bluuebunny/crossref_metadata_2025 huggingface dataset:
How Does Trust Influence Farmers’ Low-Carbon Agricultural Technology Adoption? Evidence from Rural Southwest, China
Authors: Zhou Wenfeng , He Jia , Liu Shaoquan , Xu Dingde
Published: February 2023

Carbon emission reduction in agriculture is an important link to achieving green agricultural development and a rural ecological environment, and Low-Carbon Agricultural Technology (LCAT) of farmers is an important means to achieve carbon emission reduction in agriculture. Based on data obtained from a survey of 540 farmers in Sichuan province in 2021, the Tobit model was used to empirically analyze the effect of trust on farmers’ LCAT adoption. The results show that (1) the trust level of farmers is high and the order is special trust > institutional trust > general trust. At the same time, the intensity of adoption of LCAT by farmers is not high, and the average number of LCAT adopted by each family is 1.13. Among them, straw-returning technology was adopted to a high degree, with 54.63% of farmers using it. (2) Farmers’ trust significantly enhances farmers’ LCAT adoption behavior, and the magnitude of the effect is characterized by specific trust > general trust > institutional trust chain. (3) Heterogeneity analysis shows that the influence of farmers’ specific trust and institutional trust in plain areas on the intensity of LCAT adoption is stronger than that of farmers in non-plain areas, and the influence of general trust of farmers in non-plain areas on the intensity of LCAT adoption is stronger than that of farmers in plain areas. The impact of specific trust, general trust, and institutional trust on LCAT adoption was stronger for the new generation of farmers than for the older generation of farmers. (4) Herding effect plays a mediating role in special trust, institutional trust, and LCAT adoption. This study can deepen our understanding of the relationship between farmers’ trust and LCAT adoption behavior, and then provide theoretical reference and practical basis for the promotion of LCAT and the improvement of farmers’ LCAT adoption level from the perspective of trust.
Diabetes Mellitus and Heart Failure: Epidemiology, Pathophysiologic Mechanisms, and the Role of SGLT2 Inhibitors
Authors: Theofilis Panagiotis , Oikonomou Evangelos , Tsioufis Konstantinos , Tousoulis Dimitris
Published: February 2023

Diabetes mellitus (DM) and heart failure (HF) are frequently encountered afflictions that are linked by a common pathophysiologic background. According to landmark studies, those conditions frequently coexist, and this interaction represents a poor prognostic indicator. Based on mechanistic studies, HF can be propagated by multiple pathophysiologic pathways, such as inflammation, oxidative stress, endothelial dysfunction, fibrosis, cardiac autonomic neuropathy, and alterations in substrate utilization. In this regard, DM may augment myocardial inflammation, fibrosis, autonomic dysfunction, and lipotoxicity. As the interaction between DM and HF appears critical, the new cornerstone in DM and HF treatment, sodium-glucose cotransporter-2 inhibitors (SGLT2i), may be able to revert the pathophysiology of those conditions and lead to beneficial HF outcomes. In this review, we aim to highlight the deleterious pathophysiologic interaction between DM and HF, as well as demonstrate the beneficial role of SGLT2i in this field.
Bionanotechnology in Agriculture: A One Health Approach
Authors: dos Santos Mayara Santana , Antunes Filho Sérgio , Backx Bianca Pizzorno
Published: February 2023

Healthy eating habits are one of the requirements for the health of society. In particular, in natura foods are increasingly encouraged, since they have a high concentration of nutrients. However, these foods are often grown in the presence of agrochemicals, such as fertilizers and pesticides. To increase crop productivity and achieve high vigor standards in less time, farmers make excessive use of agrochemicals that generate various economic, environmental, and clinical problems. In this way, bionanotechnology appears as an ally in developing technologies to improve planting conditions, ranging from the health of farmers and consumers to the production of new foods and functional foods. All these improvements are based on the better use of land use in synergy with the lowest generation of environmental impacts and the health of living beings, with a view to the study and production of technologies that take into account the concept of One Health in its processes and products. In this review article, we will address how caring for agriculture can directly influence the quality of the most desired foods in contemporary society, and how new alternatives based on nanotechnology can point to efficient and safe solutions for living beings on our planet.
Therapeutic Efficacy and Radiobiological Effects of Boric-Acid-Mediated BNCT in an Osteosarcoma-Bearing SD Rat Model
Authors: Hsu Chen-Fang , Liu Hong-Ming , Peir Jinn-Jer , Liao Jiunn-Wang , Chen Kuan-Sheng , Chen Yi-Wei , Chuang Yung-Jen , Chou Fong-In
Published: February 2023

