Rapid determination of phenolic composition in chamomile (Matricaria recutita L.) using surface-enhanced Raman spectroscopy.

Flavonoids and hydroxycinnamic acids are the main responsible of the antioxidant activity of chamomile (Matricaria recutita L.). Traditional methods for the analysis of the phenolic content in vegetables often suffer from limitations such as being expensive, time-consuming, and complex. In this study, we propose, for the first time, the use of surface-enhanced Raman spectroscopy (SERS) for the rapid determination of the main components of the polyphenolic fraction in chamomile. Results demonstrate that SERS can serve as an alternative or complementary technique to main analytical strategies for qualitative and quantitative determination of polyphenol compounds in plant extracts. The method can be proposed for quasi real-time analysis of herbal teas and infusions, facilitating rapid screening of their main antioxidant components.

Dynamics of a cross beam with a straight crack in a mining linear vibrating screen.

Cross beam fracture is one of the common failures of vibrating screens, and crack is the early manifestation of fracture, which is hard to detect. In order to meet the screening requirement of the vibrating screen and improve the service life of the cracked beam, the cracked Euler-Bernoulli beam model is established to investigate the dynamics of the cross beam with a straight crack under different weights of eccentric block, processing capacities, and Rayleigh damping coefficients based on the finite element method in this paper. The local flexibility coefficients are derived from the principles of fracture mechanics and strain release energy and solved by the adaptive five-point Gaussian Legende algorithm. The stiffness matrix of the cracked beam element is calculated through the inverse method of total flexibility. The four order Runge-Kutta algorithm and MATLAB tools are used to solve the dynamic equation of the cracked cross beam. The relationship between the vibration amplitude of the cracked cross beam and the weight of the eccentric block is studied by fitting formulas using the least squares method. The influence of different weights of eccentric block, processing capacities, and Rayleigh damping coefficients on the vibration amplitude and service life of the cracked beam are discussed. The results show that the greater the weight of the eccentric block, the shorter service life of the beam. When the damping is greater, the service life of the cracked beam is longer.

Half-Space Sound Field Reconstruction Based on the Combination of the Helmholtz Equation Least-Squares Method and Equivalent Source Method.

In practical conditions, near-field acoustic holography (NAH) requires the measurement environment to be a free sound field. If vibrating objects are located above the reflective ground, the sound field becomes non-free in the presence of a reflecting surface, and conventional NAH may not identify the sound source. In this work, two types of half-space NAH techniques based on the Helmholtz equation least-squares (HELS) method are developed to reconstruct the sound field above a reflecting plane. The techniques are devised by introducing the concept of equivalent source in HELS-method-based NAH. Two equivalent sources are tested. In one technique, spherical waves are used as the equivalent source, and the sound reflected from the reflecting surface is regarded as a linear superposition of orthogonal spherical wave functions of different orders located below the reflecting surface. In the other technique, some monopoles are considered equivalent sources, and the reflected sound is considered a series of sounds generated by simple sources distributed under the reflecting surface. The sound field is reconstructed by matching the pressure measured on the holographic surface with the orthogonal spherical wave source in the vibrating object and replacing the reflected sound with an equivalent source. Therefore, neither technique is related to the surface impedance of the reflected plane. Compared with the HELS method, both methods show higher reconstruction accuracy for a half-space sound field and are expected to broaden the application range of HELS-method-based NAH techniques.

Beyond the basics: A deep dive into parameter estimation for advanced PBPK and QSP models.

Physiologically-based pharmacokinetic (PBPK) models and quantitative systems pharmacology (QSP) models have contributed to drug development strategies. The parameters of these models are commonly estimated by capturing observed values using the nonlinear least-squares method. Software packages for PBPK and QSP modeling provide a range of parameter estimation algorithms. To choose the most appropriate method, modelers need to understand the basic concept of each approach. This review provides a general introduction to the key points of parameter estimation with a focus on the PBPK and QSP models, and the respective parameter estimation algorithms. The latter part assesses the performance of five parameter estimation algorithms - the quasi-Newton method, Nelder-Mead method, genetic algorithm, particle swarm optimization, and Cluster Gauss-Newton method - using three examples of PBPK and QSP modeling. The assessment revealed that some parameter estimation results were significantly influenced by the initial values. Moreover, the choice of algorithms demonstrating good estimation results heavily depends on factors such as model structure and the parameters to be estimated. To obtain credible parameter estimation results, it is advisable to conduct multiple rounds of parameter estimation under different conditions, employing various estimation algorithms.

