bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of the Technical Condition of High-Voltage Insulators during Operation
Authors: Ivanov Dmitry , Golenishchev-Kutuzov Aleksandr , Sadykov Marat , Yaroslavsky Danil , Galieva Tatyana
Published: November 2022

During the operation process of high-voltage insulators, the characteristics of assessing their technical state are evaluated by using remote contactless monitoring and by subsequent forecasting of their residual life based on the developed set of diagnostic parameters of critical defects. Special attention is paid to the challenges of the practical application for remote contactless monitoring of high-voltage insulators’ current operating state. Measurements of characteristics for partial discharges on high-voltage insulators with various types of critical defects taken by electromagnetic and acoustic sensors are described. Based on the measurements, it was found that the unusual properties of the PD begin to manifest themselves starting from the intensities q ≥ 1.5–2 nC, and their maximum intensity can reach 5–7 nC. Up to PD intensities q ≤ 3 nC, most parameters of PD characteristics measured by electromagnetic and acoustic sensors correspond with an accuracy of 70–90%. It was found that for small defects with sizes d ≤ 300 μm in HVI, the PD intensity does not exceed 100 pC and depends little on the size of the defect. However, with an increase in the size of defects above 0.4–0.6 mm, a sharp rise in the intensity of the emerging VLPD begins.
A Novel Computational-Based Visual Brand Identity (CbVBI) Product Design Methodology
Authors: Manavis Athanasios , Tzotzis Anastasios , Tsagaris Apostolos , Kyratsis Panagiotis
Published: November 2022

Product design is a promising field for the application of new technologies and methodologies emerging from the digital evolution of Industry 4.0. A great number of tools have been developed in order to accentuate the use of modern Computer-Aided Design (CAD) systems and computational design techniques for design customization in product applications. The present paper deals with the development of two different applications for designing furniture based on the Computational-based Visual Brand Identity (CbVBI) design methodology. For the first case study, the Application Programming Interface (API) SolidworksTM (VBA event-driven programming language) is used. The second case study focuses on the visual programming language of GrasshopperTM, which is incorporated within Rhinoceros3DTM. The proposed case studies offer a great deal of flexibility in both design and manufacturing, while many design alternatives could become available in a very short period.
A Review of Lightweight Design for Space Mirror Core Structure: Tradition and Future
Authors: Zhang Changhao , Li Zongxuan
Published: November 2022

With the continuous improvement of the imaging quality requirement of the space optical system, the large-aperture mirror becomes the research focus. However, the increase of the aperture will increase the whole weight which results in high launch cost and degrades the mirror surface figure accuracy. Therefore, the lightweight design method of the mirror structure is of great importance. In recent years, many space telescope system schemes have demonstrated the progress of the structural lightweight design of mirrors, such as Spitzer, SOFIA, JWST, etc. This article reviews the main content and innovations of the research on the structural designs of mirrors including conventional machining designs and topology optimization structures. Meanwhile, some emerging designs (e.g., lattices and Voronoi structures) considering additive manufacturing (AM) are also introduced. Several key elements of different structural design approaches for lightweight mirrors are discussed and compared, such as material, lightweight ratio, design methods, surface figure, etc. Finally, future challenges, trends, and prospects of lightweight design for mirrors are discussed. This article provides a reference for further related research and engineering applications.
Residual-Electrical-Endurance Prediction of AC Contactor Based on CNN-GRU
Authors: Liu Shuxin , Gao Shuyu , Peng Shidong , Liu Yang , Li Jing
Published: November 2022

AC contactors are used frequently in various low-voltage control lines, so remaining-life prediction for them can significantly improve the operational reliability of power control systems. To address the problem that the existing AC contactor remaining-life prediction methods do not make full use of the correlation between previous and later states in the degradation process, a CNN-GRU (convolutional neural network-gated recurrent unit) method for AC-contactor remaining-life prediction is proposed. Firstly, the entire cycle of an AC contactor’s degradation data is obtained through a whole-life test, from which the characteristic parameters that effectively reflect the operating states of the contactor are extracted; secondly, neighborhood component analysis (NCA) and maximal information coefficient (MIC) are used to eliminate the redundant information of multidimensional parameters in order to select the optimal feature subset; and then, CNN is used to compress the feature dimension and mine the regular information between the features, so as to extract the effective feature vectors; finally, taking the AC contactor remaining electrical life as a long time sequence issue, time-series accurate prediction is performed using GRU. It is verified that this model is better than RNN (recurrent neural network), LSTM (long short-term memory) and GRU models in prediction, with an effective accuracy of 96.63%, which effectively supports the feasibility of time-series prediction in the field of the remaining-life prediction of electrical devices.
In Situ Ultrasonic Testing for Wire Arc Additive Manufacturing Applications
Authors: Lopez Ana Beatriz , Sousa José Pedro , Pragana João P. M. , Bragança Ivo M. F. , Santos Telmo G. , Silva Carlos M. A.
Published: November 2022

