bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data-driven approach for prediction of band diagram of locally resonant sonic crystal
Authors: Karthik R , Barathula Sreeram , Srinivasan K 
Published: December 2023

Abstract
The present study focuses on the prediction of the band diagram of locally resonance sonic crystal (LRSC) using machine learning models from structural, lattice material parameters. The data set for the study is generated from the numerical simulations of LRSC for wide ranges of structural, lattice material parameters using COMSOL multiphysics solver. Three machine learning algorithms namely, support vector machine (SVM), artificial neural network (ANN), and random forest regression (RFR), are employed for the study. A total of 23040 samples are simulated and included in the training of the models. Hyperparameter tuning and data set size optimization are carried out to find the optimum machine learning model given the minimum required data set. The R2 score, root mean square error (RMSE), computational time, and inference time are used to evaluate the performance of machine learning algorithms. The feature importance scores and partial dependence plots (PDPs) are used to understand each input feature’s critical role in predicting the band diagram. Among all the machine learning models studied, RFR outperformed the ANN and SVM models. RFR with 50 decision trees performed well. However, RFR with 10 decision trees also performed well with slight higher RMSE offering lower inference time compared to RFR with 50 decision trees. Due to the importance of the first two band gaps in noise attenuation, the width and center frequency of the first two bandgaps are predicted through the band diagram. The feature importance scores and PDPs of RFR models show that the structural and lattice parameters play a crucial role in predicting the first and second bandgap, aligning with physical significance.
A MCKF-based cascade vector tracking method designed for ship navigation
Authors: Liu Wei , Ma Panting , Hu Yuan , Wang Xingdi , Hsieh Tsung-Hsuan , Han Bing , Wang Shengzheng 
Published: December 2023

Abstract
In ship navigation, the most widely used technology is global navigation satellite systems (GNSS), which provide the ship’s position and velocity continuously over a period of time. However, when ships are blocked by port buildings or bridges, the quality of signals received from shipborne GNSS receivers may be reduced, resulting in inaccurate ship positioning that poses a risk to navigational safety. In an occluded environment, the measurement process during the signal processing of shipborne GNSS receivers is nonstationary and prone to measurement anomalies, which can contaminate measurement noise with outliers. To address this problem, a cascaded non-coherent vector tracking loop is designed, with the maximum correntropy Kalman filter serving as a cascaded carrier/code pre-filter for shipborne GNSS receivers. The measurement noise covariance matrix of the pre-filter is adaptively calculated and corrected using the carrier-to-noise ratio and the maximum correntropy criterion, respectively. The algorithm proposed is more sensitive to outliers than the traditional tracking methods and can effectively solve the state estimation problem under the condition of measurement anomalies. Specifically, the algorithm offers ships with more precise position and velocity estimations and lower signal tracking errors than traditional tracking methods under both static and dynamic conditions, as demonstrated by shipboard experiments. The horizontal positioning is increased by 88.4% and the horizontal velocity error is reduced by 62.1% in the occluded environment under dynamic conditions.
Ab initio study of the processes of nitrogen functionalisation in graphene
Authors: Malenfant-Thuot Olivier , Morinière Maxime , Côté Michel 
Published: December 2023

Abstract
Nitrogen functionalisation of graphene is studied with the help of ab initio electronic structure methods. Both static formation energies and energy barriers obtained from nudged elastic band calculations are considered. If carbon defects are present in the graphene structure, low energy barriers on the order of 0.5 eV were obtained to incorporate nitrogen atoms inside the sheet. For defect-free graphene, much larger barriers in the range of 3.70–4.38 eV were found, suggesting an external energy source is required to complete this type of incorporation.
Variable RBE in proton radiotherapy: a comparative study with the predictive Mayo Clinic Florida microdosimetric kinetic model and phenomenological models of cell survival
Authors: Parisi Alessio , Beltran Chris J. , Furutani Keith M. 
Published: December 2023