Advancing illicit connection diagnosis of urban stormwater pipes: Comprehensive analysis with EEM fluorescence spectroscopy.

Urban drainage systems are significant contributors to the issue of black-odorous water bodies. The current application of stormwater pipe inspection technologies faces substantial limitations, especially in industrial areas with diverse wastewater. This study introduced an innovative approach using excitation-emission matrix (EEM) fluorescence spectroscopy for rapid and accurate diagnosis, providing a new perspective for diagnosing illicit connections. In single wastewater-type areas like residential zones, the method achieved a remarkable 91.5 % accuracy solely through spectra observation and fluorescence peak intensity comparison, outperforming conventional NH3-N-based techniques, which reached an accuracy of only 68.1 %. For regions with complex wastewater scenarios, after EEM subtraction, the residual spectra can be roughly categorized into four distinctive categories based on characteristics. This provides a preliminary assessment and helps in initially identifying the types and sources of inflowing wastewater. Furthermore, the least squares (LS) method refines diagnosis results, offering calculated coefficients reflecting the probability and severity of suspected wastewater intrusion. Simulation experiments and field sample analyses validated the feasibility and accuracy of the EEM-based method, highlighting its advantages for diagnosing illicit connections in both single and mixed wastewater scenarios. The results can significantly narrow down the investigation scope and enhance the confirmation of wastewater sources, exhibiting promising application prospects.

Relative Entropy Application to Study the Elastoplastic Behavior of S235JR Structural Steel.

The main issue in this work is to study the limit functions necessary for the reliability assessment of structural steel with the use of the relative entropy apparatus. This will be done using a few different mathematical theories relevant to this relative entropy, namely those proposed by Bhattacharyya, Kullback-Leibler, Jeffreys, and Hellinger. Probabilistic analysis in the presence of uncertainty in material characteristics will be delivered using three different numerical strategies-Monte Carlo simulation, the stochastic perturbation method, as well as the semi-analytical approach. All of these methods are based on the weighted least squares method approximations of the structural response functions versus the given uncertainty source, and they allow efficient determination of the first two probabilistic moments of the structural responses including stresses, displacements, and strains. The entire computational implementation will be delivered using the finite element method system ABAQUS and computer algebra program MAPLE, where relative entropies, as well as polynomial response functions, will be determined. This study demonstrates that the relative entropies may be efficiently used in reliability assessment close to the widely engaged first-order reliability method (FORM). The relative entropy concept enables us to study the probabilistic distance of any two distributions, so that structural resistance and extreme effort in elastoplastic behavior need not be restricted to Gaussian distributions.

Comparison of Frequency-Domain and Time-Domain Baseline Correction Approaches for Infrared Absorption Spectroscopy of Mixtures Containing Up to 464 Components.

Many baseline correction approaches have been developed to address baseline artifacts observed in measured infrared (IR) absorption spectra during post-processing. These approaches offer distinct advantages and disadvantages, and the choice of which one to employ depends on the complexity of baseline artifacts present in a particular application. In this paper, we compare the performance of two baseline correction approaches: a frequency-domain polynomial fitting approach and a time-domain modified free induction decay approach, under various baseline scenarios, spectral resolutions, and noise levels for mixtures containing up to 464 species. Our results showed that the frequency-domain approach outperformed the time-domain approach by a factor of up to 16 when the baseline was represented by a sine wave with fewer than two cycles over the full spectral range. On the other hand, the time-domain approach performed up to 12 times better when the baseline featured two cycles of a sine wave. Additionally, we observed that the time-domain approach exhibited higher sensitivity to spectral resolution and underperformed when the noise level was high. The findings of this study emphasize the importance of numerically testing a few candidate approaches for a given application, taking into consideration baseline characteristics, as well as the spectral resolution and noise constraints of the application.

A Novel Four-Step Algorithm for Detecting a Single Circle in Complex Images.