Background: Osteosarcoma (OS) is the most common primary malignancy of the bone and is notoriously resistant to radiation therapy. High-dose cytotoxic chemotherapy and surgical resection have improved the survival rate and prognosis of patients with OS. Nonetheless, treatment challenges remain when the tumor cannot be removed by surgery. Boron neutron capture therapy (BNCT) provides high linear energy transfer (LET) radiation, and its internal targeted characteristics make BNCT a novel therapy for removing OS and reducing radiation damage to adjacent healthy tissues. Methods: In this study, a UMR-106-grafted OS rat model was developed, and boric acid (BA) was used as the boron drug for BNCT. The pharmacokinetics of BA, following intravenous injection, were evaluated to determine the optimal time window for neutron irradiation. OS-bearing rats were irradiated by an epithermal neutron beam at Tsing Hua Open-Pool Reactor (THOR). The therapeutic efficacy of and tissue response after BNCT were evaluated by radiographic and histopathological observations. Results: OS-bearing rats were irradiated by neutrons in the first hour following the intravenous injection of BA. The prescription-absorbed doses in the tumor regions were 5.8 and 11.0 Gy. BNCT reduced the body weight of the tumor-bearing rats, but they recovered after a few days. The BA-mediated BNCT effectively controlled the orthotopic OS tumor, reduced osteolysis, and induced bone healing. Autoradiography and histological analysis confirmed that the BA retention region is consistent with the calcification region in OS tissue. Conclusion: BA is specifically retained in OS, and the BA-mediated BNCT can significantly reduce the tumor burden and osteolysis in OS-bearing rats.
Long-Term Efficacy and Safety of Modified Canaloplasty Versus Trabeculectomy in Open-Angle Glaucoma
Authors: Stingl Julia V. , Wagner Felix M. , Liebezeit Sarah , Baumgartner Raphael , Spät Helene , Schuster Alexander K. , Prokosch Verena , Grehn Franz , Hoffmann Esther M.
Published: February 2023

Background: To evaluate the long-term efficacy and safety of modified canaloplasty versus trabeculectomy in open-angle glaucoma. Methods: In total, 210 subjects with open-angle glaucoma were included. 70 were treated with Mitomycin C-augmented modified canaloplasty with enhanced subconjunctival filtration and 140 with Mitomycin C-augmented trabeculectomy. Cases were matched 1:2 by sex and age. Results: In canaloplasty and trabeculectomy groups, 61.4% and 57.9% of participants were female. Mean age was 60.0 ± 13.9 and 63.0 ± 12.2 years, median follow-up time was 4.6 [IQR 4.3, 5.05] years and 5.8 [IQR 5.4, 6.3]. Strict success was achieved in 20.0% and 56.4%, complete success in 24.3% and 66.4%, and qualified success in 34.3% and 73.6% (each p < 0.001). Kaplan–Meier survival analysis showed a better survival probability for trabeculectomy than for canaloplasty (p < 0.001) and Cox regression analysis revealed an HR of 6.03 (95%-CI 3.66, 9.93, p < 0.001) after canaloplasty. Trabeculectomy showed superiority in terms of IOP decrease (9.2 ± 7.9 mmHg vs. 13.7 ± 10.4 mmHg, p = 0.002), use of AGM (50.0% vs. 10.7%, p < 0.001), and the number of revision surgeries (41.4% vs. 21.4%, p = 0.004). Occurrence of complications was similar in both groups (14.5% vs. 7.5%, p = 0.19). Conclusions: Trabeculectomy showed superiority in efficacy and equality in safety compared to modified canaloplasty.
Establishment and Calibration of a Digital Twin to Replicate the Friction Behaviour of a Pin-on-Disk Tribometer
Authors: Hansen Erik , Vaitkunaite Gerda , Schneider Johannes , Gumbsch Peter , Frohnapfel Bettina
Published: February 2023

While the modification of surface contacts offers significant potential for friction reduction, obtaining an underlying consistent friction behaviour of real-life experiments and virtual simulations is still an ongoing challenge. In particular, most works in the literature only consider idealised geometries that can be parametrised with simple analytical functions. In contrast to this approach, the current work describes the establishment of a digital twin of a pin-on-disk tribometer whose virtual geometry is completely replicated from real-life post-test topography measurements and fed into a two-scale mixed lubrication solver. Subsequently, several calibration steps are performed to identify the sensitivities of the friction behaviour towards certain geometry features and enable the digital twin to robustly represent the Stribeck curve of the physical experiments. Furthermore, a derivation of the Hersey number is used to generalise the obtained friction behaviour for different dynamic viscosities and allow the validation of the presented method.
Sustainable Vegetable Oil-Based Minimum Quantity Lubrication Assisted Machining of AZ91 Magnesium Alloy: A Grey Relational Analysis-Based Study
Authors: Alshibi Assem , Nasreldin Abdelrahman , Pervaiz Salman
Published: February 2023

The implementation of magnesium alloys in a multitude of industries has been proven to be a mere effect of their attractive light weight, corrosion resistant, and biodegradable properties. These traits allow these materials to portray an excellent sustainable machinability. However, with increasing demand, it is essential to explore sustainable means of increasing production while mitigating reductions in sustainability. The current work aims to assess and optimize the high-speed machinability of AZ91 with the use of a vegetable oil-based minimum quantity lubrication (MQL) system using the grey relational analysis (GRA) on the basis of chip morphology and tool wear. The investigation entailed a full factorial design with MQL flow rate, cutting speed, and feed rate as the control parameters and flank wear, land width, chip contact length, saw-tooth pitch, chip segmentation ratio, chip compression ratio, and shear angle as the output responses. The optimal control parameters predicted and experimentally confirmed were an MQL flow rate of 40 mL/h, cutting speed of 300 m/min, and feed rate of 0.3 mm/rev. The usage of said optimal parameters results in a grey relational grade improvement of 0.2675 in comparison to the referenced first experimental run. Moreover, the MQL flow rate was regarded as the critical variable with a contribution percentage of 20% for the grey relational grade.
Inorganic Particles Contribute to the Compatibility of Polycarbonate/Polystyrene Polymer Blends
Authors: Takayama Tetsuo
Published: February 2023