In this paper, we present a non-destructive testing (NDT) technique based on in situ detection of defects up to 100 °C by ultrasonic testing (UT) during construction of parts by a metal additive manufacturing technology known as wire arc additive manufacturing (WAAM). The proposed technique makes use of interlayer application of commercial solder flux to serve as coupling medium for in situ inspection using a special-purpose UT probe. The experimental work was carried out in deposited ER5356 aluminum straight walls following a threefold structure. First, characterization tests with geometrically similar walls with and without interlayer application of solder flux highlight its neutrality, with no effect on the chemical, metallurgical and mechanical properties of the walls. Secondly, UT tests on walls at temperatures ranging from room temperature to 100 °C demonstrate the satisfactory performance of the solder flux as a coupling medium, with little to no soundwave amplitude losses or noise. Finally, acoustic attenuation, impedance and transmission estimations highlight the effectiveness of the proposed technique, establishing a basis for the future development of automated NDT systems for in situ UT of additive manufacturing processes.
Congruence for Lattice Path Models with Filter Restrictions and Long Steps
Authors: Solovyev Dmitry
Published: November 2022

We derive a path counting formula for a two-dimensional lattice path model with filter restrictions in the presence of long steps, source and target points of which are situated near the filters. This solves the problem of finding an explicit formula for multiplicities of modules in tensor product decomposition of T(1)⊗N for Uq(sl2) with divided powers, where q is a root of unity. Combinatorial treatment of this problem calls for the definition of congruence of regions in lattice path models, properties of which are explored in this paper.
The Analytical Solutions of the Stochastic mKdV Equation via the Mapping Method
Authors: Mohammed Wael W. , Al-Askar Farah M. , Cesarano Clemente
Published: November 2022

Here, we analyze the (2+1)-dimensional stochastic modified Kordeweg–de Vries (SmKdV) equation perturbed by multiplicative white noise in the Stratonovich sense. We apply the mapping method to obtain new trigonometric, elliptic, and rational stochastic fractional solutions. Because of the importance of the KdV equation in characterizing the behavior of waves in shallow water, the obtained solutions are beneficial in interpreting certain fascinating physical phenomena. We plot our figures in MATLAB and show several 3D and 2D graphical representations to show how the multiplicative white noise affects the solutions of the SmKdV. We show that the white noise around zero stabilizes SmKdV solutions.
Polynomial Automorphisms, Deformation Quantization and Some Applications on Noncommutative Algebras
Authors: Zhang Wenchao , Yavich Roman , Belov-Kanel Alexei , Razavinia Farrokh , Elishev Andrey , Yu Jietai
Published: November 2022

This paper surveys results concerning the quantization approach to the Jacobian Conjecture and related topics on noncommutative algebras. We start with a brief review of the paper and its motivations. The first section deals with the approximation by tame automorphisms and the Belov–Kontsevich Conjecture. The second section provides quantization proof of Bergman’s centralizer theorem which has not been revisited for almost 50 years and formulates several related centralizer problems. In the third section, we investigate a free algebra analogue of a classical theorem of Białynicki-Birula’s theorem and give a noncommutative version of this famous theorem. Additionally, we consider positive-root torus actions and obtain the linearity property analogous to the Białynicki-Birula theorem. In the last sections, we introduce Feigin’s homomorphisms and we see how they help us in proving our main and fundamental theorems on screening operators and in the construction of our lattice Wn-algebras associated with sln, which is by far the simplest known approach concerning constructing such algebras until now.
Modeling the Cognitive Activity of an Individual Based on the Mathematical Apparatus of Self-Oscillatory Quantum Mechanics
Authors: Petukhov Alexandr Yurevich , Petukhov Yury Vasilevich
Published: November 2022

The goal of this research is to design a model of cognitive activity in the human brain. The fundamental component of such a model is the mathematical apparatus of self-oscillating quantum mechanics considered through the theory of information images/representations. Methods. This article provides a brief description of the proposed theory and highlights remarkable similarities between information images/representations and certain elementary particles, in particular—virtual Feynman particles. Following this principle, the human mind is considered as a one-dimensional potential hole with finite walls of different sizes. The internal potential barrier in this model represents the border between consciousness and subconsciousness. The authors carried out parametrization, taking into account the proposed theory. This allowed authors to lay down the foundations of the mathematical apparatus, viewing the proposed model both from the standpoint of classical quantum mechanics and through the mathematical apparatus of self-oscillatory quantum mechanics. The findings could open a way to the prediction of certain cognitive functions of the human brain. Additionally, the authors formulated the equation, which describes the state function of the information image during the cognitive activity of an individual. Conclusions. The key outcome of this research are the primary calculations of the state functions of information images/representations on the computer model, as well as the patterns of movement of the information image into and out of the human consciousness.
Nonlinear Hammerstein System Identification: A Novel Application of Marine Predator Optimization Using the Key Term Separation Technique
Authors: Mehmood Khizer , Chaudhary Naveed Ishtiaq , Khan Zeshan Aslam , Cheema Khalid Mehmood , Raja Muhammad Asif Zahoor , Milyani Ahmad H. , Azhari Abdullah Ahmed
Published: November 2022

