bluuebunny/crossref_metadata_2025 huggingface dataset:
Optoelectronic Characterization of Natural Dyes in the Quest for Enhanced Performance in Dye-Sensitized Solar Cells: A Density Functional Theory Study
Authors: Gunawardhana Pramesh , Balasooriya Yashas , Kandanapitiye Murthi S. , Chau Yuan-Fong Chou , Kooh Muhammad Raziq Rahimi , Thotagamuge Roshan
Published: December 2023

This study employs density functional theory (DFT) to evaluate the optoelectronic features of five natural dyes (cyanidin, delphinidin, pelargonidin, peonidin, and petunidin) in gas and ethanol phases for potential dye-sensitized solar cell (DSSC) applications. Calculations cover HOMO and LUMO energy levels, charge transfer potential gaps, and light absorption properties correlated with oscillator strengths. Photovoltaic aspects, including light-harvesting efficiency (LHE), electron injection efficiency (ΔGinject), regeneration efficiency (ΔGregen), open-circuit voltage (VOC), excited-state lifetime (τ), and the electronic coupling constant (|VRP|), were computed to assess DSSC suitability. DFT analysis reveals that cyanidin, delphinidin, and petunidin exhibit favorable LUMOs for efficient electron injection into the semiconductor’s conduction band. Cyanidin demonstrates a high quantum yield for light absorption. Delphinidin and petunidin act as effective light absorbers with high excitation energies and oscillator strengths, while petunidin and delphinidin display strong LHE, indicating excellent electron-donating capabilities. Peonidin shows promising ΔGinject despite needing more energy for injection. Pelargonidin excels in ΔGregen and |VRP|, enhancing DSSC performance. Petunidin and delphinidin exhibit a high VOC. Petunidin efficiently transmits energy through a large τ, while pelargonidin’s |VRP| confirms its potential as a favorable sensitizer. In summary, each dye possesses unique properties, and understanding them aids in selecting the most suitable dye for enhanced DSSC performance.
A Hard-Constraint Wide-Body Physics-Informed Neural Network Model for Solving Multiple Cases in Forward Problems for Partial Differential Equations
Authors: Chen Simin , Liu Zhixiang , Zhang Wenbo , Yang Jinkun
Published: December 2023

In the fields of physics and engineering, it is crucial to understand phase transition dynamics. This field involves fundamental partial differential equations (PDEs) such as the Allen–Cahn, Burgers, and two-dimensional (2D) wave equations. In alloys, the evolution of the phase transition interface is described by the Allen–Cahn equation. Vibrational and wave phenomena during phase transitions are modeled using the Burgers and 2D wave equations. The combination of these equations gives comprehensive information about the dynamic behavior during a phase transition. Numerical modeling methods such as finite difference method (FDM), finite volume method (FVM) and finite element method (FEM) are often applied to solve phase transition problems that involve many partial differential equations (PDEs). However, physical problems can lead to computational complexity, increasing computational costs dramatically. Physics-informed neural networks (PINNs), as new neural network algorithms, can integrate physical law constraints with neural network algorithms to solve partial differential equations (PDEs), providing a new way to solve PDEs in addition to the traditional numerical modeling methods. In this paper, a hard-constraint wide-body PINN (HWPINN) model based on PINN is proposed. This model improves the effectiveness of the approximation by adding a wide-body structure to the approximation neural network part of the PINN architecture. A hard constraint is used in the physically driven part instead of the traditional practice of PINN constituting a residual network with boundary or initial conditions. The high accuracy of HWPINN for solving PDEs is verified through numerical experiments. One-dimensional (1D) Allen–Cahn, one-dimensional Burgers, and two-dimensional wave equation cases are set up for numerical experiments. The properties of the HWPINN model are inferred from the experimental data. The solution predicted by the model is compared with the FDM solution for evaluating the experimental error in the numerical experiments. HWPINN shows great potential for solving the PDE forward problem and provides a new approach for solving PDEs.
Unveiling the Nexus of Cervical Proprioception, Postural Stability, and Impeding Factors in Cervical Spondylosis: Insights from Reposition Errors, Limits of Stability, and Mediation Analysis
Authors: Alahmari Khalid A. , Reddy Ravi Shankar
Published: December 2023