Polycarbonate (PC), an engineering plastic, has excellent mechanical strength and toughness. Moreover, this transparent polymer material can be used in fields where materials require mechanical properties and transparency. Nevertheless, PC is known to have a high melt viscosity. Moreover, blending with polystyrene (PS), an inherently brittle material, has been used to adjust its melt viscosity. As a result, the PS makes PC/PS polymer blends more brittle than PC alone. As described herein, after attempting to achieve compatibility with inorganic particles, the results show that the dispersion of small amounts of inorganic clay and silica particles in PC/PS polymer blends maintained transparency while improving the impact strength to a level comparable to that of polycarbonate. Apparently, the inorganic particles promote the fine dispersion of PS. Moreover, the spherical morphology of the inorganic particles is more effective at compatibilizing the polymer blend because the inorganic particles can apply isotropic interaction forces.
Failure Analysis of Cracking of Cast Aluminum Alloy Manhole Cover
Authors: Ren Facai , Li Hezong
Published: February 2023

In this paper, the abnormal fracture failure of a ZL104 aluminum alloy quick-opening manhole cover of a cement tank truck is systematically studied to discover the root cause of an accident. The unloading operation procedures of cement tank trucks, the effectiveness of safety valves, the chemical composition, mechanical properties and material quality of aluminum alloy manhole covers, and the macroscopic and microscopic morphology of fractures were comprehensively analyzed. The results show that although the Mg content in the chemical composition of an aluminum alloy manhole cover exceeds the standard, it is not the root cause of the accident. The root cause of the failure is that, during the unloading operation, the operator did not strictly follow the unloading procedures. One of the buckles was in the released state, which led to uplift cracking, resulting in the successive cracking and slipping of adjacent buckles, and the manhole cover finally cracked and flew out. Based on the failure causes, suggestions are put forward to prevent the manhole cover from failing during the unloading operation of cement tank trucks in the future.
A New Energy Approach to Predicting Fracture Resistance in Metals
Authors: Dutkiewicz Maciej , Hembara Oksana , Chepil Olha , Hrynenko Mykhailo , Hembara Taras
Published: February 2023

To ensure the reliability and durability of structural elements, modern approaches require data characterizing the local stress-strain state of the material in risk zones. In order to predict the fracture resistance of structural elements, a theoretical-experimental method based on the damage accumulation model using the energy approach is proposed. One of the unique characteristics of the proposed approach is that it uses local parameters of the stress-strain state, which are determined using a highly accurate and easy-to-use noncontact method of optical–digital image correlation (ODIC). This can be used both in laboratory conditions and for structural elements under real operating conditions. The proposed method of plotting stress–strain curves makes it possible to determine the true stresses near the concentrators in structural elements under a complex load. Using these diagrams in calculations and the finite element method (FEM), a study of local strain not only of the surface, but also of the internal volumes of the material was carried out. The damage parameter is introduced as the ratio of the elastoplastic strain energy of the local volume to its critical value. It is confirmed that the damage of the sample material starts from its centre. It was established that the damage parameter in the centre of the sample is 25–35% higher than its value on the surface of the sample.
Thin-Walled Commercially Pure Titanium Structures: Laser Powder Bed Fusion Process Parameter Optimization
Authors: Depboylu Fatma Nur , Yasa Evren , Poyraz Ozgur , Korkusuz Feza
Published: February 2023

Laser powder bed fusion (L-PBF) process parameters can be changeable depending on the part geometry due to thermal conductivity differences. The number of studies on the process parameter development for commercial pure titanium (Cp-Ti) with the L-PBF process is also quite limited in the literature. The aim of this study is to present a comprehensive process development for the production of Cp-Ti bulk and thin structures with the L-PBF technology. In the first phase, the right process parameters, including scan speed, laser power, hatch distance, and layer thickness, were identified with prismatic specimens with thin walls so that the obtained parameters could be used for both bulky sections and thin features such as lattice structures. The process parameters were varied to change the volumetric energy density from 19 to 208 J/mm3 among 80 different parameter sets. Parameter sets having a Volumetric Energy Density (VED) value between 32 J/mm3 and 47 J/mm3 gave almost fully dense Cp-Ti parts while the laser power was set to 200–250 W and the scan speed was used as 1000–1400 mm/s. Finally, Vickers hardness and tensile tests were applied to highly dense Cp-Ti parts. This study involving investigating the effect of process parameters on a wide range demonstrated that L-PBF is a favorable manufacturing technology for Cp-Ti parts with almost full density and good mechanical properties as well as good dimensional accuracy even on thin geometries. Moreover, the results show that combining parameters into a single one, i.e., VED, is not a proper way to optimize the process parameters since increasing laser power or decreasing the scan speed may alter the results, although VED is increased in both manners.
Sizing of a Traction Switched Reluctance Motor for an Electric Refuse-Collecting Vehicle Application
Authors: Forsyth Alexander , Juarez-Leon Francisco , Bilgin Berker
Published: February 2023

