bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid model based on novel SVM-SVR and weighted combination strategy for build-up rate prediction
Authors: Wang Hongyu , Geng Yanfeng , Zhang Menghua , Wang Weiliang , Yang Yisen , Qian Haiyu , Xi Chaoyue 
Published: October 2024

Abstract
The build-up rate prediction is of great importance for trajectory control in the field of drilling. However, it is very difficult to achieve accurate prediction due to the complexity, nonlinearity, and multiple uncertainties of the drilling system. As a consequence, a novel hybrid prediction model is proposed, which uses multiple feature selection methods, the model combination strategy based on machine learning, and three prediction models to improve the prediction accuracy of the build-up rate. More precisely, correlation analysis, importance analysis, and statistical analysis are employed to ensure the effectiveness of feature selection. Then, a novel classification prediction model called support vector machine-support vector regression (SVM-SVR) is proposed to improve the accuracy of samples with the higher build-up rate. Subsequently, the SVR optimized by grey wolf optimizer (GWO-SVR) and back propagation (BP) neural network are constructed. Finally, the three models are integrated by a weighted combination method based on SVR to realize the accurate prediction of the build-up rate. To verify the performance of the hybrid model, the data of the Z48 well in Sichuan province is used, and the results show that the hybrid model can reduce by 22.7% in mean absolute error and 32% in mean square error when compared with the existing models.
Heterogeneous graph neural network for modeling intelligent manufacturing systems
Authors: Zhu Guangyi , Wang Siyuan , Wang Lilin 
Published: October 2024

Abstract
Currently, manufacturing systems have become more and more complex, often involving multiple machines, systems and processes to produce workpieces. In order to facilitate comprehensive analysis and control of manufacturing processes, the integration of connections between machine level, system level, and process level in manufacturing process modeling is needed. However, traditional graph deep learning models are unable to take into account the heterogeneity of different machines in the system when modeling manufacturing systems. To address this problem, this paper proposes a new approach: modeling manufacturing systems using the heterogeneous graph neural network sample and aggregate algorithm based on cutting-edge Bayesian neural networks and graph deep learning. This method considers the connection between different manufacturing system levels, treats machine operations as nodes, and connects different nodes through material flow and operational similarity. The effectiveness of the method is demonstrated through its application to model an aero-engine blade production line. Extensive numerical experiments show that the proposed graph modeling method is effective in expressing the heterogeneity of different machines and multi-level manufacturing processes. By integrating machine heterogeneity into the modeling of a manufacturing system, it not only facilitates comprehensive analysis and control of the manufacturing process, but also lays the foundation for cost savings and productivity improvements in the manufacturing system.
Explainable AI for automated respiratory misalignment detection in PET/CT imaging
Authors: Salimi Yazdan , Mansouri Zahra , Amini Mehdi , Mainta Ismini , Zaidi Habib 
Published: October 2024

Abstract

Purpose. Positron emission tomography (PET) image quality can be affected by artifacts emanating from PET, computed tomography (CT), or artifacts due to misalignment between PET and CT images. Automated detection of misalignment artifacts can be helpful both in data curation and in facilitating clinical workflow. This study aimed to develop an explainable machine learning approach to detect misalignment artifacts in PET/CT imaging. Approach. This study included 1216 PET/CT images. All images were visualized and images with respiratory misalignment artifact (RMA) detected. Using previously trained models, four organs including the lungs, liver, spleen, and heart were delineated on PET and CT images separately. Data were randomly split into cross-validation (80%) and test set (20%), then two segmentations performed on PET and CT images were compared and the comparison metrics used as predictors for a random forest framework in a 10-fold scheme on cross-validation data. The trained models were tested on 20% test set data. The model’s performance was calculated in terms of specificity, sensitivity, F1-Score and area under the curve (AUC). Main results. Sensitivity, specificity, and AUC of 0.82, 0.85, and 0.91 were achieved in ten-fold data split. F1_score, sensitivity, specificity, and AUC of 84.5 vs 82.3, 83.9 vs 83.8, 87.7 vs 83.5, and 93.2 vs 90.1 were achieved for cross-validation vs test set, respectively. The liver and lung were the most important organs selected after feature selection. Significance. We developed an automated pipeline to segment four organs from PET and CT images separately and used the match between these segmentations to decide about the presence of misalignment artifact. This methodology may follow the same logic as a reader detecting misalignment through comparing the contours of organs on PET and CT images. The proposed method can be used to clean large datasets or integrated into a clinical scanner to indicate artifactual cases.
Box-counting measure of metric spaces
Authors: Huang Liang-yi , Rao Hui , Wen Zhiying , Xu Yan-li 
Published: October 2024

