bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Flood Damage on Urban Road Networks in Italy: The Critical Function of Underpasses
Authors: Turconi Laura , Bono Barbara , Genta Rebecca , Luino Fabio
Published: September 2024

The urban areas of Mediterranean Europe, and particularly Italy, have experienced considerable expansion since the late 19th century in terms of settlements, structures, and infrastructure, especially in large population centers. In such areas, the geohydrological risk is high not only for inhabited areas but also along roadways exposed to flooding. This scenario is worrying, especially in road underpass sections, where drivers are unlikely to perceive a real risk due to the high degree of confidence that comes from the habit of driving. Underpasses have been widely used to obviate the need to find shorter alternative routes and manage vehicular traffic in urban settings impeded by previous anthropogenic and natural constraints. To assess the numerical consistency, frequency, and areal distribution of flood risk around road underpasses, several hundred pieces of data were selected (mostly from international, national and local newspapers, CNR IRPI archive and local archives) and cataloged in a thematic database, referring mainly to the Italian territory. The behavioral aspects in the face of risk were also examined in order to provide a better understanding and raise awareness for preventive purposes. The results of this specific CNR research, which lasted about two years, confirm the exposure of underpasses to extreme risk events, affecting road users. In Italy alone, between 1942 and 2023, 698 underpasses were identified as having experienced a flooding event at least once. The database shows that 680 vehicles were involved in Italy, with a total of at least 812 individuals, of whom 19 died. Despite incomplete and uneven information, the findings of the analysis regarding the increment in underpasses flooding and the drivers action in front of a flooded underpass may be useful for undertaking the appropriate mitigation strategies.
Evaluation of Coupled Human–Natural System Coordination in Xinjiang and Analysis of Obstacle Factors
Authors: Wang Xinyun , Fang Chuanglin
Published: September 2024

The coupling and coordination of humans and natural systems, as the core of geographical research, is an important issue that social development needs to confront and explore. The study of the coupling and coordination of the human–natural system in Xinjiang, as well as the obstacles, is of great significance for its ecological environment and social development. This study establishes a multidimensional index system for the coupling of the human–natural system in Xinjiang. The comprehensive evaluation index and coupling coordination degree of the human–natural system from 2013 to 2020 were calculated, using weighted methods and a coupling coordination evaluation model. The main obstacles to the development of coupling and coordination in Xinjiang were identified, with the aid of a barrier model. The study indicates: (1) the human–natural system composed of ecological environment, urban–rural livability, cultural characteristics, civil harmony, and green development reflects the comprehensive development level of Xinjiang; (2) from 2013 to 2020, the sustainable development of the human–natural system in Xinjiang was good, with an upward trend in the evaluation index; (3) from 2013 to 2020, the level of coupling and coordination of the human–natural system in Xinjiang improved, transitioning from low to high levels; (4) from 2013 to 2020, the main factors impeding the coordinated development of the human–natural system changed. In addition to urban–rural differences and water resource conditions, medical conditions and carbon emissions also became major influencing factors on the coupling and coordination degree of the human–natural system in arid regions. Therefore, the research on the coupling and coordination relationship of the human–natural system and the analysis of obstacles in Xinjiang can provide scientific basis for the high-quality sustainable development and the construction of a beautiful Xinjiang.
Exploring Ecological Quality and Its Driving Factors in Diqing Prefecture, China, Based on Annual Remote Sensing Ecological Index and Multi-Source Data
Authors: Wang Chen , Sheng Qianqian , Zhu Zunling
Published: September 2024

The interaction between the natural environmental and socioeconomic factors is crucial for assessing the dynamics of plateau ecosystems. Therefore, the remote sensing ecological index (RSEI) and CatBoost-SHAP model were employed to investigate changes in the ecological quality and their driving factors in the Diqing Tibetan Autonomous Prefecture, China, from 2001 to 2021. The results showed an increase from 0.44 in 2001 to 0.71 in 2021 in the average RSEI for the Diqing Prefecture, indicating an overall upward trend in the ecological quality. Spatial analysis shows the percentage of the area covered by different levels of RSEI and their temporal changes. The results revealed that “good” ecological quality accounted for the largest proportion of the study area, at 42.77%, followed by “moderate” at 21.93%, and “excellent” at 16.62%. “Fair” quality areas accounted for 16.11% and “poor” quality areas only 2.57%. The study of ecological and socioeconomic drivers based on the CatBoost-SHAP framework also indicated that natural climate factors have a greater impact on ecological quality than socioeconomic factors; however, this effect differed significantly with altitude. The findings suggest that, in addition to strengthening climate monitoring, further advancements in ecological engineering are required to ensure the sustainable development of the ecosystem and the continuous improvement of the environmental quality in the Diqing Prefecture.
Understanding How People Perceive and Interact with Public Space through Social Media Big Data: A Case Study of Xiamen, China
Authors: Li Shuran , Wang Chengwei , Rong Liying , Zhou Shiqi , Wu Zhiqiang
Published: September 2024

