Regularization Method Research Articles

Broad‐spectrum and sensitive screening of more than 1000 compounds in equine urine using liquid chromatography/high‐resolution mass spectrometry

RationaleTo uphold the integrity of horseracing and equestrian sports, it is critical for an equine doping control laboratory to develop a comprehensive screening method to cover a wide range of target substances at the required detection levels in equine urine.MethodsThe procedure involved the enzymatic hydrolysis of 3 mL urine samples followed by solid‐phase extraction using HF Bond Elut C18 cartridge. The resulting extracts were then separated on a C18 reversed‐phase column and analyzed using liquid chromatography/high‐resolution mass spectrometry (LC/HRMS) in both electrospray ionization positive and negative modes in two separate injections. The analytical data were obtained in full scan and product ion scan (PIS) modes in an 11 min LC run.ResultsThe method can detect 1011 compounds (in both positive and negative ion modes). Over 95% of the target compounds have limits of detections (LODs) ≤10 ng/mL, and more than 50% of the LODs are ≤0.5 ng/mL. The lowest LOD can reach down to 0.01 ng/mL. The applicability of the method was demonstrated by the successful detection of prohibited substances in overseas and domestic equine urine samples.ConclusionsWe have successfully developed a regular screening method for equine urine samples that can detect more than 1000 compounds at sub‐ppb levels in both positive and negative ion modes with full scan and PIS using LC/HRMS. Furthermore, this method can theoretically be expanded to accommodate an unlimited number of prohibited substances in full‐scan mode.

Sedimentation of a Charged Soft Sphere within a Charged Spherical Cavity.

The sedimentation of a soft particle composed of an uncharged hard sphere core and a charged porous surface layer inside a concentric charged spherical cavity full of a symmetric electrolyte solution is analyzed in a quasi-steady state. By using a regular perturbation method with small fixed charge densities of the soft sphere and cavity wall, a set of linearized electrokinetic equations relevant to the fluid velocity field, electrical potential profile, and ionic electrochemical potential energy distributions are solved. A closed-form formula for the sedimentation velocity of the soft sphere is obtained as a function of the ratios of core-to-particle radii, particle-to-cavity radii, particle radius-to-Debye screening length, and particle radius-to-porous layer permeation length. The existence of the surface charge on the cavity wall increases the settling velocity of the charged soft sphere, principally because of the electroosmotic enhancement of fluid recirculation within the cavity induced by the sedimentation potential gradient. When the porous layer space charge and cavity wall surface charge have the same sign, the particle velocity is generally enhanced by the presence of the cavity. When these fixed charges have opposite signs, the particle velocity will be enhanced/reduced by the presence of the cavity if the wall surface charge density is sufficiently large/small relative to the porous layer space charge density in magnitude. The effect of the wall surface charge on the sedimentation of the soft sphere increases with decreases in the ratios of core-to-particle radii, particle-to-cavity radii, and particle radius-to-porous layer permeation length but is not a monotonic function of the ratio of particle radius-to-Debye length.

Three Regularization Methods for A Homogeneous Time Fractional Diffusion Equation with Space - Dependent Diffusivity Coefficient

We studied an inverse problem for a time fractional diffusion equation with space - dependent diffusivity coefficient in the nonhomogeneous case. This problem is ill – posed in Hadamard’s sense. So, a regularization is essential. Using three regularization methods, we get the estimation of the error between the regularized solution and the exact solution

Reduction of finite sampling noise in quantum neural networks

Quantum neural networks (QNNs) use parameterized quantum circuits with data-dependent inputs and generate outputs through the evaluation of expectation values. Calculating these expectation values necessitates repeated circuit evaluations, thus introducing fundamental finite-sampling noise even on error-free quantum computers. We reduce this noise by introducing the variance regularization, a technique for reducing the variance of the expectation value during the quantum model training. This technique requires no additional circuit evaluations if the QNN is properly constructed. Our empirical findings demonstrate the reduced variance speeds up the training and lowers the output noise as well as decreases the number of necessary evaluations of gradient circuits. This regularization method is benchmarked on the regression of multiple functions and the potential energy surface of water. We show that in our examples, it lowers the variance by an order of magnitude on average and leads to a significantly reduced noise level of the QNN. We finally demonstrate QNN training on a real quantum device and evaluate the impact of error mitigation. Here, the optimization is feasible only due to the reduced number of necessary shots in the gradient evaluation resulting from the reduced variance.

