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This document discusses the importance of a scientific approach in the field of abdominal wall surgery. It emphasizes the need for a combination of factors, including personal experience, guidelines, and analysis of scientific literature, in order to provide patients with the best possible care. The document also highlights the complexity of the field and the value of research in addressing challenging situations. This special issue of the journal Hernia, guest edited by international experts, aims to provide surgeons with valuable insights and support in their daily practice. [Extracted from the article]

In order to scientifically and rationally evaluate the susceptibility to landslide hazards in Tekes County, Yili State. This paper takes Tekes County in Xinjiang as an example, on the basis of a comprehensive analysis of the regional geological environment conditions and the distribution pattern and formation conditions of geological disasters, using the data of geological disaster points (landslide center points), and through the correlation matrix calculation of the evaluation factors, the nine evaluation factors with larger absolute values of correlation coefficients were determined to construct the evaluation system of the susceptibility to landslide geological hazards in Tekesi County. Combining the information quantity method and the entropy value method, using the weights determined by the entropy value method, the information quantity method is used to calculate the information quantity value of each factor within the factor, calculate the susceptibility index of landslide geological disasters within the territory of Tekes County, and then carry out the landslide susceptibility evaluation. The susceptibility of landslide disasters was evaluated by ArcGIS. The results show that the landslide disaster susceptibility level in Tekes County can be divided into four levels: high susceptibility, medium susceptibility, low susceptibility, and not susceptible, with areas of 491.3276 km2, 1181.5171 km2, 1674.7609 km2 and 5295.2976 km2 accounting for 5.68%, 13.67%, 19.38% and 61.27% of the total area of Tex County, respectively. The AUC number obtained by the success curve method (ROC) is 0.8736, reflecting the evaluation accuracy of 87.36%, indicating that the model method used in this paper is effective. The results are expected to provide practical data support for landslide disaster control in Tekes County and provide a reference for geological disaster monitoring, early warning and engineering prevention and control deployment in Yili Valley. [ABSTRACT FROM AUTHOR]

Purpose: This work presents a new two-step iterative technique for solving absolute value equations. The developed technique is valuable and effective for solving the absolute value equation. Various examples are given to demonstrate the accuracy and efficacy of the suggested technique. Design/methodology/approach: In this paper, we present a new two-step iterative technique for solving absolute value equations. This technique is very straightforward, and due to the simplicity of this approach, it can be used to solve large systems with great effectiveness. Moreover, under certain assumptions, we examine the convergence of the proposed method using various theorems. Numerical outcomes are conducted to present the feasibility of the proposed technique. Findings: This paper gives numerical experiments on how to solve a system of absolute value equations. Originality/value: Nowadays, two-step approaches are very popular for solving equations (1). For solving AVEs, Liu in Shams (2021), Ning and Zhou (2015) demonstrated two-step iterative approaches. Moosaei et al. (2015) introduced a novel approach that utilizes a generalized Newton's approach and Simpson's rule to solve AVEs. Zainali and Lotfi (2018) presented a two-step Newton technique for AVEs that converges linearly. Feng and Liu (2016) have proposed minimization approaches for AVEs and presented their convergence under specific circumstances. Khan et al. (2023), suggested a nonlinear CSCS-like technique and a Picard-CSCS approach. Based on the benefits and drawbacks of the previously mentioned methods, we will provide a two-step iterative approach to efficiently solve equation (1). The numerical results show that our proposed technique converges rapidly and provides a more accurate solution. [ABSTRACT FROM AUTHOR]

Inhomogeneous damping distribution leads to the occurrence of complex modes of structures. Complex modes' vibration and acoustic radiation characteristics are different from real modes. This paper studies the complex modal characteristics of inhomogeneously damped plates for forced vibration. We used the state space method to obtain the complex eigenvalues and eigenvectors of the vibration system and calculated the relationship between modal coordinates and frequency under unit force. The results show that the absolute values of the modal coordinates of two conjugate complex eigenvectors are different, and the structure's vibration is dominated by the eigenvectors corresponding to eigenvalues with positive imaginary parts near natural frequencies. When investigating the structural sound radiation in the vibration mode space, each mode's acoustic radiation is not independent but coupled with each other. The influence of the coupling between complex modes on the calculation results of the acoustic radiation power of the plate is studied in this paper. The results show that the coupling effect between modes cannot be ignored when calculating the acoustic radiation power based on complex modes. Finally, the error of calculating acoustic power using the decoupling approximation instead of the complex mode method is analyzed. [ABSTRACT FROM AUTHOR]

