bluuebunny/crossref_metadata_2025 huggingface dataset:
Does Resin Cement Type and Cement Preheating Influence the Marginal and Internal Fit of Lithium Disilicate Single Crowns?
Authors: Samy Nourhan , Al-Zordk Walid , Elsherbini Ahmed , Özcan Mutlu , Sakrana Amal Abdelsamad
Published: January 2022

This paper assesses the effect of cement type and cement preheating on the marginal and internal fit of lithium disilicate single crown. Methods: 40 maxillary premolars were selected, restored with lithium disilicate single crowns. Teeth were randomly assigned into four groups (n = 10) based on cement type (Panavia SA or LinkForce) and preheating temperature (25 °C or 54 °C). After fabrication of the restoration, cements were incubated at 25 °C or 54 °C for 24 h, and each crown was cemented to its corresponding tooth. After 24 h, all specimens were thermally aged to (10,000 thermal cycles between 5 °C and 55 °C), then load cycled for 240,000 cycles. Each specimen was then sectioned in bucco-palatal direction and inspected under a stereomicroscope at x45 magnification for marginal and internal fit evaluation. The data were statistically analyzed (significance at p ≤ 0.05 level). Results: At the mid-buccal finish line, mid-buccal wall, palatal cusp, mid-palatal wall, mid-palatal finish line, and palatal margin measuring points, there was a significant difference (p ≤ 0.05) between the lithium disilicate group cemented with Panavia SA at 25 °C and the group cemented with LinkForce at 25 °C, while there was no significant difference (p > 0.05) at the other points. At all measuring points, except at the palatal cusp tip (p = 0.948) and palatal margin (p = 0.103), there was a statistically significant difference (p ≤ 0.05) between the lithium disilicate group cemented with Panavia SA at 54 °C and the group cemented with LinkForce at 54 °C. Regardless of cement preheating, statistically significant differences were found in the buccal cusp tip, central groove, palatal cusp tip, and mid-palatal wall (p ≤ 0.05) in the lithium disilicate group cemented with Panavia SA at 25 °C and 54 °C, as well as the mid-palatal chamfer finish line and palatal margin in the LinkForce group cemented with Panavia SA at 25 °C and 54 °C. At the other measurement points, however, there was no significant difference (p > 0.05). Conclusions: The type of resin cement affects the internal and marginal fit of lithium disilicate crowns. At most measuring points, the cement preheating does not improve the internal and marginal fit of all lithium disilicate crowns.
Rheological Behavior of High-Performance Shotcrete Mixtures Containing Colloidal Silica and Silica Fume Using the Bingham Model
Authors: Yun Kyong Ku , Kim Jong Beom , Song Chang Seok , Hossain Mohammad Shakhawat , Han Seungyeon
Published: January 2022

There have been numerous studies on shotcrete based on strength and durability. However, few studies have been conducted on rheological characteristics, which are very important parameters for evaluating the pumpability and shootability of shotcrete. In those studies, silica fume has been generally used as a mineral admixture to simultaneously enhance the strength, durability, pumpability, and shootability of shotcrete. Silica fume is well-known to significantly increase the viscosity of a mixture and to prevent material sliding at the receiving surface when used in shotcrete mixtures. However, the use of silica fume in shotcrete increases the possibility of plastic shrinkage cracking owing to its very high fineness, and further, silica fume increases the cost of manufacturing the shotcrete mixture because of its cost and handling. Colloidal silica is a new material in which nano-silica is dispersed in water, and it could solve the above-mentioned problems. The purpose of this research is to develop high-performance shotcrete with appropriate levels of strength and workability as well as use colloidal silica for normal structures without a tunnel structure. Thereafter, the workability of shotcrete with colloidal silica (2, 3, and 4%) was evaluated with a particle size of 10 nm and silica fume replacement (4 and 7%) of cement. In this study, an air-entraining agent for producing high-performance shotcrete was also used. The rheological properties of fresh shotcrete mixtures were estimated using an ICAR rheometer and the measured rheological parameters such as flow resistance and torque viscosity were correlated with the workability and shootability. More appropriate results will be focusing on the Bingham model properties such that the main focus here is to compare all data using the Bingham model and its performance. The pumpability, shootability, and build-up thickness characteristics were also evaluated for the performance of the shotcrete. This research mainly focuses on the Bingham model for absolute value because it creates an exact linear line in a graphical analysis, which provides more appropriate results for measuring the shotcrete performance rather than ICAR rheometer relative data.
Blending Colored and Depth CNN Pipelines in an Ensemble Learning Classification Approach for Warehouse Application Using Synthetic and Real Data
Authors: Piratelo Paulo Henrique Martinez , de Azeredo Rodrigo Negri , Yamao Eduardo Massashi , Bianchi Filho Jose Francisco , Maidl Gabriel , Lisboa Felipe Silveira Marques , de Jesus Laercio Pereira , Penteado Neto Renato de Arruda , Coelho Leandro dos Santos , Leandro Gideon Villar
Published: January 2022