Refuse-collecting vehicles are significant polluters due to their expected drive cycles involving frequent stops and long idle periods. Electric refuse-collecting vehicles, still in their infancy, promise to address this through the replacement of internal combustion engines with batteries and electric traction motors. Today, typical motors for these vehicles involve heavy use of rare earth permanent magnets, which are subject to high price volatility, environmentally damaging mining practices, and occupational health hazards associated with refinement. The switched reluctance motor, which makes use of no permanent magnets, is a suitable substitute. This type of motor technology offers several advantages such as simple and robust construction, the ability to operate at high speeds and high temperature conditions, fault tolerance capability, and lower production costs in comparison with other technologies. This paper focuses on the design process of a switched reluctance motor for a battery electric refuse-collecting vehicle. The designed motor has a 36/24 outer rotor configuration, and its electrical and mechanical characteristics are based on the commercial traction motor TM4 SUMO HD HV3500-9P. The performance of the motor is evaluated using simulation tools such as JMAG and MATLAB/Simulink.
Finite Difference Method to Evaluate the Characteristics of Optically Dense Gray Nanofluid Heat Transfer around the Surface of a Sphere and in the Plume Region
Authors: Ashraf Muhammad , Khan Anwar , Abbas Amir , Hussanan Abid , Ghachem Kaouther , Maatki Chemseddine , Kolsi Lioua
Published: February 2023

The current research study is focusing on the investigation of the physical effects of thermal radiation on heat and mass transfer of a nanofluid located around a sphere. The configuration is investigated by solving the partial differential equations governing the phenomenon. By using suitable non-dimensional variables, the governing set of partial differential equations is transformed into a dimensionless form. For numerical simulation, the attained set of dimensionless partial differential equations is discretized by using the finite difference method. The effects of the governing parameters, such as the Brownian motion parameter, the thermophoresis parameter, the radiation parameter, the Prandtl number, and the Schmidt number on the velocity field, temperature distribution, and mass concentration, are presented graphically. Moreover, the impacts of these physical parameters on the skin friction coefficient, the Nusselt number, and the Sherwood number are displayed in the form of tables. Numerical outcomes reflect that the effects of the radiation parameter, thermophoresis parameter, and the Brownian motion parameter intensify the profiles of velocity, temperature, and concentration at different circumferential positions on the sphere.
Decisions for a Retailer-Led Low-Carbon Supply Chain Considering Altruistic Preference under Carbon Quota Policy
Authors: Zhou Xiao , Wu Xiancong
Published: February 2023

With the release of the national energy-saving emission reduction policy and the improvement of consumers’ awareness of environmental protection, the demand for low-carbon products is growing rapidly. In a retailer-led low-carbon supply chain, the increased cost of carbon emission reduction puts manufacturers at a disadvantage. Under the carbon quota policy, to improve manufacturers’ profits as well as enhance carbon emission reduction, this paper studies the players’ decisions in a low-carbon supply chain consisting of one dominant retailer and one manufacturer. To maintain the supply chain’s stability and sustainability, the dominant retailer tends to employ altruistic preference policies towards the manufacturer. The optimal decision, carbon emission reduction and supply chain profit are compared and analyzed under three decision models: (i) centralized decision, (ii) decentralized decision without altruistic preference and (iii) decentralized decision with altruistic preference. The results indicate that the carbon emission reduction rate, market demand and profit in the centralized model are higher than in the decentralized model. The retailer’s altruistic preference is beneficial to the improvement of carbon emission reduction, market demand and the profit of the manufacturer and the supply chain. Under certain conditions, carbon trading can effectively reduce the cost pressure of manufacturers and improve the level of carbon emission reduction and the overall profit of the supply chain. These results will guide low-carbon supply chain decision-making and provide insight into the research of irrational behaviors in supply chain decision-making under carbon policies.
Complex Fractional-Order LQIR for Inverted-Pendulum-Type Robotic Mechanisms: Design and Experimental Validation
Authors: Saleem Omer , Abbas Faisal , Iqbal Jamshed
Published: February 2023