Cervical proprioception and postural stability play crucial roles in maintaining optimal head and neck positioning, yet their relationship and implications in cervical spondylosis (CS) remain underexplored. This study aims to investigate cervical proprioceptive reposition errors, limits of stability, and their association in individuals with CS while considering the mediating effects of pain and kinesiophobia. The primary objectives are to compare cervical proprioceptive reposition errors and limits of stability variables between individuals with CS and age-matched healthy controls, explore their associations within the CS group, and determine the mediating roles of pain and kinesiophobia. A cross-sectional study recruited 60 individuals with CS and 60 healthy controls. Cervical joint reposition errors (JREs) were assessed using a cervical range-of-motion device, while limits of stability were evaluated using a computerized dynamic posturography system. Pain, kinesiophobia, and demographic data were collected. Parametric tests, correlation analyses, and multiple regression were employed for data analysis. Individuals with CS exhibited significantly higher cervical JREs in flexion, extension, and rotation compared with healthy controls (p < 0.001). Within the CS group, correlations revealed associations between JREs and limits-of-stability variables (p < 0.05). Mediation analysis demonstrated significant direct and indirect effects of pain and kinesiophobia on the relationship between JREs and limits-of-stability variables in the CS group (p < 0.005). CS is associated with impaired cervical proprioception, increased reposition errors, and compromised postural stability. This study highlights the interplay between proprioception, stability, pain, and psychological factors, emphasizing the need for comprehensive interventions in individuals with CS to enhance functional outcomes and quality of life.
Computational Accuracy and Efficiency of Room Acoustics Simulation Using a Frequency Domain FEM with Air Absorption: 2D Study
Authors: Okuzono Takeshi
Published: December 2023

Recently, to simulate sound propagation inside architectural spaces at high frequencies, the application of computationally expensive wave-based numerical methods to room acoustics simulation is increasing gradually. Generally, standard room acoustics simulations in the frequency domain are performed based on the lossless Helmholtz equation. However, for acoustics simulation at high frequencies, consideration of the sound attenuation effect caused by air absorption is an aspect to increase the reliability of predictions. Although a simple approach based on the lossy Helmholtz equation is available to include the air absorption effect in the frequency domain, its accuracy and efficiency are still not discussed well. This paper presents an accuracy and efficiency estimation of FEM based on the lossy Helmholtz equation via two numerical problems in two dimensions: a plane wave propagation problem up to 20 kHz in a long duct with 1 km length and a sound propagation problem in a real-scale office up to 6 kHz. Results revealed that the lossy Helmholtz equation-based FEM can include the air absorption effect accurately up to 20 kHz. Moreover, a possibility of providing a higher computational efficiency at higher frequencies is suggested when the magnitude of the pure-tone sound attenuation coefficient is large.
The Green Cooling Factor: Eco-Innovative Heating, Ventilation, and Air Conditioning Solutions in Building Design
Authors: Ali Bashar Mahmood , Akkaş Mehmet
Published: December 2023

This research investigates the compatibility of conventional air conditioning with the principles of green building, highlighting the need for systems that enhance indoor comfort while aligning with environmental sustainability. Though proficient in regulating indoor temperatures, conventional cooling systems encounter several issues when incorporated into green buildings. These include energy waste, high running costs, and misalignment with eco-friendly practices, which may also lead to detrimental environmental effects and potentially reduce occupant comfort, particularly in retrofit situations. Given the emphasis on sustainability and energy conservation in green buildings, there is a pressing demand for heating, ventilation, and air conditioning (HVAC) solutions that support these goals. This study emphasises the critical need to reconsider traditional HVAC strategies in the face of green building advances. It advocates for the adoption of innovative HVAC technologies designed for eco-efficiency and enhanced comfort. These technologies should integrate seamlessly with sustainable construction, use greener refrigerants, and uphold environmental integrity, driving progress towards a sustainable and occupant-friendly built environment.
Construction Schedule versus Various Constraints and Risks
Authors: Kostrzewa-Demczuk Paulina
Published: December 2023

The organization and planning of construction works are difficult issues due to the complexity, numerous limitations, uncertainty and risks associated with them. Construction planning is usually based on deterministic data. However, numerous studies and analyses of real cases show that a different computational approach is needed—one based on probabilistic data. The computational algorithms of the Time Coupling Method make it possible to introduce probabilistic data generated in the Multivariate Method of Statistical Models (MMSM) and via standard deviations. As a result, a new methodology was created, the Probabilistic Time Coupling Method (PTCM), through which it is possible to obtain a very good forecast of the investment implementation time compared to its real time. The paper presents theoretical considerations, computational schemes and validation exercises of this new method—known as the PTCM. The computational results of the PTCM (with a mapping accuracy prediction of 99%) confirm the effectiveness of the method. The computational algorithms of the PTCM enable the creation of a computational application based on a well-known program, e.g., Microsoft Excel, thanks to which the method can be quickly disseminated in the planning environment and widely used.
An Improved YOLOv5 Algorithm for Drowning Detection in the Indoor Swimming Pool
Authors: Yang Ruiliang , Wang Kaikai , Yang Libin
Published: December 2023