Single-circle detection is vital in industrial automation, intelligent navigation, and structural health monitoring. In these fields, the circle is usually present in images with complex textures, multiple contours, and mass noise. However, commonly used circle-detection methods, including random sample consensus, random Hough transform, and the least squares method, lead to low detection accuracy, low efficiency, and poor stability in circle detection. To improve the accuracy, efficiency, and stability of circle detection, this paper proposes a single-circle detection algorithm by combining Canny edge detection, a clustering algorithm, and the improved least squares method. To verify the superiority of the algorithm, the performance of the algorithm is compared using the self-captured image samples and the GH dataset. The proposed algorithm detects the circle with an average error of two pixels and has a higher detection accuracy, efficiency, and stability than random sample consensus and random Hough transform.

Examining the Acceptance of Blockchain by Real Estate Buyers and Sellers.

Buying and selling real estate is time consuming and labor intensive, requires many intermediaries, and incurs high fees. Blockchain technology provides the real estate industry with a reliable means of tracking transactions and increases trust between the parties involved. Despite the benefits of blockchain, its adoption in the real estate industry is still in its infancy. Therefore, we investigate the factors that influence the acceptance of blockchain technology by buyers and sellers of real estate. A research model was designed based on the combined strengths of the unified theory of technology acceptance and use model and the technology readiness index model. Data were collected from 301 real estate buyers and sellers and analyzed using the partial least squares method. The study found that real estate stakeholders should focus on psychological factors rather than technological factors when adopting blockchain. This study adds to the existing body of knowledge and provides valuable insights to real estate stakeholders on how to implement blockchain technology.

Simple Method for Optical Detection and Characterization of Surface Agents on Conjugated Gold Nanoparticles.

In this article, we propose a simple method to calculate electrical permittivity and refractive index of surface agents of gold nanoparticles (Au NPs), in which it is possible to find the refractive index of surface agents shell by using the absorption peak of the gold nano-colloid. One of the usual tests for detection of surface agents is colorimetric methods based on the change of color of Au NPs. The color change is mainly due to the shift of localized surface plasmon resonance which is related to electrical interactions of surface agents. Although there are many mathematical models for simulating the absorption spectrum and calculating the plasmonic peak, using them is not simple and possible for everyone due to the need for programming. Here, the necessary simulations have been performed for different values ​​of refractive index of surface agents and particle size, and absorption peaks have been obtained. Using numerical methods, a simple formula is obtained between the wavelength of plasmonic peak, the ratio of hydrodynamic diameter to Feret size of the particles, and the refractive index of the surface agents. This method can help researchers to obtain the refractive index and consequently the type or concentration of surface agents around Au NPs without the need for programming or complex mathematical operations. It can also open new horizons in analyzing colorimetric diagnosis of biological agents such as viral antibodies, antigens, and other biological agents.

Automatic Calculation of the Kinetic Parameters of Enzymatic Reactions with Their Standard Errors Using Microsoft Excel.

We created a Microsoft Excel file, Enzyme_Kinetics_Calculator, which includes macro programs that automatically calculates kinetic parameters for typical kinetic equations of enzymatic reactions, accompanied by their standard errors, by minimizing the residual sum of squares thereof. The [S]-v plot is automatically drawn with the theoretical lines and, similarly, the 1/[S]-1/v plot in the case of linear theoretical lines. Enzyme_Kinetics_Calculator is available as a supplementary file for this paper (see J. Appl. Glycosci. Web site).

Error identification and compensation regarding the kinematic parameter of the MD-PEF for tibial deformity correction.

The correction accuracy of an external fixator is crucial to the treatment outcome of deformity correction and patient safety. In this study, the mapping model is established between the pose error and kinematic parameter error of the motor-driven parallel external fixator (MD-PEF). Subsequently, the kinematic parameter identification and error compensation algorithm of the external fixator is established based on the least squares method. An experimental platform based on the developed MD-PEF and Vicon motion capture system is constructed for kinematic calibration experiments. Experimental results show that the correction accuracy of the MD-PEF after calibration is as follows: translation accuracy dE1 = 0.36 mm, axial translation accuracy dE2 = 0.25 mm, angulation accuracy dE3 = 0.27°, and rotation accuracy dE4 = 0.2°. The accuracy detection experiment verifies the kinematic calibration results, which further validates the feasibility and reliability of the error identification and compensation algorithm constructed by the least squares method. The calibration approach used in this work also provides an effective way to improve the accuracy of other medical robots.