Abstract

Objectives. (1) To examine to what extent the cell- and exposure- specific information neglected in the phenomenological proton relative biological effectiveness (RBE) models could influence the computed RBE in proton therapy. (2) To explore similarities and differences in the formalism and the results between the linear energy transfer (LET)-based phenomenological proton RBE models and the microdosimetry-based Mayo Clinic Florida microdosimetric kinetic model (MCF MKM). (3) To investigate how the relationship between the RBE and the dose-mean proton LET is affected by the proton energy spectrum and the secondary fragments. Approach. We systematically compared six selected phenomenological proton RBE models with the MCF MKM in track-segment simulations, monoenergetic proton beams in a water phantom, and two spread-out Bragg peaks. A representative comparison with in vitro data for human glioblastoma cells (U87 cell line) is also included. Main results. Marked differences were observed between the results of the phenomenological proton RBE models, as reported in previous studies. The dispersion of these models’ results was found to be comparable to the spread in the MCF MKM results obtained by varying the cell-specific parameters neglected in the phenomenological models. Furthermore, while single cell-specific correlation between RBE and the dose-mean proton LET seems reasonable above 2 keV μm−1, caution is necessary at lower LET values due to the relevant contribution of secondary fragments. The comparison with in vitro data demonstrates comparable agreement between the MCF MKM predictions and the results of the phenomenological models. Significance. The study highlights the importance of considering cell-specific characteristics and detailed radiation quality information for accurate RBE calculations in proton therapy. Furthermore, these results provide confidence in the use of the MCF MKM for clonogenic survival RBE calculations in proton therapy, offering a more mechanistic approach compared to phenomenological models.
Integro-differential equations implicated with Caputo-Hadamard derivatives under nonlocal boundary constraints
Authors: Hammad Hasanen A , Aydi Hassen , Kattan Doha A 
Published: December 2023

Abstract
The goal of this work is to derive a new type of fractional system that arises from the combination of the Caputo-Hadamard derivative with the integro-differential equation. Also, the existence and uniqueness of solutions to this problem have been studied under nonlocal boundary conditions. Moreover, Hyer-Ulam stability has been studied for the considered problem. Finally, to reinforce the theoretical results and provide applications for our paper, two supporting examples have been emphasized.
Single photon hybrid quantum key distribution
Authors: Ferro Laryssa F , Avelar Ardiley T , Cardoso Wesley B , Gomes Rafael M 
Published: December 2023

Abstract
In this work, we propose a quantum key distribution protocol using the polarization and transverse spatial degrees of freedom of single photons. We show that the protocol is secure and easy to implement experimentally, thus being able to be used in investigations on optical communication. In addition, we show that the information transmitted between two separate parties is always greater than the information retained by a eavesdropper. In this way, it is always possible to employ classical error correction and privacy amplification to minimize eavesdropper information.
MIM plasmonic sensors based on single-side ring cavity with one stub and their applications
Authors: Sun Yiping , Qu Desheng , Wu Qiaohua , Li Chunlei 
Published: December 2023

Abstract
A plasmonic sensor is proposed, comprising a metal–insulator–metal (MIM) straight waveguide and a ring cavity with one stub (RCS). Using the finite element method, its transport properties are simulated and systematically analyzed. By optimizing the structure parameters, the sensor obtains the maximum sensitivity (S) of 2010 nm/RIU and the maximum figure of merit (FOM) of 49219.04 RIU−1. It demonstrates a sensing resolution (SR) of 4.98 × 10−7 RIU in the detection of refractive index variation. Based on the optimized parameters, temperature sensing is investigated utilizing Polydimethylsiloxane (PDMS) as the temperature-sensitive medium, and the temperature sensitivity is found to be −0.90 nm/°C. In addition, multiple independently tunable resonances are achieved by adding a ring cavity (RC) above the straight waveguide. This derived structure enables the simultaneous detection of electrolyte samples (Na+ and K+) in blood with bio-sensing sensitivities reaching 0.1833 nm·dL/mg and 0.2 nm·dL/mg. These results have directive significance for the development of multifunctional and ultra-compact plasmonic sensor.
A novel adaptive synchronization algorithm for a general class of fractional-order complex-valued systems with unknown parameters, and applications to circuit realization and color image encryption
Authors: Shoreh A A-H , Mahmoud Gamal M 
Published: December 2023

