Miracle-dz/UniFAR-FTUs huggingface dataset:
Manufacturing flow control and preventing maintenance: a stochastic control approach

A stochastic control model for simultaneously planning production and maintenance in a flexible manufacturing system (FMS) is proposed, and an efficient technique for computing the optimal control policy is developed. The model extends previous formulations by including an age-dependent machine failure rate and by allowing the control to influence some jump rates (namely the preventive maintenance activities). By using an adaptation to the case of piecewise-deterministic systems of the approximation technique initially proposed by H.J. Kushner (1977) in the realm of the optimal control of diffusions, one shows how it is possible to computer the optimal control for a two-machine system. >
Breast Cancer Diagnosis in Thermography Using Pre-Trained VGG16 with Deep Attention Mechanisms

One of the most prevalent cancers in women is breast cancer. The mortality rate related to this disease can be decreased by early, accurate diagnosis to increase the chance of survival. Infrared thermal imaging is one of the breast imaging modalities in which the temperature of the breast tissue is measured using a screening tool. The previous studies did not use pre-trained deep learning (DL) with deep attention mechanisms (AMs) on thermographic images for breast cancer diagnosis. Using thermal images from the Database for Research Mastology with Infrared Image (DMR-IR), the study investigates the use of a pre-trained Visual Geometry Group with 16 layers (VGG16) with AMs that can produce good diagnosis performance utilizing the thermal images of breast cancer. The symmetry of the three models resulting from the combination of VGG16 with three types of AMs is evident in all its stages in methodology. The models were compared to state-of-art breast cancer diagnosis approaches and tested for accuracy, sensitivity, specificity, precision, F1-score, AUC score, and Cohen’s kappa. The test accuracy rates for the AMs using the VGG16 model on the breast thermal dataset were encouraging, at 99.80%, 99.49%, and 99.32%. Test accuracy for VGG16 without AMs was 99.18%, whereas test accuracy for VGG16 with AMs improved by 0.62%. The proposed approaches also performed better than previous approaches examined in the related studies.
Study of the Performance Enhancement of Sc-Doped AlN Super High Frequency Cross-Sectional Lamé Mode Resonators

The increasing use of mobile broadband requires new acoustic filtering technologies that can operate efficiently at frequencies above 6 GHz. Previous research has shown that AlN Super High Frequency (SHF) Cross-Sectional Lamé Mode resonators (CLMRs) can address this challenge, but their performance is limited by the piezoelectric strength of AlN. In this work, we explore the use of substitutional doping of Al in AlN with Sc to enhance the kt2 values of SHF CLMRs. Our results showed that the measured kt2·Qm product of Al72Sc28N CLMRs was four times greater than that of AlN CLMRs operating at the same frequency. Additionally, the measured fractional bandwidth (FWB) of Al72Sc28N 2nd order ladder filters was 4.13%, a fourfold improvement over AlN filters with the same design. We also discuss other aspects of the technology, such as power handling, losses, and spurious mode suppression, and identify potential areas for future research.
Path Integral Derivation of Black Hole Radiance

The Feynman path-integral method is applied to the quantum mechanics of a scalar particle moving in the background geometry of a Schwarzschild black hole. The amplitude for the black hole to emit a scalar particle in a particular mode is expressed as a sum over paths connecting the future singularity and infinity. By analytic continuation in the complexified Schwarzschild space this amplitude is related to that for a particle to propagate from the past singularity to infinity and hence by time reversal to the amplitude for the black hole to absorb a particle in the same mode. The form of the connection between the emission and absorption probabilities shows that a Schwarzschild black hole will emit scalar particles with a thermal spectrum characterized by a temperature which is related to its mass, $M$, by $T=\frac{\ensuremath{\hbar}{c}^{3}}{8\ensuremath{\pi}}\mathrm{GMk}$. Thereby a conceptually simple derivation of black-hole radiance is obtained. The extension of this result to other spin fields and other black-hole geometries is discussed.
Radiation induced loss measurements of optical fibres with optical time domain reflectometers (OTDR) at high and low dose rates

The proven way of determining induced loss of optical fibres are transmission loss measurements. For longterm irradiations of radiation hard fibres at low dose rates, however, the induced loss is mostly small compared to the unavoidable drifts of the measuring system. Measurements with OTDRs where each time a new absolute loss measurement is performed could overcome this problem, provided this method yields the same results as transmission loss measurements. The authors made measurements on single mode and graded index fibres with OTDRs of three different manufacturers and found that, under comparable conditions, OTDR measurements yield exactly the same results. <<ETX>>
Control and stabilization of nonholonomic Caplygin dynamic systems