Optimal Configuration for Monitoring Stations in a Wireless Localisation Network Based on Received Signal Strength Differences.

A smart city is a city equipped with many sensors communicating with each other for different purposes. Cybersecurity and signal security are important in such cities, especially for airports and harbours. Any signal interference or attack on the navigation of autonomous vehicles and aircraft may lead to catastrophes and risks in people's lives. Therefore, it is of tremendous importance to develop wireless security networks for the localisation of any radio frequency interferer in smart cities. Time of arrival, angle of arrival, time-difference of arrivals, received signal strength and received signal strength difference (RSSD) are known observables used for the localisation of a signal interferer. Localisation means to estimate the coordinates of an interferer from some established monitoring stations and sensors receiving such measurements from an interferer. The main goal of this study is to optimise the geometric configuration of the monitoring stations using a desired dilution of precision and/or variance-covariance matrix (VCM) for the transmitter's location based on the RSSD. The required mathematical models are developed and applied to the Arlanda international airport of Sweden. Our numerical tests show that the same configuration is achieved based on dilution of precision and VCM criteria when the resolution of design is lower than 20 m in the presence of the same constraints. The choice of the pathloss exponent in the mathematical models of the RSSDs is not important for such low resolutions. Finally, optimisation based on the VCM is recommended because of its larger redundancy and flexibility in selecting different desired variances and covariances for the coordinates of the transmitter.

Calculation of decision thresholds according to the standard ISO 11929-3 in case of presence of the peaked background.

The method of calculation of the decision threshold with the Least Squares Method, described in the standard ISO 11929, is presented for the case when the sources of peaked background contribute to the peak holding the indication. The decision threshold is calculated from spectral data corresponding to the indication zero; therefore, the observed indication must be removed from the spectrum. When the peaked background is present, the indication completely overlaps with the peaked background, so it can't be unfolded directly. Therefore, two steps are needed in the calculation: the unfolding of the peak, housing the indication, from the continuous background and the possible overlapping peaks, and separating of the indication from the peaked background using the background data obtained from separate calculations and measurements. In this article it is shown that the method of least squares is flexible enough to accommodate all sources of uncertainty into the uncertainty matrix of input quantities. Its derivation is presented in detail and the calculation of the indication corresponding to the decision threshold is described. As a proof of the concept an example of calculating the number of counts corresponding to the decision threshold as a function of the indication is presented. The method of calculation and the results of the calculation are briefly discussed.

Optimization of the pressurized processing technology of Strychnos nux-vomica boiled with mung beans based on genetic algorithm / 中国药房

OBJECTIVE To optimize the pressurized processing technology of Strychnos nux-vomica boiled with mung beans. METHODS The least squares method was used to establish a one-dimensional model for the effects of four factors， namely， processing time， processing pressure， mung bean dosage and water added， on the contents of strychnine and toxiferine， and the multivariate model hypothesis was proposed by analyzing the function of one-dimensional model. Based on the orthogonal experiment， the genetic algorithm was used to solve the undetermined coefficients in the model. A bi-objective optimization model based on strychnine and toxiferine content was constructed according to the actual conditions， and the optimal technology was obtained by solving the model function and validated. RESULTS The optimal processing technology was boiling S. nux-vomica with mung beans at 2.393 MPa saturated steam pressure for 5.5 h， and then draining； rinsing to remove mung beans， scraping off the bark of S. nux-vomica and cutting into slice of 0.6 mm； using 180 g of mung beans and 15 L of water per 500 g of S. nux- vomica. CONCLUSIONS The optimized pressurized processing technology is stable and feasible， and can provide a reference for the optimization of processing technology of S. nux-vomica boiled with mung beans.

[Rapid prediction of flavonoid content in Epimedium sagittatum by infrared spectroscopy].