The mathematical modelling and optimization of nonlinear problems arising in diversified engineering applications is an area of great interest. The Hammerstein structure is widely used in the modelling of various nonlinear processes found in a range of applications. This study investigates the parameter optimization of the nonlinear Hammerstein model using the abilities of the marine predator algorithm (MPA) and the key term separation technique. MPA is a population-based metaheuristic inspired by the behavior of predators for catching prey, and utilizes Brownian/Levy movement for predicting the optimal interaction between predator and prey. A detailed analysis of MPA is conducted to verify the accurate and robust behavior of the optimization scheme for nonlinear Hammerstein model identification.
Early Detection of Parkinson’s Disease Using Fusion of Discrete Wavelet Transformation and Histograms of Oriented Gradients
Authors: Das Himanish Shekhar , Das Akalpita , Neog Anupal , Mallik Saurav , Bora Kangkana , Zhao Zhongming
Published: November 2022

Parkinson’s disease primarily affects people in their later years, and there is no cure for this disease; however, the proper medication of patients can lead to a healthy life. Appropriate care and treatment of Parkinson’s disease can be improved if the disease is detected in its early phase. Thus, there is an urgent need to develop novel methods for early illness detection. With this aim for the early detection of Parkinson’s disease, in this study, we utilized hand-drawn images by Parkinson’s disease patients to effectively reduce the clinical experimental costs for poor people. Initially, discrete wavelet coefficients were extracted for each pattern of images; thereafter, on top of that, histograms of oriented gradient features were also extracted to refine the level of features. Thereafter, the fusion approach-based features were fed to various machine learning algorithms. The proposed work was validated on two different datasets, each of which consisted of various patterns, including spiral, wave, cube, and triangle images. The main contribution of this work is the fusion of two feature extraction techniques, which are histograms of oriented gradient features and discrete wavelet transform coefficients. The extracted features were then provided as input into different machine learning algorithms. In our experiment(s) on two datasets, the results achieved an accuracy of 79.7% and 97.8%, respectively, for all four discrete wavelet transform coefficients. This work demonstrates the utilities of fusion-based features for all four discrete wavelet transformation coefficients to detect Parkinson’s disease, using image processing and machine learning techniques.
Controllability of Stochastic Delay Systems Driven by the Rosenblatt Process
Authors: Almarri Barakah , Wang Xingtao , Elshenhab Ahmed M.
Published: November 2022

In this work, we consider dynamical systems of linear and nonlinear stochastic delay-differential equations driven by the Rosenblatt process. With the aid of the delayed matrix functions of these systems, we derive the controllability results as an application. By using a delay Gramian matrix, we provide sufficient and necessary criteria for the controllability of linear stochastic delay systems. In addition, by employing Krasnoselskii’s fixed point theorem, we present some necessary criteria for the controllability of nonlinear stochastic delay systems. Our results improve and extend some existing ones. Finally, an example is given to illustrate the main results.
Fractal Analytical Solutions for Nonlinear Two-Phase Flow in Discontinuous Shale Gas Reservoir
Authors: Shang Xiaoji , Zhang Zhizhen , Zhang Zetian , Wang J. G. , Zhou Yuejin , Yang Weihao
Published: November 2022

The paths of a two-phase flow are usually non-linear and discontinuous in the production of shale gas development. To research the influence mechanism between shale gas and water, several integer two-phase flow models have been studied but few analytical solutions have been obtained on shale gas and water pressure. This study first developed a local fractional mathematical model for gas and water two-phase flow in shale gas production. The model thus created considers the effects of capillary pressure, the fractal dimension of the flow pipe, and the discontinuity of the flow path. Second, the local fractional traveling wave method and variational iteration method were applied to this model for the development of iterative analytical solutions. Both shale gas and water pressure were analytically derived. Third, the depressurization process of the shale gas and water was analyzed, and a parametric study was conducted to explore the impacts of fractional dimension, entry capillary pressure, and travel wave velocity on shale gas pressure. Finally, our conclusions are drawn, based on the results of these studies.
Steady-State Solutions for MHD Motions of Burgers’ Fluids through Porous Media with Differential Expressions of Shear on Boundary and Applications
Authors: Fetecau Constantin , Rauf Abdul , Qureshi Tahir Mushtaq , Vieru Dumitru
Published: November 2022

Steady-state solutions for two mixed initial-boundary value problems are provided. They describe isothermal MHD steady-state motions of incompressible Burgers’ fluids over an infinite flat plate embedded in a porous medium when differential expressions of shear stress are given on a part of the boundary. The fluid is electrically conductive under the influence of a uniform transverse magnetic field. For the validation of the results, the expressions of the obtained solutions are presented in different forms and their equivalence is graphically proved. All of the obtained results could easily be particularized to give exact solutions for the incompressible Oldroyd-B, Maxwell, second-grade, and Newtonian fluids that were performing similar motions. For illustration, the solutions corresponding to Newtonian fluids are provided. In addition, as an application, the velocity fields were used to determine the time required to reach the steady or permanent state for distinct values of magnetic and porous parameters. We found that this time declined with increasing values of the magnetic or porous parameters. Consequently, the steady state for such motions of Burgers’ fluids was earlier reached in the presence of a magnetic field or porous medium.
Multiple Derivative Inversions and Lagrange-Good Expansion Formulae
Authors: Chu Wenchang
Published: November 2022

