bluuebunny/crossref_metadata_2025 huggingface dataset:
Endothelial Dysfunction and Heart Failure with Preserved Ejection Fraction—An Updated Review of the Literature
Authors: De Luca Mariarosaria , Crisci Giulia , Armentaro Giuseppe , Cicco Sebastiano , Talerico Giovanni , Bobbio Emanuele , Lanzafame Lorena , Green Christopher G. , McLellan Abbie G. , Debiec Radek , Caferra Paolo , Scicali Roberto , Cannatà Antonio , Israr Muhammad Zubair , Heaney Liam M. , Salzano Andrea
Published: December 2023

Heart failure (HF) is a clinical syndrome consisting of typical symptoms and signs due to structural and/or functional abnormalities of the heart, resulting in elevated intracardiac pressures and/or inadequate cardiac output. The vascular system plays a crucial role in the development and progression of HF regardless of ejection fraction, with endothelial dysfunction (ED) as one of the principal features of HF. The main ED manifestations (i.e., impaired endothelium-dependent vasodilation, increased oxidative stress, chronic inflammation, leukocyte adhesion, and endothelial cell senescence) affect the systemic and pulmonary haemodynamic and the renal and coronary circulation. The present review is aimed to discuss the contribution of ED to HF pathophysiology—in particular, HF with preserved ejection fraction—ED role in HF patients, and the possible effects of pharmacological and non-pharmacological approaches. For this purpose, relevant data from a literature search (PubMed, Scopus, EMBASE, and Medline) were reviewed. As a result, ED, assessed via venous occlusion plethysmography or flow-mediated dilation, was shown to be independently associated with poor outcomes in HF patients (e.g., mortality, cardiovascular events, and hospitalization due to worsening HF). In addition, SGLT2 inhibitors, endothelin antagonists, endothelial nitric oxide synthase cofactors, antioxidants, and exercise training were shown to positively modulate ED in HF. Despite the need for future research to better clarify the role of the vascular endothelium in HF, ED represents an interesting and promising potential therapeutic target.
Loss of Human Epidermal Receptor 2 Expression in Formalin-Fixed Paraffin-Embedded Breast Cancer Samples and the Rescuing Effect of Enhanced Antigen Retrieval and Signal Amplification
Authors: Ma Xiuli , Zhou Lixin , Wu Qi , Jia Ling , Diao Xinting , Kang Qiang , Huang Xiaozheng , Liu Yiqiang , Hu Taobo , Long Mengping
Published: December 2023

As an important therapeutic target in breast cancer, HER2 expression assessed by immunohistochemistry plays a critical role in breast cancer treatment. Recent advances in HER2 antibody–drug conjugate therapy have enabled patients with HER2-low expression breast cancer to benefit from the drugs. However, it is not known whether the HER2-low expression in breast cancer FFPE blocks would be lost as storage time increased. In this study, we aimed to assess the loss of HER2 antigenicity in stored FFPE blocks of breast cancer and the rescue effect of modifying the protocol of antigen staining. We selected archived HER2-low breast cancer FFPE blocks with stored time ranging from 1 year to over 15 years and re-detected the expression of HER2. Our study showed that HER2 antigenicity loss increased with storage time and could cause false negativity in HER2-low detection. Moreover, we showed that by either increasing the antigen retrieval time or applying the tyramide signal amplification (TSA) kit, the HER2 signal can be rescued and detected in about half of the cases with HER2-low loss without causing false positivity.
A Novel COCH p.D544Vfs*3 Variant Associated with DFNA9 Sensorineural Hearing Loss Causes Pathological Multimeric Cochlin Formation
Authors: Peng Yingqiu , Xiang Mengya , Fan Ting , Zhong Xiaofang , Dai Aqiang , Feng Jialing , Guan Pengfei , Gong Jiamin , Li Jian , Wang Yunfeng
Published: December 2023

COCH (coagulation factor C homology) is one of the most frequently mutated genes of autosomal dominant non-syndromic hearing loss. Variants in COCH could cause DFNA9, which is characterized by late-onset hearing loss with variable degrees of vestibular dysfunction. In this study, we report a Chinese family with a novel COCH variant (c.1687delA) causing p.D544Vfs*3 in the cochlin. Comprehensive audiometric tests and vestibular function assessments were taken to acquire the phenotypic profile of the subjects. Next-generation sequencing was conducted and segregation analysis was carried out using Sanger sequencing. The proband presented mild vestibular symptoms and normal functional assessment results in almost every test, while the variant co-segregated with hearing impairment in the pedigree. The variant was located beyond the vWFA2 domain, which was predicted to affect the post-translational cleavage of the cochlin via molecular modeling analysis. Notably, in the overexpressing study, by transient transfecting the HEK 293T cells, we found that the p.D544Vfs*3 variant increased the formation of multimeric cochlin. Our result enriched the spectrum of DFNA9-linked pathological COCH variants and suggested that variants, causative of cochlin multimerization, could be related to DFNA9 with sensorineural hearing loss rather than serious vestibular symptoms.
Effect of Nb Addition on the Corrosion and Wear Resistance of Laser Clad AlCr2FeCoNi High-Entropy Alloy Coatings
Authors: Ji Xiulin , Guan Kunpeng , Bao Yayun , Mao Zhongfa , Wang Fengtao , Dai Houfu
Published: December 2023