Evaluation of the Training Program in Physical Education for Students without Major of Physical Education Hung Vuong University – Phu Tho

Using regular scientific research methods to evaluate the current status of the quality of the physical education program for students at Hung Vuong University on the following aspects: Current status of factors affecting quality of students' physical education program. The results show that students' results in physical education subjects are generally at an average level. The proportion of students achieving good and excellent results is still small. The rate of students failing is still relatively high.

A semi-supervised segmentation method for microscopic hyperspectral pathological images based on multi-consistency learning.

Pathological images are considered the gold standard for clinical diagnosis and cancer grading. Automatic segmentation of pathological images is a fundamental and crucial step in constructing powerful computer-aided diagnostic systems. Medical microscopic hyperspectral pathological images can provide additional spectral information, further distinguishing different chemical components of biological tissues, offering new insights for accurate segmentation of pathological images. However, hyperspectral pathological images have higher resolution and larger area, and their annotation requires more time and clinical experience. The lack of precise annotations limits the progress of research in pathological image segmentation. In this paper, we propose a novel semi-supervised segmentation method for microscopic hyperspectral pathological images based on multi-consistency learning (MCL-Net), which combines consistency regularization methods with pseudo-labeling techniques. The MCL-Net architecture employs a shared encoder and multiple independent decoders. We introduce a Soft-Hard pseudo-label generation strategy in MCL-Net to generate pseudo-labels that are closer to real labels for pathological images. Furthermore, we propose a multi-consistency learning strategy, treating pseudo-labels generated by the Soft-Hard process as real labels, by promoting consistency between predictions of different decoders, enabling the model to learn more sample features. Extensive experiments in this paper demonstrate the effectiveness of the proposed method, providing new insights for the segmentation of microscopic hyperspectral tissue pathology images.

A regularization strategy to a backward problem for general nonlinear parabolic equations in Sobolev spaces

This article is devoted to solving a backward problem for general nonlinear parabolic equations in Sobolev spaces. The problem is hardly solved by computation since it is severely ill‐posed in Hadamard's sense. Using the Fourier transform and the truncation of high‐frequency components, we construct a regularized solution for the problem from the data given inexactly. As usual for ill‐posed problems, the rate of convergence can be obtained under additional smoothness assumptions on the regularity of the exact solution, the so‐called source conditions. By using a source condition in a generalized form, we prove a convergence estimate in a Sobolev space . Corresponding to different levels of the source condition, the convergence rates are improved gradually. We apply our theory to the backward problem with a convection–diffusion operator and a cubic nonlinearity. Finally, the numerical results are presented to test the validity of the proposed regularization method.

Temperature-Dependent Viscosity Analysis of Powell-Eyring Fluid Model during a Roll-over Web Coating Process.

The roll coating method is of considerable significance in several industries, as it is applied practically in the production of paint, the manufacturing of PVC-coated cloth, and the plastic industry. The current study theoretically and computationally analyses the Powell-Eyring fluids with variable viscosity during the non-isothermal roll-over web phenomenon. Based on the lubrication approximation theory (LAT), the problem was formulated. The system of partial differential equations (PDEs) obtained from the mathematical modeling was further simplified to a set of ordinary differential equations (ODEs) using suitable transformations. A regular perturbation method was implemented to obtain the solution in terms of velocity, pressure gradient, pressure, and flow rate per unit width. This study also captures important engineering characteristics such as coating thickness, Nusselt number, shear stress, roll/sheet separating force, and roll-transmitted power to the fluid. Along with a comparison between the present work and published work, both graphical and tabular representations wer made to study the effects of various factors. It was observed that the velocity profile is the decreasing function of non-Newtonian and Reynold viscosity parameters. In addition, the response surface methodology (RSM) was employed to investigate the sensitivity of the shear stress and the Nusselt number.