Electric companies face flow control and inventory obstacles such as reliability, outlays, and time-consuming tasks. Convolutional Neural Networks (CNNs) combined with computational vision approaches can process image classification in warehouse management applications to tackle this problem. This study uses synthetic and real images applied to CNNs to deal with classification of inventory items. The results are compared to seek the neural networks that better suit this application. The methodology consists of fine-tuning several CNNs on Red–Green–Blue (RBG) and Red–Green–Blue-Depth (RGB-D) synthetic and real datasets, using the best architecture of each domain in a blended ensemble approach. The proposed blended ensemble approach was not yet explored in such an application, using RGB and RGB-D data, from synthetic and real domains. The use of a synthetic dataset improved accuracy, precision, recall and f1-score in comparison with models trained only on the real domain. Moreover, the use of a blend of DenseNet and Resnet pipelines for colored and depth images proved to outperform accuracy, precision and f1-score performance indicators over single CNNs, achieving an accuracy measurement of 95.23%. The classification task is a real logistics engineering problem handled by computer vision and artificial intelligence, making full use of RGB and RGB-D images of synthetic and real domains, applied in an approach of blended CNN pipelines.
Investigation on Unsteady Cavitation Flow and Excited Pressure Fluctuations in Regulating Valve
Authors: Liu Xiumei , He Jie , Xie Yongwei , Li Beibei , Zhang Yujia , Chen Jinsong , Liu Qihang
Published: January 2022

A multi-field synchronous measurement system for the cavitation flow in a regulating valve was established. The system combines a high-speed full-flow field display system with a pressure measurement system to realize the simultaneous acquisition of cavitation shapes and pressure pulsations. Cavitation flow occurs near the throttle orifice, which is obviously a quasi-periodic behavior. The unsteady cavitation flow mainly includes three stages: the growth of the attached cavity, the fracture and shedding of the attached cavity and the growth and collapse of the free cavity. The time evolution of the cavitation behaviors is highly related with excited pressure fluctuations. With the increasing attached cavity area, the corresponding pressure in the flow field decreases slowly. When the attached cavity falls off and develops downstream, the cavity area decreases gradually, and the pressure increases gradually. When the free cavity shrinks and collapses, the pressure in the flow field reaches the peak value. The pressure pulsation and the change of cavity area have the same dominant frequency, around 2000 Hz, at the monitoring point in the upstream, throat and expansion monitoring points. Furthermore, with increasing inlet pressure, the mean and variance values of cavitation area become larger, and the excited pressure fluctuation at each measuring point becomes more intense. The mean value of pulsating pressure at the throat gradually increases, while the pressure in the expansion section presents a downward trend. The variance of pressure pulsation and the maximum pressure also increase gradually with the increase in inlet pressure. The change of cavitation area and the pressure pulsation in the regulating valve complement each other. The results in this paper could provide experimental guidance on optimizing the structure of the valve, inhibiting cavitation occurrence and prolonging the service life of the valve.
Analysis, Design and Experimental Research of a Novel Bilateral Patient Transfer Robot
Authors: Sang Lingfeng , Wang Hongbo , Tian Yu
Published: January 2022

Patient transfer has always been a difficult problem in the hospital. For medical staff, there are problems including high risk of infection, heavy physical labor and low efficiency of transfer; for patients, there are problems including poor comfort and secondary injury. In this paper, a novel bilateral patient transfer robot is investigated and designed. The following tasks are conducted: (1) Based on the process of patient transfer, a transfer model, which consists of two degrees of freedom, is proposed, and the working principle of bilateral patient transfer robot is obtained and analyzed in detail. (2) Force analysis of the patient transfer robot is conducted. The corresponding relationship between the patient comfort and the insertion angle is proposed, and the optimal sizes of mechanical structure are obtained. (3) Based on the theoretical analysis, the mechanical structure and the control system of the robot are designed, and the prototype is manufactured. (4) Experimental research is conducted. The results show that the prototype can complete the required motion performance with a carrying capacity up to 150 kg and patient comfort is excellent. The results of this paper prove that this kind of patient transfer robot has good performance, it can also reduce the burden on medical staff.
Fault-Tolerant Multilevel Converter to Feed a Switched Reluctance Machine
Authors: Pires Vítor Fernão , Cordeiro Armando , Foito Daniel , Pires Armando J.
Published: January 2022

