Miracle-dz/UniFAR-FTUs huggingface dataset:
A review of reconstruction techniques for capacitance tomography

Capacitance tomography has been used to image several processes, such as liquid/gas pipe flow, oil/water/gas gravity separation, pneumatic conveying, fluidized beds and flame combustion. The nature of the capacitance sensors is such that reconstruction algorithms well developed for medical tomography are not applicable. The main problem is that the relationship between the measured quantity (capacitance) and the parameter of interest (distribution of the dielectric constant) is nonlinear. Furthermore, it is impossible to establish an explicit expression which relates the dielectric constant distribution to the measured capacitance. Also it should be pointed out that the number of measurements in capacitance tomography is small (typically less than 100) compared to medical tomography. For these reasons the first tested algorithm in capacitance tomography was based on the crude back projection algorithm. This algorithm has over the years been enhanced for use with a capacitance tomograph. In addition other techniques, such as various iterative methods, algorithms based on artificial neural networks and `look-up' tables have been developed and tested. This paper outlines the working principles for the different techniques and presents the main results.
PRACTICAL SOLUTIONS FOR NONLINEAR ACCELERATOR LATTICE WITH STABLE NEARLY REGULAR MOTION

The use of nonlinear lattices with the large betaron tune spreads can increase instablity and space charge thresholds by orders of magnitude compared to typical linear accelarator lattices. Unfortunately, strong nonlinear fields create, in general, strong resonances and chaotic motion. This shrinks the dynamic aperture to impractical values, thus erasing all benefits from their use. Previously known examples of stable and regular accelerator motion with special nonlinear lenses were related to one dimensional motion or round beams. However, no solution has been realized with real 2D tranverse magnetic fields to produce stable, close to regular 2D motion with the large dynamic aperture and betatron tune spread comparable to the betatron tune itself. This paper presents possible solutions for such 2D lattices. They consist of straight sections with short linear and nonlinear lenses with transverse magnetic fields.
Convenient and highly efficient microwave-assisted synthesis of 2-Arylimidazo[1,2-a]pyrimidine-3-carbaldehydes in glycerol

Abstract A simple and highly efficient method adopted for the synthesis of 2-Arylimidazo[1,2-a]pyrimidine-3-carbaldehyde from reaction of 2-phenylimidazo[1,2-a]pyrimidines, with (Vilsmeier–Haack reagent) in the presence of glycerol as a green reaction medium under microwave irradiation at 400 watt, at 90 °C. Mild reaction conditions, high yield, short reaction time, a clean reaction profile, avoiding toxic catalysts, hazardous organic solvents, and less waste materials are the advantages over the previously adopted method. Graphical Abstract
Measurement of tokamak error fields using plasma response and its applicability to ITER

The nonlinear response of a low-beta tokamak plasma to non-axisymmetric fields offers an alternative to direct measurement of the non-axisymmetric part of the vacuum magnetic fields, often termed ‘error fields’. Possible approaches are discussed for determination of error fields and the required current in non-axisymmetric correction coils, with an emphasis on two relatively new methods: measurement of the torque balance on a saturated magnetic island, and measurement of the braking of plasma rotation in the absence of an island. The former is well suited to ohmically heated discharges, while the latter is more appropriate for discharges with a modest amount of neutral beam heating to drive rotation. Both can potentially provide continuous measurements during a discharge, subject to the limitation of a minimum averaging time. The applicability of these methods to ITER is discussed, and an estimate is made of their uncertainties in light of the specifications of ITER's diagnostic systems. The use of plasma response-based techniques in normal ITER operational scenarios may allow identification of the error field contributions by individual central solenoid coils, but identification of the individual contributions by the outer poloidal field coils or other sources is less likely to be feasible.
The impact of investor sentiment on sectoral returns and volatility: Evidence from the Johannesburg stock exchange