대학 입학전형 선택의 영향 요인 분석

Objectives The purpose of this study is to analyze the factors that affect the choice of admission types among college students, including personal background, self-efficacy, autonomy, learning motivation, and major selection motivation. Methods To achieve this goal, a survey was conducted on 1,099 students enrolled at A University in Seoul. Factors influencing admission type preferences were analyzed using chi-square tests, one-way ANOVA, and multinomial logistic regression. Results Differences in admission type preferences emerged based on students' backgrounds, including the region and type of their high school, and the highest educational attainment of their guardians. Among personal characteristics, significant disparities in admission-type preferences were observed based on self-efficacy and major selection motivation. In relation to the origin of the high school, as the region shifted to Seoul and the metropolitan area, and as the educational attainment of male guardians increased, along with stronger intrinsic motives for major selection, the likelihood of opting for the regular comprehensive evaluation process increased. Conversely, in cases where the originating high school was located in urban or smaller cities, and when female guardians possessed higher educational qualifications, along with stronger extrinsic motives for major selection, there was an elevated probability of preferring the regular admission method. Conclusions Given the variations in the backgrounds and attributes of students selecting university admission types, universities should take a keen interest not only in the selection process but also in academic and career support.

Design, modeling and optimization of an adhesively bonded ring joint with U-section for ceramic cylindrical pressure hull of deep-sea underwater vehicles

The brittleness of ceramic increases the risk of damage or collapse when the ceramic cylindrical pressure hull is directly connected with a rigid part, especially under high hydrostatic pressure. To solve the above problem, this paper systematically explores the design, modeling and optimization of an adhesively bonded ring joint with U-section (ABRJ-U) to avoid the direct connection of the ceramic hull of a small hadal glider, Petrel, with the hemispherical metal end caps. The ABRJ-U is comprised of a U-shaped metal ring, a gasket, and epoxy adhesive layer. To optimize the design parameters, a mechanical model of ABRJ-U is established. The stress tests prove that the model has better efficiency in optimization, but lowered accuracy compared with regular finite element method. Considering the difficulty of obtaining a more accurate theoretical model, the optimization efficiency of regular finite element method is selected for further improvement by integrating the response surface methodology and multi-objective genetic algorithm. According to the optimization results, our optimization method considers the stress calibration of both the adhesive and gasket, simultaneously achieving a 20.8% reduction in the mass of ABRJ-U. The proposed methods also provide valuable reference for the design, modeling, and optimization of other bonded joints.

The Piston Slap Force Reconstruction of Diesel Engine Using WOA-VMD and Deconvolution.

In a diesel engine, piston slap commonly occurs concurrently with fuel combustion and serves as the main source of excitation. Although combustion pressure can be measured using sensors, determining the slap force is difficult without conducting tests. In this study, we propose a method to identify the slap force of the piston to solve this difficult problem. The traditional VMD algorithm easily receives noise interference, which affects the value of parameter combination [k, α] and thus affects the extraction accuracy of the algorithm. First, we obtain the transfer function between the incentive and vibration response through percussion tests. Secondly, a variational modal decomposition method based on whale algorithm optimization is used to separate the slap response from the surface acceleration of the block. Finally, we calculated the slap force using the deconvolution method. Deconvolution is a typical inverse problem of mathematics, often prone to ill-conditioning, and the singular value decomposition and regularization method is used to overcome this flaw and improve accuracy. The proposed method provides an important means to evaluate the angular distribution of the slap force, identify the shock positions on the piston liner, and determine the peak value of the waveform which helps us analyze the vibration characteristics of the piston and optimize the structural design of the engine.