Laser clad AlCr2FeCoNiNbx (x = 0, 0.5, 1.0, 1.5, 2.0, with x values in molar ratio) high-entropy alloy (HEA) coatings were fabricated on Q345 carbon steel. This study delves into the impact of Nb incorporation on the reciprocating sliding wear resistance of these laser clad coatings against a Φ6 mm silicon nitride ball. The microstructure of the as-clad AlCr2FeCoNiNbx coatings transformed from a single Face-Centered Cubic (FCC) solid solution (when x = 0) to the hypoeutectic state (when x = 0.5) and progressed to the hypereutectic state (when x ≥ 1.0). This evolution was marked by an increase in the Laves phase and a decrease in FCC. Consequently, the HEA coatings exhibited a gradually increasing Vickers hardness, reaching a peak at HV 820. Despite a decline in corrosion resistance, there was a notable enhancement in wear resistance, and the friction of the HEA coating could be reduced by Nb addition. The phase evolution induced by Nb addition led to a shift in the predominant wear mechanism from delamination wear to abrasive wear. The wear rate of Nb0.5 was impressively low, at 6.2 × 10−6 mm N−1 m−1 when reciprocating sliding under 20 N in air. In comparison to Nb0, Nb0.5 showcased 3.6, 7.2, and 6.5 times higher wear resistance at 5 N, 10 N, and 20 N, respectively. Under all applied loads, Nb1.5 has the lowest wear rate among all HEA coatings. This substantiates that the subtle introduction of Laves phase-forming elements to modulate hardness and oxidation ability proves to be an effective strategy for improving the wear resistance of HEA coatings.
Self-Assembly TiO2-Ti3C2Tx Ball–Plate Structure for Highly Efficient Electromagnetic Interference Shielding
Authors: Zhang Zhen , Ning Xingyang , Liu Bin , Zhou Jian , Sun Zhimei
Published: December 2023

MXene is a promising candidate for the next generation of lightweight electromagnetic interference (EMI) materials owing to its low density, excellent conductivity, hydrophilic properties, and adjustable component structure. However, MXene lacks interlayer support and tends to agglomerate, leading to a shorter service life and limiting its development in thin-layer electromagnetic shielding material. In this study, we designed self-assembled TiO2-Ti3C2Tx materials with a ball–plate structure to mitigate agglomeration and obtain a thin-layer and multiple absorption porous materials for high-efficiency EMI shielding. The TiO2-Ti3C2Tx composite with a thickness of 50 μm achieved a shielding efficiency of 72 dB. It was demonstrated that the ball–plate structure generates additional interlayer cavities and internal interface, increasing the propagation path for an electromagnetic wave, which, in turn, raises the capacity of materials to absorb and dissipate the wave. These effects improve the overall EMI shielding performance of MXene and pave the way for the development of the next-generation EMI shielding system.
Research Progress in Special Engineering Plastic-Based Electrochromic Polymers
Authors: Liu Yixuan , Xing Zhen , Jia Songrui , Shi Xiangfu , Chen Zheng , Jiang Zhenhua
Published: December 2023

SPECPs are electrochromic polymers that contain special engineering plastic structural characteristic groups (SPECPs). Due to their high thermal stability, mechanical properties, and weather resistance, they are also known as high-performance electrochromic polymer (HPEP or HPP). Meanwhile, due to the structural characteristics of their long polymer chains, these materials have natural advantages in the application of flexible electrochromic devices. According to the structure of special engineering plastic groups, SPECPs are divided into five categories: polyamide, polyimide, polyamide imide, polyarylsulfone, and polyarylketone. This article mainly introduces the latest research on SPECPs. The structural design, electrochromic properties, and applications of these materials are also introduced in this article, and the challenges and future development trends of SPECPs are prospected.
A Comparative Study between Blended Polymers and Copolymers as Emitting Layers for Single-Layer White Organic Light-Emitting Diodes
Authors: Tselekidou Despoina , Papadopoulos Kyparisis , Foris Vasileios , Kyriazopoulos Vasileios , Andrikopoulos Konstantinos C. , Andreopoulou Aikaterini K. , Kallitsis Joannis K. , Laskarakis Argiris , Logothetidis Stergios , Gioti Maria
Published: December 2023