Public space is a crucial forum for public interaction and diverse activities among urban residents. Understanding how people interact with and perceive these spaces is essential for public placemaking. With billions of users engaging in social media expression and generating millions of data points every second, Social Media Big Data (SMBD) offers an invaluable lens for evaluating public spaces over time, surpassing traditional methods like surveys and questionnaires. This research introduces a comprehensive analytical framework that integrates SMBD with placemaking practices, specifically applied to the city of Xiamen, China. The result shows the social sentiment, vibrancy heatmaps, leisure activities, visitor behaviors, and preferred visual elements of Xiamen, offering urban designers valuable insights into the dynamic nature of citizen experiences. The findings underscore the potential of SMBD to inform and enhance public space design, providing a holistic approach to creating more inclusive, vibrant, and functional urban environments.
Synergistic Use of Synthetic Aperture Radar Interferometry and Geomorphological Analysis in Slow-Moving Landslide Investigation in the Northern Apennines (Italy)
Authors: Parenti Carlotta , Grassi Francesca , Rossi Paolo , Soldati Mauro , Pattuzzi Edda , Mancini Francesco
Published: September 2024

In mountain environments, landslide activity can be assessed through a combination of remote and proximal sensing techniques performed at different scales. The complementarity of methods and the synergistic use of data can be crucial for landslide recognition and monitoring. This paper explored the potential of Multi-Temporal Differential Synthetic Aperture Radar Interferometry (MT-DInSAR) to detect and monitor slope deformations at the basin scale in a catchment area of the Northern Apennines (Italy) and verified the consistency between the landslide classification by the Inventory of Landslide Phenomena in Italy (IFFI) and displacements from the SAR data. In this research, C- and X-band SAR were considered to provide insights into the performances and suitability of sensors operating at different frequencies. This study provides clues about the state of activity of slow-moving landslides and critically assessed its contribution to the IFFI inventory update. Moreover, it demonstrated the benefits of the synergistic use of SAR and geomorphological analysis to investigate slope dynamics in clayey terrains by exemplifying the approach for a relevant case study, the Gaiato landslide. Notwithstanding the widespread use of MT-DInSAR for landslide kinematics investigations, the main limiting factors are discussed along with the expected improvements related to the upcoming new generations of L-band SAR satellites.
Intravenous Levosimendan versus Inhalational Milrinone in the Management of Pulmonary Hypertension during Adult Cardiac Surgery: A Randomized Clinical Trial
Authors: Ftikos Panagiotis , Gkantinas Georgios , Karageorgos Vlasios , Smirli Anna , Kogerakis Nektarios , Leontiadis Evangelos , Petsios Konstantinos , Antoniou Theofani , Theodoraki Kassiani
Published: September 2024

Introduction: The perioperative management of patients with pulmonary hypertension (PH) undergoing cardiac surgery is challenging, mainly due to the potential risk of right ventricular failure (RVF). Levosimendan is a calcium-sensitizing agent that has primarily been used in the treatment of decompensated heart failure. However, recently levosimendan has been shown to be an effective and safe therapeutic strategy for patients with pulmonary arterial hypertension and PH associated with left heart disease. The aim of this study was to investigate the potential utility of the preemptive administration of levosimendan in cardiac surgical patients with preexisting PH and to compare its effectiveness with milrinone, which represents an already established therapeutic option in the management of PH during cardiac surgery. Materials and Methods: In this study, 40 adult cardiac surgical patients with PH were randomly assigned to receive either levosimendan intravenously or milrinone via inhalation in a double-blind fashion prior to a cardiopulmonary bypass (CPB). Hemodynamic and echocardiographic parameters were recorded and evaluated before and after the administration of the drugs. Results and Conclusions: The results of this study demonstrated that both levosimendan and milrinone administered before CPB in cardiac surgical patients with PH may offer protective benefits, reducing pulmonary artery pressure and preventing the exacerbation of PH and RVF. Pulmonary vasodilation attributed to levosimendan is of longer duration and greater magnitude compared to pulmonary vasodilation afforded by milrinone.
From a Cup of Tea to Cardiovascular Care: Vascular Mechanisms of Action
Authors: Sagris Marios , Vlachakis Panayotis K. , Simantiris Spyridon , Theofilis Panagiotis , Gerogianni Maria , Karakasis Paschalis , Tsioufis Konstantinos , Tousoulis Dimitris
Published: September 2024

Tea consumption is increasingly recognized for its potential benefits to cardiovascular health. This study reviews the available research, concentrating on the major components of tea and their mechanisms of action in the cardiovascular system. Tea is abundant in bioactive compounds, such as flavonoids and polysaccharides, which possess significant antioxidant and anti-inflammatory properties. These compounds play a crucial role in mitigating oxidative stress and inflammation, thereby supporting cardiovascular health. They enhance endothelial function, leading to improved vascular relaxation and reduced arterial stiffness, and exhibit antithrombotic effects. Additionally, regular tea consumption is potentially associated with better regulation of blood pressure, improved cholesterol profiles, and effective blood sugar control. It has been suggested that incorporating tea into daily dietary habits could be a practical strategy for cardiovascular disease prevention and management. Despite the promising evidence, more rigorous clinical trials are needed to establish standardized consumption recommendations and fully understand long-term effects. This review offers a more comprehensive analysis of the current evidence based on endothelium function and identifies the gaps that future research should address.
Dynamic Modeling and Behavior of Cylindrical Roller Bearings Considering Roller Skew and the Influence of Eccentric Load
Authors: Yang Yang , Wang Jiayu , Wang Meiling , Wen Baogang
Published: September 2024