A Thermodynamically Consistent Anisotropic Continuum Damage Mechanics Model With Damage-Dependent Equivalent Strain

Abstract This paper proposes a new thermodynamically consistent anisotropic continuum damage mechanics model that the degradation of material is described by a set of damage variables. We adopt a set of novel equivalent strains which are functions of both the strain and the damage state variables as well. A viscous stabilization method is considered to improve the convergence during the material softening. The evolution of damage state variables is updated through a Newton–Raphson iterative process. The expression of the consistent tangent stiffness matrix is also derived. A smoothed exponential damage evolution shape function with rescaling regularization method is proposed to describe the material softening process and the mesh dependency phenomenon is relieved. Several sets of numerical examples including three-point-bending of a notched beam, uniaxial tension of unnotched and notched plate of composite material with multiple layups are presented to verify the anisotropic damage models.

URCA: Uncertainty-based region clipping algorithm for semi-supervised medical image segmentation

Background and objectiveTraining convolutional neural networks based on large amount of labeled data has made great progress in the field of image segmentation. However, in medical image segmentation tasks, annotating the data is expensive and time-consuming because pixel-level annotation requires experts in the relevant field. Currently, the combination of consistent regularization and pseudo labeling-based semi-supervised methods has shown good performance in image segmentation. However, in the training process, a portion of low-confidence pseudo labels are generated by the model. And the semi-supervised segmentation method still has the problem of distribution bias between labeled and unlabeled data. The objective of this study is to address the challenges of semi-supervised learning and improve the segmentation accuracy of semi-supervised models on medical images. MethodsTo address these issues, we propose an Uncertainty-based Region Clipping Algorithm for semi-supervised medical image segmentation, which consists of two main modules. A module is introduced to compute the uncertainty of two sub-networks predictions with diversity using Monte Carlo Dropout, allowing the model to gradually learn from more reliable targets. To retain model diversity, we use different loss functions for different branches and use Non-Maximum Suppression in one of the branches. The other module is proposed to generate new samples by masking the low-confidence pixels in the original image based on uncertainty information. New samples are fed into the model to facilitate the model to generate pseudo labels with high confidence and enlarge the training data distribution. ResultsComprehensive experiments on the combination of two benchmarks ACDC and BraTS2019 show that our proposed model outperforms state-of-the-art methods in terms of Dice, HD95 and ASD. The results reach an average Dice score of 87.86 % and a HD95 score of 4.214 mm on ACDC dataset. For the brain tumor segmentation, the results reach an average Dice score of 84.79 % and a HD score of 10.13 mm. ConclusionsOur proposed method improves the accuracy of semi-supervised medical image segmentation. Extensive experiments on two public medical image datasets including 2D and 3D modalities demonstrate the superiority of our model. The code is available at: https://github.com/QuintinDong/URCA.

A New Regularization Method for a Class of Ill-Posed Cauchy Problems

A New Regularization Method for a Class of Ill-Posed Cauchy Problems

An accelerated inexact Newton-type regularizing algorithm for ill-posed operator equations

We propose and analyze a new iterative regularization approach, called IN-SETPG, for efficiently solving nonlinear ill-posed operator equations in the Hilbert-space setting. IN-SETPG consists of an outer iteration and an inner iteration. The outer iteration is terminated by the discrepancy principle and consists of an inexact Newton regularization method, while the inner iteration is performed by a sequential subspace optimization method based on the two-point gradient iteration. The key idea behind IN-SETPG is that, unlike the standard Landweber method, it uses multiple search directions per iteration in combination with an adaptive step size in order to reduce the total number of iterations. The regularization property of IN-SETPG has been established, i.e., the iterate converges to a solution of the nonlinear problem with exact data when the noise level tends to zero. Various numerical experiments are presented to demonstrate that, compared with the original inexact Newton iteration, IN-SETPG can achieve better reconstruction results and remarkable acceleration.