Extensive research has been dedicated to the solution-processable white organic light-emitting diodes (WOLEDs), which can potentially influence future solid-state lighting and full-color flat-panel displays. The proposed strategy based on WOLEDs involves blending two or more emitting polymers or copolymerizing two or more emitting chromophores with different doping concentrations to produce white light emission from a single layer. Toward this direction, the development of blends was conducted using commercial blue poly(9,9-di-n-octylfluorenyl2,7-diyl) (PFO), green poly(9,9-dioctylfluorenealt-benzothiadiazole) (F8BT), and red spiro-copolymer (SPR) light-emitting materials, whereas the synthesized copolymers were based on different chromophores, namely distyryllanthracene, distyrylcarbazole, and distyrylbenzothiadiazole, as yellow, blue, and orange–red emitters, respectively. A comparative study between the two approaches was carried out to examine the main challenge for these doping systems, which is ensuring the proper balance of emissions from all the units to span the entire visible range. The emission characteristics of fabricated WOLEDs will be explored in terms of controlling the emission from each emitter, which depends on two possible mechanisms: energy transfer and carrier trapping. The aim of this work is to achieve pure white emission through the color mixing from different emitters based on different doping concentrations, as well as color stability during the device operation. According to these aspects, the WOLED devices based on the copolymers of two chromophores exhibit the most encouraging results regarding white color emission coordinates (0.28, 0.31) with a CRI value of 82.
A Comprehensive Investigation of the Mechanical and Tribological Properties of AZO Transparent Conducting Oxide Thin Films Deposited by Medium Frequency Magnetron Sputtering
Authors: Mazur Michał , Kiliszkiewicz Milena , Posadowski Witold , Domaradzki Jarosław , Małachowska Aleksandra , Sokołowski Paweł
Published: December 2023

This paper presents a detailed analysis of aluminium-doped zinc oxide (AZO) thin films and considers them a promising alternative to indium tin oxide in transparent electrodes. The study focusses on critical properties of AZO, including optical, electrical, and mechanical properties, with potential applications in displays, photovoltaic cells, and protective coatings. The deposited AZO thin films are characterised by excellent optical and electrical parameters, with transparency in the visible light range exceeding 80% and resistivity of 10−3 Ω·cm, which gives a high value of figure of merit of 63. Structural analysis confirms the nanocrystalline nature of as-deposited AZO thin films, featuring hexagonal ZnO, orthorhombic Al2O3, and cubic Al2ZnO4 phases. The study includes nanoindentation measurements, which reveal exceptional hardness (11.4 GPa) and reduced elastic modulus (98 GPa), exceeding typical values reported in the literature, highlighting their protective potential. Abrasion tests have shown extraordinary scratch resistance due to the lack of impact on topography and surface roughness up to 10,000 cycles. This comprehensive study demonstrated that as-deposited AZO thin films are multifunctional materials with exceptional optical, electrical, and mechanical properties. The findings open up possibilities for a variety of applications, especially in protective coatings, where the combination of hardness, scratch resistance, and transparency is both rare and valuable.
A Polymer-Based Metallurgical Route to Produce Aluminum Metal-Matrix Composite with High Strength and Ductility
Authors: Gutta Bindu , Huilgol Prashant , Perugu Chandra S. , Kumar Govind , Reddy S. Tejanath , Toth Laszlo S. , Bouaziz Olivier , Kailas Satish V.
Published: December 2023

In this investigation, an attempt was made to develop a new high-strength and high-ductility aluminum metal–matrix composite. It was achieved by incorporating ceramic reinforcement into the metal which was formed in situ from a polymer by pyrolysis. A crosslinked PMHS polymer was introduced into commercially pure aluminum via friction stir processing (FSP). The distributed micro- and nano-sized polymer was then converted into ceramic particles by heating at 500 °C for 10 h and processed again via FSP. The produced composite showed a 2.5-fold increase in yield strength (to 119 MPa from 48 MPa) and 3.5-fold increase in tensile strength (to 286 MPa from 82 MPa) with respect to the base metal. The ductility was marginally reduced from 40% to 30%. The increase in strength is attributed to the grain refinement and the larger ceramic particles. High-temperature grain stability was obtained, with minimal loss to mechanical properties, up to 500 °C due to the Zenner pinning effect of the nano-sized ceramic particles at the grain boundaries. Fractures took place throughout the matrix up to 300 °C. Above 300 °C, the interfacial bonding between the particle and matrix became weak, and fractures took place at the particle–matrix interface.
Special Issue: “Soft Magnetic Materials and Their Applications”
Authors: Che Shenglei
Published: December 2023

Soft magnetic materials normally show no magnetic properties outside of a magnetic field but can be easily magnetized and demagnetized within magnetic fields [...]
Functional 3D-Printed Polymeric Materials with Metallic Reinforcement for Use in Cut-Resistant Gloves
Authors: Żyłka Emilia , Irzmańska Emilia , Saramak Jakub , Jurczyk-Kowalska Magdalena
Published: December 2023

Given the mechanical hazards occurring in the workplace, cut resistance is a particularly important protective parameter. 3D printing is an innovative technology that has recently garnered great interest. It enables the creation of functional polymeric materials with metal reinforcement for use in cut-resistant gloves. The present study characterized and tested 3D-printed polymeric materials intended for such applications. The materials were made from commercially available 3D printing polymer filaments. Metallic reinforcement (stainless steel wire with a diameter of 0.04 mm) was added to the two selected materials (thermoplastic polyurethane and FiberFlex30D). Tests have shown that materials containing metallic reinforcement demonstrate higher mechanical resistance. Cut resistance increased by 70%, and the force needed to tear the sample increased by over 20% compared to the pure polymer. The presence of metallic reinforcement strengthens the structure of the material and changes the cracking mechanism. The tearing occurs in the test area, not in the bell area. These findings demonstrate the feasibility of applying functional 3D-printed polymeric materials with metal reinforcement in cut-resistant gloves.
Exploration of Alloying Elements of High Specific Modulus Al–Li Alloy Based on Machine Learning
Authors: Li Huiyu , Li Xiwu , Li Yanan , Gao Guanjun , Wen Kai , Li Zhihui , Zhang Yongan , Xiong Baiqing
Published: December 2023