At high speeds, skew and skid may frequently occur for the rollers in cylindrical roller bearings, especially when under eccentric load, as the uneven load distribution along the generatrix of the roller further aggravates this phenomenon. In this paper, a dynamic model of a cylindrical roller bearing was established, taking into account roller skewing and interactions with the cage. Firstly, the interaction between the roller and the raceway was calculated by slicing the roller along its generatrix. Furthermore, the computation of the interaction between the roller and the cage is based on elastic theory, taking into account pocket clearance. Subsequently, the dynamic equations for both rollers and cage were derived. Based on this foundation, an investigation was conducted to reveal how rotational speed, radial loads, and moment loads affect roller slipping, skewing characteristics, and interactions with the cage under uneven load conditions. The findings indicate a direct proportionality between roller slipping and bearing speed while exhibiting an inverse relationship with load magnitude. Additionally, it was observed that both bearing speed and load have a direct influence on roller skewing angle. Moreover, normal interaction force between the roller and cage demonstrates a direct proportionality to bearing speed while inversely correlating with load magnitude.
Vibration Friction Investigation on the NCS of Joints of the CNC Machine Tools Considering Friction Factor
Authors: Teng Yunnan , Liu Xiangpu , Xie Liyang
Published: September 2024

Machine tool vibrations play a significant role in hindering productivity during machining. The growing vibrations accelerate tool wear and chipping, cause a poor wave surface finish, and may damage the spindle bearing. Some research showed that tribological properties such as friction factors can have obvious influences on the topography of rough surfaces and the nonlinear dynamic characteristics of machine tool systems. Therefore, studying the vibration friction dynamic characteristics on the normal contact stiffness (NCS) of joints of CNC machine tools is absolutely necessary for improving the machining accuracy and precision of the whole system. The study results of NCS of joints of the CNC and the friction coefficient are discussed in this paper. The model of NCS based on fractal parameters was obtained. The models of deformations of the rough surfaces and contact surfaces were deduced. The results showed that the NCS based on the calculation method considering the elastic–plastic deformation of the asperity is much higher in precision than the methods considering only elastic or plastic deformation separately. The observations this paper described suggest that in the CNC machine tools system, higher D and G and higher friction coefficients lead to higher normal contact stresses (NCSs).
Study on the Performance of Epoxy-Modified Asphalt and Steel Slag Ultra-Thin Friction Course
Authors: Zhang Quanmin , Lu Ziyu , Chen Anqi , Wu Shaopeng , Feng Jianlin , Xu Haiqin , Li Yuanyuan
Published: September 2024

Ultra-thin overlays (UTOL) are a standard highway pre-maintenance method used to improve the road surface performance of asphalt pavements and to repair minor rutting and cracking. However, the thin thickness makes it very sensitive to external changes, which increases its wear and shortens its life. So, this paper aims to prepare a durable and skid-resistance asphalt ultra-thin overlay using epoxy asphalt (EA) and steel slag. First, the physical properties of EA were characterized by penetration, softening point, flexibility, and kinematic viscosity tests. The dynamic shear rheometer (DSR) test characterizes EA’s rheological properties. Differential Scanning Calorimetry (DSC), kinematic viscosity, and Fourier transform infrared spectroscopy (FTIR) characterized the EA’s curing process. Finally, the pavement performance of an epoxy ultra-thin overlay (EUTOL) prepared with EA and steel slag was tested. The results show that the epoxy resin particles increase with the increase in epoxy resin dosage, and at 40%, its epoxy particles are uniformly distributed with the most significant area share. With the addition of epoxy resin, the needle penetration of EA decreases and then increases, the flexibility decreases at a slower rate, and the softening point rises significantly. Moreover, the growth of the elastic component in EA significantly improved the high-temperature viscoelastic properties. Considering its physical and rheological properties, the optimal doping amount of 40% was selected. By analyzing the curing behavior of EA (optimum dosage), the combination temperature of EA is 150 °C, which meets the needs of mixing and paving asphalt mixtures. After 12 h of maintenance at 120 °C, its reaction is sufficient. The skid-resistance durability, high-temperature, low-temperature, water stability, and fatigue resistance of UTOL can be effectively improved using steel slag coarse aggregate.
Calcined Clays as Concrete Additive in Structural Concrete: Workability, Mechanical Properties, Durability, and Sustainability Performance
Authors: Strybny Bastian , Schack Tobias , Link Julian , Haist Michael
Published: September 2024

