Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Measurements with Modified HVD Series of High Voltage Dividers

HVD series of precision high voltage dividers manufactured by Spellman are specified for DC measurements only. As such, they possess very high input impedance (1 $\mathrm{G}\Omega$ and higher) and are corona-free. We modified 100-kV and 200-kV models for time-domain measurements, extending the range of HVD100 to 140 kV. These models are dubbed HVD100C, HVD140C, and HVD200C (“C” stands for “compensated”). The last two models' corona suppression electrodes have also been modified, and E-field analysis is described showing that the field is below corona inception. Typical usable risetime is 2 ${\mu} \mathrm{s}$ for 100-kV and 140-kV models, and 10 $\mu \mathrm{s}$ for the 200-kV model. Settling time to 0.2 % is less than 2 ms for 100-kV and 140-kV models. HVDs are calibrated for fast response both at low and high voltage by step response method; calibration results are provided. The modified, compensated, versions retain the same NIST-traceable DC accuracy as their original DC counterparts. Compensated HVDs are useful for laboratory and manufacturing practices when fast HV time domain measurements are necessary in combination with high dc accuracy and high input impedance.
Stabilization of a class of infinite-dimensional systems subjected to unknown matched disturbances

In this paper, we consider the problem of constructing an output-feedback controller for stabilizing an un-stable linear PDE system with bounded control and observation operators driven by an unknown disturbance. The disturbance is matched with the input of the PDE system and its derivative is assumed to be bounded. Under a smoothness assumption on the observation operator and an observability matching condition, we first develop a linear observer with disturbance decoupling for state estimation and then we develop a sliding mode observer for estimating the disturbance. Using the estimated state and disturbance we implement a state-feedback control law which guarantees the exponential decay of the state of the PDE system to zero for all initial states. Our approach assumes certain prior knowledge regarding the stabilization and estimation of the PDE system in the absence of disturbances. Our contribution lies in performing stabilization (convergence of state to zero) and estimation in the presence of unknown disturbances. We illustrate our controller design approach in simulations using an unstable 1D heat equation.
Texture classification using Curvelet Statistical and Co-occurrence Features

Texture classification has long been an important research topic in image processing. Now a days classification based on wavelet transform is being very popular. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Recently, ridgelet transform which deal effectively with line singularities in 2-D is introduced. But images often contain curves rather than straight lines, so curvelet transform is designed to handle it. It allows representing edges and other singularities along lines in a more efficient way when compared with other transforms. In this paper, the issue of texture classification based on curvelet transform has been analyzed. Curvelet Statistical Features (CSFs) and Curvelet Co-occurrence Features (CCFs) are derived from the sub-bands of the curvelet decomposition and are used for classification. Experimental results show that this approach allows obtaining high degree of success rate in classification.
Delay-dependent stabilization for time-delay systems: An LMI approach ∗

This paper focuses on the problem of asymptotic stabilization for time-delay systems. To this end, a memoryless state feedback controller is proposed. Then, based on the Lyapunov method, a delay-dependent stabilization criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. Certain free weighting matrices are used to express this relationship and linear matrix inequalities (LMIs)-based algorithm to design the controller stabilizing the system.
RESEARCH ON HIGH SPEED TRAIN PANTOGRAPH/CATENARY CONTACT UNDER CONTROL WITH DIFFERENTIAL GEOMETRY THEORY

The catenary stiffness is fitted with the nonlinear least square method and a nonlinear dynamical model of catenary/pantograph system is put forward. Output perturbance uncoupled method educed from differential geometry is first used to study the high speed pantograph catenary system. It is demonstrated that the nonlinear model is transferred to a simple linear system by a proper coordinate transform and the optimal control strategy is applied , the numerical results show that this method can reduce the fluctuations of the contact force, and the controller is effective.
Health Belief Model Constructs Affect Influenza Vaccine Uptake in Kidney Transplant Recipients

This secondary analysis explored how the constructs of the health belief model affect influenza vaccine uptake in kidney transplant recipients (KTRs). In the parent study, a total of 180 KTRs were recruited at an organ transplant center in South Korea. A nonlinear path analysis using generalized structural equation modeling was performed. Previous influenza vaccination had a direct effect on their behavior, while cues to action alone did not directly affect their behavior. Perceived benefits played a key role as a mediator in improving influenza vaccine uptake in KTRs. This study highlights the need for health professionals to assess perceived benefits at the individual level and provide patient-centered interventions based on a consideration of theoretical mechanisms. As cues to action, recommendations for recipients’ first vaccination after kidney transplant should focus on changing patients’ perceptions of benefits by emphasizing the positive aspects of the influenza vaccine for immunosuppressed patients.
On structural shape optimization using an embedding domain discretization technique