In the aerospace sector, the development of lightweight aircraft heavily relies on the utilization of advanced aluminum–lithium alloys as primary structural materials. This study introduces an investigation aimed at optimizing the composition of an Al-2.32Li-1.44Cu-2.78Mg-0.3Ag-0.3Mn-0.1Zr alloy. The optimization process involves the selection of alloying elements through the application of machine learning techniques, with a focus on expected improvements in the specific modulus of these alloys. Expanding upon the optimization of the benchmark alloy’s components, a more generalized modulus prediction model for Al–Li alloys was formulated. This model was then employed to evaluate the anticipated specific modulus of alloys within a virtual search space, encompassing substitutional elements. The study proceeded to validate six Al–Li alloys with a notably high potential for achieving an improved specific modulus. The results revealed that an alloy incorporating 0.96 wt.% of Ga as a substitutional element exhibited the most favorable microstructure. This alloy demonstrated optimal tensile strength (523 MPa) and specific modulus (31.531 GPa/(g·cm−3)), closely resembling that of the benchmark alloy. This research offers valuable insights into the application of compositional optimization to enhance the mechanical properties of Al–Li alloys. It emphasizes the significance of selecting alloying elements based on considerations such as their solid solubility thresholds and the expected enhancement of the specific modulus in Al–Li alloys.
Analysis of the Process and Results of High-Pressure Abrasive Water Jet Multilayer Cutting of Electrical Steel
Authors: Szada-Borzyszkowska Monika , Kacalak Wojciech , Bohdal Łukasz , Szada-Borzyszkowski Wiesław
Published: December 2023

Electrical steels are magnetically soft materials and are widely used in the electrical industry for the construction of power transformer cores, distribution transformers, current transformers, and voltage transformers. An important parameter of electrical components, which determines the efficiency of devices, is energy loss during remagnetization. Energy losses are caused by eddy currents, hysteresis, and magnetic delay associated with the low quality of the cut edge after the cutting of steels, and material deformations and excessive stress concentration in the surrounding cutting zones. Common techniques for cutting electrical materials in industrial lines include mechanical cutting and laser cutting. Work has shown that mechanical cutting of electrical steel single layers results in the occurrence of large deformation zones, and in cutting processes with a high-pressure abrasive water jet (AWJ), significant uplifts of material and burrs at the bottom edges of sheets occur. The problem of increasing the cutting quality was solved through selecting the stream parameters for bundle cutting of electrical steels. It has been shown that in the process of cutting electrical sheet bundles, the height of burrs on the cut surface and the zone of plastic deformation are reduced. The work also presents comparison and analysis of characteristic features of the cut edge of electrical sheets obtained through high-pressure abrasive water jet and mechanical cutting processes. The influence of the type and processing parameters on the characteristic features of the material hysteresis loop was determined.
Coarse-Grained Monte Carlo Simulations with Octree Cells for Geopolymer Nucleation at Different pH Values
Authors: Valencia Nicolas Castrillon , Izadifar Mohammadreza , Ukrainczyk Neven , Koenders Eduardus
Published: December 2023

Geopolymers offer a potential alternative to ordinary Portland cement owing to their performance in mechanical and thermal properties, as well as environmental benefits stemming from a reduced carbon footprint. This paper endeavors to build upon prior atomistic computational work delving deeper into the intricate relationship between pH levels and the resulting material’s properties, including pore size distribution, geopolymer nucleate cluster dimensions, total system energy, and monomer poly-condensation behavior. Coarse-grained Monte Carlo (CGMC) simulation inputs include tetrahedral geometry and binding energy parameters derived from DFT simulations for aluminate and silicate monomers. Elevated pH values may can alter reactivity and phase stability, or, in the structural concrete application, may passivate the embedded steel reinforcement. Thus, we examine the effects of pH values set at 11, 12, and 13 (based on silicate speciation chemistry), investigating their respective contributions to the nucleation of geopolymers. To simulate a larger system to obtain representative results, we propose the numerical implementation of an Octree cell. Finally, we further digitize the resulting expanded structure to ascertain pore size distribution, facilitating a comparative analysis. The novelty of this study is underscored by its expansion in both system size, more accurate monomer representation, and pH range when compared to previous CGMC simulation approaches. The results unveil a discernible correlation between the number of clusters and pores under specific pH levels. This links geopolymerization mechanisms under varying pH conditions to the resulting chemical properties and final structural state.
Experimental Analysis of the Influence of Carrier Layer Material on the Performance of the Control System of a Cantilever-Type Piezoelectric Actuator
Authors: Grzybek Dariusz
Published: December 2023