Calcined clays (CCs) as supplementary cementitious materials (SCMs) can be a promising option to reduce clinker content and CO2 emissions in eco-friendly concretes. Although CCs as components of composite cements in combination with Ordinary Portland Cement (OPC) and limestone powder (LSP) have attracted industry interest, their use as concrete additives is limited. This study investigates the effects of the addition of CCs on the fresh and hardened properties of industry-standard ready-mixed concretes. Four concrete mix designs, each with three superplasticizer dosages, were tested, resulting in 12 variations. The CCs used, which are typical of 2:1 bentonite clays with low metakaolin content, reflect the clays available in Germany. The results showed that CCs significantly influenced the workability, which could be controlled with a high superplasticizer dosage. Increased CC contents reduced bleeding tendencies, which was beneficial for certain structural applications. Early age strength decreased with CCs, but the 28-day strength exceeded that of pure OPC concretes up to 30 wt% CCs. Resistance to CO2-induced carbonation decreased with higher levels of CCs but was comparable up to 15 wt%. Freeze–thaw damage decreased, and chloride migration resistance improved due to a denser microstructure. The global warming potential (GWP) of the concretes tested is in line with that reported in the literature for concretes made from highly blended cements, suggesting that CCs can improve the sustainability of concrete production.
Fabrication of Silicon Carbide Nanoparticles Using Pulsed Laser Ablation in Liquid and Viscosity Optimization via Solvent Tuning
Authors: Heidarinassab Saeid , Nyabadza Anesu , Ahad Inam Ul , Brabazon Dermot
Published: September 2024

In this study, silicon carbide nanoparticles (NPs) were produced via pulsed laser ablation in liquid, aiming to investigate the influence of processing parameters on the properties of the resultant NPs and their applicability for inkjet printing. The results revealed an increase in NP concentration with increasing laser power, but the maximal absorbance in the case of 0.743 and 1.505 W is lower than that for 1.282 W laser. Dynamic light scattering was employed to determine the size distribution of the NPs, demonstrating a range of 89 to 155 nm in diameter. Notably, an inverse relationship was established between increasing laser scanning speed and pulse repetition rate (PRR) and the mean size of the NPs. Higher PRR and laser power exhibited an augmentation in the concentration of NPs. Conversely, an increase in scanning speed resulted in a reduction in NP concentration. Based on FTIR, data formation of SiC NPs based on the target material is the most dominant behavior observed followed by an amount of oxidation of the NPs. Examination of the resulting NPs through field emission scanning electron microscopy equipped with energy-dispersive X-ray analysis (EDX) unveiled a predominantly spherical morphology, accompanied by particle agglomeration in some cases, and the elemental composition showed silicon, carbon, and some oxygen present in the resulting NPs. Furthermore, the modulation of colloidal solution viscosity was explored by incorporating glycerol, yielding a maximal viscosity of 10.95 mPa·s.
The Influence of Thermomechanical Conditions on the Hot Ductility of Continuously Cast Microalloyed Steels
Authors: Sharifi Saham Sadat , Bakhtiari Saeid , Shahryari Esmaeil , Sommitsch Christof , Poletti Maria Cecilia
Published: September 2024

Continuous casting is the most common method for producing steel into semi-finished shapes like billets or slabs. Throughout this process, steel experiences mechanical and thermal stresses, which influence its mechanical properties. During continuous casting, decreased formability in steel components leads to crack formation and failure. One reason for this phenomenon is the appearance of the soft ferrite phase during cooling. However, it is unclear under which conditions this ferrite is detrimental to the formability. In the present research, we investigated what microstructural changes decrease the formability of microalloyed steels during continuous casting. We studied the hot compression behaviour of microalloyed steel over temperatures ranging from 650 °C to 1100 °C and strain rates of 0.1 s−1 to 0.001 s−1 using a Gleeble 3800® (Dynamic Systems Inc, Poestenkill, NY, USA) device. We examined microstructural changes at various deformation conditions using microscopy. Furthermore, we implemented a physically-based model to describe the deformation of austenite and ferrite. The model describes the work hardening and dynamic restoration mechanisms, i.e., discontinuous dynamic recrystallisation in austenite and dynamic recovery in ferrite and austenite. The model considers the stress, strain, and strain rate distribution between phases by describing the dynamic phase transformation during the deformation in iso-work conditions. Increasing the strain rate below the transformation temperature improves hot ductility by reducing dynamic recovery and strain concentration in ferrite. Due to limited grain boundary sliding, the hot ductility improves at lower temperatures (<750 °C). In the single-phase domain, dynamic recrystallisation improves the hot ductility provided that fracture occurs at strains in which dynamic recrystallisation advances. However, at very low strain rates, the ductility decreases due to prolonged time for grain boundary sliding and crack propagation.
Calculation of Wear of Railway Wheels with Multibody Codes: Benchmarking of the Modelling Choices
Authors: Magelli Matteo , Zampieri Nicolò
Published: September 2024