The calculation of satellite orbit involves some very complex formula derivations and expansions, which are very difficult to manually derive and prone to errors. And the efficiency of manual derivation is not high. We can use computer algebra systems to derive complex formulas related to satellite orbits. This can avoid some of the drawbacks of manual derivation and significantly improve computational efficiency and accuracy. In the past, the relationship among three anomalies was generally represented in the form of a trigonometric series with the first eccentricity e as the parameter. In this paper, the trigonometric series with the parameter m = 1 − 1 − e 2 e is used, as determined by the Lagrange conjugate series. We can use the formula of the Lagrange conjugate series to derive the relationship between the true anomaly and elliptic anomaly. And the relationship between the elliptic anomaly and the mean anomaly is derived by using the symbolic iteration method. In this research paper, we calculated the accuracy of the trigonometric series expansion among three types of anomalies at the first eccentricity e equal to values of 0.01, 0.1, and 0.2. The calculation results indicate that the accuracy of the trigonometric series expansion with m as the parameter is better than 10−5. Moreover, in some cases, the trigonometric series expansion among the three anomalies with m as a parameter is simpler in form than the expansion expressed with parameter e. This paper also derived and calculated the symbolic expressions and extreme values of the difference among three anomalies and expressed the extreme values of the difference in the form of a power series of e. It can be seen that the extreme value increases with the increase in eccentricity e. And the absolute values of the extreme value of the difference between the elliptic anomaly and the mean anomaly, the true anomaly and the elliptic anomaly, and the true anomaly and the mean anomaly increase in this order. When the eccentricity is small, the absolute value of the extreme value of the difference between the true anomaly and the mean anomaly is about twice as large as the elliptic anomaly and the mean anomaly and the true anomaly and the mean anomaly. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the nonlinear least squares problem: \min _{{\boldsymbol {x}}\in \mathbb {H}^d}\|\lvert A{\boldsymbol {x}}\rvert -{\boldsymbol {b}}\| where A\in \mathbb {H}^{m\times d}, {\boldsymbol {b}}\in \mathbb {R}^m with \mathbb {H}\in \left \{\mathbb {R},\mathbb {C}\right \} and consider the uniqueness and stability of solutions. This problem arises in applications such as phase retrieval and absolute value rectification neural networks. While several results have been developed to characterize the uniqueness and stability of solutions when {\boldsymbol {b}}=\lvert A{\boldsymbol {x}}_0\rvert for some {\boldsymbol {x}}_0\in \mathbb {H}^d, no existing results address the case where {\boldsymbol {b}} is arbitrary. In this paper, we investigate the uniqueness and stability of solutions for the more general case where {\boldsymbol {b}} is not necessarily equal to \lvert A{\boldsymbol {x}}_0\rvert for any {\boldsymbol {x}}_0\in \mathbb {H}^d. We prove that for any matrix A\in \mathbb {H}^{m\times d}, there is always a vector {\boldsymbol {b}}\in \mathbb {R}^m for which the solution to the nonlinear least squares problem is not unique. However, we show that such "bad" vectors {\boldsymbol {b}} are negligible in practice; specifically, if {\boldsymbol {b}}\in \mathbb {R}_{ }^m does not lie in some measure zero set, then the solution is unique. Furthermore, we establish certain conditions under which the solution is guaranteed to be unique. Regarding the stability of solutions, we prove that the solution is not uniformly stable. However, if we restrict the vectors {\boldsymbol {b}} to a convex set where the solution to the least squares problem is unique, then the solution becomes stable. To the best of our knowledge, our results represent the first theoretical results of the uniqueness and stability of solutions for the nonlinear least squares problem. [ABSTRACT FROM AUTHOR]

INTRODCTION: Listening strategy analysis and assessment not only need objective and fair sound listening strategy analysis, but also need high-precision and high real-time assessment model, and even more need in-depth analysis and feature extraction of the influencing factors of listening assessment. OBJECTIVES: To address the problems of current automatic assessment methods, such as non-specific application, poor generalization, low assessment accuracy, and poor real-time performance. METHODS: This paper proposes an automatic assessment method based on a deep confidence network based on crawfish optimization algorithm. First, the multi-dimensional listening strategy evaluation system is constructed by analyzing the listening improvement strategy; then, the depth confidence network is improved by the crayfish optimization algorithm to construct the automatic evaluation model; finally, through the analysis of simulation experiments. RESLUTS: The proposed method improves the evaluation accuracy, robustness, and real-time performance. The absolute value of the relative error of the automatic evaluation value of the proposed method is controlled in the range of 0.011, and the evaluation time is less than 0.005 s. The method is based on a deep confidence network based on the crayfish optimization algorithm. CONCLUSION: The problems of non-specific application of automated assessment methods, poor generalization, low assessment accuracy, and poor real-time performance are addressed. [ABSTRACT FROM AUTHOR]

The discrete cosine transform is a commonly used technique in the field of signal processing that employs cosine basis functions for signal analysis. Traditionally, the regression coefficients of the cosine basis functions are solely based on frequency information. This paper extends the regression coefficients associated with the cosine basis functions to take into account both frequency and time information, not just frequency information alone. This modification results in an ill-posed linear system, which requires regularization to prevent overfitting. To address this, this paper uses shaping regularization, a technique used to stabilize ill-posed problems. By doing so, the absolute values of these extended coefficients, now exhibiting variations in both frequency and time domains, are defined as the time–frequency distribution of that input signal. The numerical experiments conducted to validate this approach demonstrate that the proposed method yields a commendable time–frequency resolution. Consequently, it proves valuable for interpreting seismic data, showcasing its potential for applications in this field. [ABSTRACT FROM AUTHOR]

Hills and mountain fields have a high proportion in coastal areas around the world. Especially in China, lots of low-rise buildings are in complex mountain terrain. Compared with the flat topography under typhoons, due to the change caused by complex topography, the damage ratio of low-rise buildings is much larger. This paper investigates the wind pressure distribution in three different configurations of typical mountain terrain on low-rise buildings in coastal areas by wind tunnel tests. At the same time, the results are compared with the wind pressure distribution of low-rise buildings without surrounding structures. The variation of the average pressure coefficient and shape coefficient with the change of hillside height under a wind attack angle of 0° and the trends of average wind pressure coefficients of a low-rise building under wind attack angles of 0° – 90° are studied. The results show that the distribution of pressure in low buildings is significantly affected by the height of the mountain. When the hillside height is half of the scale physical model, the influence coefficient from the mountain to each surface of the whole building is within 50%. When the hillside height is four times that of the model, the influence factor from the mountain to each surface of the whole building is obvious and is most significantly influenced by the leeward roof. The mean design criteria of the low-rise building, such as windward midline, leeward roof, and windward roof in these three typical mountain terrains, should be designed for their higher absolute value of the average pressure coefficient. The mean pressure coefficient under different wind angles and mountain environments has a significant relationship. The most unfavorable wind angle of wind load calculations should be considered when designing low-rise buildings. [ABSTRACT FROM AUTHOR]

Roller bearings are critical components in various mechanical systems, and the timely detection of potential failures is essential for preventing costly downtimes and avoiding substantial machinery breakdown. This research focuses on finding and verifying a robust method that can detect failures early, without creating false positive failure states. Therefore, this paper introduces a novel algorithm for the early detection of roller bearing failures, particularly tailored to high-precision bearings and automotive test bed systems. The featured method (AFI—Advanced Failure Indicator) utilizes the Fast Fourier Transform (FFT) of wideband accelerometers to calculate the spectral content of vibration signals emitted by roller bearings. By calculating the frequency bands and tracking the movement of these bands within the spectra, the method provides an indicator of the machinery's health, mainly focusing on the early stages of bearing failure. The calculated channel can be used as a trend indicator, enabling the method to identify subtle deviations associated with impending failures. The AFI algorithm incorporates a non-static limit through moving average calculations and volatility analysis methods to determine critical changes in the signal. This thresholding mechanism ensures the algorithm's responsiveness to variations in operating conditions and environmental factors, contributing to its robustness in diverse industrial settings. Further refinement was achieved through an outlier detection filter, which reduces false positives and enhances the algorithm's accuracy in identifying genuine deviations from the normal operational state. To benchmark the developed algorithm, it was compared with three industry-standard algorithms: VRMS calculations per ISO 10813-3, Mean Absolute Value of Extremums (MAVE), and Envelope Frequency Band (EFB). This comparative analysis aimed to evaluate the efficacy of the novel algorithm against the established methods in the field, providing valuable insights into its potential advantages and limitations. In summary, this paper presents an innovative algorithm for the early detection of roller bearing failures, leveraging FFT-based spectral analysis, trend monitoring, adaptive thresholding, and outlier detection. Its ability to confirm the first failure state underscores the algorithm's effectiveness. [ABSTRACT FROM AUTHOR]