A theoretical framework is established for the control of nonholonomic Caplygin dynamic systems, i.e., nonholonomic systems with certain symmetry properties which can be expressed by the fact that the Lagrangian and constraints are cyclic in certain of the variables. A model is presented in terms of differential-algebraic equations defined on a phase space. A nonlinear control system in a normal form is then introduced to completely describe the dynamics. The structure of the normal form equations allows identification of a base spaces, on which a set of decoupled controllable dynamics is defined. The emphasis of the present work is on control of the normal form equations on the complete phase space. The control system, linearized at an equilibrium, always has uncontrollable eigenvalues with zero real part, their number being equal to the number of nonintegrable constraints. However, the equilibrium is shown to be strongly accessible and small time locally controllable. Conditions for smooth asymptotic stabilization to an m-dimensional equilibrium manifold are presented. <<ETX>>
Aerosol Characterization and Direct Radiative Forcing Assessment over the Ocean. Part I: Methodology and Sensitivity Analysis

A method based on the synergistic use of low earth orbit (LEO) and geostationary earth orbit (GEO) satellite data for aerosol-type characterization, as well as aerosol optical thickness (AOT) retrieval and monitoring over the ocean, is presented. These properties are used for the estimation of the direct shortwave aerosol radiative forcing at the top of the atmosphere. The synergy serves the purpose of monitoring aerosol events at the GEO time and space scales while maintaining the accuracy level achieved with LEO instruments. Aerosol optical properties representative of the atmospheric conditions are obtained from the inversion of high-spectral-resolution measurements from the Global Ozone Monitoring Experiment (GOME). The aerosol optical properties are input for radiative transfer calculations for the retrieval of the AOT from GEO visible broadband measurements, avoiding the use of fixed aerosol models available in the literature. The retrieved effective aerosol optical properties represent an essential component for the aerosol radiative forcing assessment. A sensitivity analysis is also presented to quantify the effects that changes on the aerosol model may have on modeled results of spectral reflectance, AOT, and direct shortwave aerosol radiative forcing at the top of the atmosphere. The impact on modeled values of the physical assumptions on surface reflectance and vertical profiles of ozone and water vapor are analyzed. Results show that the aerosol model is the main factor influencing the investigated radiative variables. Results of the application of the method to several significant aerosol events, as well as their validation, are presented in a companion paper.
Robust stability analysis of uncertain linear systems with input saturation using piecewise Lyapunov functions

In this paper, we consider the problem of finding the stability region in state space for uncertain linear systems with input saturation. For stability analysis, two Lyapunov functions are chosen. One is for the linear region and the other is for the saturated region. Piecewise Lyapunov functions are obtained by solving successive linear matrix inequalities(LMIs) relaxations. A sufficient condition for robust stability is derived in the form of stability region of initial conditions. A numerical example shows the effectiveness of the proposed method. c
Direct numerical simulation of stationary homogeneous stratified sheared turbulence

Abstract Using direct numerical simulation, we investigate stationary and homogeneous shear-driven turbulence in various stratifications, ranging from neutral to very stable. To attain and maintain a stationary flow, we throttle the mean shear so that the net production stays constant for all times. This results in a flow that is characterized solely by its mean shear and its mean buoyancy gradient, independent of initial conditions. The method of throttling is validated by comparison with experimental spectra in the case of neutral stratification. With increasing stratification comes the emergence of vertically sheared large-scale horizontal motions that preclude a straightforward interpretation of flow statistics. However, once these motions are excluded, simply by subtracting the horizontal average, the underlying flow appears amenable to the standard methods of turbulence analysis. It is shown that a direct acknowledgement of the confining influence of the periodic simulation box can lead to a meaningful physical interpretation of the large scales. Once an appropriate confinement scale is identified, many features, including horizontal spectra, flux–gradient relationships and length scales, of stratified sheared turbulence can be readily understood, both qualitatively and quantitatively, in terms of Monin–Obukhov similarity theory. Finally, the similarity-theory framework is used to interpret the scaling of the vertical diapycnal diffusivity in stratified turbulence.
Effect of pleural invasion on survival of patients with small cell lung cancer: Propensity score analysis and nomogram establishment based on the SEER database