Abstract
This article proposes an adaptive synchronization (AS) algorithm to synchronize a general class of fractional-order complex-valued systems with completely unknown parameters, which may appear in physical and engineering problems. The analytical and theoretical concepts of the algorithm rely on the mathematical framework of the Mittag-Leffler global stability of fractional-order systems. A specific control system is established analytically based on the fractional-order adaptive laws of parameters, and the corresponding numerical results are executed to verify the accuracy of the AS algorithm. The proposed synchronization method is evaluated using the fractional-order complex Rabinovich system as an attractive example. The electronic circuits of the new system with different fractional orders are designed. By utilizing the Multisim electronic workbench software, various chaotic/hyperchaotic behaviors have been observed, and a good agreement is found between the numerical results and experimental simulation. In addition, the approximation of the transfer function for different fractional-order are presented. And the corresponding resistor and capacitor values in the chain ship model (CSM) are estimated, which can be utilized in designing electronic circuits for other fractional-order systems. Furthermore, two strategies for encrypting color images are proposed using the AS algorithm and fractional-order adaptive laws of parameters. In the first strategy, the color image is treated as a single package and divided into two vectors. The first vector is embedded into transmitter parameters, while the second vector is injected into the transmitter state signals. In the second strategy, the primary RGB channel components of the original color image are extracted and separated into two vectors, and the same process is followed as in the first strategy. These strategies complicate the decryption task for intruders. Different scales of white Gaussian noise are added to color images to examine the robustness of the proposed color images encryption strategies.
Emergent Unparticles Dark Energy can restore cosmological concordance
Authors: Ben-Dayan Ido , Kumar Utkarsh 
Published: December 2023

Abstract
Addressing the discrepancy between the late and early time measurements of the Hubble parameter, H
0, and the so-called S
8 parameter has been a challenge in precision cosmology. Several models are present to address these tensions, but very few of them can do so simultaneously. In the past, we have suggested Banks-Zaks/Unparticles as an emergent Dark Energy model, and claimed that it can ameliorate the Hubble tension. In this work, we test this claim, and perform a likelihood analysis of the model and its parameters given current data, and compare it to ΛCDM. The model offers a possible resolution of Hubble tension and softens the Large Scale Structure (LSS) tension without employing a scalar field or modifying the gravitational sector. Our analysis shows a higher value of H
0 ∼ 70 – 73 km/sec/Mpc and a slightly lower value of S
8 for certain combinations of data sets. Consideration of Planck CMB data combined with the Pantheon sample and SH0ES priors lowers the H
0 and S
8 tension to 0.96σ and 0.94σ respectively with best-fit Δχ
2 ≈ -11 restoring cosmological concordance. Significant improvement in the likelihood persists for other combinations of data sets as well. Evidence for the model is given by inferring one of its parameters to be x
0 ≃ -4.46.
The improvement in the fit is driven by the inclusion of the SH0ES prior. In its absence most of the improvement is due to larger error bars in the Emergent Unparticles Dark Energy model.
Power generation Technology of condensed water Temperature Differences in central air conditioning
Authors: Li Chenchen , Guo Changbao 
Published: December 2023

Abstract
With the rapid development of modern society, the improvement of people’s requirements for living comfort makes the utilization rate of central air conditioning in civil buildings and industrial plants greatly improved. The research and development of energy-saving technology under “double carbon” has also been paid attention to. As a hot new energy technology in recent years, thermoelectric power generation technology can improve the efficiency of old energy and be used in acquiring renewable energy, which is widely a concern by researchers. And central air conditioning in the summer operation of the condensate water still has much cold capacity not used. Therefore, the purpose of this study is to use the temperature difference between the low-temperature condensed water of central air conditioning and the external high temperature of the environment to achieve the purpose of energy saving and emission reduction.
Configuration and Robust Optimization Method of Energy Storage Capacity on the User Side of Power Grid Based on Improved Grey Wolf Algorithm
Authors: Hu Yuou , Zhang Jing , Cui Fubo , Wang Yimeng , Xu Yijing , Zhu Yanan 
Published: December 2023