Purpose: This study presents a two-step numerical iteration method specifically designed to solve absolute value equations. The proposed method is valuable and efficient for solving absolute value equations. Several numerical examples were taken to demonstrate the accuracy and efficiency of the proposed method. Design/methodology/approach: We present a two-step numerical iteration method for solving absolute value equations. Our two-step method consists of a predictor-corrector technique. The new method uses the generalized Newton method as the predictor step. The four-point open Newton-Cotes formula is considered the corrector step. The convergence of the proposed method is discussed in detail. This new method is highly effective for solving large systems due to its simplicity and effectiveness. We consider the beam equation, using the finite difference method to transform it into a system of absolute value equations, and then solve it using the proposed method. Findings: The paper provides empirical insights into how to solve a system of absolute value equations. Originality/value: This paper fulfills an identified need to study absolute value equations. [ABSTRACT FROM AUTHOR]

In this paper we resolve a conjecture of Kresch and Tamvakis [Duke Math. J. 110 (2001), pp. 359–376]. Our result is the following. Theorem : For any positive integer D and any integers i,j (0\leq i,j \leq D), \; the absolute value of the following hypergeometric series is at most 1: \begin{equation*} {_4F_3} \left [ \begin {array}{c} -i, \; i+1, \; -j, \; j+1 \\ 1, \; D+2, \; -D \end{array} ; 1 \right ]. \end{equation*} To prove this theorem, we use the Biedenharn-Elliott identity, the theory of Leonard pairs, and the Perron-Frobenius theorem. [ABSTRACT FROM AUTHOR]

The document is a correction notice for an article titled "Power Approximations for Overall Average Effects in Meta-Analysis With Dependent Effect Sizes" published in the Journal of Educational and Behavioral Statistics. The correction addresses an error in Equation 17 of the article, providing the correct formula. The correction also includes revised values for weights used in the CE working model and corrects the weights reported in an example. The correction has a negligible effect on the power estimates for the CE working model and does not affect the substantive findings of the study. The correction notice also mentions revised versions of Figure 1 and Figure 2A in the original paper, which depict the approximate power of different tests and the difference between approximate power and true power, respectively. The correction does not significantly impact the results presented in these figures. [Extracted from the article]

Lateral roots, including adventitious roots, are the main component of rapeseed roots with support, absorb, and synthesis functions and their morphological parameters directly affecting the plant's aboveground growth and yield. Root biomass, as a material base for lateral root growth, can be used as a link between plant phenotypes and their physiological processes, as well as to enhance root 3D growth model mechanisms and accuracy. To quantify the relationships between lateral root morphological indices and the corresponding organ biomass for rapeseed, we used two cultivars, NY 22 (conventional) and NZ 1818 (hybrid), and conducted cultivar and fertilizing cylindrical tube experiments during the 2016–2019, with two fertilizer levels, no fertilizer, and 180 kg N ha−1 fertilizer. The lateral root biomass and morphological parameters were determined during the whole growth period. The biomass‐based lateral root morphological parameter models were developed by analyzing the quantitative relationship between the lateral root morphological indices and their corresponding biomass, and the descriptive models were verified with independent experimental data. The results showed that the correlation (r) of simulated and observed values for the lateral root morphological parameters are all greater than 0.9 with significant levels at p < 0.001. The absolute values of the average absolute difference (da) of simulated and observed values for the lateral root length (LLR), lateral root average diameter (ADLR), lateral root surface area (SALR), and lateral root volume (VLR) are −30.408 cm, −0.003 mm, 12.902 cm2, and 0.039 cm3, respectively. The RMSE values are 175.183 cm, 0.010 mm, 59.710 cm2, and 1.513 cm3, respectively. The ratio of da to the average observed values (dap) for the LLR and VLR are all less than 5%, and the ADLR and SALR are all <6%. The models developed in this paper have good performance and reliability for predicting lateral root morphological parameters of rapeseed. The study provides a mechanistic method for linking the rapeseed growth model with the morphological model using corresponding organic biomass and laying a good foundation for establishing a 3D morphological model for rapeseed root system based on biomass. [ABSTRACT FROM AUTHOR]

Topography can strongly affect ground motion, and studies of the quantification of hill surfaces' topographic effect are relatively rare. In this paper, a new quantitative seismic topographic effect prediction method based upon the BP neural network algorithm and three-dimensional finite element method (FEM) was developed. The FEM simulation results were compared with seismic records and the results show that the PGA and response spectra have a tendency to increase with increasing elevation, but the correlation between PGA amplification factors and slope is not obvious for low hills. New BP neural network models were established for the prediction of amplification factors of PGA and response spectra. Two kinds of input variables' combinations which are convenient to achieve are proposed in this paper for the prediction of amplification factors of PGA and response spectra, respectively. The absolute values of prediction errors can be mostly within 0.1 for PGA amplification factors, and they can be mostly within 0.2 for response spectra's amplification factors. One input variables' combination can achieve better prediction performance while the other one has better expandability of the predictive region. Particularly, the BP models only employ one hidden layer with about a hundred nodes, which makes it efficient for training. [ABSTRACT FROM AUTHOR]