In order to mitigate the risk of irreversible drowning injuries, this study introduces an enhanced YOLOv5 algorithm aimed at improving the efficacy of indoor swimming pool drowning detection and facilitating the timely rescue of endangered individuals. To simulate drowning and swimming positions accurately, four swimmers were deliberately chosen and observed, with monitoring conducted by drones flying above the swimming pool. The study was approved by the ethics committee of our institution, with the registration number 2022024. The images captured by the drones underwent a meticulous evaluation, and only those deemed suitable were selected to construct the self-made dataset, comprising a total of 8572 images. Furthermore, two enhancements were implemented in the YOLOv5 algorithm. Firstly, the inclusion of the ICA module strengthened category classification and the localization of water behavioral postures, which is improved from the coordinated attention module (CA). Secondly, the PAN module was replaced with the bi-directional feature pyramid network (BiFPN). Subsequently, the improved YOLOv5 algorithm underwent training using the self-made dataset. Evaluation of the algorithm’s performance revealed a notably improved detection accuracy rate, recall rate, and an impressive mean Average Precision (mAP) score of 98.1%, 98.0%, and 98.5%, respectively. Our paper introduces the improved YOLOv5 algorithm, surpassing the original YOLOv5 algorithm in terms of recognition accuracy for instances of drowning.
Partial Discharge Inception Modelling of Insulating Materials and Systems: Contribution of Electrodes to Electric Field Profile Calculation
Authors: Gardan Giovanni , Montanari Gian Carlo
Published: December 2023

Partial discharge inception modeling is a powerful tool for material investigation and insulation system design in order to achieve the objective of PD-free operation of insulation systems. Model validation, however, requires accurate and repeatable testing conditions, and the aim of this paper is to look at the influence of electrodes and electric field simulation on partial discharge inception model prediction accuracy. Awareness of the geometric electrode configuration is important to forecast both the typology of discharge and the corresponding partial discharge inception voltage value. It is shown, in fact, that inaccurate evaluation of electrode shape (e.g., its flat part and contour) might impact significantly on electric field estimation, the typology of incepted discharges, and, thus, on model accuracy, i.e., on partial discharge inception voltage prediction, which is the basis for the partial discharge-free design of insulating materials and systems. In particular, small electrode curvature radius variations do not significantly affect the PDIV value or PD typology identification. However, worsening electrode/insulation specimen contact can significantly impact PD inception and typology evaluation.
Seismic Vulnerability of Segmental Bridges with Drop-In Span by Pushover Analysis
Authors: Colajanni Piero , Granata Michele Fabio , La Mendola Lidia
Published: December 2023

Insight into the application of pushover analysis to prestressed concrete segmental bridges built in the 1950s–1970s by cantilevering with medium-large span length is provided. Seismic assessment must be carried out considering the whole structural response and, in particular, the task of tall piers, bearings, and drop-in spans with Gerber saddles, which are likely to be subjected to girder pounding and/or unseating. In this paper, the assessment of seismic vulnerability is initially performed by linear modal dynamic analysis; then, the efficiency in assessing the seismic response of different methods of pushover analyses is compared, assuming as a benchmark the results of non-linear time history analysis. The outcomes show that, for the bridge with the drop-in span, criteria for selecting the load pattern considered in pushover analysis, the reliable modeling of the bearings, and tall piers play a dominant role in the assessment of the seismic vulnerability, particularly in longitudinal motion.
ICVTest: A Practical Black-Box Penetration Testing Framework for Evaluating Cybersecurity of Intelligent Connected Vehicles
Authors: Zhang Haichun , Wang Jie , Wang Yijie , Li Minfeng , Song Jinghan , Liu Zhenglin
Published: December 2023

Intelligent connected vehicles (ICVs) are equipped with extensive electronic control units which offer convenience but also pose significant cybersecurity risks. Penetration testing, recommended in ISO/SAE 21434 “Road vehicles—Cybersecurity engineering”, is an effective approach to identify cybersecurity vulnerabilities in ICVs. However, there is limited research on vehicle penetration testing from a black-box perspective due to the complex architecture of ICVs. Additionally, no penetration testing framework has been proposed to guide security testers on conducting penetration testing for the whole vehicle. The lack of framework guidance results in the inexperienced security testers being uncertain about the processes to follow for conducting penetration testing. Moreover, the inexperienced security testers are unsure about which tests to perform in order to systematically evaluate the vehicle’s cybersecurity. To enhance the penetration testing efficiency of ICVs, this paper presents a black-box penetration testing framework, ICVTest. ICVTest proposes a standardized penetration testing process to facilitate step-by-step completion of the penetration testing, thereby addressing the issue of inexperienced testers lacking guidance on how to initiate work when confronted with ICV. Also, ICVTest includes 10 sets of test cases covering hardware and software security tests. Testers can select appropriate test cases based on the specific cybersecurity threats faced by the target object, thereby reducing the complexity of penetration testing tasks. Furthermore, we have developed a vehicle cybersecurity testing platform for ICVTest that seamlessly integrates various testing tools. The platform enables even novice testers to conduct vehicle black-box penetration testing in accordance with the given guidance which addresses the current industry’s challenge of an overwhelming number of testing tasks coupled with a shortage of skilled professionals. For the first time, we propose a comprehensive black-box penetration testing framework and implement the framework in the form of a cybersecurity testing platform. We apply ICVTest to evaluate an electric vehicle manufactured in 2021 for assessing the framework’s availability. With the aid of ICVTest, even testers with limited experience in automotive penetration can effectively evaluate the security risks of ICVs. In our experiments, numerous cybersecurity vulnerabilities were identified involving in-vehicle sensors, remote vehicle control systems, and in-vehicle controller area network (CAN) bus.
Multi-User Tracking in Reconfigurable Intelligent Surface Aided Near-Field Wireless Communications System
Authors: Mei Yidan , Wang Rui , Liu Erwu , Soto Ismael
Published: December 2023