The switched reluctance machine (SRM) is one of the most interesting machines, being adopted for many applications. However, this machine requires a power electronic converter that usually is the most fragile element of the system. Thus, in order to ensure high reliability for this system, it is fundamental to design a power electronic converter with fault-tolerant capability. In this context, a new solution is proposed to give this capability to the system. This converter was designed with the purpose to ensure fault-tolerant capability to two types of switch faults, namely open- and short-circuit. Moreover, apart from this feature, the proposed topology is characterized by a multilevel operation that allows improvement of the performance of the SRM, taking into consideration a wide speed range. Although the proposed solution is presented for an 8/6 SRM, it can be used for other configurations. The operation of the proposed topology will be described for the two modes, fault-tolerant and normal operation. Another aspect that is addressed in this paper is the proposal of fault detection and diagnosis method for this fault-tolerant inverter. It was specifically developed for a multilevel SRM drive. The theoretical assumptions will be verified through two different types of tests, firstly by simulation and secondly by experiments with a laboratory prototype.
Estimation and Mitigation of Unknown Airplane Installation Effects on GPA Diagnostics
Authors: Stenfelt Mikael , Kyprianidis Konstantinos
Published: January 2022

In gas turbines used for airplane propulsion, the number of sensors are kept at a minimum for accurate control and safe operation. Additionally, when data are communicated between the airplane main computer and the various subsystems, different systems may have different constraints and requirements regarding what data transmit. Early in the design process, these parameters are relatively easy to change, compared to a mature product. If the gas turbine diagnostic system is not considered early in the design process, it may lead to diagnostic functions having to operate with reduced amount of data. In this paper, a scenario where the diagnostic function cannot obtain airplane installation effects is considered. The installation effects in question is air intake pressure loss (pressure recovery), bleed flow and shaft power extraction. A framework is presented where the unknown installation effects are estimated based on available data through surrogate models, which is incorporated into the diagnostic framework. The method has been evaluated for a low-bypass turbofan with two different sensor suites. It has also been evaluated for two different diagnostic schemes, both determined and underdetermined. Results show that, compared to assuming a best-guess constant-bleed and shaft power, the proposed method reduce the RMS in health parameter estimation from 26% up to 80% for the selected health parameters. At the same time, the proposed method show the same degradation pattern as if the installation effects were known.
Correlation between the Internal Flow Pattern and the Blade Load Distribution of the Centrifugal Impeller
Authors: Chen Bo , Chen Xiaowu , Zhu Zuchao , Li Xiaojun
Published: January 2022

The blade load distributions reflect the working characteristics of centrifugal impellers, and the vortexes in the impeller channel affect the blade load distribution, but the mechanism of this phenomenon is still unclear. In this study, particle image velocimetry (PIV) was adopted to clarify the correlation between the internal flow pattern and the blade load distribution. The internal flow pattern and the blade load distribution were presented under different working conditions to study the influence of the internal flow pattern on the blade load. Results showed that the vortexes in the flow channel redistributed the blade load. The clockwise vortex made the position of the maximum blade load closer to the outlet, while the counterclockwise vortex had the opposite effect. Meanwhile, the vortexes caused the blade load distribution to be steeper, which reduced energy conversion efficiency. Moreover, the mean absolute flow angle was introduced to explain the mechanism of the effects of vortexes on blade load. The results can be used as a theoretical basis for the design of high-performance impellers.
An Intravascular Catheter Bending Recognition Method for Interventional Surgical Robots
Authors: Wei Wei , Yang Dong , Li Li , Xia Yuxuan
Published: January 2022

Robot-assisted interventional surgery can greatly reduce the radiation received by surgeons during the operation, but the lack of force detection and force feedback is still a risk in the operation which may harm the patient. In those robotic surgeries, the traditional force detection methods may have measurement losses and errors caused by mechanical transmission and cannot identify the direction of the force. In this paper, an interventional surgery robot system with a force detection device is designed and a new force detection method based on strain gauges is proposed to detect the force and infer the bending direction of the catheter in the vessel by using BP neural network. In addition, genetic algorithm is used to optimize the BP neural network, and the error between the calculated results and the actual results is reduced by 37%, which improves the accuracy of catheter bending recognition. Combining this new method with traditional force sensors not only reduces the error caused by the traditional mechanical transmission, but also can detect the bending direction of the catheter in the blood vessel, which greatly improves the safety of the operation.
On the Double Roman Domination in Generalized Petersen Graphs P(5k,k)
Authors: Rupnik Poklukar Darja , Žerovnik Janez
Published: January 2022

A double Roman dominating function on a graph G=(V,E) is a function f:V→{0,1,2,3} satisfying the condition that every vertex u for which f(u)=0 is adjacent to at least one vertex assigned 3 or at least two vertices assigned 2, and every vertex u with f(u)=1 is adjacent to at least one vertex assigned 2 or 3. The weight of f equals w(f)=∑v∈Vf(v). The double Roman domination number γdR(G) of a graph G equals the minimum weight of a double Roman dominating function of G. We obtain closed expressions for the double Roman domination number of generalized Petersen graphs P(5k,k). It is proven that γdR(P(5k,k))=8k for k≡2,3mod5 and 8k≤γdR(P(5k,k))≤8k+2 for k≡0,1,4mod5. We also improve the upper bounds for generalized Petersen graphs P(20k,k).
Vertical Nonlinear Temperature Gradient and Temperature Load Mode of Ballastless Track in China
Authors: Yan Bin , Cheng Ruiqi , Xie Haoran , Zhang Xiangmin
Published: January 2022