The subject of this article is an experimental analysis of the control system of a composite-based piezoelectric actuator and an aluminum-based piezoelectric actuator. Analysis was performed for both the unimorph and bimorph structures. To carry out laboratory research, two piezoelectric actuators with a cantilever sandwich beam structure were manufactured. In the first beam, the carrier layer was made of glass-reinforced epoxy composite (FR4), and in the second beam, it was made of 1050 aluminum. A linear mathematical model of both actuators was also developed. A modification of the method of selecting weights in the LQR control algorithm for a cantilever-type piezoelectric actuator was proposed. The weights in the R matrix for the actuator containing a carrier layer made of stiffer material should be smaller than those for the actuator containing a carrier layer made of less stiff material. Additionally, regardless of the carrier layer material, in the case of a bimorph, the weight in the R matrix that corresponds to the control voltage of the compressing MFC patch should be smaller than the weight corresponding to the control voltage of the stretching MFC patch.
Variation of Corrosion Rate, Vcorr, during the Carbonation-Induced Corrosion Propagation Period in Reinforced Concrete Elements
Authors: Sánchez Montero Javier , Saura Gómez Pascual , Torres Martín Julio Emilio , Chinchón-Payá Servando , Rebolledo Ramos Nuria
Published: December 2023

The structural systems of residential buildings in many developed countries have widely utilized reinforced concrete as the most common solution in construction systems since the early 20th century. The durability of reinforced concrete columns and beams is compromised, in most cases, by pathologies caused by the corrosion of their reinforcements. This study analyses the corrosion processes induced by carbonation in 25 buildings with reinforced concrete structures. The models estimate the service life of reinforced concrete elements by differentiating between the initiation period and the propagation period of damage, considering two possible stages: the time of corrosion propagation until the cracking of the concrete cover, and the time of propagation until a loss of section is considered unacceptable for structural safety. However, the mathematical expressions that model the propagation periods consider the same corrosion rate in both cases. This research has found that the average corrosion rate in elements with an unacceptable loss of reinforcement section was in the order of 8 times higher than the corrosion rate in cracked columns and beams without a loss of reinforcement. This opens up a path to improve the definition of the different stages experienced by a reinforced concrete element suffering corrosion of its reinforcements due to carbonation, because once the concrete has cracked, the corrosion rate increases significantly.
Formulation and Biodegradation of Surface-Supported Biopolymer-Based Microgels Formed via Hard Templating onto Vaterite CaCO3 Crystals
Authors: Mammen Mariam , Hogg Cain , Craske Dominic , Volodkin Dmitry
Published: December 2023

In recent decades, there has been increased attention to the role of layer-by-layer assembled bio-polymer 3D structures (capsules, beads, and microgels) for biomedical applications. Such free-standing multilayer structures are formed via hard templating onto sacrificial cores such as vaterite CaCO3 crystals. Immobilization of these structures onto solid surfaces (e.g., implants and catheters) opens the way for the formulation of advanced bio-coating with a patterned surface. However, the immobilization step is challenging. Multiple approaches based mainly on covalent binding have been developed to localize these multilayer 3D structures at the surface. This work reports a novel strategy to formulate multilayer surface-supported microgels (ss-MG) directly on the surface via hard templating onto ss-CaCO3 pre-grown onto the surface via the direct mixing of Na2CO3 and CaCl2 precursor solutions. ss-MGs were fabricated using biopolymers: polylysine (PLL) as polycation and three polyanions—hyaluronic acid (HA), heparin sulfate (HS), and alginate (ALG). ss-MG biodegradation was examined by employing the enzyme trypsin. Our studies indicate that the adhesion of the ss-MG to the surface and its formation yield directly correlate with the mobility of biopolymers in the ss-MG, which decreases in the sequence of ALG > HA > HS-based ss-MGs. The adhesion of HS-based ss-MGs is only possible via heating during their formation. Dextran-loading increases ss-MG formation yield while reducing ss-MG shrinking. ss-MGs with higher polymer mobility possess slower biodegradation rates, which is likely due to diffusion limitations for the enzyme in more compact annealed ss-MGs. These findings provide valuable insights into the mechanisms underlying the formation and biodegradation of surface-supported biopolymer structures.
Obstacle Avoidance in Operational Configuration Space Kinematic Control of Redundant Serial Manipulators
Authors: Peidro Adrian , Haug Edward J.
Published: December 2023

Kinematic control of redundant serial manipulators has been carried out for the past half century based primarily on a generalized inverse velocity formulation that is known to have mathematical deficiencies. A recently developed inverse kinematic configuration mapping is employed in an operational configuration space differentiable manifold formulation for redundant-manipulator kinematic control with obstacle avoidance. This formulation is shown to resolve deficiencies in the generalized inverse velocity formulation, especially for high-degree-of-redundancy manipulators. Tracking a specified output trajectory while avoiding obstacles for four- and twenty-degree-of-redundancy manipulators is carried out to demonstrate the effectiveness of the differentiable manifold approach for applications with a high degree of redundancy and to show that it indeed resolves deficiencies of the conventional generalized inverse velocity formulation in challenging applications.
Development of a Simulator for Household Refrigerator Using Equation-Based Optimization Control with Bayesian Calibration
Authors: Yoo Mooyoung
Published: December 2023