An uplink multi-user tracking problem aided by multiple passive reconfigurable intelligent surfaces (RISs) is addressed in this work. Under a near-field circumstance, a multi-antenna base station (BS) localizes multiple moving single-antenna users by processing the received signals transmitted by users and reflected by RISs. Considering the users’ mobility and the potential obstruction of line-of-sight paths, a multi-user tracking system based on the extended Kalman filter (EKF) which fully exploits the temporal correlations between each user’s coordinate changes is designed. Then, the Bayesian Cramér–Rao bound (BCRB) of tracking errors is derived in a pattern consistent with the EKF process. Subsequently, an optimization scheme for passive phase shift design at the RISs is devised by minimizing the derived BCRB and is solved using the Gradient Descent method. Numerical results indicate that the accuracy of our tracking algorithm can approach the BCRB. With abundant RISs deployed and optimized, high-precision multi-user tracking via a single BS can be realized even in harsh localization environments.
Research on Underwater Wireless Optical Communication Channel Model and Its Application
Authors: Sun Kai , Li Yiyang , Han Zekai
Published: December 2023

Underwater wireless optical communication (UWOC) is an emerging technology with wide-ranging applications in marine exploration, offshore industries, environmental monitoring, and underwater robotics. In order to investigate the application of UWOC in environments of different water quality, this study establishes a model of an optical communication channel and analyzes the impact of water quality on communication range. Our experimental design is employed to validate the effectiveness of the model and analyze the sources of model errors. Furthermore, this research introduces the concept of an “effective communication space” for underwater optical wireless communication and constructs an experimental platform to test the effective communication space under various water quality conditions. In addition, the application methods and workflow of wireless optical communication on underwater mobile platforms are discussed, and field tests are conducted in a practical lake environment to verify the application value of the effective communication space. This research offers valuable guidance for advancing the study and engineering applications of UWOC technology.
The Law and Mechanism of the Effect of Surface Roughness on Microwave-Assisted Rock Breaking
Authors: Chen Fangfang , Li Guoqing , Zhang Zhiqiang , Wu Zhanqiang
Published: December 2023

In physical engineering, a rock surface, whether naturally or artificially formed, is rough. When irradiating rocks, microwaves produce reflections and diffractions on the surface of rough rocks, which significantly affect the absorption of microwave energy by rocks, thus influencing the result of microwave irradiation. In order to explore the influence of rough rock surfaces on the effect of microwave-assisted rock breaking, microwave irradiation tests were carried out on basalt samples with different values of roughness to test the temperature and P-wave velocity of the samples before and after microwave irradiation. Numerical test methods were used to systematically study the influence of rough rock surfaces on microwave irradiation. The results show that, under the same microwave irradiation conditions, the effect of microwave irradiation on rough surface basalt is more significant than that of flat surface basalt. The surface temperature distribution range of flat surface specimens is narrow, the surface temperature range of rough surface specimens is wider and more inhomogeneous, and the maximum surface temperatures of rough surface specimens are much higher than those of flat surface specimens. After irradiation, new macroscopic cracks were generated on the surface of the samples, and the crack propagation of the rough surface samples was more obvious. The decrease in P-wave velocity before and after the irradiation of flat surface samples is small, and that of rough surface samples is larger. The main factors affecting the effect of microwave irradiation on the rough surface are the refraction and reflection of electromagnetic waves, heat conduction, and stress concentration on the surface.
Estimation of SAR Average in Rats during 5G NR Chronic Exposure
Authors: Makhmanazarov Ramdas , Tseplyaev Ilya , Shipilov Sergey , Krivova Natalya
Published: December 2023

To study physiological reactions in the brain and skin of higher mammals exposed to chronic radiofrequency radiation, specific absorption ratio (SAR) determination is required and time-consuming numerical methods are used. The paper deals with the estimation of the whole-body specific absorption rate (SAR) in rats chronically exposed to external electromagnetic fields, as well as the development of a laboratory setup simulating the operation of a fifth-generation 5G New Radio base station (with a signal bandwidth of 15 MHz and a carrier frequency of 2.4 GHz). The paper presents a modified method for theoretical SAR estimation for one-sided irradiation and distributed absorption. Mean whole-body SAR values were estimated by the proposed method and numerically modeled with the CST Microwave Studio simulation software 2020package using primitive rat models. Dielectric parameters in the numerical simulation were used from the software library. The IEEE/IEC 62704-1 algorithm was used to investigate SAR in numerical simulations. The theoretical estimates and numerical simulations were compared for different SAR distributions and were found to be qualitatively comparable. The differences between approximate theoretical estimates and numerical simulations are 7% and 10% for distributed and non-distributed absorptions, respectively. The proposed method, which takes into account the decreasing power flux density, can be used to estimate the approximate whole-body SAR during chronic electromagnetic field exposure in rats.
The Impact of Orthodontic Treatment on Teeth Previously Treated with Regenerative Endodontics: A Systematic Review
Authors: Bucchi Cristina , Arias-Betancur Alain , Badilla-Wenzel Nicolás , Zaror Carlos
Published: December 2023