AbstractIn a recent paper, Baker and Oliver Lorscheid showed that Descartes’s Rule of Signs and Newton’s Polygon Rule can both be interpreted as multiplicities of polynomials over hyperfields. Hyperfields are a generalization of fields which encode things like the arithmetic of signs or of absolute values. By looking at multiplicities of polynomials over such algebraic structures, Baker and Lorscheid showed that you can recover the rules of Descartes and Newton. In this paper, we define tropical extensions for idylls. Such extensions have appeared for semirings with negation symmetries in the work of Akian-Gaubert-Guterman and for hypergroups and hyperfields in the work of Bowler-Su. Examples of tropical extensions are extending the tropical hyperfield to higher ranks, or extending the hyperfield of signs to the tropical real hyperfield by including a valuation. The results of this paper concern the interaction of multiplicities and tropical extensions. First, there is a lifting theorem from initial forms to the entire polynomial from which we will show that multiplicities for a polynomial are equal to the corresponding multiplicity for some initial form. Second, we show that tropical extensions preserve the property that the sum of all multiplicities is bounded by the degree. Consequentially, we have this degree bound for every stringent hyperfield. This gives a partial answer to a question posed by Baker and Lorscheid about which hyperfields have this property. [ABSTRACT FROM AUTHOR]

In recent years, there has been extensive research and application of unsupervised monocular depth estimation methods for intelligent vehicles. However, a major limitation of most existing approaches is their inability to predict absolute depth values in physical units, as they generally suffer from the scale problem. Furthermore, most research efforts have focused on ground vehicles, neglecting the potential application of these methods to unmanned aerial vehicles (UAVs). To address these gaps, this paper proposes a novel absolute depth estimation method specifically designed for flight scenes using a monocular vision sensor, in which a geometry-based scale recovery algorithm serves as a post-processing stage of relative depth estimation results with scale consistency. By exploiting the feature correspondence between successive images and using the pose data provided by equipped navigation sensors, the scale factor between relative and absolute scales is calculated according to a multi-view geometry model, and then absolute depth maps are generated by pixel-wise multiplication of relative depth maps with the scale factor. As a result, the unsupervised monocular depth estimation technology is extended from relative depth estimation in semi-structured scenes to absolute depth estimation in unstructured scenes. Experiments on the publicly available Mid-Air dataset and customized data demonstrate the effectiveness of our method in different cases and settings, as well as its robustness to navigation sensor noise. The proposed method only requires UAVs to be equipped with monocular camera and common navigation sensors, and the obtained absolute depth information can be directly used for downstream tasks, which is significant for this kind of vehicle that has rarely been explored in previous depth estimation studies. [ABSTRACT FROM AUTHOR]

In order to investigate the deformation characteristics of interbedded weak expansive rocks in water immersion, the sandstone–mudstone interbedded structures were taken as the object of this study. A total of 27 sets of indoor immersion tests were designed with three influencing factors, namely, the layer thickness ratios of sandstone and mudstone (1:1, 2:1, 3:1), the occurrence of the rock layers (flat, oblique, and vertical), and the overburden loadings (0 kPa, 12.5 kPa, and 25 kPa). Tests were conducted to obtain the deformation time series data of the samples during the immersion loading process. Based on this, the influence pattern of each influencing factor on the sample deformation was analyzed individually. The results show that with the increase in overburden loading and rock inclination angle, the sample develops from expansion deformation to compression deformation. Changes in the layer thickness ratio will not change the deformation trend of the sample, and the decrease in the relative mudstone content will only reduce the absolute value of the sample's expansion and compression deformation. The deformation stability rate of the sample under load is 5~7 times that under no load. The increase in layer thickness ratio and rock inclination angle will lead to different degrees of attenuation of sample expansion force in the range of 8.91~38.68% and 51.00~58.83%, respectively. The research results of this paper can provide a meaningful reference for the design and maintenance of a high-speed railway subgrade in a weak expansive rock area with an interbedded structure. [ABSTRACT FROM AUTHOR]

In this paper, a signal model and a mathematical analysis of an efficient approach are derived to acquire the approximate magnitude of a complex signal by inducing a pre-biased or a pre-scaled factor in the design criteria. According to the deductive results, the pre-biased or pre-scaled factor can be 2∼3 dB, which is determined through its application. The numerical evaluations show that the mean square error (MSE) of the proposed efficient approach for the random signal is around −33 dB. Based on the design templates for the considered approaches, the occupied areas of the proposed type-1 and -2 approaches are merely 0.13 and 0.09 times the area of the direct-method, respectively. As a result, the proposed efficient approach is certainly a cost-efficient method for obtaining the approximate magnitude of a complex signal. [ABSTRACT FROM AUTHOR]

A double-volute centrifugal pump is a very important pump type; the internal flow field of a centrifugal pump will change drastically during the transition process of power failure, which will affect the safety and stability of the pump's operation. In this paper, the CFD numerical simulation method is used, and the UDF procedure is developed to realize the continuous update of the impeller speed at each time step. The working parameters, such as the torque and flow rate at the instantaneous moment, are obtained through the sequential iteration of each small step, and a numerical simulation of the power-off transient is carried out on a double-volute centrifugal pump; additionally, the changes in the external characteristic parameters and the internal flow field of the centrifugal pump are analyzed in detail. The results show that the double-volute centrifugal pump experienced four different modes after power failure, namely pump mode, braking mode, turbine mode, and runaway mode, and the absolute values of the runaway speed and runaway flow rate are 1.465 times and 1.21 times the initial values, respectively. Through the analysis of the flow field in different regions, the change processes of the generation, development, and disappearance of the vortex at each position of the centrifugal pump are obtained, and the change and development processes of the internal velocity gradient of the centrifugal pump are obtained. In addition, it is found that the high-speed area located in the second volute runner is larger than that of the first volute runner because the second volute runner is shorter and narrower than the first volute runner. [ABSTRACT FROM AUTHOR]

The aim of this paper was to investigate intumescent coatings based on polyfurfuryl alcohol (PFA) resin as a binder benefiting from high char yield and low smoke emission. To this end, the coatings composition in terms of PFA binder resin, long oil alkyd plasticizing resin, TiO2 pigment, and flame-retardant additives (FR) was changed as input parameters according to a mixture design-of-experiments. The corresponding changes in the backside temperature of mild steel substrate (Tb), residual char expansion ratio, limiting oxygen index, and char residue (wt% @1000 °C) were studied as the response variables describing fire performance characteristics of the coatings. The results showed that the backside temperature of the plate increased and the expansion ratio decreased with increasing in the alkyd resin concentration. Also, the flame-retardant efficiency of coatings strongly depends on the content of FR additives. When the content of PFA and alkyd resin was increased at a high level (35 and 4 wt%, respectively), the Tb of the coated plates reached 415 °C rapidly, due to the cracking of the coating and the lower concentration of FR additives. However, the formula with higher FR content, i.e., 68 wt%, showed the lowest Tb value ca. 128 °C. Flame-retardant characteristics directly depended on the expansion ratio of the coatings and the morphology of the char layer remaining on the substrate after the flame test; therefore, coatings with a higher expansion ratio showed lower backside temperature. The findings were supported by examining of the remaining char morphology after a flame test by optical microscopy and validated by comparing the predicted and actual responses for optimization. The value of absolute relative deviation was obtained in the range of 1.6–7.9, which indicates a good agreement between the proposed and experimental results. [ABSTRACT FROM AUTHOR]