In the process of heat exchange with the external environment, the internal temperature of ballastless track structure presents a nonlinear distribution. The vertical temperature gradient will cause repeated warping and deformation of track slab, resulting in mortar layer separation, which will affect driving comfort and track durability. The traditional temperature field analysis method of concrete structure based on thermodynamics has the disadvantages of too many assumptions, difficult parameter selection and too much calculation of energy consumption. In this paper, based on the finite element software ANSYS, the heat exchange was transformed into the boundary condition of heat flux, which was applied to the thermodynamic analysis model to study the nonlinear temperature distribution law of ballastless track. The accuracy of the analysis method was verified by the measured data. On this basis, the regional distribution law of temperature gradient of ballastless track under different geographical coordinates and climatic conditions was studied. By adding a regional adjustment coefficient, the vertical temperature load model of ballastless track suitable for typical areas in China was proposed. The proposed temperature load model makes up for the lack of refinement of climate division and temperature load model in relevant specifications, and has strong engineering application and popularization value.
Algorithmic Differentiation of the MWGS-Based Arrays for Computing the Information Matrix Sensitivity Equations within the Problem of Parameter Identification
Authors: Tsyganov Andrey , Tsyganova Julia
Published: January 2022

The paper considers the problem of algorithmic differentiation of information matrix difference equations for calculating the information matrix derivatives in the information Kalman filter. The equations are presented in the form of a matrix MWGS (modified weighted Gram–Schmidt) transformation. The solution is based on the usage of special methods for the algorithmic differentiation of matrix MWGS transformation of two types: forward (MWGS-LD) and backward (MWGS-UD). The main result of the work is a new MWGS-based array algorithm for computing the information matrix sensitivity equations. The algorithm is robust to machine round-off errors due to the application of the MWGS orthogonalization procedure at each step. The obtained results are applied to solve the problem of parameter identification for state-space models of discrete-time linear stochastic systems. Numerical experiments confirm the efficiency of the proposed solution.
On the Eventually Periodic Continued β-Fractions and Their Lévy Constants
Authors: Xiao Qian , Ma Chao , Wang Shuailing
Published: January 2022

In this paper, we consider continued β-fractions with golden ratio base β. We show that if the continued β-fraction expansion of a non-negative real number is eventually periodic, then it is the root of a quadratic irreducible polynomial with the coefficients in Z[β] and we conjecture the converse is false, which is different from Lagrange’s theorem for the regular continued fractions. We prove that the set of Lévy constants of the points with eventually periodic continued β-fraction expansion is dense in [c, +∞), where c=12logβ+2−5β+12.
Additive Noise Effects on the Stabilization of Fractional-Space Diffusion Equation Solutions
Authors: Mohammed Wael W. , Iqbal Naveed , Botmart Thongchai
Published: January 2022

This paper considers a class of stochastic fractional-space diffusion equations with polynomials. We establish a limiting equation that specifies the critical dynamics in a rigorous way. After this, we use the limiting equation, which is an ordinary differential equation, to approximate the solution of the stochastic fractional-space diffusion equation. This equation has never been studied before using a combination of additive noise and fractional-space, therefore we generalize some previously obtained results as special cases. Furthermore, we use Fisher’s and Ginzburg–Landau equations to illustrate our results. Finally, we look at how additive noise affects the stabilization of the solutions.
An Unconditional Positivity-Preserving Difference Scheme for Models of Cancer Migration and Invasion
Authors: Kolev Mikhail K. , Koleva Miglena N. , Vulkov Lubin G.
Published: January 2022

In this paper, we consider models of cancer migration and invasion, which consist of two nonlinear parabolic equations (one of the convection–diffusion reaction type and the other of the diffusion–reaction type) and an additional nonlinear ordinary differential equation. The unknowns represent concentrations or densities that cannot be negative. Widely used approximations, such as difference schemes, can produce negative solutions because of truncation errors and can become unstable. We propose a new difference scheme that guarantees the positivity of the numerical solution for arbitrary mesh step sizes. It has explicit and fast performance even for nonlinear reaction terms that consist of sums of positive and negative functions. The numerical examples illustrate the simplicity and efficiency of the method. A numerical simulation of a model of cancer migration is also discussed.
Response Times Reconstructor Based on Mathematical Expectation Quotient for a High Priority Task over RT-Linux
Authors: González-Baldovinos Diana L. , Guevara-López Pedro , Cano-Rosas Jose Luis , Valdez-Martínez Jorge Salvador , López-Chau Asdrúbal
Published: January 2022