By establishing new multiple inverse series relations (with their connection coefficients being given by higher derivatives of fixed multivariate analytic functions), we illustrate a general framework to provide new proofs for MacMahon’s master theorem and the multivariate expansion formula due to Good (1960). Further multivariate extensions of the derivative identities due to Pfaff (1795) and Cauchy (1826) will be derived and the generalized multifold convolution identities due to Carlitz (1977) will be reviewed.
Efficient Implementation of SPEEDY Block Cipher on Cortex-M3 and RISC-V Microcontrollers
Authors: Kim Hyunjun , Eum Siwoo , Sim Minjoo , Seo Hwajeong
Published: November 2022

The SPEEDY block cipher family announced at the CHES 2021 shows excellent performance on hardware architectures. Due to the nature of the hardware-friendly design of SPEEDY, the algorithm has low performance for software implementations. In particular, 6-bit S-box and bit permutation operations of SPEEDY are inefficient in software implementations, where it performs word-wise computations. We implemented the SPEEDY block cipher on a 32-bit microcontroller for the first time by applying the bit-slicing techniques. The optimized encryption performance results on ARM Cortex-M3 for SPEEDY-5-192, SPEEDY-6-192, and SPEEDY-7-192 are 65.7, 75.25, and 85.16 clock cycles per byte (i.e., cpb), respectively. It showed better performance than AES-128 constant-time implementation and GIFT constant-time implementation in the same platform. In RISC-V, the performance showed 81.9, 95.5, and 109.2 clock cycles per byte, which outperformed the previous works. Finally, we conclude that SPEEDY can show efficient software implementation on low-end embedded environments.
Novel Formulae of Certain Generalized Jacobi Polynomials
Authors: Abd-Elhameed Waleed Mohamed
Published: November 2022

The main goal of this article is to investigate theoretically a kind of orthogonal polynomials, namely, generalized Jacobi polynomials (GJPs). These polynomials can be expressed as certain combinations of Legendre polynomials. Some basic formulas of these polynomials such as the power form representation and inversion formula of these polynomials are first introduced, and after that, some interesting formulas concerned with these polynomials are established. The formula of the derivatives of the moments of these polynomials is developed. As special cases of this formula, the moment and high-order derivative formulas of the GJPs are deduced. New expressions for the high-order derivatives of the GJPs, but in terms of different symmetric and non-symmetric polynomials, are also established. These expressions lead to some interesting connection formulas between the GJPs and some various polynomials.
Bifurcation and Multiplicity of Solutions of the Navier–Stokes Equations in Driven Semi-Elliptical Cavity Flow
Authors: Erturk Ercan , Allahviranloo Tofigh
Published: November 2022

In this paper, bifurcations in the solution of the Navier–Stokes equations are studied and multiple solutions of the driven semi-elliptical cavity flow are presented. The two-dimensional steady incompressible driven viscous flow in a semi-elliptical cavity is solved numerically. To this end, the problem is formulated using an elliptic coordinate system that transforms the geometry conformally and provides a body fitted coordinate system. The presented results show that above a bifurcation Reynolds number the solution of the governing flow equations bifurcates and there exist multiple solutions for a particular Reynolds number when the aspect ratio of the semi-elliptical cavity geometry is 0.26 ⩽D⩽ 0.8. The bifurcation Reynolds numbers for different aspect ratios and also multiple solutions at different Reynolds numbers are presented in detail.
On Reliability Function of a k-out-of-n System with Decreasing Residual Lifetime of Surviving Components after Their Failures
Authors: Rykov Vladimir , Ivanova Nika , Kozyrev Dmitry , Milovanova Tatyana
Published: November 2022

We consider the reliability function of a k-out-of-n system under conditions that failures of its components lead to an increase in the load on the remaining ones and, consequently, to a change in their residual lifetimes. Development of models able to take into account that failures of a system’s components lead to a decrease in the residual lifetime of the surviving ones is of crucial significance in the system reliability enhancement tasks. This paper proposes a novel approach based on the application of order statistics of the system’s components lifetime to model this situation. An algorithm for calculation of the system reliability function and two moments of its uptime has been developed. Numerical study includes sensitivity analysis for special cases of the considered model based on two real-world systems. The results obtained show the sensitivity of system’s reliability characteristics to the shape of lifetime distribution, as well as to the value of its coefficient of variation at a fixed mean.
Improved G-Optimal Designs for Small Exact Response Surface Scenarios: Fast and Efficient Generation via Particle Swarm Optimization
Authors: Walsh Stephen J. , Borkowski John J.
Published: November 2022

G-optimal designs are those which minimize the worst-case prediction variance. Thus, such designs are of interest if prediction is a primary component of the post-experiment analysis and decision making. G-optimal designs have not attained widespread use in practical applications, in part, because they are difficult to compute. In this paper, we review the last two decades of algorithm development for generating exact G-optimal designs. To date, Particle Swarm Optimization (PSO) has not been applied to construct exact G-optimal designs for small response surface scenarios commonly encountered in industrial settings. We were able to produce improved G-optimal designs for the second-order model and several sample sizes under experiments with K=1,2,3,4, and 5 design factors using an adaptation of PSO. Thereby, we publish updated knowledge on the best-known exact G-optimal designs. We compare computing cost/time and algorithm efficacy to all previous published results including those generated by the current state-of-the-art (SOA) algorithm, the G(Iλ)-coordinate exchange. PSO is hereby demonstrated to produce better designs than the SOA at commensurate cost. In all, the results of this paper suggest PSO should be adopted by more practitioners as a tool for generating exact optimal designs.
Numerical Coefficient Reconstruction of Time-Depending Integer- and Fractional-Order SIR Models for Economic Analysis of COVID-19
Authors: Georgiev Slavi , Vulkov Lubin
Published: November 2022