This article presents a systematic approach to formulate and experimentally validate a novel Complex Fractional Order (CFO) Linear Quadratic Integral Regulator (LQIR) design to enhance the robustness of inverted-pendulum-type robotic mechanisms against bounded exogenous disturbances. The CFO controllers, an enhanced variant of the conventional fractional-order controllers, are realised by assigning pre-calibrated complex numbers to the order of the integral and differential operators in the control law. This arrangement significantly improves the structural flexibility of the control law, and hence, subsequently strengthens its robustness against the parametric uncertainties and nonlinear disturbances encountered by the aforementioned under-actuated system. The proposed control procedure uses the ubiquitous LQIR as the baseline controller that is augmented with CFO differential and integral operators. The fractional complex orders in LQIR are calibrated offline by minimising an objective function that aims at attenuating the position-regulation error while economising the control activity. The effectiveness of the CFO-LQIR is benchmarked against its integer and fractional-order counterparts. The ability of each controller to mitigate the disturbances in inverted-pendulum-type robotic systems is rigorously tested by conducting real-time experiments on Quanser single-link rotary pendulum system. The experimental outcomes validate the superior disturbance rejection capability of the CFO-LQIR by yielding rapid transits and strong damping against disturbances while preserving the control input economy and closed-loop stability of the system.
Intelligent Global Fast Terminal Sliding Mode Control of Active Power Filter
Authors: Yang Jiahao , Li Xiangguo , Fei Juntao
Published: February 2023

Faced with serious harmonic pollution, a global fast terminal sliding mode control (GFTSMC) based on a novel recurrent fuzzy neural network (NRFNN) strategy for an active power filter (APF) with uncertainty is proposed in this article, which is aimed at improving the power quality and realizing harmonic suppression. First, the GFTSMC is adopted due to its advantages in finite-time convergence and faster convergence rate of tracking error in the system. Second, NRFNN is adopted to approximate the unknown model and lump the uncertainty of the APF system. Because the values of base width, center vector and feedback gain of NRFNN can be adjusted adaptively according to adaptive laws, the accurate approximation of the unknown model can be achieved, and the robustness and accuracy of the APF system can be guaranteed. Finally, the validity and feasibility of the proposed GFTSMC-NRFNN scheme is fully verified by simulation results, showing it has better steady-state and dynamic performance than other existing methods.
A Fuzzy-Based Fast Feature Selection Using Divide and Conquer Technique in Huge Dimension Dataset
Authors: Tanwar Arihant , Alghamdi Wajdi , Alahmadi Mohammad D. , Singh Harpreet , Rana Prashant Singh
Published: February 2023

Feature selection is commonly employed for identifying the top n features that significantly contribute to the desired prediction, for example, to find the top 50 or 100 genes responsible for lung or kidney cancer out of 50,000 genes. Thus, it is a huge time- and resource-consuming practice. In this work, we propose a divide-and-conquer technique with fuzzy backward feature elimination (FBFE) that helps to find the important features quickly and accurately. To show the robustness of the proposed method, it is applied to eight different datasets taken from the NCBI database. We compare the proposed method with seven state-of-the-art feature selection methods and find that the proposed method can obtain fast and better classification accuracy. The proposed method will work for qualitative, quantitative, continuous, and discrete datasets. A web service is developed for researchers and academicians to select top n features.
Anisotropic Hyperelastic Material Characterization: Stability Criterion and Inverse Calibration with Evolutionary Strategies
Authors: Canales Claudio , García-Herrera Claudio , Rivera Eugenio , Macías Demetrio , Celentano Diego
Published: February 2023

In this work, we propose a reliable and stable procedure to characterize anisotropic hyperelastic materials. For this purpose, a metaheuristic optimization method known as evolutionary strategies is used. The advantage of this technique with respect to traditional methods used for non-linear optimization, such as the Levenberg–Marquardt Method, is that this metaheuristic algorithm is oriented to the global optimization of a problem, is independent of gradients and allows to solve problems with constraints. These features are essential when characterizing hyperelastic materials that have non-linearities and are conditioned to regions of stability. To characterize the mechanical behavior of the arteries analyzed in this work, the anisotropic hyperelastic models of Holzapfel–Gasser–Ogden and Gasser–Holzapfel–Ogden are used. An important point of the analysis is that these models may present a non-physical behavior: this drawback is overcome by defining a new criterion of stabilization in conjunction with the evolutionary strategies. Finally, the finite element simulations are used in conjunction with the evolutionary strategies to characterize experimental data of the artery pressurization test, ensuring that the parameters obtained are stable and representative of the material response.
Dynamics of Classical Solutions of a Two-Stage Structured Population Model with Nonlocal Dispersal
Authors: Onyido Maria A. , Salako Rachidi B. , Uba Markjoe O. , Udeani Cyril I.
Published: February 2023

We study the dynamics of classical solutions of a two-stage structured population model with nonlocal dispersal in a spatially heterogeneous environment and address the question of the persistence of the species. In particular, we show that the species’ persistence is completely determined by the sign of the principal spectrum point, λp, of the linearized system at the trivial solution: the species goes extinct if λp≤0, while it persists uniformly in space if λp>0. Sufficient conditions are provided to guarantee the existence, uniqueness, and stability of a positive steady state when the parameters are spatially heterogeneous. Furthermore, when the model parameters are spatially homogeneous, we show that the unique positive equilibrium is globally stable with respect to positive perturbations.
New Approaches on Parameter Estimation of the Gamma Distribution
Authors: Ke Xiao , Wang Sirao , Zhou Min , Ye Huajun
Published: February 2023