Every computer task generates response times depending on the computer hardware and software. The response times of tasks executed in real-time operating systems such as RT-Linux can vary as their instances evolve even though they always execute the same algorithm. This variation decreases as the priority of the tasks increases; however, the minimum and maximum response times are still present in the same task, and this complicates its monitoring, decreasing its level of predictability in case of contingency or overload, as well as making resource sizing difficult. Therefore, the need arises to propose a model capable of reconstructing the dynamics of response times for the instances of a task with high priority in order to analyze their offline behavior under specific working conditions. For this purpose, we develop the necessary theory to build the response time reconstruction model. Then, to test the proposed model, we set up a workbench consisting of a single board computer, PREEMPT_RT, and a high priority task generated by the execution of a matrix inversion algorithm. This work demonstrates the application of the theory in an experimental process, presenting a way to model and reconstruct the dynamics of response times by a high-priority task on RT-Linux.
Unified Convergence Analysis of Chebyshev–Halley Methods for Multiple Polynomial Zeros
Authors: Ivanov Stoil I.
Published: January 2022

In this paper, we establish two local convergence theorems that provide initial conditions and error estimates to guarantee the Q-convergence of an extended version of Chebyshev–Halley family of iterative methods for multiple polynomial zeros due to Osada (J. Comput. Appl. Math. 2008, 216, 585–599). Our results unify and complement earlier local convergence results about Halley, Chebyshev and Super–Halley methods for multiple polynomial zeros. To the best of our knowledge, the results about the Osada’s method for multiple polynomial zeros are the first of their kind in the literature. Moreover, our unified approach allows us to compare the convergence domains and error estimates of the mentioned famous methods and several new randomly generated methods.
Developing a Constructive Conceptual Framework of a Pre-Service Mathematics Teachers’ Content Knowledge Instrument on Space and Shape
Authors: Ekawati Rooselyna , Masriyah  , Rosyidi Abdul Haris , Prawoto Budi Priyo , Prahmana Rully Charitas Indra , Lin Fou-Lai
Published: January 2022

Space and shape is one of the geometry topics that should be mastered by students and require proper teachers’ Mathematics Content Knowledge (MCK) for teaching to avoid misconception. This study aimed at developing a constructive conceptual framework as an instrument to examine mathematics pre-service teachers’ MCK on space and shape contents and describing their profile on this topic. The present study used mixed methods, in which the obtained data were analyzed both quantitatively using Exploratory Factor Analysis (EFA) and qualitatively described in nature. The developed MCK instrument was administered to 21 senior Indonesian mathematics pre-service teachers who were in their third year of study which and by a purposive sampling technique. The results showed that the instrument had very good 10 final items with a consistent reliability coefficient of 0.67 and resulted in four factor components, namely, figural representation, area and circumference of object, relationship between properties of objects, and figural reasoning. Of the four factors, figural representation and reasoning factors had mostly been the challenges for Indonesian mathematics pre-service teachers. On the contrary, they performed better in the area and circumference of objects and the relationships between properties of objects. The findings lead to redesigning the curriculum for mathematics pre-service teachers’ learning to accommodate all their challenges.
When Is σ (A(t)) ⊂ {z ∈ ℂ; ℜz ≤ −α < 0} the Sufficient Condition for Uniform Asymptotic Stability of LTV System ẋ = A(t)x?
Authors: Vrabel Robert
Published: January 2022

In this paper, the class of matrix functions A(t) is determined for which the condition that the pointwise spectrum σ(A(t))⊂z∈C;ℜz≤−α for all t≥t0 and some α>0 is sufficient for uniform asymptotic stability of the linear time-varying system x˙=A(t)x. We prove that this class contains as a proper subset the matrix functions with the values in the special orthogonal group SO(n).
Quantum and Classical Log-Bounded Automata for the Online Disjointness Problem
Authors: Khadiev Kamil , Khadieva Aliya
Published: January 2022

We consider online algorithms with respect to the competitive ratio. In this paper, we explore one-way automata as a model for online algorithms. We focus on quantum and classical online algorithms. For a specially constructed online minimization problem, we provide a quantum log-bounded automaton that is more effective (has less competitive ratio) than classical automata, even with advice, in the case of the logarithmic size of memory. We construct an online version of the well-known Disjointness problem as a problem. It was investigated by many researchers from a communication complexity and query complexity point of view.
Stochastic Approximate Algorithms for Uncertain Constrained K-Means Problem
Authors: Lu Jianguang , Tang Juan , Xing Bin , Tang Xianghong
Published: January 2022

The k-means problem has been paid much attention for many applications. In this paper, we define the uncertain constrained k-means problem and propose a (1+ϵ)-approximate algorithm for the problem. First, a general mathematical model of the uncertain constrained k-means problem is proposed. Second, the random sampling properties of the uncertain constrained k-means problem are studied. This paper mainly studies the gap between the center of random sampling and the real center, which should be controlled within a given range with a large probability, so as to obtain the important sampling properties to solve this kind of problem. Finally, using mathematical induction, we assume that the first j−1 cluster centers are obtained, so we only need to solve the j-th center. The algorithm has the elapsed time O((1891ekϵ2)8k/ϵnd), and outputs a collection of size O((1891ekϵ2)8k/ϵn) of candidate sets including approximation centers.
Models of Privacy and Disclosure on Social Networking Sites: A Systematic Literature Review
Authors: Nemec Zlatolas Lili , Hrgarek Luka , Welzer Tatjana , Hölbl Marko
Published: January 2022