This contribution presents a novel approach to structural shape optimization that relies on an embedding domain discretization technique. The evolving shape design is embedded within a uniform finite element background mesh which is then used for the solution of the physical state problem throughout the course of the optimization. We consider a boundary tracking procedure based on adaptive mesh refinement to separate between interior elements, exterior elements, and elements intersected by the physical domain boundary. A selective domain integration procedure is employed to account for the geometric mismatch between the uniform embedding domain discretization and the evolving structural component. Thereby, we avoid the need to provide a finite element mesh that conforms to the structural component for every design iteration, as it is the case for a standard Lagrangian approach to structural shape optimization. Still, we adopt an explicit shape parametrization that allows for a direct manipulation of boundary vertices for the design evolution process. In order to avoid irregular and impracticable design updates, we consider a geometric regularization technique to render feasible descent directions for the course of the optimization. Copyright © 2016 John Wiley & Sons, Ltd.
A Recent Review on Cancer Nanomedicine

Simple Summary The advancement of nanotechnology over the last three decades has given new hope to cancer management. The first FDA-approved nanomedicine (DOXIL) was made available in the market in 1995. Since then, numerous nanocarriers have been synthesized and extensively evaluated for antitumor efficacy to establish them as premier therapeutic tools. Even though nanomedicine is one of the most promising breakthroughs in the modern era of medicine, several challenges are still faced during scaling up from a laboratory setup to a clinical arrangement. In this review, we describe and compare various types of nanoparticles and their role in advancing cancer treatment. Moreover, we highlight various nanomedicines currently available for cancer therapy and nanoformulations that are through various stages of clinical testing. Abstract Cancer is one of the most prevalent diseases globally and is the second major cause of death in the United States. Despite the continuous efforts to understand tumor mechanisms and various approaches taken for treatment over decades, no significant improvements have been observed in cancer therapy. Lack of tumor specificity, dose-related toxicity, low bioavailability, and lack of stability of chemotherapeutics are major hindrances to cancer treatment. Nanomedicine has drawn the attention of many researchers due to its potential for tumor-specific delivery while minimizing unwanted side effects. The application of these nanoparticles is not limited to just therapeutic uses; some of them have shown to have extremely promising diagnostic potential. In this review, we describe and compare various types of nanoparticles and their role in advancing cancer treatment. We further highlight various nanoformulations currently approved for cancer therapy as well as under different phases of clinical trials. Finally, we discuss the prospect of nanomedicine in cancer management.
Fabrication of nanostructured electrodes for electrochemical surface-enhanced Raman spectroscopy (E-SERS): a review

ABSTRACT Electrochemical surface-enhanced Raman spectroscopy (E-SERS) is a powerful technique for the detection of trace levels of analytes in solution. It has wide ranging applications with a particular focus on biomarker detection. To perform E-SERS, nanostructured plasmonic metal electrodes are needed. Currently, a variety of fabrication methods are employed. This review defines the requirements for E-SERS electrodes and then describes and evaluates the current fabrication methods. The limitations of these techniques are discussed with the balance between ease of manufacture and magnitude of enhancement being identified as the key issue. Finally, suggestions for future areas of research are presented.
The Koszul Complex and Duality

Introduction This paper is basically about local, Cohen-Macaulay rings although many of the theorems are more general in nature. The major tool that we shall use is the Koszul complex and its self duality. The Koszul complex is closely linked with the functors Γ and λ which we shall define presently. Our main results will be the computation of the derived functors of Γ and λ.
Assessing Effects of Diet Alteration on Carbohydrate–Lipid Metabolism of Antipsychotic-Treated Schizophrenia Patients in Interventional Study