Blind channel evaluation using OFDM-FHSS technology

Pseudo-random tuning of the operating frequency (PRFC) is one of the effective methods of spectrum expansion, in which the signal occupies a frequency band significantly wider than the minimum required for transmitting information. Тhe operating frequency of the signal is hopped over a wide range of the frequency range allocated for communication in accordance with a pseudo-random code, known only on the receiving side and unknown to anyone trying to intercept a radio transmission or organize jamming. The main disadvantage of HFPR is the low data transfer rate. Therefore, recently there have been ideas of using the hopping method with broadband signals, for example OFDM-hopping where the frequency changes within a set of orthogonal carriers. This approach makes it possible to preserve the advantages of the frequency converter method, supplementing them with the ability to implement high-speed digital communications. The paper considers the situation when one OFDM symbol is transmitted in the time interval of one hop, formed without a prefix and postfix. In this case, the transmission signal in the time interval of one step was a set of sequentially transmitted complex samples of the OFDM symbol envelope. Samples of the OFDM symbol envelope, after they are generated during transmission in the OBPF block, must be sequentially transmitted over a communication channel whose properties are unknown. In the case when there is temporary dissipation of the energy of the transmitted signal in the channel (channel memory), during the sequential transmission of complex samples of the OFDM symbol envelope, due to temporary dissipation, each of the previous samples will have an interference effect on any transmitted sample at reception. Assuming that the channel parameters are constant over the analysis interval at the receiving location, it is necessary, with an unknown impulse response of the channel, to generate estimates of the OFDM symbol envelope samples, which, in order to solve the demodulation problem, must be subjected to the FFT calculation operation. The constancy of the channel parameters over the analysis interval allows us to solve the problem of estimating samples of the channel impulse response using blind identification based on the maximum likelihood method. In this case, it is necessary to use diversity reception and impose some non-burdensome restrictions on the statistical properties of the transmitted message. After solving the problem of identifying the impulse response of a channel with memory, the problem of estimating the components of the sample vector of the envelope of the received OFDM symbol is solved by the regularization method. Using the “reception “as a whole” with element-by-element assessment generation” (PCPFO) algorithm and using “assessment feedback” (EFE), minimization of the regularizing functional leads to the solution of a system of linear algebraic equations, the order of which is determined by the number of samples of the impulse response of the communication channel with memory. By modeling, the upper limit of noise immunity for receiving OFDM-QAM-4 signals was obtained with a Gaussian distribution of errors in estimating OFDM-symbol envelope samples. The proposed procedure for normalizing envelope samples after solving systems of linear equations eliminates the appearance of outliers characteristic of the generated noise sequence.

Influence of heat flow due to concentration gradient on unsteady MHD heat and mass transform dissipative flow with spanwise fluctuating temperature

This study investigates the influence of heat flow due to a concentration gradient on unsteady Newtonian free convective magnetohydrodynamic heat and mass transform dissipative fluid flow over a heated normal porous plate in the presence of radiation absorption and chemical reaction. The plate temperature is assumed to fluctuate in a spanwise cosinusoidal manner over a time and exhibit heat generation with suction velocity. The analysis employs the multiple regular perturbation method to evaluate the governing equations under stipulated boundary conditions. The outcomes are visually depicted to assess the impact of various parameters on the system dynamics. Graphical representations illustrate the physical significance of various parameters on velocity, temperature, and concentration. Additionally, skin friction, mass transfer rate, and heat transfer coefficients are presented in tabular form. The significant findings indicate that velocity, temperature, and skin friction are directly proportional to parameters such as radiation absorption, heat generation, and heat flux due to a chemical potential gradient, whereas Sherwood and concentration are inversely proportional to the Schmidt number and chemical reaction. The outcomes obtained in this study have been cross-referenced with existing scientific literature, demonstrating strong concordance. This alignment provides confidence in the numerical results.