In the present work, a fractional temporal SIR model is considered. The total population is divided into three compartments—susceptible, infected and removed individuals. It generalizes the classical SIR model and consists of three coupled time-fractional ordinary differential equations (ODEs). The fractional derivative is introduced to account for the subdiffusion process of confirmed, cured and deceased people dynamics. Although relatively basic, the model is robust and captures the real dynamics, helped by the memory property of the fractional system. In the paper, the issue of an adequate model reconstruction is addressed, and a coefficient identification inverse problem is solved; in particular, the transition and recovering rates, varying in time, are recovered. A least-squares cost functional is minimized for solving the problem. The time-dependent parameters are reconstructed with an iterative predictor–corrector algorithm. Its application is demonstrated via tests with synthetic and real data. What is more, an approach for economic impact assessment is proposed.
An Open Scattering Model in Polymerized Quantum Mechanics
Authors: Giesel Kristina , Kobler Michael
Published: November 2022

We derive a quantum master equation in the context of a polymerized open quantum mechanical system for the scattering of a Brownian particle in an ideal gas environment. The model is formulated in a top-down approach by choosing a Hamiltonian with a coupling between the system and environment that is generally associated with spatial decoherence. We extend the existing work on such models by using a non-standard representation of the canonical commutation relations, inspired by the quantization procedure applied in loop quantum gravity, which yields a model in which position operators are replaced by holonomies. The derivation of the master equation in a top-down approach opens up the possibility to investigate in detail whether the assumptions, usually used in such models in order to obtain a tractable form of the dissipator, hold also in the polymerized case or whether they need to be dropped or modified. Furthermore, we discuss some physical properties of the master equation associated to effective equations for the expectation values of the fundamental operators and compare our results to the already existing models of collisional decoherence.
Preprocessing of Spectroscopic Data Using Affine Transformations to Improve Pattern-Recognition Analysis: An Application to Prehistoric Lithic Tools
Authors: Esquivel Francisco Javier , Esquivel José Antonio , Morgado Antonio , Romero-Béjar José L. , Moral Luis F. García del
Published: November 2022

The analysis of spectral reflectance data is an important tool for obtaining relevant information about the mineral composition of objects and has been used for research in chemistry, geology, biology, archaeology, pharmacy, medicine, anthropology, and other disciplines. In archaeology, the use of spectroscopic data allows us to characterize and classify artifacts and ecofacts, to analyze patterns, and to study the exchange of materials, etc., as well as to explain some properties, such as color or post-depositional processes. The spectroscopic data are of the so-called “big data” type and must be analyzed using multivariate statistical techniques, usually principal component analysis and cluster analysis. Although there are different transformations of the raw data, in this paper, we propose preprocessing by means of an affine transformation. From a mathematical point of view, this process modifies the values of reflectance for each spectral signature scaling them into a [0, 1] interval using minimum and maximum values of reflectance, thus highlighting the features of spectral curves. This method optimizes the characteristics of amplitude and shape, reduces the influence of noise, and improves results by highlighting relevant features as peaks and valleys that may remain hidden using the raw data. This methodology has been applied to a case study of prehistoric chert (flint) artifacts retrieved in archaeological excavations in the Andévalo area located in the Archaeological Museum of Huelva (Huelva, Andalusia). The use of transformed data considerably improves the results obtained with raw data, highlighting the peaks, valleys, and the shape of spectral signatures.
Is Catalan’s Constant Rational?
Authors: Reynolds Robert , Stauffer Allan
Published: November 2022

This paper employs a contour integral method to derive and evaluate the infinite sum of the Euler polynomial expressed in terms of the Hurwitz Zeta function. We provide formulae for several classes of infinite sums of the Euler polynomial in terms of the Riemann Zeta function and fundamental mathematical constants, including Catalan’s constant. This representation of Catalan’s constant suggests it could be rational.
Bounds for the Rate of Convergence in the Generalized Rényi Theorem
Authors: Korolev Victor
Published: November 2022