Epimedii Folium is a well-known Chinese herbal medicine with the effect of nourishing kidney and strengthening Yang. Its main active ingredients are flavonoids. In this study, 60 samples of Epimedium sagittatum were collected for the determination of total flavonoids(TF) including the total amount of epimedin A, epimedin B, epimedin C, and icariin(abbreviated as ABCI) specified in the Chinese Pharmacopoeia as well as rhamnosylicariside Ⅱ and icariside Ⅱ. The calibration parameters of "first derivativemultiva-riate scattering correction in 1 900-650 cm~(-1) band(4-point smoothing)" and "first derivativestandard normal variable correction in 4 000-650 cm~(-1) full band(4-point smoothing)" were confirmed respectively. The quantitative model was established via Fourier infrared spectroscopy plus attenuated total reflection(FTIR-ATR) accessory combined with partial least squares(PLS) method and then used to predict the flavonoid content of 11 validation sets. The average prediction accuracy for ABCI in calibration set and validation set was 98.985% and 96.087%, respectively. The average prediction accuracy for TF in calibration set and validation set was 98.998% and 94.771%, respectively. These results indicated that FTIR-ATR combined with PLS model could be used for rapid prediction of flavonoid content in E. sagittatum, with the prediction accuracy above 94.7%. The establishment of this method provides a new solution for the detection of a large number of E. sagittatum samples.

Sphero-Conical Modeling for the Estimation of Very Long Baseline Interferometry Invariant Point.

A geodetic reference frame is a fundamental element in geoinformation fields such as autonomous navigation and digital twins. The international terrestrial reference frame is established and maintained using several space-geodetic techniques, including very long baseline interferometry (VLBI) and satellite laser ranging (SLR). For several decades, geodesists have been devoted to connecting these two sensors at a site (local tie). The reference point of the VLBI antenna and SLR telescope, called invariant point (IVP), should be precisely determined to connect these two solutions. We developed an innovative integrated model to estimate the IVP, which is composed of spherical and conical models, depending on the rotational axis. In this model, all target points in 3D spaces were directly connected to the IVP; thus, the stability and robustness of the system were secured. Furthermore, all inherent errors in the coordinates were predicted by applying the total least-squares approach.

The new gravimetric network of the north-eastern part of Algeria.

The north of Algeria is situated between the limit of the African and Eurasian plates. It considers as one of the best areas to study neotectonics structures and their geodynamical effects. On offshore, recent geophysical studies have allowed to imaging the deep structure of the Algerian basin. However, these images need to be improved and adjusted on onshore, especially in the easternmost part where, the process of geodynamic evolution is particular, with slow but hot accretion processes. This paper presents all stages of the gravimetric network of the north-eastern part of Algeria, including its development and data processing. The established gravimetric network is located between coordinates 07°00' -08°00' east and 36°00'-36°45' north. It consists of thirty-nine stations connected to the zero-order gravimetric network by means of relative gravimetric measurements. This gravimetric network contains 61 triangular geometry loops and 99 links. The description of the design, the gravity survey network and the gravimetric stations coordinates are given. The accuracy of the determination of gravity values at each station is about 11 µGal, using a terrestrial Scintrex CG3 gravimeter. The gravimetric network is compensated using ginning and the least squares methods. The main objective of the establishment of this gravimetric network is to ensure a quality basis for all future works with respect to the gravimetric studies in the north-eastern part of Algeria.

A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation.

We consider a least-squares/relaxation finite element method for the numerical solution of the prescribed Jacobian equation. We look for its solution via a least-squares approach. We introduce a relaxation algorithm that decouples this least-squares problem into a sequence of local nonlinear problems and variational linear problems. We develop dedicated solvers for the algebraic problems based on Newton's method and we solve the differential problems using mixed low-order finite elements. Various numerical experiments demonstrate the accuracy, efficiency and the robustness of the proposed method, compared for instance to augmented Lagrangian approaches.

A Novel Sparsity Adaptive Algorithm for Underwater Acoustic Signal Reconstruction.

In view of the fact that most of the traditional algorithms for reconstructing underwater acoustic signals from low-dimensional compressed data are based on known sparsity, a sparsity adaptive and variable step-size matching pursuit (SAVSMP) algorithm is proposed. Firstly, the algorithm uses Restricted Isometry Property (RIP) criterion to estimate the initial value of sparsity, and then employs curve fitting method to adjust the initial value of sparsity to avoid underestimation or overestimation, before finally realizing the close approach of the sparsity level with the adaptive step size. The algorithm selects the atoms by matching test, and uses the Least Squares Method to filter out the unsuitable atoms, so as to realize the precise reconstruction of underwater acoustic signal received by the sonar system. The experimental comparison reveals that the proposed algorithm overcomes the drawbacks of existing algorithms, in terms of high computation time and low reconstruction quality.