Abstract This study investigated the impact of investor sentiment impact on sectoral returns and their volatility on the Johannesburg Stock Exchange using a proxy-based composite investor sentiment index and generalised autoregressive conditional heteroscedasticity models. Overall, findings showed a negative relationship between prevailing sentiment and subsequent returns and a positive relationship between investor sentiment and sector returns volatilities. Additionally, there was evidence of variability of sentiment effects on the sector returns and volatilities. Accordingly, firms that raise financing through the stock market, portfolio managers with investments thereon and policymakers seeking to ensure that markets operate efficiently need to consider the impact of market-wide investor sentiment on volatility and returns.
ACOUSTIC AXISYMMETRIC RADIATION AND SCATTERING FROM BODIES OF REVOLUTION USING THE INTERNAL SOURCE DENSITY AND FOURIER METHODS

A brief review is presented of a previously developed mean-square error method to solve the Neumann boundary-value problem corresponding to acoustic axisymmetric harmonic radiation and rigid body scattering from bodies of revolution of arbitrary shape. The method is based on the use of an internal line monopole source distribution along the axis. In contrast to earlier work, the pressures are simply expressed as line integrals of the source distributions which in the far field reduce to Fourier transform relationships. Exact expressions for the source strength distributions for a sphere are developed using the Fourier transform relationships. The source strength distributions involve spatial derivatives of Dirac delta functions and thus have a vanishingly small region of support about the center of the sphere. For cylindrically shaped bodies with large aspect ratios the spatial characteristics of the source strength distributions are shown to be more closely matched to the normal velocity distribution. Th.
Stripe stabilization in vertical Bloch line memory

Partially grooved, long, rectangular grooves on the garnet surface were used to stabilize minor loop stripes in a vertical Bloch line memory. These stripes reside beneath the stripe confinement groove. The test chip contained 10 or 20 minor loop grooves, 10 read/write (r/w) gate grooves, and a major line groove. The film thickness was 4.76 μm, and the groove was 0.5 μm deep. Each minor loop groove was 500 μm long, four widths were tried: 3.5, 4, 4.5, and 5 μm. Two groove periods were tried: 10 and 20 μm. For stripe initialization, a bubble was nucleated in every minor loop groove by a single current pulse at a 90 Oe bias field. As the bias field was decreased slowly, bubbles began to stripe out at 80 Oe. At 75 Oe, all 10 stripes were stretched to the full groove length. These stripes were stable at bias fields between 70 and 80 Oe. Stripes decreased in length at higher fields, and escaped from the confinement groove at low fields. When stripes escaped from the groove, it always occured from the end not fa.
Shell-model study of the lattice dynamics of hydroxyapatite

A shell model has been developed and used in a study of the lattice dynamics of hydroxyapatite. The results give insight into the modes of vibration of the lattice, but in addition, the dynamics has been used to obtain quantities involved in x-ray and neutron diffraction patterns and in infrared spectra to help in the interpretation of experimerimental data. Phonons throughout the Brillouin zone were obtained and used to calculate atomic thermal factors entering the x-ray and neutron scattering intensity. The calculated values were in very good agreement with experiment. The phonon modes were also obtained for the $\ensuremath{\Gamma}$-point taking into account the long range Coulomb correction to the dynamical matrix. They were used to calculate the infrared reflectivity for single crystals of hydroxyapatite through the dielectric function and using the dipole approximation, and the powder spectrum was also obtained using the dipole method. Although the positions of peaks in the measured intensities were in good agreement with the frequencies of features in the calculated phonon density of states, the calculated intensities were in poorer agreement with experiment.
Exponential data fitting using multilinear algebra: the decimative case