This study aimed at finding whether healthy eating habits could be introduced to and maintained by chronically mentally ill permanent residents of a nursing home. Of interest was also if the effects of the dietary intervention would be observable as improved carbohydrate and lipid metabolism indicators were selected. Assays covered 30 antipsychotics-treated residents diagnosed with schizophrenia. The prospective method applied involved questionnaires, nutrition-related interviews, anthropometric measurements, and determination of selected biochemical parameters of the blood. The dietary intervention as well as the parallel health-promoting nutrition-related education was aimed at balancing the energy and nutrient contents. Schizophrenia patients were shown to be capable of accepting and observing the principles of appropriate nutrition. The intervention was strong enough to result in a significant blood glucose concentration drop to the reference level in all patients, regardless of the antipsychotic they were treated with. The blood lipid levels also improved, but the reduction in triacylglycerols, total cholesterol and LDL-cholesterol levels was significant in the male patients only. Nutritional changes were reflected in overweight and obese women only, in body weight reduction and in waist adipose tissue loss.
Progress in Understanding Metabolic Syndrome and Knowledge of Its Compltableex Pathophysiology

The metabolic syndrome (MetS), first introduced by Haller in 1975, was sometimes also known as insulin resistance syndrome, syndrome X, and plurimetabolic syndrome. In 1989, it was rechristened by Kaplan as the “Deadly Quartet” based on a consolidation of central obesity, impaired glucose tolerance, dyslipidemia, and systemic hypertension. MetS is positively associated with a pro-inflammatory and pro-thrombotic state, attributed to increased pro-thrombotic and inflammatory marker activity. Moreover, MetS is frequently associated with increased atherosclerotic cardiovascular disease, impaired glucose tolerance, hyperuricemia, obstructive sleep apnea, and chronic kidney disease. Despite concerted endeavors worldwide, the complexity of the pathophysiology of metabolic syndrome still needs to be clearly understood. Currently, therapeutic possibilities are confined to individual therapy for hyperglycemia, hypertension, hypertriglyceridemia, hyperuricemia, regular physical exercise, and a restricted diet. In this review, progress regarding the understanding and pathophysiology of MetS; recent emerging technologies, such as metabolomics and proteomics; the relation of MetS with obesity, diabetes, and cardiovascular diseases; and the association of MetS with COVID-19 are discussed.
Intracavity beam shaping using an SLM

Intracavity laser beam shaping has been achieved by adding intensity or phase filters to a Fabry-Perot resonator. Changing the output beam from one mode to another is a tedious process, requiring the replacing of custom optical elements, and careful realignment. The digital laser [1] is an innovation which allows the laser beam produced by a laser to be dynamically controlled by a computer. Essentially, one of the resonator mirrors is replaced by a spatial light modulator (SLM), which is a computer controlled, pixellated, liquid-crystal device. While the concept is the device is simple, the implementation revealed subtle properties of spatial light modulators and the liquid crystals contained in them. These properties had to be well understood before their undesirable characteristics could be overcome, allowing the laser to function as conceived in the design.
A new fault diagnosis method for wheelset-bearing system based on VME convergence tendency diagram

Aiming at the difficulty of accurate diagnosis of wheelset-bearing system composite faults, a multi-fault feature extraction method based on self-adaptive variational mode extraction (SAVME) was proposed. Variational mode extraction (VME) can extract a specific sub-signal from a multi-component signal. The key to the success of this algorithm is to determine appropriate initial parameters in advance, including initial center frequency (ICF) and penalty factor. To determine the key parameters of VME adaptively, the convergence characteristics of VME are analyzed deeply, and the VME convergence tendency diagram is proposed creatively according to the trend of the iterative curve of the center frequency of the desired mode. By analyzing the test signal with the VME convergence tendency diagram, the number of main latent sub-signals in the test signal and the ICF of each sub-signal corresponding to the VME can be determined efficiently. Then, according to the position of the ICF of each sub-signal in the frequency domain, the empirical formula of the penalty factor is used to quickly obtain the appropriate penalty factor. The proposed SAVME method not only improves the parameter selection adaptability of the traditional VME algorithm but also extends the VME algorithm to the field of multi-fault diagnosis. By analyzing the simulated signal and two experimental signals, the effectiveness of the SAVME algorithm is verified. Compared with the fast kurtogram method and the adaptive variational mode decomposition method, the proposed method is more accurate and superior in the multi-fault feature extraction of the wheelset-bearing system.
New Process Method for End Effects of HILBERT-HUANG Transform