In this paper, by using Hölder-İşcan, Hölder integral inequality and an general identity for differentiable functions we can get new estimates on generalization of Hadamard, Ostrowski and Simpson type integral inequalities for functions whose derivatives in absolute value at certain power are quasi-convex functions. It is proved that the result obtained Hölder-İşcan integral inequality is better than the result obtained Hölder inequality. [ABSTRACT FROM AUTHOR]

In this paper, we are introducing very first time the class of (α, β, γ, δ)-convex function in mixed kind, which is the generalization of many classes of convex functions. We would like to state well-known Ostrowski inequal- ity via Montgomery identity for ψ - (α, β, γ, δ)-convex function in mixed kind. In addition, we establish some Ostrowski type inequalities for the class of functions whose derivatives in absolute values at certain powers are ψ – (α, β, γ, δ)-convex functions in mixed kind by using different techniques including Hölder's inequality and power mean inequality. Also, various established results would be captured as special cases. Moreover, some applications in terms of special means would also be given. [ABSTRACT FROM AUTHOR]

In this paper, we focus on solving the generalized absolute value equations (GAVE). We present a new method named as modulus-based block triangular splitting iteration (MBTS) method based on the block matrix structure resulting from the transformation of the GAVE into two equations. This method is developed by decomposing the matrix into diagonal and triangular matrices, as well as applying a series of suitable combination and modification techniques. The advantage of the MBTS method is that it is not necessary to solve the inverse of the coefficient matrix of the linear equation system during each iteration, which greatly improves the computational speed and reduces its storage requirements. In addition, we present some convergent theorems proving by different techniques and the estimate of the required number of iteration steps. Furthermore, in the accompanying corollaries, we provide some estimations for choosing appropriate parameter values. Finally, we validated the effectiveness and efficiency of our newly developed method through two numerical examples of the GAVE. [ABSTRACT FROM AUTHOR]

In this paper, an analytical exact form of the ramp function is presented. This seminal function constitutes a fundamental concept of the digital signal processing theory and is also involved in many other areas of applied sciences and engineering. In particular, the ramp function is performed in a simple manner as the pointwise limit of a sequence of real and continuous functions with pointwise convergence. This limit is zero for strictly negative values of the real variable x , whereas it coincides with the independent variable x for strictly positive values of the variable x . Here, one may elucidate beforehand that the pointwise limit of a sequence of continuous functions can constitute a discontinuous function, on the condition that the convergence is not uniform. The novelty of this work, when compared to other research studies concerning analytical expressions of the ramp function, is that the proposed formula is not exhibited in terms of miscellaneous special functions, e.g., gamma function, biexponential function, or any other special functions, such as error function, hyperbolic function, orthogonal polynomials, etc. Hence, this formula may be much more practical, flexible, and useful in the computational procedures, which are inserted into digital signal processing techniques and other engineering practices. [ABSTRACT FROM AUTHOR]

Vanadium redox flow batteries are promising energy storage devices and are already ahead of lead–acid batteries in terms of installed capacity in energy systems due to their long service life and possibility of recycling. One of the crucial tasks today is the development of models for assessing battery performance and its residual resource based on the battery's present state. A promising method for estimating battery capacity is based on analyzing present voltage and current values under various load conditions. This paper analyzes the discharge characteristics of a 10 kW all-vanadium redox flow battery at fixed load powers from 6 to 12 kW. A linear dependence of operating voltage and initial discharge voltage on load power is established. It is also determined that the slope of the discharge curve linear section does not increase linearly in absolute value, and the Box–Lucas model can be used to describe it. Models for predicting current VRFB capacity based on different curve fitting functions are proposed. These models can be used to roughly estimate battery capacity at different load powers. [ABSTRACT FROM AUTHOR]

In this paper, we propose a modified spectral conjugate gradient (MSCG) method for solving absolute value equations associated with second-order cones (SOCAVEs). Some properties of the SOCAVEs are analyzed, and the global convergence of the MSCG method is discussed in depth. Numerical experiments are given to illustrate the effectiveness and competitiveness of our algorithm. [ABSTRACT FROM AUTHOR]

Positive and unlabeled learning (PU learning) is a significant binary classification task in machine learning; it focuses on training accurate classifiers using positive data and unlabeled data. Most of the works in this area are based on a two-step strategy: the first step is to identify reliable negative examples from unlabeled examples, and the second step is to construct the classifiers based on the positive examples and the identified reliable negative examples using supervised learning methods. However, these methods always underutilize the remaining unlabeled data, which limits the performance of PU learning. Furthermore, many methods require the iterative solution of the formulated quadratic programming problems to obtain the final classifier, resulting in a large computational cost. In this paper, we propose a new method called the absolute value inequality support vector machine, which applies the concept of eccentricity to select reliable negative examples from unlabeled data and then constructs a classifier based on the positive examples, the selected negative examples, and the remaining unlabeled data. In addition, we apply a hyperparameter optimization technique to automatically search and select the optimal parameter values in the proposed algorithm. Numerical experimental results on ten real-world datasets demonstrate that our method is better than the other three benchmark algorithms. [ABSTRACT FROM AUTHOR]

The spectral radius of a square matrix is the maximum among absolute values of its eigenvalues. Suppose a square matrix is nonnegative; then, by Perron–Frobenius theory, it will be one among its eigenvalues. In this paper, Perron–Frobenius theory for adjacency matrix of graph with self-loops A G S will be explored. Specifically, it discusses the nontrivial existence of Perron–Frobenius eigenvalue and eigenvector pair in the matrix A G S − σ n I , where σ denotes the number of self-loops. Also, Koolen–Moulton type bound for the energy of graph G S is explored. In addition, the existence of a graph with self-loops for every odd energy is proved. [ABSTRACT FROM AUTHOR]