In the paper, an overview is presented of the results on the convergence rate bounds in limit theorems concerning geometric random sums and their generalizations to mixed Poisson random sums, including the case where the mixing law is itself a mixed exponential distribution. The main focus is on the upper bounds for the Zolotarev ζ-metric as the distance between the pre-limit and limit laws. New results are presented that extend existing estimates of the rate of convergence of geometric random sums (in the well-known Rényi theorem) to a considerably more general class of random indices whose distributions are mixed Poisson, including generalized negative binomial (e.g., Weibull-mixed Poisson), Pareto-type (Lomax)-mixed Poisson, exponential power-mixed Poisson, Mittag-Leffler-mixed Poisson, and one-sided Linnik-mixed Poisson distributions. A transfer theorem is proven that makes it possible to obtain upper bounds for the rate of convergence in the law of large numbers for mixed Poisson random sums with mixed exponential mixing distribution from those for geometric random sums (that is, from the convergence rate estimates in the Rényi theorem). Simple explicit bounds are obtained for ζ-metrics of the first and second orders. An estimate is obtained for the stability of representation of the Mittag-Leffler distribution as a geometric convolution (that is, as the distribution of a geometric random sum).
Ethyl Acetate Extract of Marine Algae, Halymenia durvillei, Provides Photoprotection against UV-Exposure in L929 and HaCaT Cells
Authors: Kraokaew Pichnaree , Manohong Preeyanuch , Prasertsuksri Prachayaporn , Jattujan Prapaporn , Niamnont Nakhon , Tamtin Montakan , Sobhon Prasert , Meemon Krai
Published: November 2022

Halymenia durvillei is a red alga distributed along the coasts of Southeast Asian countries including Thailand. Previous studies have shown that an ethyl acetate fraction of H. durvillei (HDEA), containing major compounds including n-hexadecanoic acid, 2-butyl-5-hexyloctahydro-1H-indene, 3-(hydroxyacetyl) indole and indole-3-carboxylic acid, possesses high antioxidant and anti-lung cancer activities. The present study demonstrated that HDEA could protect mouse skin fibroblasts (L929) and human immortalized keratinocytes (HaCaT) against photoaging due to ultraviolet A and B (UVA and UVB) by reducing intracellular reactive oxygen species (ROS) and expressions of matrix metalloproteinases (MMP1 and MMP3), as well as increasing Nrf2 nuclear translocation, upregulations of mRNA transcripts of antioxidant enzymes, including superoxide dismutase (SOD), heme oxygenase (HMOX) and glutathione S-transferase pi1 (GSTP1), and procollagen synthesis. The results indicate that HDEA has the potential to protect skin cells from UV irradiation through the activation of the Nrf2 pathway, which leads to decreasing intracellular ROS and MMP production, along with the restoration of skin collagen.
Eremophilane-Type Sesquiterpenes from a Marine-Derived Fungus Penicillium Copticola with Antitumor and Neuroprotective Activities
Authors: Zhang Jianping , Liu Dong , Fan Aili , Huang Jian , Lin Wenhan
Published: November 2022

Chemical examination of a marine sponge-associated Penicillium copticola fungus resulted in the isolation of ten undescribed eremophilanes, namely copteremophilanes A–J (1–10), along with two new glycosides, 5-glycopenostatin F (11) and 5-glucopenostatin I (12). Their structures were determined by extensive spectroscopic data, in association with ECD data and chemical conversions for configurational assignments. Analogs 1, 2, and 10 represent a group of uncommon skeletons of eremophilanes with an aromatic ring and a methyl migration from C-5 to C-9, and analogs 11 and 12 are characteristic of a PKS scaffold bearing a glucose unit. The incorporation of a chlorinated phenylacetic unit in 3–9 is rarely found in nature. Analog 7 showed neuroprotective effect, whereas 8 exhibited selective inhibition against human non-small cell lung cancer cells (A549). This study enriched the chemical diversity of eremophilanes and extended their bioactivities to neuroprotection.
Depression in Rheumatoid Arthritis: A Narrative Review—Diagnostic Challenges, Pathogenic Mechanisms and Effects
Authors: Ionescu Cătălina-Elena , Popescu Claudiu Costinel , Agache Mihaela , Dinache Georgiana , Codreanu Cătălin
Published: November 2022

Depression is one of the most frequent comorbidities in rheumatoid arthritis (RA); it takes an important toll on the quality of life of these patients and also leads to a decrease in life expectancy. The current article is a narrative review on depression in RA, with the objective to emphasize and raise awareness on the high prevalence, pathogenic mechanisms, and effects that depression has on RA patients. In RA, the prevalence of depression has been shown to be 2 to 3 times higher than in the general population, with a meta-analysis reporting that 16.8% of RA patients have a major depressive disorder. Future studies are needed to determine the most accurate self-reported depression questionnaires and their ideal threshold for defining depression as compared to diagnostic interview as gold-standard for patients with RA to allow better comparisons across studies. The pathogenesis of depression remains to be fully understood, but recent specialty literature suggests that immune-mediated processes are involved and that there are similarities between the neural networks recruited in inflammation and those implicated in the pathophysiology of depression. Depression in patients with RA is associated with poor long-term outcomes. Multiple studies have shown that depression in RA is associated with increased pain, fatigue, and physical disability. It alters treatment compliance, causes more comorbidities, and leads to higher mortality, partly through increased suicide risk. Depression in RA also increases health service utilization and healthcare costs directly through hospitalization, but also indirectly through loss of work productivity. Assessing depression could be a significant psychomarker of rheumatological outcome in RA.
Determination of the Predictors with the Greatest Influence on Walking in the Elderly
Authors: Chung Chul-Min , Shin Sunghoon , Lee Yungon , Lee Do-Youn
Published: November 2022