This paper discusses new approaches to parameter estimation of gamma distribution based on representative points. In the first part, the existence and uniqueness of gamma mean squared error representative points (MSE-RPs) are discussed theoretically. In the second part, by comparing three types of representative points, we show that gamma MSE-RPs perform well in parameter estimation and simulation. The last part proposes a new Harrel–Davis sample standardization technique. Simulation studies reveal that the standardized samples can be used to improve estimation performance or generate MSE-RPs. In addition, a real data analysis illustrates that the proposed technique yields efficient estimates for gamma parameters.
The Novel Analytical–Numerical Method for Multi-Dimensional Multi-Term Time-Fractional Equations with General Boundary Conditions
Authors: Lin Ji , Reutskiy Sergiy , Zhang Yuhui , Sun Yu , Lu Jun
Published: February 2023

This article presents a simple but effective two-step analytical–numerical algorithm for solving multi-dimensional multi-term time-fractional equations. The first step is to derive an analytic representation that satisfies boundary requirements for 1D, 2D, and 3D problems, respectively. The second step is the meshless approximation where the Müntz polynomials are used to form the approximate solution and the unknown parameters are obtained by imposing the approximation for the governing equations. We illustrate first the detailed derivation of the analytic approximation and then the numerical implementation of the solution procedure. Several numerical examples are provided to verify the accuracy, efficiency, and adaptability to problems with general boundary conditions. The numerical results are compared with exact solutions and numerical methods reported in the literature, showing that the algorithm has great potential for multi-dimensional multi-term time-fractional equations with various boundary conditions.
Bias-Corrected Inference of High-Dimensional Generalized Linear Models
Authors: Tang Shengfei , Shi Yanmei , Zhang Qi
Published: February 2023

In this paper, we propose a weighted link-specific (WLS) approach that establishes a unified statistical inference framework for high-dimensional Poisson and Gamma regression. We regress the parameter deviations as well as the initial estimation errors and utilize the resulting regression coefficients as correction weights to reduce the total mean square error (MSE). We also develop the asymptotic normality of the correction estimates under sparse and non-sparse conditions and construct associated confidence intervals (CIs) to verify the robustness of the new method. Finally, numerical simulations and empirical analysis show that the WLS method is extensive and effective.
Modeling Negotiating Abilities in the Construction Sector: A Proposed Mathematical Model Using the Confirmatory Factor Analysis Method
Authors: Algezawy Mohamed , Azazz Alaa M. S. , Tork Magdy E. A. , Elshaer Ibrahim A.
Published: February 2023

This study aims to develop a mathematical model for evaluating the objective abilities needed for negotiation and to provide a tool that companies can use to select a negotiation team. The model was constructed using a Likert pentagonal scale, where numbers from 5 to 1 represented the level of agreement or disagreement, and seven objective abilities were considered, including analytical ability, economic knowledge, legal knowledge, linguistic ability, psychological understanding, normative understanding, and general knowledge. The model was tested using a structured interview (sixteen interviews) with experts and specialists in the construction industry as a case study and then validated by quantitative data analysis method using first-order confirmatory factor analysis (CFA) with a sample of consultants (220 responses) from companies and offices related to the construction sector. The study found that the model is valid for use in the construction industry and can be useful for selecting negotiators. The developed model can be used, adapted, and modified according to the needs of different negotiation situations. This research is the first of its kind to develop a mathematical model for evaluating negotiating abilities and can be used as a model for similar research studies.
New Development of Variational Iteration Method Using Quasilinearization Method for Solving Nonlinear Problems
Authors: Sinha Vikash Kumar , Maroju Prashanth
Published: February 2023

In this paper, we developed a new variational iteration method using the quasilinearization method and Adomian polynomial to solve nonlinear differential equations. The convergence analysis of our new method is also discussed under the Lipschitz continuity condition in Banach space. Some application problems are included to test the efficacy of our proposed method. The behavior of the method is investigated for different values of parameter t. This is a powerful technique for solving a large number of nonlinear problems. Comparisons of our technique were made with the available exact solution and existing methods to examine the applicability and efficiency of our approach. The outcome revealed that the proposed method is easy to apply and converges to the solution very fast.
A Sustainable Fault Diagnosis Approach for Photovoltaic Systems Based on Stacking-Based Ensemble Learning Methods
Authors: Mellit Adel , Zayane Chadia , Boubaker Sahbi , Kamel Souad
Published: February 2023

In this study, a novel technique for identifying and categorizing flaws in small-scale photovoltaic systems is presented. First, a supervised machine learning (neural network) was developed for the fault detection process based on the estimated output power. Second, an extra tree supervised algorithm was used for extracting important features from a current-voltage (I–V) curve. Third, a multi-stacking-based ensemble learning algorithm was developed to effectively classify faults in solar panels. In this work, single faults and multiple faults are investigated. The benefit of the stacking strategy is that it can combine the strengths of several machine learning-based algorithms that are known to deliver good results on classification tasks, producing results that are more precise and efficient than those produced by a single algorithm. The approach was tested using an experimental dataset and the findings show that it could accurately diagnose faults (a detection rate of around 98.56% and a classification rate of around 96.21%). A comparison study with different ensemble learning algorithms (AdaBoost, CatBoost, and XGBoost) was conducted to evaluate the effectiveness of the suggested method.
Reliability Prediction of Tunnel Roof with a Nonlinear Failure Criterion
Authors: Yang Xin , Long Jiangping
Published: February 2023