Text processing tasks commonly grapple with the challenge of high dimensionality. One of the most effective solutions to this challenge is to preprocess text data through feature selection methods. Feature selection can select the most advantageous features for subsequent operations (e.g., classification) from the native feature space of the text. This process effectively trims the feature space's dimensionality, enhancing subsequent operations' efficiency and accuracy. This paper proposes a straightforward and efficient filter feature selection method based on document-term matrix unitization (DTMU) for text processing. Diverging from previous filter feature selection methods that concentrate on scoring criteria definition, our method achieves more optimal feature selection by unitizing each column of the document-term matrix. This approach mitigates feature-to-feature influence and reinforces the role of the weighting proportion within the features. Subsequently, our scoring criterion subtracts the sum of weights for negative samples from positive samples and takes the absolute value. We conduct numerical experiments to compare DTMU with four advanced filter feature selection methods: max–min ratio metric, proportional rough feature selector, least loss, and relative discrimination criterion, along with two classical filter feature selection methods: Chi-square and information gain. The experiments are performed on four ten-thousand-dimensional feature space datasets: b o o k , d v d , m u s i c , m o v i e and two thousand-dimensional feature space datasets: i m d b , a m a z o n _ c e l l s , sourced from Amazon product reviews and movie reviews. Experimental findings demonstrate that DTMU selects more advantageous features for subsequent operations and achieves a higher dimensionality reduction rate than those of the other six methods used for comparison. Moreover, DTMU exhibits robust generalization capabilities across various classifiers and dimensional datasets. Notably, the average CPU time for a single run of DTMU is measured at 1.455 s. • This paper offers DTMU, a filter feature selection method enhancing feature quality via unitization for improved properties. • DTMU is notably user-friendly, involving only two straightforward steps. • This paper substantiates, through numerical experiments, that DTMU stands as an advanced and effective method. [ABSTRACT FROM AUTHOR]

Graph polynomials is one of the important research directions in mathematical chemistry. The coefficients of some graph polynomials, such as matching polynomial and permanental polynomial, are related to structural properties of graphs. The Hosoya index of a graph is the sum of the absolute value of all coefficients for the matching polynomial. And the permanental sum of a graph is the sum of the absolute value of all coefficients of the permanental polynomial. In this paper, we characterize the second to sixth minimal Hosoya indices of all bicyclic graphs. Furthermore, using the results, the second to sixth minimal permanental sums of all bicyclic graphs are also characterized. [ABSTRACT FROM AUTHOR]

Shame we are told is as intense as it is unrelenting. Shame we are told, further still, is as contagious as it is transmittable. By fastidiously attending to clinical reports and theoretical depictions of shame's totalizing character, I argue in this paper that we can notice something that has broadly gone unnoticed: shame assumes for itself absolute value. To bear this out, I contrast my view with that of the dominant one: that shame has an instrumental value. I show some limitations of the dominant view by reflecting on the role of shame in psychoanalytic training. The picture that emerges may seem quaintly commonsensical, and even commonplace, but it has, I think, vast clinical implications. I believe that it certainly has the potential to open some new horizons. The arguments for such a bold claim will occupy the concluding section of my paper. [ABSTRACT FROM AUTHOR]

The breeding and selection of resistant varieties is an effective way to minimize wheat Fusarium head blight (FHB) hazards, so it is important to identify and evaluate resistant varieties. The traditional resistance phenotype identification is still largely dependent on time-consuming manual methods. In this paper, the method for evaluating FHB resistance in wheat ears was optimized based on the fusion feature wavelength images of the hyperspectral imaging system and the Faster R-CNN algorithm. The spectral data from 400-1000 nm were preprocessed by the multiple scattering correction (MSC) algorithm. Three feature wavelengths (553 nm, 682 nm and 714 nm) were selected by analyzing the X-loading weights (XLW) according to the absolute value of the peaks and troughs in different principal component (PC) load coefficient curves. Then, the different fusion methods of the three feature wavelengths were explored with different weight coefficients. Faster R-CNN was trained on the fusion and RGB datasets with VGG16, AlexNet, ZFNet, and ResNet-50 networks separately. Then, the other detection models SSD, YOLOv5, YOLOv7, CenterNet, and RetinaNet were used to compare with the Faster R-CNN model. As a result, the Faster R-CNN with VGG16 was best with the mAP (mean Average Precision) ranged from 97.7% to 98.8%. The model showed the best performance for the Fusion Image-1 dataset. Moreover, the Faster R-CNN model with VGG16 achieved an average detection accuracy of 99.00%, which was 23.89%, 1.21%, 0.75%, 0.62%, and 8.46% higher than SSD, YOLOv5, YOLOv7, CenterNet, and RetinaNet models. Therefore, it was demonstrated that the Faster R-CNN model based on the hyperspectral feature image fusion dataset proposed in this paper was feasible for rapid evaluation of wheat FHB resistance. This study provided an important detection method for ensuring wheat food security. [ABSTRACT FROM AUTHOR]

The distance energy of a connected graph G is the sum of absolute values of the eigenvalues of the distance matrix of G. In this paper, we study how the distance energy of the complete split graph G S (m , n) = K m + K ¯ n changes when an edge is deleted from it. The complete split graph G S (m , n) consists of a clique on m vertices and an independent set on n vertices in which each vertex of the clique is adjacent to each vertex of the independent set. We prove that the distance energy of the complete split graph G S (m , n) always increases when an edge is deleted from it. [ABSTRACT FROM AUTHOR]

A porous anti-reflective coating (P-ARC) with average transmittance in the visible range of 97.9% was fabricated through the sol-gel method, followed by calcination at a relatively low temperature (220 °C) using the porogen of Laureth-5 carboxylic acid via a one-step approach. The results demonstrated the coating had an absolute value that was 7.5% higher than that of bare glass (92%). The prepared porous anti-reflective coating had a refractive index as low as 1.21. The coating remained undamaged during 3M tape stripping tests while maintaining excellent light transmittance. This work presents a film that has good thermal stability, chemical stability, and mechanical stability. [ABSTRACT FROM AUTHOR]