Abstract
The configuration and optimization of energy storage capacity on the user side of the power grid are currently active research areas in the power system. This article presents a method that utilizes an enhanced Grey Wolf algorithm to address the issues of configuring and optimizing energy storage capacity on the user side. The Grey Wolf algorithm is improved by incorporating differential evolution and calculating the fitness value. Based on this, the objective function for the configuration model of user-side energy storage capacity is established, considering the uncertainty parameters as uncertainty set to achieve robust optimization. The design of the method for user-side energy storage capacity configuration and robust optimization, utilizing the improved Grey Wolf algorithm, is accomplished. The experimental results confirm the practicality of the proposed method.
Design and Optimization of Complex High-Frequency Electromagnetic Treatment Cavity
Authors: Qin Chunyu , Wang Dongqiang , Li Gangsheng , Dong Xuewu , Jiang Haiqin 
Published: December 2023

Abstract
High-frequency electromagnetic water treatment devices play a crucial role in the scale inhibition and fouling control process of industrial water treatment. They are widely used in various factories and can be classified into coaxial treatment cavities and coil-wound treatment cavities. To address the issues of low energy distribution at the edge of the coaxial treatment cavity and weak peak energy in the coil-wound treatment cavity, which result in unstable scale inhibition and fouling control effectiveness, this study derives a numerical calculation formula for electromagnetic energy in a complex treatment cavity based on the theories of active polarization and quasi-static field. A complex high-frequency electromagnetic water treatment device is designed using this formula, and the internal structure of the treatment cavity is visually analyzed using simulation software. Through the optimization of the complex treatment cavity’s structure, the optimal range of the anode-cathode radius ratio is determined. The research results show that the energy distribution in the complex treatment cavity is significantly higher than that in the coaxial and coil-wound cavities. This study provides theoretical and practical guidelines for the design of high-frequency electromagnetic water treatment device cavities.
Modeling and simulation of dynamic characteristics of marine PEM fuel cells
Authors: Wang Jie , Teng Xianbin , Zhu Faxin , Chen Tian , Chen Hao , Wang Yining 
Published: December 2023

Abstract
This paper aims to achieve stable and reliable operation of the marine PEM fuel cell systems. To accomplish this, a dynamic model that incorporates the thermodynamic electric potential and the three irreversible voltage losses of the fuel cell was established and simulated using Matlab/Simulink software based on the steady-state model of the PEM fuel cell. Under certain ideal conditions, the dynamic response of the PEM fuel cell was simulated and analyzed concerning various environmental factors and internal parameters of the fuel cell stack. An input signal source was used as an applied load for this purpose. The simulations and analysis focused on examining the impact of each factor on the performance of the PEM fuel cell. Specifically, the dynamic response is investigated when the load signal undergoes a step change. In addition to enhancing the drawbacks of the conventional steady-state system model, which tends to be complex with redundant parameters and a large amount of data, the dynamic model also establishes a theoretical foundation for optimizing the performance of PEM fuel cells and enabling automatic control of the system.
LiCoO2 Cathode Modified With Liquid-exfoliated Graphene for High-performance Full Batteries
Authors: Nan Wenzheng 
Published: December 2023

Abstract
Graphene has been successfully applied for modification of LiCoO2 cathode, but finding a large-scale preparation method of high-quality graphene for commercial application remains a great challenge. In this work, we have demonstrated a facile strategy to prepare few-layer defect-free graphene. The prepared graphene performs well in application for LiCoO2 cathode in the full battery system as conductive additives. The superior conductive graphene is attached to LiCoO2 particles, and fast pathways of electronic transport in the bulk electrode and protective layer on the interface between LiCoO2 and electrolyte are constructed. The cathode with 0.35% wt% graphene displays superior rate capacity (145 mAh/g at 2C) and excellent 4.5 V high-voltage cycle performance, which can be contributed to lower internal resistance and a more stabilized interface. The graphene shows great potential in commercial applications for high-performance LiCoO2-based full batteries.
ICEEMDAN-IWOA-BiLSTM Hybrid Algorithm-based Model for Short-term Load Forecasting
Authors: Dong Enchong , Luan Wenting 
Published: December 2023