This paper presents a high‐precision method for the estimation of the parameters of a signal, modelled as a finite sum of complex damped exponentials, whose poles may be close. It is well known that increasing the sampling rate increases the accuracy of traditional methods, like total least squares (TLSs)‐ESPRIT and HTLS, in the case of closely spaced exponentials. However, in the case of long sequences, the computational complexity makes these methods hard to apply. To overcome this problem, the HTLSDstack and the HTLSDsum methods make use of decimated sequences. In this paper, we propose a higher order counterpart of HTLSDstack, based on concepts from multilinear algebra. Basically, it consists of decimating an oversampled signal by a factor D, making sure that no aliasing occurs. Each sequence is arranged in a Hankel matrix and the D Hankel matrices are stacked in a third‐order tensor. A dimensionality reduction algorithm is applied to the tensor and the resulting subspace is used to retrieve the parameters of interest. The dimensionality reduction is possibly unsymmetric in the different modes of the tensor, which allows us to take into account ill conditioning when poles are close. The new method yields better results than HTLSDstack while its complexity stays fairly low compared to non‐decimative methods. Copyright © 2009 John Wiley & Sons, Ltd.
A New Data-Driven Diagnosis Method for Mixed Eccentricity in External Rotor Permanent Magnet Motors

In this article, a new data-driven diagnosis method is proposed for mixed eccentricity (ME) in the external rotor permanent magnet motors (ERPMMs). Differently from the previous articles, the proposed method has the advantages of large sample size, high sample diversity, high efficiency, and strong generalization ability. First, the improved parametric analytical model (AM) of back electromotive force (EMF) of the ERPMMs is established. Then, the characteristics of the back EMF are analyzed. Accordingly, its amplitudes of fundamental waves and sideband harmonics are selected as the ME indexes. Afterwards, by using the proposed parametric AM, a database of ME signals is established efficiently, which contains tens of thousands of labeled samples. Furthermore, based on the back propagation neural network, a high-precision diagnosis model for ME in the ERPMM is established. Interference faults, such as unbalanced stator windings and uneven magnetization are also discussed. Finally, an experimental prototype for simulating the ME is manufactured and the effectiveness of the proposed method is verified. The maximum absolute diagnostic error is less than 4.0%. It provides a new idea for multiparameter diagnosis for ME.
Gigasanalis, a new genus of the tribe Achilini with the description of a new species from China (Hemiptera, Fulgoromorpha, Achilidae)

A new planthopper genus, Gigasanalis Long & Chen gen. nov. (Hemiptera, Fulgoromorpha, Achilidae, Achilinae, Achilini) is established from South China (Hainan Province). A new species, Gigasanalis jianfenglingensis Long & Chen sp. nov., is described and illustrated.
Optimal guaranteed cost control and filtering for uncertain linear systems

The paper presents results on the design of robust state feedback controllers and steady-state robust state estimators for a class of uncertain linear systems with norm bounded uncertainty. The state feedback results extend the linear quadratic regulator to the case in which the underlying system is dependent on uncertain parameters. The state estimation results extend the steady-state Kalman filter to the case in which the underlying system is also uncertain. >
Effect of antiferromagnetic order on a propagating single-cycle THz pulse

Employing polarization sensitive terahertz (THz) transmission spectroscopy, we explored how the waveform of initially single-cycle linearly polarized THz pulses changes upon propagation through a thick antiferromagnetic crystal of CoF2. The changes upon propagation through CoF2 are found to depend strongly on both the incoming polarization and temperature. In particular, the ellipticity and polarization rotation acquired by initially linearly polarized light are quantified and explained in terms of magnetic linear birefringence and dichroism. Although the magneto-optical effects are often considered to be relatively weak, our experiments reveal that the polarization of the THz pulse substantially changes along the pulse duration. The pulse shape is further complicated by features assigned to the formation of magnon-polaritons. The findings clearly show the importance of accounting for propagation effects in antiferromagnetic spintronics and magnonics.
Interactive Left-Turning of Autonomous Vehicles at Uncontrolled Intersections