Objective: To assess the tooth survival rates, adverse events, and need for further treatment of teeth previously treated with regenerative endodontics undergoing orthodontic treatment. Material and Methods: A literature search was performed using MEDLINE, EMBASE, Cochrane, Scopus, and Lilacs databases, grey literature, and endodontic journals, and the date of the last search was 20 April 2022. The included studies involved patients undergoing orthodontic treatment and at least one tooth that was previously treated with regenerative endodontics. A narrative synthesis of the findings was made. The risk of bias and evidence quality were assessed using the Effective Public Health Practice Project tool and the GRADE approach. Results: Five case reports included seven patients and eight teeth with a follow-up of 4 to 11 years. The overall risk of bias was high, and the certainty of evidence was very low. The survival rate was 87.5%. Adverse effects included sinus tracts, root resorption, symptomatology, apical periodontitis, and intracanal tissue necrosis. Five out of eight teeth required further intervention after orthodontics. Conclusions: A high prevalence of adverse effects and further intervention is observed in teeth treated with regenerative endodontics undergoing orthodontic treatment. The low quality of evidence highlights the need for comparative studies and evidence-based guidelines for managing these teeth during orthodontic treatment.
Formation Control of Nonlinear Multi-Agent Systems with Nested Input Saturation
Authors: Trakas Panagiotis S. , Tantoulas Andreas , Bechlioulis Charalampos P.
Published: December 2023

A decentralized robust control protocol addressing leader-follower formation control of unknown nonlinear input-constrained multi-agent systems with adaptive performance specifications is proposed in this paper. The performance characteristics predefined by the user are adaptively modified in order to comply with the actuation constraints of the agents regarding both the magnitude and the rate of the control signals, ensuring closed-loop stability. The proposed control protocol is characterized by easy gain tuning and low structural complexity which simplifies the integration to real systems. A thorough experiment involving a system of multiple quadrotors was conducted to clarify and verify the theoretical findings.
Efficient Zero-Sequence Impedance Measurement in Autotransformers Using Low-Voltage Excitation
Authors: Zhang Min , Fang Jian , Wang Hongbin , Huang Qingdan , Hong Haicheng , Lin Xiang , Zhou Niancheng
Published: December 2023

In accordance with the IEEE standard, the zero-sequence impedance test of transformers necessitates an open or short circuit test on the high-voltage side winding. Power source excitation is applied to the high-voltage test winding using a high-capacity test power supply. To circumvent the need for a large-capacity, high-voltage test power supply in field tests, this paper proposes a method for measuring zero-sequence impedance in autotransformers based on low-voltage excitation and disconnection testing. By applying a three-phase power supply to the lowest voltage side of the autotransformer and creating a disconnection condition, an unbalanced test scenario is established. Subsequently, the composite sequence network equivalent circuit for one-phase and two-phase disconnections between the high-voltage side and the low-voltage side of the transformer is formulated. Calculation formulas for the zero-sequence impedance of the autotransformer under various conditions are derived. The accuracy of the zero-sequence impedance is verified using MATLAB/Simulink simulation software 2018b, evaluating double-winding and three-winding autotransformers in breaking tests under different connection modes. The error is found to be less than 3%. The results of this study affirm the high accuracy of the proposed method.
Boron Neutron Capture Therapy: Microdosimetry at Different Boron Concentrations
Authors: Conte Valeria , Bianchi Anna , Selva Anna
Published: December 2023

This paper explores the role of microdosimetry in boron neutron capture therapy (BNCT), a cancer treatment involving the selective accumulation of boron-containing compounds in cancer cells, followed by neutron irradiation. Neutron interactions with 10B induces a nuclear reaction, releasing densely ionizing particles, specifically alpha particles and recoiling lithium-7 nuclei. These particles deposit their energy within a small tissue volume, potentially targeting cancer cells while sparing healthy tissue. The microscopic energy distribution, subject to significant fluctuations due to the short particle range, influences treatment efficacy. Microdosimetry, by studying this distribution, plays a crucial role in optimizing BNCT treatment planning. The methodology employs paired tissue equivalent proportional counters (TEPCs), one with cathode walls enriched with boron and the other without. Precise assessment of boron concentration is essential, as well as the ability to extrapolate results to the actual 10B concentration within the treatment region. The effective 10B concentrations within four boronated TEPCs, containing 10, 25, 70, and 100 ppm of 10B, have been determined. Results show variations of less than 3% from nominal values. Additionally, dose enhancement due to BNC interactions was measured and found to be proportional to the 10B concentration, with a proportionality factor of 7.7 × 10−3 per ppm of boron. Based on these findings, a robust procedure is presented for assessing the impact of BNCT in the treatment region, considering potential variations in boron content relative to the TEPC used.
Gaussian-Linearized Transformer with Tranquilized Time-Series Decomposition Methods for Fault Diagnosis and Forecasting of Methane Gas Sensor Arrays
Authors: Zhang Kai , Ning Wangze , Zhu Yudi , Li Zhuoheng , Wang Tao , Jiang Wenkai , Zeng Min , Yang Zhi
Published: December 2023