In this paper, we construct a new class of convex functions, so-called generalized n-polynomial p-convex functions. We investigate their algebraic properties and provide some relationships between these functions and other types of convex functions. We establish Hermite–Hadamard (H–H) inequality for the newly defined class of functions. Additionally, we derive refinements of H–H inequality for functions whose first derivatives in absolute value at certain power are generalized n-polynomial p-convex. When p = − 1 , our definition evolves into a new definition for the class of convex functions so-called generalized n-polynomial harmonically convex functions. The results obtained in this study generalize regarding those found in the existing literature. By extending these particular types of inequalities, the objective is to unveil fresh mathematical perspectives, attributes and connections that can enhance the evolution of more resilient mathematical methodologies. This study aids in the progression of mathematical instruments across diverse scientific fields. [ABSTRACT FROM AUTHOR]

The leakage flow has a significant impact on the aerodynamic losses and efficiency of the compressor. This paper investigates the loss mechanism in the tip region based on a high-load cantilevered stator cascade. Firstly, a high-fidelity flow field structure was obtained based on the Enhanced Delay Detached Eddy Simulation (EDDES) method. Subsequently, the Liutex method was employed to study the vortex structures in the tip region. The results indicate the presence of a tip leakage vortex (TLV), passage vortex (PV), and induced vortex (IV) in the tip region. At i = 4 ° , 8 ° , the induced vortex interacts with the PV and low-energy fluid, forming a "three-shape" mixed vortex. Finally, a qualitative and quantitative analysis of the loss sources in the tip flow field was conducted based on the entropy generation rate, and the impact of the incidence on the losses was explored. The loss sources in the tip flow field included endwall loss, blade profile loss, wake loss, and secondary flow loss. At i = 0 ° , the loss primarily originated from the endwall and blade profile, accounting for 40 % and 39 % , respectively. As the incidence increased, the absolute value of losses increased, and the proportion of loss caused by secondary flow significantly increased. At i = 8 ° , the proportion of secondary flow loss reached 47%, indicating the most significant impact. [ABSTRACT FROM AUTHOR]

Codebooks with small maximum cross-correlation amplitudes are used to distinguish the signals from different users in multiple access communication systems in code division. Firstly, this paper studies the Jacobi sums over Galois rings of arbitrary characteristics and completely determines their absolute values. This extends the work by Li et al. (Sci China 56(7):1457–1465, 2013), where the Jacobi sums over some Galois rings with characteristics of a prime square were discussed. It is worth mentioning that the generalization is not trivial, as the Galois rings of arbitrary characteristics have a more complicated structure. Our deterministic construction of codebooks is based on Jacobi sums over Galois rings of arbitrary characteristics, producing asymptotically optimal codebooks for the Welch bound. Finally, compared to the literature, this article proposes for the first time design of codebooks based on Jacobi sums over Galois rings. In addition, the parameters of the presented codebooks are new. [ABSTRACT FROM AUTHOR]

Time series forecasting is an important application of many statistical methods. When it is appropriate to assume that the data may be projected towards the future based on the past history of the dataset, a preliminary examination is usually required to ensure that the data sequence is autocorrelated. This is a quite obvious assumption that has to be made and can be the object of a formal test of hypotheses. The most widely used test is the portmanteau test, i.e., a sum of the squared standardized autocorrelations up to an appropriate maximum lag (the truncation point). The choice of the truncation point is not obvious and may be data-driven exploiting supplementary information, e.g. the largest autocorrelation and the lag where such maximum is found. In this paper, we propose a portmanteau test with a truncation point equal to the lag of the largest (absolute value) estimated autocorrelation. Theoretical and simulation-based comparisons based on size and power are performed with competing portmanteau tests, and encouraging results are obtained. [ABSTRACT FROM AUTHOR]

It is of great significance to explore the flow velocity characteristics of piped cars when they are started under different loads. In this paper, the flow velocity characteristics of the water flow around a piped car when it is started in the straight pipe section are studied through physical experiments. The masses of the piped cars are 1.5 kg, 1.9 kg, and 2.3 kg, respectively. The results show that, with the increase in the load of the pipeline car, the axial flow velocity in the front section increases, the absolute values of radial flow velocity and circumferential flow velocity increase, and the gradient of flow velocity increases. The positive radial flow velocity and negative circumferential flow velocity regions increase, and the distribution of positive and negative radial flow velocities and circumferential flow velocities is obvious. The gradients of axial, radial, and circumferential flow velocities in the annular section all increase, and the contour spacing becomes smaller and more densely distributed. The absolute values of the radial and circumferential flow velocities increase. The regional demarcation of axial flow velocity in the rear section is more obvious, and the average value of axial flow velocity in the high-flow-velocity area behind the vehicle increases. Additionally, the gradient of flow velocity increases. The absolute values of radial velocity and circumferential velocity increase, the gradient of velocity increases, and the velocity distribution is obviously regional. This study supplements and improves the theoretical study of a piped car when it is started and has certain reference value for the research and application of the hydraulic transport technology of the barrel-loading pipeline. [ABSTRACT FROM AUTHOR]

In this paper, we give several numerical radius inequalities for Hilbert space operators by using the Young-type inequalities and the generalization of the Buzano of the Schwarz inequality. These inequalities improve the classical numerical radius inequalities. We also give the upper bound of the numerical radius of 2x2 operator matrices. [ABSTRACT FROM AUTHOR]

Consider a quantum cat map M associated with a matrix A ∈ Sp (2 n , Z) , which is a common toy model in quantum chaos. We show that the mass of eigenfunctions of M on any nonempty open set in the position–frequency space satisfies a lower bound which is uniform in the semiclassical limit, under two assumptions: (1) there is a unique simple eigenvalue of A of largest absolute value and (2) the characteristic polynomial of A is irreducible over the rationals. This is similar to previous work (Dyatlov and Jin in Acta Math 220(2):297–339, 2018; Dyatlov et al. in J Am Math Soc 35(2):361–465, 2022) on negatively curved surfaces and (Schwartz in The full delocalization of eigenstates for the quantized cat map, 2021) on quantum cat maps with n = 1 , but this paper gives the first results of this type which apply in any dimension. When condition (2) fails we provide a weaker version of the result and discuss relations to existing counterexamples. We also obtain corresponding statements regarding semiclassical measures and damped quantum cat maps. [ABSTRACT FROM AUTHOR]