The HILBERT-HUANG transform consists of two steps:empirical mode decomposition (EMD) and HILBERT tr- ansform.The end effects produce both in the decomposition process of EMD and H1LBERT transforms applied to the intrinsic mode functions (IMFs). A novel wave characteristic matching extending method is proposed to overcome the end effects of EMD and HILBERT transform.Therefore,the decomposition precision is improved,the accurate instantaneous frequencies and instantaneous amplitudes could be obtained.The extending data derived from the original signal by the simple algorithm,only once extending needed in HILBERT-HUANG transform processing.The simulation and fault test analysis demonstrate the effectiveness of the method.
The Microwave Rotational Electric Resonance (RER) Spectrum of Benzothiazole

The microwave spectra of benzothiazole were measured in the frequency range 2–26.5 GHz using a pulsed molecular jet Fourier transform microwave spectrometer. Hyperfine splittings arising from the quadrupole coupling of the 14N nucleus were fully resolved and analyzed simultaneously with the rotational frequencies. In total, 194 and 92 hyperfine components of the main species and the 34S isotopologue, respectively, were measured and fitted to measurement accuracy using a semi-rigid rotor model supplemented by a Hamiltonian accounting for the 14N nuclear quadrupole coupling effect. Highly accurate rotational constants, centrifugal distortion constants, and 14N nuclear quadrupole coupling constants were deduced. A large number of method and basis set combinations were used to optimize the molecular geometry of benzothiazole, and the calculated rotational constants were compared with the experimentally determined constants in the course of a benchmarking effort. The similar value of the χcc quadrupole coupling constant when compared to other thiazole derivatives indicates only very small changes of the electronic environment at the nitrogen nucleus in these compounds. The small negative inertial defect of −0.056 uÅ2 hints that low-frequency out-of-plane vibrations are present in benzothiazole, similar to the observation for some other planar aromatic molecules.
Speech emotion analysis based on vision transformer

Emotion is an essential aspect of human life, and effectively identifying corresponding emotions from different scenarios will help promote the development of human-computer interaction systems. Therefore, emotion classification has gradually become a challenging and popular research field. Compared with text emotion analysis, emotion analysis of audio data is still relatively immature. Traditional audio sentiment analysis research is based on feature information such as MFCC, MFSC, etc. while using time-memory models such as LSTM and RNN for emotion analysis. Due to the rapid development of transformers and attention mechanisms, many scholars have shifted their research from the RNN family to the transformer family or deep learning models with attention mechanisms. Therefore, this paper proposes a method to convert audio data into a spectrogram and use a vision transformer model based on transfer learning for emotion classification. This paper conducts experiments on the IEMOCAP dataset and the MELD dataset. The experimental results show that the emotion classification accuracy of the Vision transformer in the IEMOCAP and the MELD datasets reach 56.18% and 37.1%.
Interpolation and approximation for data living on manifold surfaces

Meshed surfaces are ubiquitous in digital geometry processing and computer graphics. The set of attributes associated with each vertex such as the vertex locations, curvature, temperature, pressure or saliency, can be recognized as data living on manifold surfaces. So interpolation and approximation for these data are of general interest. This paper presents two approaches for manifold data interpolation and approximation through the properties of Laplace-Beltrami operator (Laplace operator defined on a manifold surface). The first one is to use Laplace operator minimizing the membrane energy of a scalar function defined on a manifold. The second one is to use bi-Laplace operator minimizing the thin plate energy of a scalar function defined on a manifold. These two approaches can process data living on high genus meshed surfaces. The approach based on Laplace operator is more suitable for manifold data approximation and can be applied manifold data smoothing, while the one based on bi-Laplace operator is more suitable for manifold data interpolation and can be applied image extremal envelope computation. All the application examples demonstrate that our procedures are robust and efficient.
Shot- and angle-domain wave-equation traveltime inversion of reflection data: Theory

ABSTRACTThe main difficulty with iterative waveform inversion is that it tends to get stuck in local minima associated with the waveform misfit function. To mitigate this problem and avoid the need to fit amplitudes in the data, we have developed a wave-equation method that inverts the traveltimes of reflection events, and so it is less prone to the local minima problem. Instead of a waveform misfit function, the penalty function was a crosscorrelation of the downgoing direct wave and the upgoing reflection wave at the trial image point. The time lag, which maximized the crosscorrelation amplitude, represented the reflection-traveltime residual (RTR) that was back projected along the reflection wavepath to update the velocity. Shot- and angle-domain crosscorrelation functions were introduced to estimate the RTR by semblance analysis and scanning. In theory, only the traveltime information was inverted and there was no need to precisely fit the amplitudes or assume a high-frequency approximation. Results w.