Methane is considered as a clean energy that is widely used in places with high environmental requirements. The increasing demand for methane exploration in polar and deep sea extreme environments has a positive role in carbon neutrality policies. As a result, there will be a gradual increase in exploration activities for deep sea methane resources. Methane sensors require high reliability but are prone to faults, so fault diagnosis and forecasting of gas sensors are of vital practical significance. In this work, a Gaussian-linearized transformer model with a tranquilized time-series decomposition method is proposed for fault diagnosis and forecasting tasks. Since the traditional transformer model requires more computational expense with time complexity of O (N2) and is not applicable to continuous-sequence prediction tasks, two blocks of the transformer are improved. First, a Gaussian-linearized attention block is modified for fault-diagnosis tasks so that its time complexity can be changed to O (N), which can reduce computational resources. Second, a model with proposed attention for fault forecasting replaces the traditional embedding block with a decomposed block, which can input the continuous sequence data to the model completely and preserve the continuity of the methane data. Results show that the Gaussian-linearized transformer improves the accuracy of fault diagnosis to 99% and forecasting with low computational cost, which is superior to that of traditional methods. Moreover, the least mean-square-error loss of fault forecasting is 0.04, which is lower compared with the traditional time series prediction models and other deep learning models, highlighting the great potential of the proposed transformer for fault diagnosis and fault forecasting of gas sensor arrays.
Climatology and Changes in Temperature Seasonality in the Arabian Peninsula
Authors: Alghamdi Ali S.
Published: December 2023

Changes in temperature seasonality influence a wide range of societal and natural activities. The characteristics of the temperature/thermal seasons in the Arabian Peninsula and how the seasons have changed remain unclear. Using observational and reanalysis data (1985–2022), this research (1) introduces a new approach to define seasons based on a hybrid hierarchical k-means clustering method, (2) documents the characteristics of temperature/thermal seasons, and (3) examines changes in the timings (onset and end) and lengths of the temperature seasons in the Peninsula. The results indicate that summer is the longest season (165 days), with the onset ranging from mid- to late April in the southern and northern Arabian Peninsula, respectively. Winter begins in late November and lasts until late February, with a length averaging around 92 days. Spring and autumn are the shortest seasons, lasting for about 52 days. The seasons demonstrate latitudinal patterns in their timings that correspond well to the seasonal changes in solar inclination. A trend analysis shows that summer is extending and becoming warmer, particularly at night. Winter is becoming shorter, with higher temperatures during both the day and night. Spring is starting and ending earlier, with a higher increase in the daytime temperature. The results of this research will be valuable in various applications relevant to sustainable ecosystems and human well-being.
The Electric State of the Surface Atmosphere in the Mountain–Steppe Landscapes of Southern Siberia According to the Measurement Data in the Khakass–Tyva Expedition in 2022
Authors: Pustovalov Konstantin , Nagorskiy Petr , Oglezneva Mariya , Sat Artysh , Smirnov Sergei
Published: December 2023

Currently, many researchers are interested in investigating the electric field in the fair-weather electric environment, along with its diurnal and seasonal variations across all regions of the world. However, a similar study in the southern part of Siberia has not yet been carried out. In this regard, this study aims to estimate the mean values of the electric field and their variations in the mountain and steppe landscapes using the measurement data from the Khakass–Tyva expedition in 2022. The maximum values of positive ion density were noted at the site in the Iyussko-Shirinsky steppe between Belyo and Tus salt lakes in the Khakass-Minusinsk Basin. The maximum values of negative ion density were observed at the site in the Shol tract in the center part of the Tyva depression. The potential gradient tends to increase with altitude and reaches a maximum in the highlands. The maximum values of the potential gradient were noted in the highlands plateau near the Mongun-Taiga Mountain Massif and Khindiktig-Khol Lake. The diurnal cycles of potential gradient at different observation sites were divided into two groups: (1) a diurnal cycle in the form of a double wave; and (2) a daily cycle with a more complex course due to the strong influence of local factors.
Application of Trigonometric Polynomial Fitting Method in Simulating the Spatial Distribution of PM2.5 Concentration in South-Central China
Authors: Chen Yang , Li Ning , Xu Minjie , Shi Wenqi , Lv Xianqing
Published: December 2023

