical modeling, the light and sound interaction in a bottom-up fabricated vertical nanowire photonic crystal. In such a system, the phonon dispersion can be tuned by varying the geometry of the constituent nanowires. In contrast, the placement of the nanowires in the photonic crystal can be used for tuning optical array modes, without altering the phonon dispersion. We demonstrate the forward and backward scattering, by acoustic phonons in the nanowires, of (1) such optical array modes and (2) guided modes of the constituent nanowires. Furthermore, our results reveal an enhanced interaction of array modes with phonons that we attribute to the specific scattering mechanism. Our results enable the design of a photonic crystal with separately tailored photon and phonon dispersion for Brillouin scattering. We anticipate these advances to be a starting point for enhanced control of light at the nanoscale.
Effects of Plasma Treatment on the Surface and Photocatalytic Properties of Nanostructured SnO2–SiO2 Films

In this work, we study the effects of treating nanostructured SnO2–SiO2 films derived by a sol-gel method with nitrogen and oxygen plasma. The structural and chemical properties of the films are closely investigated. To quantify surface site activity in the films following treatment, we employed a photocatalytic UV degradation test with brilliant green. Using X-ray photoelectron spectroscopy, it was found that treatment with oxygen plasma led to a high deviation in the stoichiometry of the SnO2 surface and even the appearance of a tin monoxide phase. These samples also exhibited a maximum photocatalytic activity. In contrast, treatment with nitrogen plasma did not lead to any noticeable changes in the material. However, increasing the power of the plasma source from 250 W to 500 W led to the appearance of an SnO fraction on the surface and a reduction in the photocatalytic activity. In general, all the types of plasma treatment tested led to amorphization in the SnO2–SiO2 samples.