Conventional household refrigerators consist of a motor-driven compressor, evaporator, condenser, and expansion valve. To determine the optimal operation strategies of refrigerators, it is essential to investigate the overall system performance, using an appropriate simulator. This study proposed a data-driven simulator based on engineering features and machine learning algorithms for conventional household refrigerators. The most correlated variables for identifying the indoor temperature of refrigerators were identified using variable importance, and these were revealed to be the circulation fan speed, compressor operation status, and refrigerant flow direction. A data-driven simulator was constructed using Bayesian calibration, which considers the important variables, combined with a straightforward heat balance equation. The Markov Chain Monte Carlo approach was used to simultaneously calibrate three coefficients on the critical variables based on the heat balancing equation on each time step, which is consistent with the actual temperature of the container. The results revealed that the proposed approach (equation-based Bayesian calibration outperforms) standard machine learning algorithms, such as linear regression and random forest models, by 38.5%. Additionally, compared to the typical numerical analysis method, it can reduce the delivery time and effort required to develop a reliable simulator for household refrigerators.
The Influence of Viscosity on Heat Dissipation under Conditions of the High-Frequency Oscillating Magnetic Field
Authors: Molcan Matus , Skumiel Andrzej , Tothova Jana , Paulovicova Katarina , Kopcansky Peter , Timko Milan
Published: December 2023

High-frequency components such as microprocessors, transistors, antennas, voltage-controlled oscillators, and many others generate a large amount of heat. In the absence of satisfactory cooling, these components may suffer damage or even destruction. Therefore, it is important to find effective ways to cool these components. A possible solution is to use oil-based magnetic fluids. Magnetic fluids contain magnetic particles dispersed in oil, and their properties, including viscosity, affect their cooling capabilities. Viscosity can be changed by adding various additives or by adjusting the concentration of magnetic particles. The advantage of using oil-based magnetic fluids for cooling is that they allow for precise dosing and control of the amount of fluid applied to the component, reducing thermal losses and increasing cooling efficiency. In addition, oil-based magnetic fluids can also act as a dielectric, reducing electrical noise and increasing electromagnetic compatibility with the components. Analyzing the heating rate of magnetic fluids consisting of mineral oils in an alternating magnetic field with a frequency of 500 kHz, we have shown the capability of controlling thermal losses by adjusting the viscosity of the carrier liquid.
A Dynamic CGE Model for Optimization in Business Analytics: Simulating the Impact of Investment Shocks
Authors: Medina-López Ana , Jiménez-Partearroyo Montserrat , Cámara Ángeles
Published: December 2023

This study formulates a mathematical dynamic Computable General Equilibrium (CGE) model within a rational expectations framework, adhering to neo-classical principles. It emphasizes the significant role of agents’ expectations in determining the broader economic trajectory over time. The model combines microeconomic and macroeconomic perspectives by merging the concept of intertemporal choice with savings behavior. Its mathematical foundations are derived and calibrated using data from a social accounting matrix to enhance its simulation capabilities. The paper presents a practical simulation investigating the economic implications of a strategic investment impact within an specific European region, Madrid as the case of study. Such demand shock affects sectors such as electronics, food, pharmaceuticals, and education. The study models the long-term effects of heightened investment and persistent demand-side shocks. The research demonstrates the CGE model’s ability to forecast economic shifts toward a new equilibrium after an investment shock, proving its utility for assessing the impacts of extensive environmental policies within a European context. The work’s originality lies in its detailed mathematical formulation, contributing to theoretical discourse and practical application in business analytics.
Several Functions Originating from Fisher–Rao Geometry of Dirichlet Distributions and Involving Polygamma Functions
Authors: Qi Feng , Agarwal Ravi Prakash
Published: December 2023

In this paper, the authors review and survey some results published since 2020 about (complete) monotonicity, inequalities, and their necessary and sufficient conditions for several newly introduced functions involving polygamma functions and originating from the estimation of the sectional curvature of the Fisher–Rao geometry of the Dirichlet distributions in the two-dimensional case.
Increasing Distributed Generation Hosting Capacity Based on a Sequential Optimization Approach Using an Improved Salp Swarm Algorithm
Authors: Tudose Andrei M. , Sidea Dorian O. , Picioroaga Irina I. , Anton Nicolae , Bulac Constantin
Published: December 2023

In recent years, a pronounced transition to the exploitation of renewable energy sources has be observed worldwide, driven by current climate concerns and the scarcity of conventional fuels. However, this paradigm shift is accompanied by new challenges for existing power systems. Therefore, the hosting capacity must be exhaustively assessed in order to maximize the penetration of distributed generation while mitigating any adverse impact on the electrical grid in terms of voltage and the operational boundaries of the equipment. In this regard, multiple aspects must be addressed in order to maintain the proper functioning of the system following the new installations’ capacities. This paper introduces a sequential methodology designed to determine the maximum hosting capacity of a power system through the optimal allocation of both active and reactive power. To achieve this goal, an Improved Salp Swarm Algorithm is proposed, aiming to establish the appropriate operational planning of the power grid considering extensive distributed generation integration, while still ensuring a safe operation. The case study validates the relevance of the proposed model, demonstrating a successful enhancement of hosting capacity by 14.5% relative to standard models.
Inequalities in Riemann–Lebesgue Integrability
Authors: Croitoru Anca , Gavriluţ Alina , Iosif Alina , Sambucini Anna Rita
Published: December 2023