The numerical simulation of wear of railway wheel profiles can be a game changer in the railway field, as it can drive the planning of wheel re-turning operations, thrust the identification of optimized profiles and evaluate the safety of railway vehicles at the early stages of design. Today, commercial multibody codes are provided with dedicated routines that can evaluate the worn profile shape due to the dynamic behaviour of the vehicle. As the outputs of such modules can depend on different user-selectable parameters and modelling choices, it is vital to assess the capabilities of these codes and get a further understanding of the implemented algorithms. This paper aims to benchmark the effects of different modelling parameters and choices, mainly related to the selected wear law and wheel–rail contact method, on the final wear outputs, with special reference to the wear module provided by the SIMPACK commercial multibody code. A relevant novelty of the paper deals with the benchmarking of the wear algorithm available in the commercial code with in-house wear routines, comparing different strategies and choices for the calculation of wear. This allows us to better understand the most critical differences and modelling issues, as well as to highlight possible improvements in wear algorithms that can lead to enhanced numerical stability. More in detail, this work suggests a change in the wear algorithm that proves to be beneficial to removing local wear peaks produced by numerical sources, which could cause instabilities in the computation.
Multidimensional Taxonomies for Research, Development, and Implementation of Electric Aircraft Ecosystem
Authors: Kabashkin Igor
Published: September 2024

The electrification of aviation represents a significant technological frontier, promising substantial advancements in sustainable transportation. This paper presents a comprehensive set of taxonomies that systematically categorize and analyze the multifaceted aspects of electric aviation, with a particular focus on machine-related components and systems. It provides detailed classifications of electric aircraft propulsion systems, power management architectures, and energy storage technologies, offering insight into their design, functionality, and integration challenges. The paper explores the ecosystem of electric aviation, including key stakeholders, use cases, and enabling technologies, which are vital for coordinating machine development strategies and fostering sustainable growth. The creation of business models that cater to the dynamic nature of the industry, emphasizing the role of innovative machine designs in shaping market adoption are discussed in the paper. The study highlights the importance of electric aviation for regional development, outlining predictive models for regional market development that consider machine capabilities and infrastructure requirements.
Methods of Multi-Criteria Optimization of Technological Processes in a Fuzzy Environment Based on the Simplex Method and the Theory of Fuzzy Sets
Authors: Orazbayev Batyr , Orazbayeva Kulman , Ospanov Yerbol , Suleimenova Salamat , Kurmangaziyeva Lyailya , Makhatova Valentina , Izbassarov Yerlan , Otebaeva Aigerim
Published: September 2024

Many modern technological objects in practice are characterized by the uncertainty of the initial information necessary for their management. Recently, one of the pressing scientific and practical problems is the development of new optimization methods for controlling the operating modes of such objects in a fuzzy environment. In this regard, the objective of this study is to develop methods of multi-criteria optimization in a fuzzy environment by modifying the simplex method and various optimality principles based on fuzzy mathematics methods. The methodology of the proposed study is based on a hybrid approach, which consists of the integrated use and modification of simplex methods and optimization methods with various optimality principles for working in a fuzzy environment. The main results are as follows: a simplex method of multi-criteria optimization of immeasurable criteria (here, we are talking about the impossibility of physical measurements of criteria, the values of which are estimated by decision maker); a theorem on the convergence of the solution sequence obtained using the proposed method to the minimum value of the criteria; a heuristic method based on a modification for fuzziness and a combination of the maximin and Pareto optimality principles, which allows effectively solving multi-criteria optimization problems in a fuzzy environment. The heuristic method proposed will be used to solve a real production problem—optimization of the technological process of benzene production.
Absolute Monotonicity of Normalized Tail of Power Series Expansion of Exponential Function
Authors: Qi Feng
Published: September 2024

In this work, the author reviews the origination of normalized tails of the Maclaurin power series expansions of infinitely differentiable functions, presents that the ratio between two normalized tails of the Maclaurin power series expansion of the exponential function is decreasing on the positive axis, and proves that the normalized tail of the Maclaurin power series expansion of the exponential function is absolutely monotonic on the whole real axis.
Generalizations of the Kantorovich and Wielandt Inequalities with Applications to Statistics
Authors: Zhang Yunzhi , Guo Xiaotian , Liu Jianzhong , Chen Xueping
Published: September 2024

By utilizing the properties of positive definite matrices, mathematical expectations, and positive linear functionals in matrix space, the Kantorovich inequality and Wielandt inequality for positive definite matrices and random variables are obtained. Some novel Kantorovich type inequalities pertaining to matrix ordinary products, Hadamard products, and mathematical expectations of random variables are provided. Furthermore, several interesting unified and generalized forms of the Wielandt inequality for positive definite matrices are also studied. These derived inequalities are then exploited to establish an inequality regarding various correlation coefficients and study some applications in the relative efficiency of parameter estimation of linear statistical models.
A Family of Conditionally Explicit Methods for Second-Order ODEs and DAEs: Application in Multibody Dynamics
Authors: Fernández de Bustos Igor , Uriarte Haritz , Urkullu Gorka , Coria Ibai
Published: September 2024