Objectives Pleural invasion (PI) is identified as an adverse prognostic factor for non-small cell lung cancer (NSCLC), but its value in small cell lung cancer (SCLC) remains unclear. We aimed to evaluate the survival effect of PI on overall survival (OS) in SCLC, meanwhile, we established a predictive nomogram based on related risk factors for OS in SCLC patients with PI. Methods We extracted the data of patients diagnosed with primary SCLC between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database. The propensity score matching (PSM) method was used to minimize the baseline difference between the non-PI and PI groups. Kaplan-Meier curves and the log-rank test were used for survival analysis. Univariate and multivariate Cox regression analyses were applied to identify the independent prognostic factors. Randomly divided the patients with PI into training (70%) and validation (30%) cohorts. A prognostic nomogram was established based on the training cohort and was evaluated in the validation cohort. The C-index, receiver operating characteristic curves (ROC), calibration curves, and decision curve analysis (DCA) were applied to assess the performance of the nomogram. Results A total of 1,770 primary SCLC patients were enrolled, including1321patients with non-PI and 449 patients with PI. After PSM, the 387 patients in the PI group matched the 387 patients in the non-PI group. By Kaplan-Meier survival analysis, we observed the exact beneficial effect of non-PI on OS in both original and matched cohorts. Multivariate Cox analysis showed similar results to demonstrate a statistically significant benefit for patients with non-PI in both original and matched cohorts. Age, N stage, M stage, surgery, radiotherapy, and chemotherapy were independent prognostic factors for SCLC patients with PI. The C-index of the nomogram in the training and validation cohort was 0.714 and 0.746, respectively. The ROC curves, calibration curves, and DCA curves also demonstrated good predictive performance in the training and validation cohorts of the prognostic nomogram. Conclusion Our study shows that PI is an independent poor prognostic factor for SCLC patients. The nomogram is a useful and reliable tool to predict the OS in SCLC patients with PI. The nomogram can provide strong references to clinicians to facilitate clinic decisions.
The kernel algorithm for PLS

A fast and memory‐saving PLS regression algorithm for matrices with large numbers of objects is presented. It is called the kernel algorithm for PLS. Long (meaning having many objects, N) matrices X (N × K) and Y (N × M) are condensed into a small (K × K) square ‘kernel’ matrix XTYYTX of size equal to the number of X‐variables. Using this kernel matrix XTYYTX together with the small covariance matrices XTX (K × K), XTY (K × M) and YTY (M × M), it is possible to estimate all necessary parameters for a complete PLS regression solution with some statistical diagnostics. The new developments are presented in equation form. A comparison of consumed floating point operations is given for the kernel and the classical PLS algorithm. As appendices, a condensed matrix algebra version of the kernel algorithm is given together with the MATLAB code.
Constrained Self-Adaptive Physics-Informed Neural Networks with ResNet Block-Enhanced Network Architecture

Physics-informed neural networks (PINNs) have been widely adopted to solve partial differential equations (PDEs), which could be used to simulate physical systems. However, the accuracy of PINNs does not meet the needs of the industry, and severely degrades, especially when the PDE solution has sharp transitions. In this paper, we propose a ResNet block-enhanced network architecture to better capture the transition. Meanwhile, a constrained self-adaptive PINN (cSPINN) scheme is developed to move PINN’s objective to the areas of the physical domain, which are difficult to learn. To demonstrate the performance of our method, we present the results of numerical experiments on the Allen–Cahn equation, the Burgers equation, and the Helmholtz equation. We also show the results of solving the Poisson equation using cSPINNs on different geometries to show the strong geometric adaptivity of cSPINNs. Finally, we provide the performance of cSPINNs on a high-dimensional Poisson equation to further demonstrate the ability of our method.
Contactless determination and parametrization of charge-carrier mobility in silicon as a function of injection level and temperature using time-resolved terahertz spectroscopy

Here, we analyze in a non-contact fashion charge carrier mobility as a function of injection level and temperature in silicon by time resolved THz spectroscopy (TRTS) and parametrize our data by the classical semi-empirical models of Klaassen and Dorkel&Leturcq. Our experimental results are in very good agreement with the pioneering works of Krausse and D\"annhauser analyzing this phenomena by employing contact-based methods. This agreement, that validates our methodology, can only be achieved by considering charge carrier diffusion effects following above bandgap near-surface pump photo-excitation of the sample. From our results, obtained over a large range of injection levels, we conclude that the model of Klaassen is the best on describing the collected data at room temperature. Furthermore, we analyze by TRTS the dependence of charge carrier mobility with temperature for a fixed injection level. Once more, the parametrization made by the classical model of Klaassen describe our data appropriately even without the necessity of applying any fitting parameters (just with the charge carrier density as an input). In this respect, our work supports the validity of the model and parametrization proposed by Klaassen, and also illustrate how TRTS can be reliably employed for the quantitative determination of mobility in semiconductors as a function of key parameters as injection level and temperature.
Spectral characterization and severity assessment of rice blast disease using univariate and multivariate models