In this paper, we prove some inequalities for Riemann–Lebesgue integrable functions when the considered integration is obtained via a non-additive measure, including the reverse Hölder inequality and the reverse Minkowski inequality. Then, we generalize these inequalities to the framework of a multivalued case, in particular for Riemann–Lebesgue integrable interval-valued multifunctions, and obtain some inequalities, such as a Minkowski-type inequality, a Beckenbach-type inequality and some generalizations of Hölder inequalities.
An Innovative Power Management Strategy for Hybrid Battery–Supercapacitor Systems in Electric Vehicle
Authors: Jarraya Imen , Abdelhedi Fatma , Rizoug Nassim
Published: December 2023

Currently, batteries and supercapacitors play a vital role as energy storage systems in industrial applications, particularly in electric vehicles. Electric vehicles benefit from the high energy density of lithium batteries as well as the high power density of supercapacitors. Hence, a robust and efficient energy management system is required to coordinate energy flows between these two storage systems, ensuring road safety. In this study, we develop a novel rule-based strategy called “Continuous Regulation with Dynamic Battery Power Limiting” to establish robust control between the lithium-ion battery and the supercapacitor. A comparative analysis is conducted to evaluate the performance of this proposed approach in comparison to conventional methods. The results show that this approach significantly enhances driving comfort and prevents depletion of the main energy source, resulting in a gain of nearly 30% compared to a lithium-ion battery electric vehicle. Additionally, this new rules-based strategy ensures that the supercapacitor is charged at the end of each drive cycle.
A New Two-Step Hybrid Block Method for the FitzHugh–Nagumo Model Equation
Authors: Rufai Mufutau Ajani , Kosti Athinoula A. , Anastassi Zacharias A. , Carpentieri Bruno
Published: December 2023

This paper presents an efficient two-step hybrid block method (ETHBM) to obtain an approximate solution to the FitzHugh–Nagumo problem. The considered partial differential equation model problems are semi-discretized, reducing them to equivalent ordinary differential equations using the method of lines. In order to evaluate the effectiveness of the proposed ETHBM, three numerical examples are presented and compared with the results obtained through existing methods. The results demonstrate that the proposed ETHBM produces more efficient results than some other numerical approaches in the literature.
Locality-Constraint Discriminative Nonnegative Representation for Pattern Classification
Authors: Li Ziqi , Song Hongcheng , Yin Hefeng , Zhang Yonghong , Zhang Guangyong
Published: December 2023

Representation-based classification methods (RBCM) have recently garnered notable attention in the field of pattern classification. Diverging from conventional methods reliant on ℓ1 or ℓ2-norms, the nonnegative representation-based classifier (NRC) enforces a nonnegative constraint on the representation vector, thus enhancing the representation capabilities of positively correlated samples. While NRC has achieved substantial success, it falls short in fully harnessing the discriminative information associated with the training samples and neglects the locality constraint inherent in the sample relationships, thereby limiting its classification power. In response to these limitations, we introduce the locality-constraint discriminative nonnegative representation (LDNR) method. LDNR extends the NRC framework through the incorporation of a competitive representation term. Recognizing the pivotal role played by the estimated samples in the classification process, we include estimated samples that involve discriminative information in this term, establishing a robust connection between representation and classification. Additionally, we assign distinct local weights to different estimated samples, augmenting the representation capacity of homogeneous samples and, ultimately, elevating the performance of the classification model. To validate the effectiveness of LDNR, extensive comparative experiments are conducted on various pattern classification datasets. The findings demonstrate the competitiveness of our proposed method.
A Comparative Sentiment Analysis of Airline Customer Reviews Using Bidirectional Encoder Representations from Transformers (BERT) and Its Variants
Authors: Li Zehong , Yang Chuyang , Huang Chenyu
Published: December 2023

The applications of artificial intelligence (AI) and natural language processing (NLP) have significantly empowered the safety and operational efficiency within the aviation sector for safer and more efficient operations. Airlines derive informed decisions to enhance operational efficiency and strategic planning through extensive contextual analysis of customer reviews and feedback from social media, such as Twitter and Facebook. However, this form of analytical endeavor is labor-intensive and time-consuming. Extensive studies have investigated NLP algorithms for sentiment analysis based on textual customer feedback, thereby underscoring the necessity for an in-depth investigation of transformer architecture-based NLP models. In this study, we conducted an exploration of the large language model BERT and three of its derivatives using an airline sentiment tweet dataset for downstream tasks. We further honed this fine-tuning by adjusting the hyperparameters, thus improving the model’s consistency and precision of outcomes. With RoBERTa distinctly emerging as the most precise and overall effective model in both the binary (96.97%) and tri-class (86.89%) sentiment classification tasks and persisting in outperforming others in the balanced dataset for tri-class sentiment classification, our results validate the BERT models’ application in analyzing airline industry customer sentiment. In addition, this study identifies the scope for improvement in future studies, such as investigating more systematic and balanced datasets, applying other large language models, and using novel fine-tuning approaches. Our study serves as a pivotal benchmark for future exploration in customer sentiment analysis, with implications that extend from the airline industry to broader transportation sectors, where customer feedback plays a crucial role.
An In-Depth Review of the Weibull Model with a Focus on Various Parameterizations
Authors: Gómez Yolanda M. , Gallardo Diego I. , Marchant Carolina , Sánchez Luis , Bourguignon Marcelo
Published: December 2023