Abstract
In this paper, we introduce a new notion called the box-counting measure of a metric space. We show that for a doubling metric space, an Ahlfors regular measure is always a box-counting measure; consequently, if E is a self-similar set satisfying the open set condition, then the Hausdorff measure restricted to E is a box-counting measure. We show two classes of self-affine sets, the generalized Lalley-Gatzouras type self-affine sponges and Barański carpets, always admit box-counting measures; this also provides a very simple method to calculate the box-dimension of these fractals. Moreover, among others, we show that if two doubling metric spaces admit box-counting measures, then the multi-fractal spectra of the box-counting measures coincide provided the two spaces are Lipschitz equivalent.
Tailoring the coexistence of Ce(PO4)@Mn3(PO4)2/MXene for supercapacitive application
Authors: Obodo Raphael M , Nsude Hope E , Okereke Benjamin O , Eze Chimezie U , Duru Miletus O , Ezike Sabastine C , Ahmad Ishaq , Maaza M 
Published: October 2024

Abstract
Recently, supercapacitors have been considered an excellent option for improving electrical and electronic systems because of their huge potential as energy storage devices. In this work, two phases of the hydrothermal process and drop casting method were used to fabricate the synthesized composites of Cerium phosphate/MXene (MX) (Ce(PO4)/MXene), Manganese phosphate (Mn3(PO4)2/MXene), and Cerium@Manganese phosphates (Ce(PO4)@Mn3(PO4)2/MXene) electrodes. These electrodes’ structural, morphological, functional, optical and electrochemical characteristics were examined. The electrochemical studies were carried out in a 3-electrode system to determine their specific capacitance, energy and power densities. The maximum obtained specific capacitance of 1125 Fg−1 and 1350 Fg−1 from Ce(PO4)@Mn3(PO4)2/MXene electrode using 1.0 mVs−1 scan rate and 0.5 Ag−1 current density respectively. Using a 1.0 molar solution of Na2SO4 as the electrolyte, 10,000 continuous charge–discharge cycles were achieved with a cyclic stability of 75.7%.
Time-fractional of cubic-quartic Schrödinger and cubic-quartic resonant Schrödinger equations with parabolic law: various optical solutions
Authors: Ahmed Hakima Khudher , Ismael Hajar Farhan 
Published: October 2024

Abstract
Schrödinger's nonlinear equation is a fundamental model in fiber optics and many other areas of science. Using the Jacobi elliptic expansion function method, the time-fractional cubic-quartic nonlinear Schrödinger equation and cubic-quartic resonant nonlinear Schrödinger equation are investigated. By applying the effective Jacobi elliptic expansion function method, optical soliton solutions such as bright, dark, singular, periodic singular, exponential, and Jacobi elliptic function solutions have been obtained. The effect of the time-fractional derivative on the solutions is also revealed. Graphical representations are illustrated to showcase the physical properties of raised solutions, providing a comprehensive understanding of the solutions’ functionality.
High-quality multimodal MRI with simultaneous EEG using conductive ink and polymer-thick film nets
Authors: Cicero Nicholas G , Fultz Nina E , Jeong Hongbae , Williams Stephanie D , Gomez Daniel , Setzer Beverly , Warbrick Tracy , Jaschke Manfred , Gupta Ravij , Lev Michael , Bonmassar Giorgio , Lewis Laura D 
Published: October 2024

Abstract

Objective. Combining magnetic resonance imaging (MRI) and electroencephalography (EEG) provides a powerful tool for investigating brain function at varying spatial and temporal scales. Simultaneous acquisition of both modalities can provide unique information that a single modality alone cannot reveal. However, current simultaneous EEG-fMRI studies are limited to a small set of MRI sequences due to the image quality and safety limitations of commercially available MR-conditional EEG nets. We tested whether the Inknet2, a high-resistance polymer thick film based EEG net that uses conductive ink, could enable the acquisition of a variety of MR image modalities with minimal artifacts by reducing the radiofrequency-shielding caused by traditional MR-conditional nets. Approach. We first performed simulations to model the effect of the EEG nets on the magnetic field and image quality. We then performed phantom scans to test image quality with a conventional copper EEG net, with the new Inknet2, and without any EEG net. Finally, we scanned five human subjects at 3 Tesla (3 T) and three human subjects at 7 Tesla (7 T) with and without the Inknet2 to assess structural and functional MRI image quality. Main results. Across these simulations, phantom scans, and human studies, the Inknet2 induced fewer artifacts than the conventional net and produced image quality similar to scans with no net present. Significance. Our results demonstrate that high-quality structural and functional multimodal imaging across a variety of MRI pulse sequences at both 3 T and 7 T is achievable with an EEG net made with conductive ink and polymer thick film technology.
Brain and muscle derived features to discriminate simple hand motor tasks for a rehabilitative BCI: comparative study on healthy and post-stroke individuals
Authors: de Seta Valeria , Colamarino Emma , Pichiorri Floriana , Savina Giulia , Patarini Francesca , Riccio Angela , Cincotti Febo , Mattia Donatella , Toppi Jlenia 
Published: October 2024