Near-surface PM2.5 estimates remain a global scientific research challenge due to their effect on human fitness and atmospheric environmental quality. However, practical near-surface PM2.5 estimates are impeded by the incomplete monitoring data. In this study, we propose the trigonometric polynomial fitting (TPF) method to estimate near-surface PM2.5 concentrations in south-central China during 2015. We employ 10-fold cross-validation (CV) to assess the reliability of TPF in estimating practical PM2.5 values. When compared to alternative methods such as the orthogonal polynomial fitting (OBF) method based on Chebyshev basis functions, Kriging interpolation, and radial basis function (RBF) interpolation, our results show that utilizing TPF31, with a maximum order of 3 in the x direction and a maximum order of 1 in the y direction, leads to superior efficiency through error minimization. TPF31 reduces MAE and RMSE by 1.93%, 24%, 6.96% and 3.6%, 23.07%, 10.43%, respectively, compared to the other three methods. In addition, the TPF31 method effectively reconstructs the spatial distribution of PM2.5 concentrations in the unevenly distributed observation stations of Inner Mongolia and the marginal regions of the study area. The reconstructed spatial distribution is remarkably smooth. Despite the non-uniform distribution of observation stations and the presence of missing data, the TPF31 method demonstrates exceptional effectiveness in accurately capturing the inherent physical attributes of spatial distribution. The theoretical and experimental results emphasize that the TPF method holds significant potential for accurately reconstructing the spatial distribution of PM2.5 in China.
Comment on Tabet et al. Vestibular Migraine versus Méniere’s Disease: Diagnostic Utility of Electrocochleography. Audiol. Res. 2023, 13, 12–22
Authors: Hornibrook Jeremy
Published: December 2023

I wish to comment on an aspect of the recently published article by Saliba I. et al., titled Vestibular Migraine versus Meniere’s Disease: Diagnostic Utility of Electrocochleograpy [...]
A Nonclassical Stefan Problem with Nonlinear Thermal Parameters of General Order and Heat Source Term
Authors: Khanfer Ammar , Bougoffa Lazhar , Bougouffa Smail
Published: December 2023

The analytic solution for a general form of the Stefan problem with nonlinear temperature-dependent thermal parameters and a heat source the term is obtained. We prove the existence and uniqueness of the solution to the problem in the absence of a heat source (β=0), and in the presence of a heat source β(x)=exp(−x2). Then, we establish lower and upper bounds for the solutions of the homogeneous equation and the nonhomogeneous equation, for different values of δi and γi. It was found that the lower bounds exhibit an excellent alignment with the numerical solutions of the homogeneous and nonhomogeneous equations, so the lower bounds can serve as approximate analytic solutions to the problem. This is a generalization to the open problem proposed by Cho and Sunderland in 1974 and also generalizes the problem proposed by Oliver and Sunderland in 1987, in addition to the problems investigated recently.
Modeling High-Frequency Zeros in Time Series with Generalized Autoregressive Score Models with Explanatory Variables: An Application to Precipitation
Authors: Vidal-Gutiérrez Pedro , Contreras-Espinoza Sergio , Novoa-Muñoz Francisco
Published: December 2023

An extension of the Generalized Autoregressive Score (GAS) model is presented for time series with excess null observations to include explanatory variables. An extension of the GAS model proposed by Harvey and Ito is suggested, and it is applied to precipitation data from a city in Chile. It is concluded that the model provides adequate prediction, and furthermore, an analysis of the relationship between the precipitation variable and the explanatory variables is shown. This relationship is compared with the meteorology literature, demonstrating concurrence.
A Review of Optimization Studies for System Appointment Scheduling
Authors: Niu Tiantian , Lei Bingyin , Guo Li , Fang Shu , Li Qihang , Gao Bingrui , Yang Li , Gao Kaiye
Published: December 2023

In the face of an increasingly high-demand environment for outpatients, achieving a balance between allocation of limited medical resources and patient satisfaction has considerable social and economic benefits. Therefore, appointment scheduling (AS) system operation is used in clinics and hospitals, and its operation optimization research is of great significance. This study reviews the research progress on appointment scheduling system optimization. Firstly, we classify and conclude the existing appointment scheduling system structures and decision-making frameworks. Subsequently, we summarize the system reliability optimization framework from three aspects: appointment scheduling system optimization objectives, decision variables and constraints. Following that, we methodically review the most applied system optimization algorithms in different appointment scheduling systems. Lastly, a literature bibliometric analysis is provided. During our review of the literature, we observe that (1) optimization methods in ASs predominantly involve the application of genetic algorithms and simulation optimization algorithms; (2) neural networks and deep learning methods are core technologies in health management optimization; (3) a bibliometric analysis reveals a heightened interest in the optimization technology of ASs within China compared to other nations; and (4) further advancements are essential in the comprehensive optimization of the system, exploration of practical usage scenarios, and the application of advanced simulation and modeling techniques in this research.
Secondary High-Temperature Treatment of Porous Carbons for High-Performance Supercapacitors
Authors: Chi Weihao , Wang Guanwen , Qiu Zhipeng , Li Qiqi , Xu Zheng , Li Zhiyuan , Qi Bin , Cao Ke , Chi Chunlei , Wei Tong , Fan Zhuangjun
Published: December 2023