There are several common procedures used to numerically integrate second-order ordinary differential equations. The most common one is to reduce the equation’s order by duplicating the number of variables. This allows one to take advantage of the family of Runge–Kutta methods or the Adams family of multi-step methods. Another approach is the use of methods that have been developed to directly integrate an ordinary differential equation without increasing the number of variables. An important drawback when using Runge–Kutta methods is that when one tries to apply them to differential algebraic equations, they require a reduction in the index, leading to a need for stabilization methods to remove the drift. In this paper, a new family of methods for the direct integration of second-order ordinary differential equations is presented. These methods can be considered as a generalization of the central differences method. The methods are classified according to the number of derivatives they take into account (degree). They include some parameters that can be chosen to configure the equation’s behavior. Some sets of parameters were studied, and some examples belonging to structural dynamics and multibody dynamics are presented. An example of the application of the method to a differential algebraic equation is also included.
A New Class of Reduced-Bias Generalized Hill Estimators
Authors: Henriques-Rodrigues Lígia , Caeiro Frederico , Gomes M. Ivette
Published: September 2024

The estimation of the extreme value index (EVI) is a crucial task in the field of statistics of extremes, as it provides valuable insights into the tail behavior of a distribution. For models with a Pareto-type tail, the Hill estimator is a popular choice. However, this estimator is susceptible to bias, which can lead to inaccurate estimations of the EVI, impacting the reliability of risk assessments and decision-making processes. This paper introduces a novel reduced-bias generalized Hill estimator, which aims to enhance the accuracy of EVI estimation by mitigating the bias.
Nonlinear Complex Wave Excitations in (2+1)-Dimensional Klein–Gordon Equation Investigated by New Wave Transformation
Authors: Wu Guojiang , Guo Yong , Yu Yanlin
Published: September 2024

The Klein–Gordon equation plays an important role in mathematical physics, such as plasma and, condensed matter physics. Exploring its exact solution helps us understand its complex nonlinear wave phenomena. In this paper, we first propose a new extended Jacobian elliptic function expansion method for constructing rich exact periodic wave solutions of the (2+1)-dimensional Klein–Gordon equation. Then, we introduce a novel wave transformation for constructing nonlinear complex waves. To demonstrate the effectiveness of this method, we numerically simulated several sets of complex wave structures, which indicate new types of complex wave phenomena. The results show that this method is simple and effective for constructing rich exact solutions and complex nonlinear wave phenomena to nonlinear equations.
MISAO: A Multi-Strategy Improved Snow Ablation Optimizer for Unmanned Aerial Vehicle Path Planning
Authors: Zhou Cuiping , Li Shaobo , Xie Cankun , Yuan Panliang , Long Xiangfu
Published: September 2024

The snow ablation optimizer (SAO) is a meta-heuristic technique used to seek the best solution for sophisticated problems. In response to the defects in the SAO algorithm, which has poor search efficiency and is prone to getting trapped in local optima, this article suggests a multi-strategy improved (MISAO) snow ablation optimizer. It is employed in the unmanned aerial vehicle (UAV) path planning issue. To begin with, the tent chaos and elite reverse learning initialization strategies are merged to extend the diversity of the population; secondly, a greedy selection method is deployed to retain superior alternative solutions for the upcoming iteration; then, the Harris hawk (HHO) strategy is introduced to enhance the exploitation capability, which prevents trapping in partial ideals; finally, the red-tailed hawk (RTH) is adopted to perform the global exploration, which, enhances global optimization capability. To comprehensively evaluate MISAO’s optimization capability, a battery of digital optimization investigations is executed using 23 test functions, and the results of the comparative analysis show that the suggested algorithm has high solving accuracy and convergence velocity. Finally, the effectiveness and feasibility of the optimization path of the MISAO algorithm are demonstrated in the UAV path planning project.
Multi-Type Self-Attention-Based Convolutional-Neural-Network Post-Filtering for AV1 Codec
Authors: Gwun Woowoen , Choi Kiho , Park Gwang Hoon
Published: September 2024

Over the past few years, there has been substantial interest and research activity surrounding the application of Convolutional Neural Networks (CNNs) for post-filtering in video coding. Most current research efforts have focused on using CNNs with various kernel sizes for post-filtering, primarily concentrating on High-Efficiency Video Coding/H.265 (HEVC) and Versatile Video Coding/H.266 (VVC). This narrow focus has limited the exploration and application of these techniques to other video coding standards such as AV1, developed by the Alliance for Open Media, which offers excellent compression efficiency, reducing bandwidth usage and improving video quality, making it highly attractive for modern streaming and media applications. This paper introduces a novel approach that extends beyond traditional CNN methods by integrating three different self-attention layers into the CNN framework. Applied to the AV1 codec, the proposed method significantly improves video quality by incorporating these distinct self-attention layers. This enhancement demonstrates the potential of self-attention mechanisms to revolutionize post-filtering techniques in video coding beyond the limitations of convolution-based methods. The experimental results show that the proposed network achieves an average BD-rate reduction of 10.40% for the Luma component and 19.22% and 16.52% for the Chroma components compared to the AV1 anchor. Visual quality assessments further validated the effectiveness of our approach, showcasing substantial artifact reduction and detail enhancement in videos.
New Geometric Theorems Derived from Integral Equations Applied to Radiative Transfer in Spherical Sectors and Circular Segments
Authors: Cabeza-Lainez Joseph
Published: September 2024