Rice is the staple food of more than half of the population of the world and India as well. One of the major constraints in rice production is frequent occurrence of pests and diseases and one of them is rice blast which often causes yield loss varying from 10 to 30%. Conventional approaches for disease assessment are time-consuming, expensive, and not real-time; alternately, sensor-based approach is rapid, non-invasive and can be scaled up in large areas with minimum time and effort. In the present study, hyperspectral remote sensing for the characterization and severity assessment of rice blast disease was exploited. Field experiments were conducted with 20 genotypes of rice having sensitive and resistant cultivars grown under upland and lowland conditions at Almora, Uttarakhand, India. The severity of the rice blast was graded from 0 to 9 in accordance to International Rice Research Institute (IRRI). Spectral observations in field were taken using a hand-held portable spectroradiometer in range of 350-2500 nm followed by spectral discrimination of different disease severity levels using Jeffires–Matusita (J-M) distance. Then, evaluation of 26 existing spectral indices (r≥0.8) was done corresponding to blast severity levels and linear regression prediction models were also developed. Further, the proposed ratio blast index (RBI) and normalized difference blast index (NDBI) were developed using all possible combinations of their correlations with severity level followed by their quantification to identify the best indices. Thereafter, multivariate models like support vector machine regression (SVM), partial least squares (PLS), random forest (RF), and multivariate adaptive regression spline (MARS) were also used to estimate blast severity. Jeffires–Matusita distance was separating almost all severity levels having values >1.92 except levels 4 and 5. The 26 prediction models were effective at predicting blast severity with R2 values from 0.48 to 0.85. The best developed spectral indices for rice blast were RBI (R1148, R1301) and NDBI (R1148, R1301) with R2 of 0.85 and 0.86, respectively. Among multivariate models, SVM was the best model with calibration R2=0.99; validation R2=0.94, RMSE=0.7, and RPD=4.10. The methodology developed paves way for early detection and large-scale monitoring and mapping using satellite remote sensors at farmers’ fields for developing better disease management options.
A Randomized, Double-Blind, Monocentric, and Placebo-Controlled Blood Glycemic Response Evaluation of Sweetch, a Natural Sugar Replacement Blend, on Healthy Volunteers

Diabetes mellitus is a serious global concern due to its long-term health-related effects and the financial burden it poses to healthcare systems and families around the world. Excess consumption of sugar is one of the main causes of the issue. There are many sweetening ingredients that claim to be the solution to substitute normal sugar while maintaining the blood sugar level at a low level, yet the evidence is lacking and not always substantiated. Sweetch Natural Sugar Replacement is a proprietary natural sugar alternative product composed of a blend of different plant-derived sweetening ingredients. It has zero calories, no added flavor, non-GMO, and the same taste profile and measure as sugar (1:1 replacement). It is appropriate in drinks as well as any form of cooking. The objective of this study is to evaluate changes in blood sugar levels, as well as the safety of human volunteers after oral absorption of Sweetch Natural Sugar Replacement, substantiating Sweetch claim on zero glycemic response. The efficacy and safety analyses were performed using the principles of a fasting blood sugar level test on 22 randomized subjects practicing a healthy lifestyle. Participants were divided into 2 groups: An active group using the investigational product (IP; 50 g of the IP dissolved into mineral water.) versus a controlled group using a placebo (plain mineral water). After 12 hours of overnight fasting, volunteers took their drink orally and their blood samples were taken at specific time points (T0, T30 min, and T2 h) to measure blood glucose levels. Results indicate that there is no significant difference in the average blood glucose level at various time points between the active group and the placebo group. This study confirms that Sweetch Natural Sugar Replacement does not cause any noticeable changes in blood sugar levels post-oral administration. No adverse health events were observed throughout the study. Through this study, Sweetch Natural Sugar Replacement’s claim on zero glycemic index (GI) is proven legitimate.
Assessing vestibular function using electroencephalogram rhythms evoked during the caloric test

Introduction The vestibular system is responsible for motion perception and balance preservation in the body. The vestibular function examination is useful for determining the cause of associated symptoms, diagnosis, and therapy of the patients. The associated cerebral cortex processes and integrates information and is the ultimate perceptual site for vestibular-related symptoms. In recent clinical examinations, less consideration has been given to the cortex associated with the vestibular system. As a result, it is crucial to increase focus on the expression of the cortical level while evaluating vestibular function. From the viewpoint of neuroelectrophysiology, electroencephalograms (EEG) can enhance the assessments of vestibular function at the cortex level. Methods This study recorded nystagmus and EEG data throughout the caloric test. Four phases were considered according to the vestibular activation status: before activation, activation, fixation suppression, and recovery. In different phases, the distribution and changes of the relative power of the EEG rhythms (delta, theta, alpha, and beta) were analyzed, and the correlation between EEG characteristics and nystagmus was also investigated. Results The results showed that, when the vestibule was activated, the alpha power of the occipital region increased, and the beta power of the central and top regions and the occipital region on the left decreased. The changes in the alpha and beta rhythms significantly correlate with nystagmus values in left warm stimulation. Discussion Our findings offer a fresh perspective on cortical electrophysiology for the assessment of vestibular function by demonstrating that the relative power change in EEG rhythms can be used to assess vestibular function.