Based on the kinematics-based upper bound theorem and reliability theory, the stability of deep tunnel roofs in nonlinear Hoek-Brown media is investigated. The performance functions of rectangular and circular tunnels are proposed according to the roof collapse mode, respectively, with support pressure and pore water pressure being considered. With the proposed performance function of the rectangular tunnels, the first-order reliability method is utilized to perform reliability analysis. The rock strength parameters are regarded as random variables following the normal or lognormal distribution. To assess the validity of the obtained results, reliability indexes for different support pressure values are calculated and compared with solutions using the response surface method and Monte-Carlo simulation. The agreement shows that the first-order reliability method effectively evaluates the reliability index with the proposed performance function. Sensitivity analysis is performed to throw light on the significance of different random variables, and the impact of the variation coefficient on reliability indexes is discussed. For circular tunnels, MCS is utilized to evaluate the roof stability with the proposed performance function. The influences of the support pressure on the reliability index and the corresponding design points are investigated. The parametric study shows that the normal distribution of random variables has more influence on the failure probability than that of the lognormal distribution. However, the difference between the two distributions is small. σt is the major factor that influences the reliability index compared to the B and ru. The supporting pressure for circular tunnels is smaller than that of rectangular tunnels when a target reliability index of 2.5 (failure probability equals 0.62%) is given.
Preface to the Special Issue “Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics”—Special Issue Book
Authors: Ou Weihua , Gou Jianping , Zeng Shaoning , Du Lan
Published: February 2023

The feature representation learning is the basic task that plays an important role in artificial intelligence, data mining and robotics [...]
Towards Future Internet: The Metaverse Perspective for Diverse Industrial Applications
Authors: Bhattacharya Pronaya , Saraswat Deepti , Savaliya Darshan , Sanghavi Sakshi , Verma Ashwin , Sakariya Vatsal , Tanwar Sudeep , Sharma Ravi , Raboaca Maria Simona , Manea Daniela Lucia
Published: February 2023

The Metaverse allows the integration of physical and digital versions of users, processes, and environments where entities communicate, transact, and socialize. With the shift towards Extended Reality (XR) technologies, the Metaverse is envisioned to support a wide range of applicative verticals. It will support a seamless mix of physical and virtual worlds (realities) and, thus, will be a game changer for the Future Internet, built on the Semantic Web framework. The Metaverse will be ably assisted by the convergence of emerging wireless communication networks (such as Fifth-Generation and Beyond networks) or Sixth-Generation (6G) networks, Blockchain (BC), Web 3.0, Artificial Intelligence (AI), and Non-Fungible Tokens (NFTs). It has the potential for convergence in diverse industrial applications such as digital twins, telehealth care, connected vehicles, virtual education, social networks, and financial applications. Recent studies on the Metaverse have focused on explaining its key components, but a systematic study of the Metaverse in terms of industrial applications has not yet been performed. Owing to this gap, this survey presents the salient features and assistive Metaverse technologies. We discuss a high-level and generic Metaverse framework for modern industrial cyberspace and discuss the potential challenges and future directions of the Metaverse’s realization. A case study on Metaverse-assisted Real Estate Management (REM) is presented, where the Metaverse governs a Buyer–Broker–Seller (BBS) architecture for land registrations. We discuss the performance evaluation of the current land registration ecosystem in terms of cost evaluation, trust probability, and mining cost on the BC network. The obtained results show the viability of the Metaverse in REM setups.
On-Orbit Verification of RL-Based APC Calibrations for Micrometre Level Microwave Ranging System
Authors: Wang Xiaoliang , Liu Xuan , Xiao Yun , Mao Yue , Wang Nan , Wang Wei , Wu Shufan , Song Xiaoyong , Wang Dengfeng , Zhong Xingwang , Zhu Zhu , Schilling Klaus , Damaren Christopher
Published: February 2023

Micrometre level ranging accuracy between satellites on-orbit relies on the high-precision calibration of the antenna phase center (APC), which is accomplished through properly designed calibration maneuvers batch estimation algorithms currently. However, the unmodeled perturbations of the space dynamic and sensor-induced uncertainty complicated the situation in reality; ranging accuracy especially deteriorated outside the antenna main-lobe when maneuvers performed. This paper proposes an on-orbit APC calibration method that uses a reinforcement learning (RL) process, aiming to provide the high accuracy ranging datum for onboard instruments with micrometre level. The RL process used here is an improved Temporal Difference advantage actor critic algorithm (TDAAC), which mainly focuses on two neural networks (NN) for critic and actor function. The output of the TDAAC algorithm will autonomously balance the APC calibration maneuvers amplitude and APC-observed sensitivity with an object of maximal APC estimation accuracy. The RL-based APC calibration method proposed here is fully tested in software and on-ground experiments, with an APC calibration accuracy of less than 2 mrad, and the on-orbit maneuver data from 11–12 April 2022, which achieved 1–1.5 mrad calibration accuracy after RL training. The proposed RL-based APC algorithm may extend to prove mass calibration scenes with actions feedback to attitude determination and control system (ADCS), showing flexibility of spacecraft payload applications in the future.
Comparative Study of Numerical Methods for Solving the Fresnel Integral in Aperiodic Diffractive Lenses
Authors: Garmendía-Martínez Adrián , Muñoz-Pérez Francisco M. , Furlan Walter D. , Giménez Fernando , Castro-Palacio Juan C. , Monsoriu Juan A. , Ferrando Vicente
Published: February 2023