Semicircles and circular sectors are both ubiquitous in the natural realm. However, mathematically speaking they have represented an enigma since antiquity. In recent years, the author has worked in integral equations with sections of spheres as related to radiative heat transfer and their associated form factors, to the point of defining new postulates. The main theorems thus far enunciated refer to the radiative exchange between circles and half disks, but recently the possibility to treat circular sectors has arrived, thanks to the research already conducted. As is known, to find the exact expression of the configuration factor by integration is complex. In the above mentioned problem of the circular sectors, the author reached the first two steps of the basic formulation for radiant exchange. Subsequently, the novelty of the procedure lies in introducing a finite differences approach for the third and fourth integrals which still remain unsolved, once we have been able to find the preliminary integrals. This possibility had not been identified by former research and the output provides us with an ample variety of unexpected scenarios. As a consequence, we are able to analyze with more precision the spatial transference of radiant heat for figures composed of circular sectors. We already know that spherical shapes cannot be discretized with any accuracy. Therefore, we would be able to reduce a considerable amount of hindrance in the progress of thermal radiation science. Important sequels will be derived for radiation in the entrance to tunnels, aircraft design and lighting as well.
Mathematical Formulations for Predicting Pressure Drop in Solid–Liquid Slurry Flow through a Straight Pipe Using Computational Modeling
Authors: Joshi Tanuj , Gupta Abhinav , Parkash Om , Gallegos Ralph Kristoffer B. , Oo Nay Lin , Krishan Gopal
Published: September 2024

The study establishes two mathematical formulations to predict the pressure drop in a solid–liquid slurry flowing through a straight pipe. Employing the Eulerian–Eulerian RNG k-ε model, the computational investigation uses water as the carrier fluid and glass beads as solid particles. The analysis spans various particle sizes (d50 = 75–175 μm), volumetric concentrations (Cvf = 10–50%), and velocities (Vm = 1–5 m/s). The first model, developed using the MATLAB curve-fitting tool, is complemented by a second empirical equation derived through non-polynomial mathematical formulation. Results from both models are validated against existing experimental and computational data, demonstrating accurate predictions for d50 = 75–175 µm particles within a Reynolds number range of 20,000 ≤ Re ≤ 320,000.
Data-Driven Modeling and Open-Circuit Voltage Estimation of Lithium-Ion Batteries
Authors: Silva-Vera Edgar D. , Valdez-Resendiz Jesus E. , Escobar Gerardo , Guillen Daniel , Rosas-Caro Julio C. , Sosa Jose M.
Published: September 2024

This article presents a data-driven methodology for modeling lithium-ion batteries, which includes the estimation of the open-circuit voltage and state of charge. Using the proposed methodology, the dynamics of a battery cell can be captured without the need for explicit theoretical models. This approach only requires the acquisition of two easily measurable variables: the discharge current and the terminal voltage. The acquired data are used to build a linear differential system, which is algebraically manipulated to form a space-state representation of the battery cell. The resulting model was tested and compared against real discharging curves. Preliminary results showed that the battery’s state of charge can be computed with limited precision using a model that considers a constant open-circuit voltage. To improve the accuracy of the identified model, a modified recursive least-squares algorithm is implemented inside the data-driven method to estimate the battery’s open-circuit voltage. These last results showed a very precise tracking of the real battery discharging dynamics, including the terminal voltage and state of charge. The proposed data-driven methodology could simplify the implementation of adaptive control strategies in larger-scale solutions and battery management systems with the interconnection of multiple battery cells.
On Signifiable Computability: Part I: Signification of Real Numbers, Sequences, and Types
Authors: Kulyukin Vladimir A.
Published: September 2024

Signifiable computability aims to separate what is theoretically computable from what is computable through performable processes on computers with finite amounts of memory. Real numbers and sequences thereof, data types, and instances are treated as finite texts, and memory limitations are made explicit through a requirement that the texts be stored in the available memory on the devices that manipulate them. In Part I of our investigation, we define the concepts of signification and reference of real numbers. We extend signification to number tuples, data types, and data instances and show that data structures representable as tuples of discretely finite numbers are signifiable. From the signification of real tuples, we proceed to the constructive signification of multidimensional matrices and show that any data structure representable as a multidimensional matrix of discretely finite numbers is signifiable.
HyperCLR: A Personalized Sequential Recommendation Algorithm Based on Hypergraph and Contrastive Learning
Authors: Zhang Ruiqi , Wang Haitao , He Jianfeng
Published: September 2024