Abstract
Given the uncertain, random, and volatile characteristics of power load, accurate forecasting of power load becomes challenging. To address this issue, this paper proposes an optimized prediction model by using a modified Adaptive White Noise Complete Integrated Empirical Modal Decomposition Algorithm (ICEEMDAN) and the improved Whale Optimization Algorithm (IWOA) for bidirectional short-term and long-term memory networks (BiLSTM). First of all, Australian power load data is preprocessed in this study. Then, the load data is decomposed into a series of sequences by using ICEEMDAN. After that, the improved whale algorithm is employed to analyze the BiLSTM super parameter optimization. Finally, each decomposed component is input into the IWOA-BiLSTM model for load forecasting. The results demonstrate that the proposed algorithm achieves higher accuracy in power load forecasting, compared to individual benchmark models and most portfolio models, indicating its applicability and practical value.
Research on the Passive Cooling System of Solar Photovoltaic Panel Based on Hybrid Solar Chimney and Ventilator
Authors: Zhang GengE , Misaran Mohd Suffian , Adzrie Mohd , Amaludin Nazrein Adrian , Guramun Stevenson 
Published: December 2023

Abstract
The efficiency of solar photovoltaic (PV) power generation is significantly impacted by factors such as ambient temperature, surrounding wind speed, and the temperature of the solar PV panels. The power generation efficiency of these panels diminishes by approximately 0.5% for each incremental rise in their temperature. To mitigate this effect, two primary methods for cooling solar photovoltaic panels are considered: active and passive cooling techniques. This review paper delves into an extensive body of literature on solar passive cooling systems, highlighting the vital role of passive cooling technology in enhancing the efficiency of solar PV power generation. We investigate the structure and cooling effect of diverse passive cooling systems, with a specific focus on the application of solar chimneys and ventilators in cooling systems for solar PV panels. Our study reveals that solar chimneys, using buoyancy, can decrease the temperature of solar PV panels by as much as 15 degrees, thereby augmenting power generation efficiency. Furthermore, the deployment of ventilator technology can boost the efficiency of solar PV power generation to an impressive 46.54%. In conclusion, this paper proposes the synergistic use of solar chimneys and ventilators to improve solar PV panel efficiency, extend their lifespan, and reduce the environmental impact resulting from inefficient solar PV panels. This comprehensive approach should inform future practices.
Design and Implementation of Device-level Load Dynamic Adjustment System for Electric Vehicles
Authors: Huang Shu , Liu Ze-san , Meng Hong-min , Xu Zhe-nan , Wen Ai-jun , Liu Di 
Published: December 2023

Abstract
The development of electric vehicles is an important means to deal with the energy crisis, relieve environmental pressure, and achieve sustainable development. The rapid growth of electric vehicle ownership brings great challenges to the planning and safe and stable operation of the power system. To ensure the stable operation of the power grid and meet the changing needs of users to the greatest extent in the case of extreme power shortage and demand response, it is necessary to dynamically adjust the power of charging piles according to the actual situation. At present, many operators cannot accurately and dynamically control the power of each charging pile in the station in the face of power limit demand, so they can only turn off some or all charging piles, which not only affects the charging experience of users but also leads to the decline of operators’ reputation and profits. To solve the above problems, this paper proposed a charging load dynamic adjustment system, which uses the TCN model based on similar days to predict the charging load. It proposed a load decomposition algorithm to control the device-level charging load. Experiments show that the load prediction model used in this system has higher accuracy than LSTM, and the load decomposition algorithm can reasonably allocate limited load resources, which means the system can meet the user’s charging demand to the greatest extent while meeting the power limit demand and improve the user experience.