In this work, we present a comparative analysis of different numerical methods to obtain the focusing properties of the zone plates based on Fibonacci and Cantor sequences. The Fresnel approximation was solved numerically in order to obtain the axial irradiance provided by these diffractive lenses. Two different methods were applied. The first one is based on numerical integration, specifically the Simpson integration method and the two-dimensional Gaussian quadrature. The second consisted in the implementation of the Fast Fourier Transform in both one and two dimensions. The axial irradiance of the lenses, the relative error with respect to the analytical solution, and the calculation time required by each method are analyzed and compared. From this analysis it was concluded that the Gauss method presents the best balance between accuracy and computation time. This analysis could be useful to decide the most convenient numerical method to be used for the study of more complex diffractive structures.
Geometric Approximation of Point Interactions in Two-Dimensional Domains for Non-Self-Adjoint Operators
Authors: Borisov Denis Ivanovich
Published: February 2023

We define the notion of a point interaction for general non-self-adjoint elliptic operators in planar domains. We show that such operators can be approximated in a geometric way by cutting out a small cavity around the point, at which the interaction is concentrated. On the boundary of the cavity, we impose a special Robin-type boundary condition with a nonlocal term. As the cavity shrinks to a point, the perturbed operator converges in the norm resolvent sense to a limiting one with a point interaction containing an arbitrary prescribed complex-valued coupling constant. The mentioned convergence holds in a few operator norms, and for each of these norms we establish an estimate for the convergence rate. As a corollary of the norm resolvent convergence, we prove the convergence of the spectrum.
Analysis of a Queue with General Service Demands and Multiple Servers with Variable Service Capacities
Authors: De Muynck Michiel , Bruneel Herwig , Wittevrongel Sabine
Published: February 2023

We present the study of a non-classical discrete-time queuing system in which the customers each request a variable amount of service, called their “service demand”, from a system with multiple servers, each of which can provide a variable amount of service, called their “service capacity”, in each time slot. The service demands are independent from customer to customer and follow a general distribution, whereas the service capacities follow a phase-type distribution and are independent from server to server and from slot to slot. Since an exact analytical analysis for this general queuing system is infeasible, we propose several approximations for the key performance characteristics in this system such as the mean system content and the mean customer delay in steady state. The accuracy of each of these approximations is compared to simulations using several numerical examples.
A New Alternative to Szeged, Mostar, and PI Polynomials—The SMP Polynomials
Authors: Knor Martin , Tratnik Niko
Published: February 2023

Szeged-like topological indices are well-studied distance-based molecular descriptors, which include, for example, the (edge-)Szeged index, the (edge-)Mostar index, and the (vertex-)PI index. For these indices, the corresponding polynomials were also defined, i.e., the (edge-)Szeged polynomial, the Mostar polynomial, the PI polynomial, etc. It is well known that, by evaluating the first derivative of such a polynomial at x=1, we obtain the related topological index. The aim of this paper is to introduce and investigate a new graph polynomial of two variables, which is called the SMP polynomial, such that all three vertex versions of the above-mentioned indices can be easily calculated using this polynomial. Moreover, we also define the edge-SMP polynomial, which is the edge version of the SMP polynomial. Various properties of the new polynomials are studied on some basic families of graphs, extremal problems are considered, and several open problems are stated. Then, we focus on the Cartesian product, and we show how the (edge-)SMP polynomial of the Cartesian product of n graphs can be calculated using the (weighted) SMP polynomials of its factors.
Unifying the Synthesis of a Whole Family of Marine Meroterpenoids through a Biosynthetically Inspired Sequence of 1,2-Hydride and Methyl Shifts as Key Step
Authors: Rosales Martínez Antonio , Rodríguez-Maecker Román Nicolay , Rodríguez-García Ignacio
Published: February 2023

Marine meroterpenoids have attracted a great deal of attention from synthetic research groups due to their attractive and varied biological activities and their unique and diverse structures. In most cases, however, further biological studies have been severely limited mainly to the scarcity of natural supply and because almost none of the reported syntheses methods has enabled unified access for a large number of marine meroterpenoids with aureane and avarane skeletons. Based on our previous publications and the study of recent manuscripts on marine meroterpenoids, we have conceived a unified strategy for these fascinating marine compounds with aureane or avarane skeletons using available drimane compounds as starting materials. The key step is a biosynthetic sequence of 1,2-hydride and methyl shifts. This strategy is of great synthetic value to access marine meroterpenoids through easy chemical synthetic procedures. Finally, several retrosynthetic proposals are made for the future synthesis of several members of this class of meroterpenoids, focused on consolidating these 1,2-rearrangements as a versatile and unified strategy that could be widely used in the preparation of these marine meroterpenoids.