Social networking sites (SNSs) are used widely, raising new issues in terms of privacy and disclosure. Although users are often concerned about their privacy, they often publish information on social networking sites willingly. Due to the growing number of users of social networking sites, substantial research has been conducted in recent years. In this paper, we conducted a systematic review of papers that included structural equations models (SEM), or other statistical models with privacy and disclosure constructs. A total of 98 such papers were found and included in the analysis. In this paper, we evaluated the presentation of results of the models containing privacy and disclosure constructs. We carried out an analysis of which background theories are used in such studies and have also found that the studies have not been carried out worldwide. Extending the research to other countries could help with better user awareness of the privacy and self-disclosure of users on SNSs.
Sufficient Conditions for Some Stochastic Orders of Discrete Random Variables with Applications in Reliability
Authors: Belzunce Félix , Martínez-Riquelme Carolina , Pereda Magdalena
Published: January 2022

In this paper we focus on providing sufficient conditions for some well-known stochastic orders in reliability but dealing with the discrete versions of them, filling a gap in the literature. In particular, we find conditions based on the unimodality of the likelihood ratio for the comparison in some stochastic orders of two discrete random variables. These results have interest in comparing discrete random variables because the sufficient conditions are easy to check when there are no closed expressions for the survival functions, which occurs in many cases. In addition, the results are applied to compare several parametric families of discrete distributions.
How Does Irrigation Affect Crop Growth? A Mathematical Modeling Approach
Authors: Díaz-González Vicente , Rojas-Palma Alejandro , Carrasco-Benavides Marcos
Published: January 2022

This article presents a qualitative mathematical model to simulate the relationship between supplied water and plant growth. A novel aspect of the construction of this phenomenological model is the consideration of a structure of three phases: (1) The soil water availability, (2) the available water inside the plant for its growth, and (3) the plant size or amount of dry matter. From these phases and their interactions, a model based on a three-dimensional nonlinear dynamic system was proposed. The results obtained showed the existence of a single equilibrium point, global and exponentially stable. Additionally, considering the framework of the perturbation theory, this model was perturbed by incorporating irrigation to the available soil water, obtaining some stability results under different assumptions. Later through the control theory, it was demonstrated that the proposed system was controllable. Finally, a numerical simulation of the proposed model was carried out, to depict the soil water content and plant growth dynamic and its agreement with the results of the mathematical analysis. In addition, a specific calibration for field data from an experiment with wheat was considered, and these parameters were then used to test the proposed model, obtaining an error of about 6% in the soil water content estimation.
Does Machine Learning Offer Added Value Vis-à-Vis Traditional Statistics? An Exploratory Study on Retirement Decisions Using Data from the Survey of Health, Ageing, and Retirement in Europe (SHARE)
Authors: Garibay Montserrat González , Srakar Andrej , Bartolj Tjaša , Sambt Jože
Published: January 2022

Do machine learning algorithms perform better than statistical survival analysis when predicting retirement decisions? This exploratory article addresses the question by constructing a pseudo-panel with retirement data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The analysis consists of two methodological steps prompted by the nature of the data. First, a discrete Cox survival model of transitions to retirement with time-dependent covariates is compared to a Cox model without time-dependent covariates and a survival random forest. Second, the best performing model (Cox with time-dependent covariates) is compared to random forests adapted to time-dependent covariates by means of simulations. The results from the analysis do not clearly favor a single method; whereas machine learning algorithms have a stronger predictive power, the variables they use in their predictions do not necessarily display causal relationships with the outcome variable. Therefore, the two methods should be seen as complements rather than substitutes. In addition, simulations shed a new light on the role of some variables—such as education and health—in retirement decisions. This amounts to both substantive and methodological contributions to the literature on the modeling of retirement.
Optimal Risk Sharing in Society
Authors: Aase Knut K.
Published: January 2022

We consider risk sharing among individuals in a one-period setting under uncertainty that will result in payoffs to be shared among the members. We start with optimal risk sharing in an Arrow–Debreu economy, or equivalently, in a Borch-style reinsurance market. From the results of this model we can infer how risk is optimally distributed between individuals according to their preferences and initial endowments, under some idealized conditions. A main message in this theory is the mutuality principle, of interest related to the economic effects of pandemics. From this we point out some elements of a more general theory of syndicates, where in addition, a group of people are to make a common decision under uncertainty. We extend to a competitive market as a special case of such a syndicate.
Research on Intellectualized Location of Coal Gangue Logistics Nodes Based on Particle Swarm Optimization and Quasi-Newton Algorithm
Authors: Yang Shengli , Wang Junjie , Li Ming , Yue Hao
Published: January 2022