The Weibull distribution is a versatile probability distribution widely applied in modeling the failure times of objects or systems. Its behavior is shaped by two essential parameters: the shape parameter and the scale parameter. By manipulating these parameters, the Weibull distribution adeptly captures diverse failure patterns observed in real-world scenarios. This flexibility and broad applicability make it an indispensable tool in reliability analysis and survival modeling. This manuscript explores five parameterizations of the Weibull distribution, each based on different moments, like mean, quantile, and mode. It meticulously characterizes each parameterization, introducing a novel one based on the model’s mode, along with its hazard and survival functions, shedding light on their unique properties. Additionally, it delves into the interpretation of regression coefficients when incorporating regression structures into these parameterizations. It is analytically established that all five parameterizations define the same log-likelihood function, underlining their equivalence. Through Monte Carlo simulation studies, the performances of these parameterizations are evaluated in terms of parameter estimations and residuals. The models are further applied to real-world data, illustrating their effectiveness in analyzing material fatigue life and survival data. In summary, this manuscript provides a comprehensive exploration of the Weibull distribution and its various parameterizations. It offers valuable insights into their applications and implications in modeling failure times, with potential contributions to diverse fields requiring reliability and survival analysis.
Robust and Adaptive Stabilization Controllers of State-Constrained Nonholonomic Chained Systems: A Discontinuous Approach
Authors: Zhang Zhongcai , Hu Xueli , Gao Yang , Hou Xiaodan
Published: December 2023

In this paper, two systematic control design strategies are proposed for strict-feedback nonholonomic systems with full-state constraints to solve stabilization and adaptive stabilization problems. The stabilization schemes involve the introduction of state scaling, the barrier Lyapunov function (BLF), the integrator backstepping method, and the tuning function approach. In addition, a discontinuous switching control strategy is proposed to achieve the control goal if the first system state’s initial state is confined to zero. In both stabilization and adaptive stabilization control, the system states can be regulated at the origin, and meanwhile, the full-state constraints are realized. Finally, it is shown that the simulation results are consistent with the theory analysis results, which further demonstrates the effectiveness of the proposed control schemes.
Physics-Informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media
Authors: Faroughi Salah A. , Soltanmohammadi Ramin , Datta Pingki , Mahjour Seyed Kourosh , Faroughi Shirko
Published: December 2023

Simulating solute transport in heterogeneous porous media poses computational challenges due to the high-resolution meshing required for traditional solvers. To overcome these challenges, this study explores a mesh-free method based on deep learning to accelerate solute transport simulation. We employ Physics-informed Neural Networks (PiNN) with a periodic activation function to solve solute transport problems in both homogeneous and heterogeneous porous media governed by the advection-dispersion equation. Unlike traditional neural networks that rely on large training datasets, PiNNs use strong-form mathematical models to constrain the network in the training phase and simultaneously solve for multiple dependent or independent field variables, such as pressure and solute concentration fields. To demonstrate the effectiveness of using PiNNs with a periodic activation function to resolve solute transport in porous media, we construct PiNNs using two activation functions, sin and tanh, for seven case studies, including 1D and 2D scenarios. The accuracy of the PiNNs’ predictions is then evaluated using absolute point error and mean square error metrics and compared to the ground truth solutions obtained analytically or numerically. Our results demonstrate that the PiNN with sin activation function, compared to tanh activation function, is up to two orders of magnitude more accurate and up to two times faster to train, especially in heterogeneous porous media. Moreover, PiNN’s simultaneous predictions of pressure and concentration fields can reduce computational expenses in terms of inference time by three orders of magnitude compared to FEM simulations for two-dimensional cases.
Extension of the Kantorovich Theorem to Equations in Vector Metric Spaces: Applications to Functional Differential Equations
Authors: Zhukovskiy Evgeny , Panasenko Elena
Published: December 2023

The equation G(x,x)=y˜, where G:X×X→Y, and X,Y are vector metric spaces (meaning that the values of a distance between the points in these spaces belong to some cones E+,M+ of a Banach space E and a linear space M, respectively), is considered. This operator equation is compared with a “model” equation, namely, g(t,t)=0, where a continuous map g:E+×E+→M+ is orderly covering in the first argument and antitone in the second one. The idea to study equations comparing them with “simpler” ones goes back to the Kantorovich fixed-point theorem for an operator acting in a Banach space. In this paper, the conditions under which the solvability of the “model” equation guarantees the existence of solutions to the operator equation are obtained. The statement proved extends the recent results about fixed points and coincidence points to more general equations in more general vector metric spaces. The results obtained for the operator equation are then applied to the study of the solvability, as well as to finding solution estimates, of the Cauchy problem for a functional differential equation.