Supercapacitors are extensively used in urban rail transit, electric vehicles, renewable energy storage, electronic products, and the military industry due to its long cycle life and high power density. Porous carbon materials are regarded as promising anode materials for supercapacitors due to their high specific surface areas and well-developed pore structures. However, the over-developed pore structure often results in poor conductivity and reduced cycle stability due to the destruction of a carbon skeleton. Herein, we introduce an advanced strategy for preparing porous carbon with high specific surface areas (3333 m2 g−1), high electrical conductivity (68.6 S m−1), and fast ion transport channels through secondary high-temperature carbonization treatment. As a result, the fabricated porous carbon anode delivers a high specific capacitance (199.2 F g−1 at 1 A g−1) and outstanding rate performance (136.3 F g−1 at 20 A g−1) in organic electrolyte. Furthermore, the assembled symmetrical supercapacitor achieves an energy density of 43.2 Wh kg−1 at 625.0 W kg−1, highlighting the potential of a secondary high-temperature carbonization strategy in practical applications.
Dissolved Oxygen Removal in Wines by Gas Sparging, Its Optimization and Chemical Impact
Authors: del Barrio-Galán Rubén , Nevares Ignacio , Pérez-Magariño Silvia , del Alamo-Sanza Maria
Published: December 2023

Sparging is a technique to remove an excess of dissolved oxygen from the wine with inerting gases before bottling to avoid negative consequences for its chemical and sensory properties. However, its effectiveness on these properties has not been studied in depth. This work investigates the effectiveness of different inerting gases (N2, CO2, and argon) in removing dissolved oxygen in different volumes of a model wine. The efficacy of these gases was also studied in white and red wine, as was their effect on the physicochemical characteristics. Sparging with N2 in the model wine gave the best results in terms of cost–benefits, and with CO2 the worst. The scaling in tanks of different sizes allowed us to establish that the N2 expenditure ranged between 0.09 L and 0.23 L of gas per liter of model wine, establishing an index (Lgas/Lwine) that can be very useful for wineries to remove the dissolved oxygen. Sparging treatments in white and red wine showed very similar results to the model wine. The effect on the chemical properties of the wines was, in some cases, different for white and red wine and for each gas used. The incorporation of oxygen and the subsequent sparging produced a significant loss of some volatile compounds of sensory interest and increased the content of others that have a negative sensory effect. In addition, it had a negative effect on the chromatic properties of red wines.
The Kavalactone Content and Profile of Fiji Kava Sold on the Local Market
Authors: Pasinszki Tibor , Devi Deepti Darshani
Published: December 2023

Kava is the traditional intoxicating beverage of the Pacific with mild sedative and muscle relaxant effects, which are attributed to a group of compounds known as kavalactones. This paper aims to evaluate the quality of kava sold in the local markets of Fiji through the quantification of the six major kavalactones in kava root bundles and powdered kava packages using ethanolic extracts and HPLC. It was found in this work that kava root bundles contain mainly noble kava roots with a total kavalactone content of 8–13%; kavain had the highest concentration among kavalactones and kavain, methysticin, and yangonin together represented 69–71% of the total kavalactone content. Adulteration via mixing noble kava roots with those of non-noble kava with a relatively high dihydrokavain and dihydromethysticin content has also been observed. Powdered kava products were found to contain lower amounts of kavalactones (3–5%) with a less favorable kavalactone profile than those of root bundles, possibly due to mixing roots, rhizomes, and/or basal stems. The findings of this work, namely the variation in kavalactone content and profile in marketed products, indicate the need for rigorous quality control and quality indicators on kava commodities. Suggestions to include quantitative measures in the previously proposed chemical standardization code are also presented.
A Biomechanical Simulation of Forearm Flexion Using the Finite Element Approach
Authors: Liang Chenyang , Jiang Fei , Kawaguchi Daisuke , Chen Xian
Published: December 2023

Upper limb movement is vital in daily life. A biomechanical simulation of the forearm with consideration of the physiological characteristics of the muscles is instrumental in gaining deeper insights into the upper limb motion mechanisms. In this study, we established a finite element model of the forearm, including the radius, biceps brachii, and tendons. We simulated the motion of the forearm resulting from the contraction of the biceps brachii by using a Hill-type transversely isotropic hyperelastic muscle model. We adjusted the contraction velocity of the biceps brachii muscle in the simulation and found that a slower muscle contraction velocity facilitated forearm flexion. Then, we changed the percentage of fast-twitch fibers, the maximum muscle strength, and the neural excitation values of the biceps brachii muscle to investigate the forearm flexion of elderly individuals. Our results indicated that reduced fast-twitch fiber percentage, maximum muscle strength, and neural excitation contributed to the decline in forearm motion capability in elderly individuals. Additionally, there is a threshold for neural excitation, below which, motion capability sharply declines. Our model aids in understanding the role of the biceps brachii in forearm flexion and identifying the causes of upper limb movement disorders, which is able to provide guidance for enhancing upper limb performance.