The optimization of an integrated coal gangue system of mining, dressing, and backfilling in deep underground mining is a multi-objective and complex decision-making process, and the factors such as spatial layout, node location, and transportation equipment need to be considered comprehensively. In order to realize the intellectualized location of the nodes for the logistics and transportation system of underground mining and dressing coal and gangue, this paper establishes the model of the logistics and transportation system of underground mining and dressing coal gangue, and analyzes the key factors of the intellectualized location for the logistics and transportation system of coal and gangue, and the objective function of the node transportation model is deduced. The PSO–QNMs algorithm is proposed for the solution of the objective function, which improves the accuracy and stability of the location selection and effectively avoids the shortcomings of the PSO algorithm with its poor local detailed search ability and the quasi-Newton algorithm with its sensitivity to the initial value. Comparison of the particle swarm and PSO–QNMs algorithm outputs for the specific conditions of the New Julong coal mine, as an example, shows that the PSO–QNMs algorithm reduces the complexity of the calculation, increases the calculation efficiency by eight times, saves 42.8% of the cost value, and improves the efficiency of the node selection of mining–dressing–backfilling systems in a complex underground mining environment. The results confirm that the method has high convergence speed and solution accuracy, and provides a fundamental basis for optimizing the underground coal mine logistics system. Based on the research results, a node siting system for an integrated underground mining, dressing, and backfilling system in coal mines (referred to as MSBPS) was developed.
A Multi-Agent Motion Prediction and Tracking Method Based on Non-Cooperative Equilibrium
Authors: Li Yan , Zhao Mengyu , Zhang Huazhi , Qu Yuanyuan , Wang Suyu
Published: January 2022

A Multi-Agent Motion Prediction and Tracking method based on non-cooperative equilibrium (MPT-NCE) is proposed according to the fact that some multi-agent intelligent evolution methods, like the MADDPG, lack adaptability facing unfamiliar environments, and are unable to achieve multi-agent motion prediction and tracking, although they own advantages in multi-agent intelligence. Featured by a performance discrimination module using the time difference function together with a random mutation module applying predictive learning, the MPT-NCE is capable of improving the prediction and tracking ability of the agents in the intelligent game confrontation. Two groups of multi-agent prediction and tracking experiments are conducted and the results show that compared with the MADDPG method, in the aspect of prediction ability, the MPT-NCE achieves a prediction rate at more than 90%, which is 23.52% higher and increases the whole evolution efficiency by 16.89%; in the aspect of tracking ability, the MPT-NCE promotes the convergent speed by 11.76% while facilitating the target tracking by 25.85%. The proposed MPT-NCE method shows impressive environmental adaptability and prediction and tracking ability.
Digital Video Tampering Detection and Localization: Review, Representations, Challenges and Algorithm
Authors: Akhtar Naheed , Saddique Mubbashar , Asghar Khurshid , Bajwa Usama Ijaz , Hussain Muhammad , Habib Zulfiqar
Published: January 2022

Digital videos are now low-cost, easy to capture and easy to share on social media due to the common feature of video recording in smart phones and digital devices. However, with the advancement of video editing tools, videos can be tampered (forged) easily for propaganda or to gain illegal advantages—ultimately, the authenticity of videos shared on social media cannot be taken for granted. Over the years, significant research has been devoted to developing new techniques for detecting different types of video tampering. In this paper, we offer a detailed review of existing passive video tampering detection techniques in a systematic way. The answers to research questions prepared for this study are also elaborated. The state-of-the-art research work is analyzed extensively, highlighting the pros and cons and commonly used datasets. Limitations of existing video forensic algorithms are discussed, and we conclude with research challenges and future directions.
Parameter Estimation in the Age of Degeneracy and Unidentifiability
Authors: Lederman Dylan , Patel Raghav , Itani Omar , Rotstein Horacio G.
Published: January 2022