This paper presents a novel interactive motion planning approach for left-turning of autonomous vehicles at uncontrolled intersections. A typical left-turning scenario that consists of agent vehicles and an autonomous ego vehicle is established. The autonomous ego vehicle aims to cross the uncontrolled intersection quickly and safely when meeting with the agent vehicles. A modified obstacle reciprocal collision avoidance (MORCA) prediction model is proposed to predict the trajectory of the agent vehicles with the considerations of longitudinal and lateral interaction-aware behaviors. The parameters of the MORCA prediction model are optimized using particle swarm optimization (PSO) with the inD datasets. Based on MORCA, a partially observable Markov decision process (POMDP) framework is established. The action and state spaces of the POMDP are extended reasonably to satisfy the requirement of real-time application. The simulation results show that the prediction precision is improved by 15% using the MORCA compared with the obstacle reciprocal collision avoidance (ORCA) prediction model. Meanwhile, the results manifest that the proposed MORCA-based POMDP planning method improves 43.8% in commuting efficiency compared with a traditional rule-based method, nearly as good as the vehicle-to-vehicle (V2V) communication is equipped. Note to Practitioners—The motivation of this article is to establish a safe and efficient planning framework for the left-turning of autonomous vehicles at uncontrolled intersections. Rule-based approaches were widely used in the previous studies but they are not optimal. In this paper, the lateral movements of vehicles at the intersection are considered for the first time. A MORCA prediction model is established and optimized to formulate a POMDP planning framework. The CARLA simulation demonstrates the effectiveness of the proposed MORCA-based POMDP planner. In future work, we will migrate the algorithm to a real-world test platform for experimentation.
Collective Molecular Motion during V-Shaped Switching in a Smectic Liquid Crystal

The molecular motion during V-shaped switching in a homogeneously aligned smectic C*-like liquid crystal (LC) cell has been investigated by measuring the effective optical anisotropy Δneff, apparent tilt angle θapp, switching current, and second-harmonic generation and comparing them with the simulated results based on two extreme models, i.e., random model and collective model, where molecules switch randomly and collectively, respectively. The comparison revealed that the collective switching motion of LC molecules is more reasonable than the random motion. Moreover, it was also confirmed that the observed infrared absorption anisotropy of the phenyl stretching mode due to LC molecular distributions strongly supports the collective model. From these results, it was demonstrated that LC molecules do not switch randomly but all the LC molecules rotate collectively on a cone under the driving field.
Prediction of the Contribution Ratio of a Target Metabolic Enzyme to Clearance from Chemical Structure Information

The contribution ratio of metabolic enzymes such as cytochrome P450 to in vivo clearance (fraction metabolized: fm) is a pharmacokinetic index that is particularly important for the quantitative evaluation of drug–drug interactions. Since obtaining experimental in vivo fm values is challenging, those derived from in vitro experiments have often been used alternatively. This study aimed to explore the possibility of constructing machine learning models for predicting in vivo fm using chemical structure information alone. We collected in vivo fm values and chemical structures of 319 compounds from a public database with careful manual curation and constructed predictive models using several machine learning methods. The results showed that in vivo fm values can be obtained from structural information alone with a performance comparable to that based on in vitro experimental values and that the prediction accuracy for the compounds involved in CYP induction or inhibition is significantly higher than that by using in vitro values. Our new approach to predicting in vivo fm values in the early stages of drug discovery should help improve the efficiency of the drug optimization process.
Edge‐based finite element method for shallow water equations

This paper describes an edge‐based implementation of the generalized residual minimum (GMRES) solver for the fully coupled solution of non‐linear systems arising from finite element discretization of shallow water equations (SWEs). The gain in terms of memory, floating point operations and indirect addressing is quantified for semi‐discrete and space–time analyses. Stabilized formulations, including Petrov–Galerkin models and discontinuity‐capturing operators, are also discussed for both types of discretization. Results illustrating the quality of the stabilized solutions and the advantages of using the edge‐based approach are presented at the end of the paper. Copyright © 2001 John Wiley & Sons, Ltd.
Curriculum-embedded experimentation

We contrast two types of experiments: pull-out experiments, in which students are pulled out of their normal educational environment and curriculum-embedded experiments, in which student experience experimental conditions as a normal consequence of proceeding through a curriculum. We argue that, for practical reasons, curriculum-embedded experiments are preferred for large-scale experimentation in schools, and such experiments may also avoid issues with ecological validity. The choice to use a curriculum-embedded approach affects methods used for randomization, subject screening and the way that student experience after the experiment concludes is affected by the experiment, even for students who did not themselves participate.
Computation of the padé table