Background and Objectives: Previous studies have revealed that independent variables (lower extremity strength, postural control ability, and body composition) influence gait performance and variability, but the difference in the relative influence between these variables is unclear. Hence, this study determines the variable that is the most influential predictor of gait performance and variability among potential independent variables in the elderly. Materials and Methods: Seventy-eight subjects aged ≥60 years participated. For each subject, the gait variables and lower extremity muscle strength were measured using an accelerometer worn on both feet during a 6-minute walk and a manual force sensor, respectively. The static balance ability was measured through two force plates, and the body composition was measured by applying bioelectrical impedance analysis. Linear regression analyses were performed stepwise to determine whether these variables affect gait performance and variability. Results: After adjusting for sex and gait performance, the ankle strength, body fat mass, mean velocity in the medial–lateral direction, ankle plantar flexion strength, and girth were predictors of gait speed dorsiflexion, gait performance, swing width of the gait performance, walking speed, and gait variability, respectively. Conclusions: Overall, gait performance in the elderly is related to muscle strength, postural control, and body composition in a complex manner, but gait variability appears to be more closely related to ankle muscle strength. This study provides further evidence that muscle strength is important in motor function and stability.
Custom-Made Implants in Ankle Bone Loss: A Retrospective Assessment of Reconstruction/Arthrodesis in Sequelae of Septic Non-Union of the Tibial Pilon
Authors: Caravelli Silvio , Ambrosino Giuseppe , Vocale Emanuele , Di Ponte Marco , Puccetti Giulia , Perisano Carlo , Greco Tommaso , Rinaldi Vito Gaetano , Marcheggiani Muccioli Giulio Maria , Zaffagnini Stefano , Mosca Massimiliano
Published: November 2022

Background and Objectives: Treating segmental tibial and ankle bone loss after radical surgery for chronic osteomyelitis is one of the most challenging problems encountered by orthopaedic surgeons. Open tibia and ankle fractures occur with an incidence of 3.4 per 100,000 and 1.6 per 100,000, respectively, and there is a high propensity of developing fracture-related infection with associated chronic osteomyelitis in patients. Segmental tibial and ankle bone loss have recently received new and improved treatments. Materials and Methods: Above all, 3D printing allows for the customization of implants based on the anatomy of each patient, using a personalized process through the layer-by-layer deposition of materials. Results: This article presents different cases from the authors’ experience. Specifically, four patients suffered tibia and ankle fractures and after radical surgery for chronic osteomyelitis combined with high-performance antibiotic therapy underwent ankle reconstruction/arthrodesis with custom-made tibial spacers. Conclusions: Thanks to 3D-printed patient-specific devices, it is possible to perform surgical procedures that, for anatomical reasons, would have been impossible otherwise. Moreover, an improvement in overall functionality and an important reduction in pain were shown in the last follow-up in all patients.
Carbonic Anhydrase IX as a Marker of Disease Severity in Obstructive Sleep Apnea
Authors: Geçkil Ayşegül Altıntop , Kıran Tuğba Raika , Berber Nurcan Kırıcı , Otlu Önder , Erdem Mehmet , İn Erdal
Published: November 2022

Background and Objectives: Carbonic anhydrase (CA) enzymes are a family of metalloenzymes that contain a zinc ion in their active sites. CA enzymes have been implied in important situations such as CO2 transport, pH regulation, and oncogenesis. CA-IX is a transmembrane glycoprotein and stimulates the expression of hypoxia-inducible factor-1 (HIF-1) CA-IX. This study aimed to determine serum CA-IX levels in OSA patients in whom intermittent hypoxia is important and to investigate the relationship between serum CA-IX levels and disease severity. Materials and Methods: The study included 88 people who applied to Malatya Turgut Özal University Training and Research Hospital Sleep Disorders Center without a history of respiratory disease, malignancy, and smoking. Patients were divided into three groups: control (AHI < 5, n = 31), mild–moderate OSA (AHI = 5–30, n = 27) and severe OSA (AHI > 30, n = 30). The analysis of the data included in the research was carried out with the SPSS (IBM Statistics 25, NY, USA). The Shapiro–Wilk Test was used to check whether the data included in the study had a normal distribution. Comparisons were made with ANOVA in multivariate groups and the t-test in bivariate groups. ANCOVA was applied to determine the effect of the CA-IX parameter for OSA by controlling the effect of independent variables. The differentiation in CA-IX and OSA groups was analyzed regardless of BMI, age, gender, and laboratory variables. ROC analysis was applied to determine the parameter cut-off point. Sensitivity, specificity, and cut-off were calculated, and the area under the curve (AUC) value was calculated. Results: Serum CA-IX levels were 126.3 ± 24.5 pg/mL in the control group, 184.6 ± 59.1 pg/mL in the mild–moderate OSA group, and 332.0 ± 39.7 pg/mL in the severe OSA group. Serum CA-IX levels were found to be higher in the severe OSA group compared to the mild–moderate OSA group and control group and higher in the mild–moderate OSA group compared to the control group (p < 0.001, p < 0.001, p < 0.001, respectively). In addition, a negative correlation between CA-IX and minimum SaO2 and mean SaO2 (r = –0.371, p = 0.004; r = –0.319, p = 0.017, respectively). A positive correlation between CA-IX and desaturation index (CT90) was found (r = 0.369, p = 0.005). A positive correlation was found between CA-IX and CRP (r = 0.340, p = 0.010). When evaluated by ROC curve analysis, the area under the curve (AUC) value was determined as 0.940 (95% CI 0.322–0.557; p < 0.001). When the cut-off value for CA-IX was taken as 254.5 pg/mL, it was found to have 96.7% sensitivity and 94.8% specificity in demonstrating severe OSA. Conclusions: Our study found that serum CA-IX value was higher in OSA patients than in control patients, and this elevation was associated with hypoxemia and inflammation. CA-IX value can be a fast, precise, and useful biomarker to predict OSA.
Antidiabetic Actions of Ethanol Extract of Camellia sinensis Leaf Ameliorates Insulin Secretion, Inhibits the DPP-IV Enzyme, Improves Glucose Tolerance, and Increases Active GLP-1 (7–36) Levels in High-Fat-Diet-Fed Rats
Authors: Ansari Prawej , Hannan J. M. A. , Choudhury Samara T. , Islam Sara S. , Talukder Abdullah , Seidel Veronique , Abdel-Wahab Yasser H. A.
Published: November 2022