Stochastic adaptive gradient decent algorithms, such as AdaGrad and Adam, are extensively used to train deep neural networks. However, randomly sampling gradient information introduces instability to the learning rates, leading to adaptive methods with poor generalization. To address this issue, the ABNGrad algorithm, which leverages the absolute value operation and the normalization technique, is proposed. More specifically, the absolute value function is first incorporated into the iteration of the second-order moment estimate to ensure that it monotonically increases. Then, the normalization technique is employed to prevent a rapid decrease in the learning rate. In particular, the techniques used in this paper can also be integrated into other existing adaptive algorithms, such as Adam, AdamW, AdaBound, and RAdam, yielding good performance. Additionally, it is shown that ABNGrad can attain the optimal regret bound for solving online convex optimization problems. Finally, many experimental results illustrate the effectiveness of ABNGrad. For a comprehensive exploration of the advantages of the proposed approach and the specifics of its detailed implementation, the readers are referred to the following https://github.com/Wenhan-Jiang/ABNGrad.git [ABSTRACT FROM AUTHOR]

Gabor phase retrieval is the problem of recovering a signal from the absolute values of Gabor transform, which has turned into a very active research area. In the paper, we define a generalized Paley–Wiener space, which is obtained by applying the special affine Fourier transform to L p ([ - B , B ]) (2 ≤ p ≤ ∞) and provide the uniqueness of the Gabor phase retrieval in the generalized Paley–Wiener space. When the window function ψ is the inverse special affine Fourier transform of ϕ = 2 1 4 e - π x 2 , we show that every signal in the generalized Paley–Wiener space can be uniquely recovered, up to a global sign, from its the magnitudes of Gabor measurement sampled on a rectangular lattice. Recently, Grohs, Liehr and Wellershoff studied the Gabor phase retrieval problems in the conventional Paley–Wiener space. The paper extends their results to the generalized Paley–Wiener space. Since the generalized Paley–Wiener space includes a broader class of signals, our results expand the applied range of the Gabor phase retrieval. [ABSTRACT FROM AUTHOR]

Micromixers play a crucial role as essential components in microfluidic analysis systems. This paper introduces a novel micromixer designed by harnessing electrokinetic vortices arising on the surface of a Janus droplet within a microchannel. The Janus droplet is characterized by different polarities of charges on its two sides (upstream part and downstream part). In the presence of a direct current electric field, the droplet's surface generates electroosmotic flows in opposite directions, resulting in the formation of vortices and facilitating solution mixing. Results from numerical simulations suggest that a better mixing performance of the micromixer is associated with both a higher absolute value of the zeta potential ratio between the downstream and upstream surfaces of the Janus droplet and a larger downstream surface area. Additionally, this study reveals that microchannel dimensions significantly influence the performance of the micromixer. Smaller microchannel widths and heights correspond to a larger mixing index for the micromixer. The micromixer presented in this study features a simple structure, easy fabrication, and holds promising application potential. [ABSTRACT FROM AUTHOR]

Deep learning is widely utilized to acquire predictive models for mobile crowdsensing systems (MCSs). These models significantly improve the availability and performance of MCSs in real-world scenarios. However, training these models requires substantial data resources, rendering them valuable to their owners. Numerous protection schemes have been proposed to mitigate potential economic loss arising from legal issues pertaining to model copyright. Although capable of providing copyright verification, these schemes either compromise the model utility or prove ineffective against adversarial attacks. Additionally, the privacy concern surrounding copyright verification is noteworthy, given the increasing privacy concerns among model owners. This paper introduces a privacy-preserving testing framework for copyright protection (PTFCP) comprising multiple protocols. Our protocols adhere to the two-cloud server model, where the owner and the suspect transmit their model output to non-colluding servers for evaluating model similarity through the public-key cryptosystem with distributed decryption (PCDD) and garbled circuits. Additionally, we have developed novel techniques to enable secure differentiation for absolute values. Our experiments in real-world datasets demonstrate that our protocols in the PTFCP successfully operate under numerous copyright violation scenarios, such as finetuning, pruning, and extraction. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to present new q-parametrized Hermite–Hadamard-like type integral inequalities for functions whose third quantum derivatives in absolute values are s-convex and  (α , m) -convex, respectively. Two new q-integral identities are presented for three time q-differentiable functions. These lemmas are used like basic elements in our proofs, along with several important tools like q-power mean inequality, and q-Holder's inequality. In a special case, a non-trivial example is considered for a specific parameter and this case illustrates the investigated results. We make links between these findings and several previous discoveries from the literature. [ABSTRACT FROM AUTHOR]

A typo in the paper [M. Hladík, SIAM J. Matrix Anal. Appl., 44 (2023), pp. 175-195] is corrected. [ABSTRACT FROM AUTHOR]

This paper presents a cost-effective and efficient closed-loop calibration method to enhance the absolute positioning accuracy of industrial robots. The method utilizes an economical and highly accurate set of simple measurement devices, including a device mounted on the robot's end effector and a spherical constraint device positioned within the robot's workspace. A novel local area measurement method is employed for the spherical constraint device, effectively converting position errors into the errors in the sphere center position of the constraint device. Furthermore, the error model considers both kinematic parameter deviations of the robot itself as well as those of the measurement device, along with non-kinematic errors caused by link self-weight. The closed-loop calibration model relies on position constraints, enabling identification and compensation of all error parameters using Levenberg Marquardt method after substituting measured data. The effectiveness of this proposed method is demonstrated through simulation and experimentation. In simulations, average position error reduces from 8.249 mm to 0.8384 mm, while absolute mean difference in sphere center positions obtained using our measurement equipment decreases from 1.206 mm to 0.1027 mm. Significant reductions in both position error and difference in sphere center position are indicated after calibration. This proves that the absolute mean value of the sphere center position difference can be used as the basis for judging the size of the robot's end position error. Experimental results show that absolute mean difference in sphere center position decreases from 0.4319 mm to 0.02869 mm, leading to substantial improvement in overall positioning accuracy. • Calibration model incorporates both kinematic and non-kinematic deviation. • Local area measurement data effectively reflects the robot's end position error. • Closed-loop calibration method exhibits robustness in the presence of noise. [ABSTRACT FROM AUTHOR]