Simple recursion formulas are presented for computing the coefficients in the Pade table of a power series f(x). A Fortran subroutine for the computation is given in an Appendix, where a second subroutine for evaluating the elements for any x is also given. Two applications are mentioned. The assumption is made that the Pade table is normal.
Observational study of health utilities in adult primary ciliary dyskinesia patients: preliminary data on associations with molecular diagnosis, clinical phenotype and HRQOL measures

Background Primary ciliary dyskinesia (PCD) is a congenital disorder characterized by chronic respiratory morbidity. To date, there is no information on PCD-specific preference-based quality of life measures such as health utilities (HU). We cross-sectionally assessed HU in adult PCD patients and explored relationships with genotype, phenotype and quality of life (QOL)-PCD scales. Methods Diagnostic testing was performed according to international guidelines, while participants completed the visual analog scale (VAS), time trade off (TTO), standard gamble (SG), and EuroQol 5 dimensions (EQ5D) HU instruments, as well as the QOL-PCD questionnaire. Hierarchical regression was used to identify the QOL-PCD scales that are most predictive of HU. Results Among 31 patients, median HU are 0.75 (VAS), 0.86 (EQ5D), 0.91 (TTO) and 0.99 (SG). The underlying genotype is not associated with HU measures. VAS and EQ5D are associated with lung function, while TTO and SG values are not sensitive to any of the examined factors. Among the QOL-PCD scales, physical functioning and lower respiratory symptoms explained much of VAS (R2= 0.419) and EQ5D (R2= 0.538) variability. Conclusions Our study demonstrates that HU elicitation in PCD is feasible using both direct and indirect methods. Overall, HU scores are relatively high among adult patients, with higher scores observed in SG and TTO, followed by EQ5D and VAS. VAS and EQ5D HU values are sensitive to lung function as well as to QOL-PCD physical functioning and lower respiratory symptom scores.
Effect of Dietary Urea in Gestating Beef Cows: Circulating Metabolites, Morphometrics, and Mammary Secretions

Simple Summary Feed costs represent 70 to 90% of total costs in beef cattle systems, with protein being the most expensive component. One of the most cost-effective means to supply protein precursor to ruminants is through dietary urea supplementation. Therefore, we set out to evaluate the influence of urea supplementation during gestation on circulating concentrations of maternal metabolites, body measures, and mammary secretion composition. In this work, we have demonstrated that the pregnant beef cow undergoes metabolic adaptation to maintain pregnancy. However, urea supplementation failed to improve any of the body or mammary parameters assessed. Therefore, it is imperative that novel supplementation strategies be developed for beef cows that maintain the body mass of the dam and improve mammary secretion quantity and quality to ultimately improve the health and productivity of both the cow and calf. Abstract Prolific use of supplementation strategies, including the utilization of urea, are practiced in beef cattle production systems. Unfortunately, the influence of urea supplementation on metabolics, adipose tissue mobilization, and mammary secretions is limited in beef cows. Therefore, the objectives of this experiment were to assess the influence of urea supplementation on metabolic profiles, morphometrics, and mammary secretions. Pregnant, multiparous beef cows were fed individually and assigned to treatment (n = 4/treatment) as Control or Urea Supplementation. Blood samples and body weight were collected every 28 d throughout gestation. Backfat thickness was measured via ultrasonography on days 28 and 280 of gestation. Total mammary secretions were sampled for composition. Concentrations of beta-hydroxybutyrate, non-esterified fatty acids, glucose, and plasma urea nitrogen did not differ by treatment. Body weight and backfat thickness changed in response to the progression of gestation, but did not differ between treatments. Finally, concentration of urea nitrogen increased in mammary secretions of cows fed urea, but total content of urea nitrogen in mammary secretions did not differ between treatments. In conclusion, we have demonstrated that the pregnant beef cow undergoes metabolic adaptation during gestation. However, urea supplementation failed to improve any of the morphometric parameters of the dams assessed.