Camellia sinensis (green tea) is used in traditional medicine to treat a wide range of ailments. In the present study, the insulin-releasing and glucose-lowering effects of the ethanol extract of Camellia sinensis (EECS), along with molecular mechanism/s of action, were investigated in vitro and in vivo. The insulin secretion was measured using clonal pancreatic BRIN BD11 β cells, and mouse islets. In vitro models examined the additional glucose-lowering properties of EECS, and 3T3L1 adipocytes were used to assess glucose uptake and insulin action. Non-toxic doses of EECS increased insulin secretion in a concentration-dependent manner, and this regulatory effect was similar to that of glucagon-like peptide 1 (GLP-1). The insulin release was further enhanced when combined with isobutylmethylxanthine (IBMX), tolbutamide or 30 mM KCl, but was decreased in the presence of verapamil, diazoxide and Ca2+ chelation. EECS also depolarized the β-cell membrane and elevated intracellular Ca2+, suggesting the involvement of a KATP-dependent pathway. Furthermore, EECS increased glucose uptake and insulin action in 3T3-L1 cells and inhibited dipeptidyl peptidase IV (DPP-IV) enzyme activity, starch digestion and protein glycation in vitro. Oral administration of EECS improved glucose tolerance and plasma insulin as well as inhibited plasma DPP-IV and increased active GLP-1 (7–36) levels in high-fat-diet-fed rats. Flavonoids and other phytochemicals present in EECS could be responsible for these effects. Further research on the mechanism of action of EECS compounds could lead to the development of cost-effective treatments for type 2 diabetes.
Isolated Effects of Plasma Freezing versus Thawing on Metabolite Stability
Authors: Buchanan Jane L. , Tormes Vaquerano Jovan , Taylor Eric B.
Published: November 2022

Freezing and thawing plasma samples is known to perturb metabolite stability. However, no study has systematically tested how different freezing and thawing methods affect plasma metabolite levels. The objective of this study was to isolate the effects of freezing from thawing on mouse plasma metabolite levels, by comparing a matrix of freezing and thawing conditions through 10 freeze–thaw cycles. We tested freezing with liquid nitrogen (LN2), at −80 °C, or at −20 °C, and thawing quickly in room temperature water or slowly on ice. Plasma samples were extracted and the relative abundance of 87 metabolites was obtained via liquid chromatography–mass spectrometry (LC–MS). Observed changes in metabolite abundance by treatment group correlated with the amount of time it took for samples to freeze or thaw. Thus, snap-freezing with LN2 and quick-thawing with water led to minimal changes in metabolite levels. Conversely, samples frozen at −20 °C exhibited the most changes in metabolite levels, likely because freezing required about 4 h, versus freezing instantaneously in LN2. Overall, our results show that plasma samples subjected to up to 10 cycles of LN2 snap-freezing with room temperature water quick-thawing exhibit remarkable metabolomic stability.
The Importance of Microorganisms for Sustainable Agriculture—A Review
Authors: Antoszewski Marcel , Mierek-Adamska Agnieszka , Dąbrowska Grażyna B.
Published: November 2022

In the face of climate change, progressive degradation of the environment, including agricultural land negatively affecting plant growth and development, endangers plant productivity. Seeking efficient and sustainable agricultural techniques to replace agricultural chemicals is one of the most important challenges nowadays. The use of plant growth-promoting microorganisms is among the most promising approaches; however, molecular mechanisms underneath plant–microbe interactions are still poorly understood. In this review, we summarized the knowledge on plant–microbe interactions, highlighting the role of microbial and plant proteins and metabolites in the formation of symbiotic relationships. This review covers rhizosphere and phyllosphere microbiomes, the role of root exudates in plant–microorganism interactions, the functioning of the plant’s immune system during the plant–microorganism interactions. We also emphasized the possible role of the stringent response and the evolutionarily conserved mechanism during the established interaction between plants and microorganisms. As a case study, we discussed fungi belonging to the genus Trichoderma. Our review aims to summarize the existing knowledge about plant–microorganism interactions and to highlight molecular pathways that need further investigation.