Sequential recommendations aim to predict users’ next interactions by modeling their interaction sequences. Most existing work concentrates on user preferences within these sequences, overlooking the complex item relationships across sequences. Additionally, these studies often fail to address the diversity of user interests, thus not capturing their varied latent preferences effectively. To tackle these problems, this paper develops a novel recommendation algorithm based on hypergraphs and contrastive learning named HyperCLR. It dynamically incorporates the time and location embeddings of items to model high-order relationships in user preferences. Moreover, we developed a graph construction approach named IFDG, which utilizes global item visit frequencies and spatial distances to discern item relevancy. By sampling subgraphs from IFDG, HyperCLR can align the representations of identical interaction sequences closely while distinguishing them from the broader global context on IFDG. This approach enhances the accuracy of sequential recommendations. Furthermore, a gating mechanism is designed to tailor the global context information to individual user preferences. Extensive experiments on Taobao, Books and Games datasets have shown that HyperCLR consistently surpasses baselines, demonstrating the effectiveness of the method. In particular, in comparison to the best baseline methods, HyperCLR demonstrated a 29.1% improvement in performance on the Taobao dataset.
On Properties of the Hyperbolic Distribution
Authors: Ivanov Roman V.
Published: September 2024

This paper is set to analytically describe properties of the hyperbolic distribution. This law, along with the variance-gamma distribution, is one of the most popular normal mean–variance mixtures from the point of view of various applications. We have found closed form expressions for the cumulative distribution and partial-moment-generating functions of the hyperbolic distribution. The obtained formulas use the values of the Humbert confluent hypergeometric and Whittaker special functions. The results are applied to the problem of European option pricing in the related Lévy model of financial market. The research demonstrates that the discussed normal mean–variance mixture is analytically tractable.
Strong Convergence of Euler-Type Methods for Nonlinear Fractional Stochastic Differential Equations without Singular Kernel
Authors: Ali Zakaria , Abebe Minyahil Abera , Nazir Talat
Published: September 2024

In this paper, we first prove the existence and uniqueness of the solution to a variable-order Caputo–Fabrizio fractional stochastic differential equation driven by a multiplicative white noise, which describes random phenomena with non-local effects and non-singular kernels. The Euler–Maruyama scheme is extended to develop the Euler–Maruyama method, and the strong convergence of the proposed method is demonstrated. The main difference between our work and the existing literature is the fact that our assumptions on the nonlinear external forces are those of one-sided Lipschitz conditions on both the drift and the nonlinear intensity of the noise as well as the proofs of the higher integrability of the solution and the approximating sequence. Finally, to validate the numerical approach, current results from the numerical implementation are presented to test the efficiency of the scheme used in order to substantiate the theoretical analysis.
The Impact of Vitamin D Receptor Gene Polymorphisms (FokI, ApaI, TaqI) in Correlation with Oxidative Stress and Hormonal and Dermatologic Manifestations in Polycystic Ovary Syndrome
Authors: Talida Vulcan , Tudor Suciu Sergiu , Mihaela Iancu , Daniela-Rodica Mitrea , Gabriela A. Filip , Lucia Maria Procopciuc
Published: September 2024

Background and Objectives: Polycystic ovary syndrome (PCOS) is a frequent and complex multidisciplinary disorder. Data regarding the role of genes involved in vitamin D metabolism in PCOS are as-yet elusive but suggest an association of VDR (vitamin D receptor) and vitamin D levels with metabolic, endocrine and cutaneous manifestations. The aim of this study was to evaluate the association between VDR gene polymorphisms and cutaneous manifestations, to find a correlation between hormonal parameters, oxidative stress and skin manifestations in women with PCOS, and to determine the impact of VDR gene polymorphisms on these parameters. Materials and Methods: This case–control study included 39 controls and 46 women with PCOS, matched by age and BMI distribution. Acne, hirsutism, seborrhea, androgenetic alopecia, oxidative stress and androgen hormones were recorded. VDR gene polymorphisms ApaI, FokI and TaqI were examined by polymerase chain reaction restriction fragment length polymorphism, and the androgen hormone (total testosterone, DHEAS), SHBG and malondialdehyde levels were assessed. Results: The most frequent skin manifestations in PCOS cases were acne followed by seborrhea, hirsutism and androgenic alopecia. The VDR-FokI polymorphism CC genotype had a significant protective role in the odds of acne (OR = 0.11, 95% CI: [0.02, 0.70], p = 0.015, p-corrected = 0.040) and seborrhea (OR = 0.15, 95% CI: [0.03, 0.75], p = 0.019, p-corrected = 0.039). The results demonstrated a significant protective effect of the C allele on the odds of acne and seborrhea in PCOS cases. Moreover, the dominant genotype of VDR-TaqI could have a protective role against oxidative stress (lower MDA levels) compared to patients carrying the TT genotype. Conclusions: In summary, this is the first study to demonstrate that the FokI CC genotype may have a protective role against both acne and seborrhea in women with PCOS, while the VDR-TaqI dominant genotype is associated with diminished oxidative stress in PCOS patients.