Parameter estimation from observable or experimental data is a crucial stage in any modeling study. Identifiability refers to one’s ability to uniquely estimate the model parameters from the available data. Structural unidentifiability in dynamic models, the opposite of identifiability, is associated with the notion of degeneracy where multiple parameter sets produce the same pattern. Therefore, the inverse function of determining the model parameters from the data is not well defined. Degeneracy is not only a mathematical property of models, but it has also been reported in biological experiments. Classical studies on structural unidentifiability focused on the notion that one can at most identify combinations of unidentifiable model parameters. We have identified a different type of structural degeneracy/unidentifiability present in a family of models, which we refer to as the Lambda-Omega (Λ-Ω) models. These are an extension of the classical lambda-omega (λ-ω) models that have been used to model biological systems, and display a richer dynamic behavior and waveforms that range from sinusoidal to square wave to spike like. We show that the Λ-Ω models feature infinitely many parameter sets that produce identical stable oscillations, except possible for a phase shift (reflecting the initial phase). These degenerate parameters are not identifiable combinations of unidentifiable parameters as is the case in structural degeneracy. In fact, reducing the number of model parameters in the Λ-Ω models is minimal in the sense that each one controls a different aspect of the model dynamics and the dynamic complexity of the system would be reduced by reducing the number of parameters. We argue that the family of Λ-Ω models serves as a framework for the systematic investigation of degeneracy and identifiability in dynamic models and for the investigation of the interplay between structural and other forms of unidentifiability resulting on the lack of information from the experimental/observational data.
Economic, Ecological and Social Analysis Based on DEA and MCDA for the Management of the Madrid Urban Public Transportation System
Authors: Rivero Gutiérrez Lourdes , De Vicente Oliva María Auxiliadora , Romero-Ania Alberto
Published: January 2022

The aim of this research is to help public transport managers to make decisions on the type of buses that should compose their public transport fleet, taking into account economic, environmental and social criteria from the point of view of sustainability. This paper fills a knowledge gap by including the social dimension of sustainability in addition to the economic and environmental dimensions. The original nature of this study lies in analyzing complementarities in the structuring of an efficiency and multicriteria problem. Our research analyzes Madrid public bus system data; the problem is structured in a comparative way between two analytical methods, a Data Envelopment Analysis (DEA) and an ELimination Et Choice Translating REality (ELECTRE) III. Our research results show that two main groups of vehicles could play a part in part the theoretical solution. The main conclusions of this research are that (a) plug-in and induction electric vehicles are not comparable to GNC and diesel–hybrid vehicles in terms of cost, pollution and service; and (b) the ELECTRE III model provides more information in solving this problem than the DEA model.
Certain Properties of a Class of Functions Defined by Means of a Generalized Differential Operator
Authors: Oluwayemi Matthew Olanrewaju , Vijaya Kaliappan , Cătaş Adriana
Published: January 2022

In this article, we construct a new subclass of analytic functions involving a generalized differential operator and investigate certain properties including the radius of starlikeness, closure properties and integral means result for the class of analytic functions with negative coefficients. Further, the relationship between the results and some known results in literature are also established.
Mono- and Dimeric Xanthones with Anti-Glioma and Anti-Inflammatory Activities from the Ascidian-Derived Fungus Diaporthe sp. SYSU-MS4722
Authors: Chen Senhua , Guo Heng , Jiang Minghua , Wu Qilin , Li Jing , Shen Hongjie , Liu Lan
Published: January 2022

Seven new xanthones, diaporthones A−G (1−7), together with 13 known analogues, including five mono- (8−14) and six dimeric xanthones (15−20), were obtained from the ascidian-derived fungus Diaporthe sp. SYSU-MS4722. Their planar structures were established by extensive spectroscopic analyses, including 1D and 2D NMR and high-resolution mass spectrometry (HR-ESIMS). The absolute configurations of 1−7 were clearly identified by X-ray crystallographic analysis and calculation of the ECD Spectra. Compounds 15−20 showed significant anti-inflammatory activity with IC50 values between 6.3 and 8.0 μM. In addition, dimeric xanthones (15−20) showed selective cytotoxicity against T98G cell lines with IC50 values ranging from 19.5 to 78.0 μM.
A Promising Potential of Brown Algae Sargassum polycystum as Irreversible Hydrocolloid Impression Material
Authors: Hamrun Nurlindah , Talib Bahruddin , Ruslin Muhammad , Pangeran Hasminar , Hatta Mochammad , Marlina Erni , Yusuf Andi Sitti Hajrah , Saito Takashi , Ou Keng-Liang
Published: January 2022

This study aimed to investigate the potential use of brown algae Sargassum polycystum as irreversible hydrocolloid (alginate) impression material. Potassium alginate extracted from Sargassum polycystum was prepared in three different compositions (14%, 15%, and 16%) and mixed with other standard components to form an alginate impression material. Prior to that, the purity of potassium alginate was quantified with Fourier Transform Infrared Spectroscopy (FTIR) analysis. As a control material, the alginate impression material from a commercially available product was used. All alginate impression materials were then applied to a die stone model. Dimensional accuracy was measured by calculating the mesiodistal width of incisors in the generated dental cast using a digital caliper 0.01 accuracy (five replications). In addition, to evaluate the dimensional stability, the impression results were poured at four different periods (immediately, 5 min, 10 min, and 15 min). An independent t-test was performed to compare the measurement results with p < 0.05 considered significant. Analytical results confirm that the impression material containing 15% potassium alginate gives the best dimensional accuracy similar to control (p > 0.05). Meanwhile, the optimal dimensional stability was produced in the impression material containing 16% potassium alginate. Our study suggested that brown algae Sargassum polycystum has a promising potential to be used as an alginate impression material in clinical application.