Study of OSPE as a Method of Assessment in the Anatomy: Implementation and Attitude among MBBS students

Introduction: Competency-based medical education (CBME) emphasizes outcome-based learning evaluation and assessment. Objective Structured Practical Examination (OSPE) is a valid, reliable, and objective tool suggested in the anatomy curriculum. OSPE modules were developed and implemented in anatomy for first-year MBBS Students, and the perception of first-year MBBS students about OSPE was studied. Methods: This study was conducted on 50 MBBS students of the 2021 admission year in the Department of Anatomy after approval from the Institutional Ethics Committee. Feedback survey questionnaires were prepared and validated by the subject experts and MEU members to study students' perceptions of OSPE. Students' perceptions were noted on a 5-point Likert scale. Data was entered through Google Forms and analyzed. Results: 93.2% of students believed that OSPE made learning competencies easier for them. Only 13.7% of students felt that time devoted to OSPE assessment was inadequate. 79.6% of students were of the opinion that It made them confident in all aspects of addressed competencies. 88.6% of students felt that OSPE improved their ability to demonstrate knowledge and skills of addressed competencies. 88.6% of students were of the view that OSPE is a satisfactory method of assessing their capabilities as a student. 83.7% of students ' opinion was that it would help them in learning the competencies of Anatomy. In the opinion of 93.2% of students, OSPE should be a regular method of assessment. 81.8% of students agreed that OSPE was a feasible exercise. Conclusions: The study concluded that implementing OSPE as a method of assessment in Anatomy for first-year MBBS Students is feasible and acceptable. 93 percent of students believe this method makes learning competencies easier for them. KEYWORDS: OSPE, Assessment, Anatomy, Perception, Competency, Curriculum.

Diffusiophoresis of a Charged Soft Sphere in a Charged Spherical Cavity

The quasi-steady diffusiophoresis of a soft particle composed of an uncharged hard sphere core and a uniformly charged porous surface layer in a concentric charged spherical cavity full of a symmetric electrolyte solution with a concentration gradient is analyzed. By using a regular perturbation method with small fixed charge densities of the soft particle and cavity wall, the linearized electrokinetic equations relevant to the fluid velocity field, electric potential profile, and ionic concentration distributions are solved. A closed-form formula for the diffusiophoretic (electrophoretic and chemiphoretic) velocity of the soft particle is obtained as a function of the ratios of the core-to-particle radii, particle-to-cavity radii, particle radius to the Debye screening length, and particle radius to the permeation length in the porous layer. In typical cases, the confining charged cavity wall significantly influences the diffusiophoresis of the soft particle. The fluid flow caused by the diffusioosmosis (electroosmosis and chemiosmosis) along the cavity wall can considerably change the diffusiophoretic velocity of the particle and even reverse its direction. In general, the diffusiophoretic velocity decreases with increasing core-to-particle radius ratios, particle-to-cavity radius ratios, and the ratio of the particle radius to the permeation length in the porous layer, but increases with increasing ratios of the particle radius to the Debye length.

The Effect of the Team Members Teaching Design vs. Regular Lectures method on the Self-efficacy of the Multiple sclerosis Patients in Iran. Randomised Controlled Trial.

This study was conducted with the aim of the effect of team members teaching design (TMTD) vs. regular Lectures method on the self-efficacy of the multiple sclerosis patients. This research is a randomized controlled trial study. In this study, 48 multiple sclerosis persons of members of Jahrom MS Society participated. The persons were selected by simple random sampling and then divided into three groups of: TMTD (n=16), regular lecture method (n=16), and control (n=16), by random allocation method. In the intervention groups, six training sessions were held twice a week; control group did not receive education. Data was collected by the MS self-efficacy questionnaire of Rigby et al. in the before, immediately and one month after the intervention. Patients in three intervention and control groups were similar in terms of demographic variables. The results of the repeated measurement test before, immediately and one month after the intervention showed that the mean of the all dimensions of self-efficacy in two intervention groups had increased significantly (p<0.05). While these changes were not significant in the control group (p ≥ 0.05). Also, there was a significant difference in the mean of the all dimensions of self-efficacy between the intervention groups of TMTD and regular lectures. Based on the findings, TMTD compared to regular lectures method had a more significant effect on improving the self-efficacy of multiple sclerosis patients. Therefore, it is recommended that nursing use this educational approach to increase patients' self-efficacy.