Abstract

Objective. Brain–Computer Interfaces targeting post-stroke recovery of the upper limb employ mainly electroencephalography to decode movement-related brain activation. Recently hybrid systems including muscular activity were introduced. We compared the motor task discrimination abilities of three different features, namely event-related desynchronization/synchronization (ERD/ERS) and movement-related cortical potential (MRCP) as brain-derived features and cortico-muscular coherence (CMC) as a hybrid brain-muscle derived feature, elicited in 13 healthy subjects and 13 stroke patients during the execution/attempt of two simple hand motor tasks (finger extension and grasping) commonly employed in upper limb rehabilitation protocols. Approach. We employed a three-way statistical design to investigate whether their ability to discriminate the two movements follows a specific temporal evolution along the movement execution and is eventually different among the three features and between the two groups. We also investigated the differences in performance at the single-subject level. Main results. The ERD/ERS and the CMC-based classification showed similar temporal evolutions of the performance with a significant increase in accuracy during the execution phase while MRCP-based accuracy peaked at movement onset. Such temporal dynamics were similar but slower in stroke patients when the movements were attempted with the affected hand (AH). Moreover, CMC outperformed the two brain features in healthy subjects and stroke patients when performing the task with their unaffected hand, whereas a higher variability across subjects was observed in patients performing the tasks with their AH. Interestingly, brain features performed better in this latter condition with respect to healthy subjects. Significance. Our results provide hints to improve the design of Brain–Computer Interfaces for post-stroke rehabilitation, emphasizing the need for personalized approaches tailored to patients’ characteristics and to the intended rehabilitative target.
Prediction of Tensile Properties of Natural Fiber Reinforced PP Hybrid Composites by Facca-Kortschot-Yan (FKY) and Palsule Equations
Authors: Pant Mridul , Palsule Sanjay 
Published: October 2024

Abstract
Natural fiber reinforced polymer hybrid composites are advanced materials for commercial and engineering applications. Rule of hybrid mixtures has been applied to develop Facca-Kortschot-Yan (FKY) Equation and Palsule equation for predicting tensile strength and modulus of these hybrid polymer composites. This study predicts the values of tensile strength and modulus of a few natural fibers reinforced polypropylene hybrid composites by these two equations and compares them with the reported experimental values.
Synthesis of nanochitosan from crab shells: an assessment of morphology, dye adsorption capability and antibacterial characteristics as future prospects for wastewater treatment
Authors: Panchal Manoj , Raghavendra G , Abhishek D , Om Prakash M , Ojha S , Yelamasetti Balram 
Published: October 2024

Abstract
In current experimental study, waste crab shells were used for the synthesis of chitosan nanoparticles and characterized. Preparation of chitosan nanoparticles were done through series of processes involving demineralization, deproteinization, decolouration, deacetylation, and ball milling. Chitosan nanoparticles thus obtained were characterized using X-ray diffraction (XRD) analysis, FTIR (Fourier transform infrared) spectroscopy, and Transmission Electron Microscopy (TEM). The methylene blue and methyl orange dye adsorption was conducted with the aid of UV-vis Spectroscopy. The antibacterial ability of chitosan nanoparticles were also assessed for four different bacterial strains. X-ray diffraction results support the chitosan production and the crystalline nature of the synthesized chitosan. The presence of amine and amide functional groups was verified through FTIR analysis. The degree of de-acetylation was found to be 70.24%, as calculated from FTIR analysis. Transmission Electron Microscopy images of chitosan nanoparticles revealed a fibrous and crystalline structure with molecules aligned in an antiparallel fashion. The dye adsorption test revealed the methylene dye adsorption capacity of 187.7 mg/g whereas for methyl orange it was found to be 296.40 mg/g. The chitosan nanoparticles showed good antibacterial ability against four different bacterial strain.
Experimentation Study of Sound and Vibration Absorption in Two-Wheeler Engines using Tea Waste and Nano-Clay Material
Authors: Senthil Kumar P , Nithiyarasan R , Kamalesh M D , Sudalai Muthu T , Vinoth P 
Published: October 2024

Abstract
Noise and vibration from vehicles is a growing problem in cities due to increased operation in transportation around. Prolonged exposure to loud noises can harm health, including hearing loss. Engine vbrations in vehicles, especially motocycles, worsen rides and pose health risks. A novel material using tea waste, nano clay, and additives like epoxy or polyester resin was developed. Tests showed that the composite material reduced vibrations, especially at lower speeds (10-25 km/h), promising smoother engine performance. Other tests, including sound absorption and SEM imaging, confirmed its effectiveness. Water absorption tests also showed it repelled water well. This novel composite material offers a solution to reduction in noise and vibrations in vechiles, improving comfort and potentially reducing health risks as biodegradable material.
Design of Unit Cells-Based Metamaterial Antenna
Authors: Nishanth Rao K , LaxmaReddy D , Monika S. , Sailaja M. 
Published: October 2024

Abstract
Artificial metallic structures with simultaneous negative permittivity (ɛ) and permeability (µ) that result in a negative refractive index are known as metamaterials. It supports backward waves, i.e., group velocities and inside Metamaterial phase velocities are antiparallel, because of its negative index. The shortcomings of a regular patch antenna, such as low gain and efficiency, can be overcome with the help of this metamaterial antenna, which is helpful for wireless communication. The shortcomings of a regular patch antenna, such as low gain and efficiency, can be overcome with the help of this metamaterial antenna, which is helpful for wireless communication. The effort is justified by the proposal to use DNG (Double Negative) Metamaterials to create compact planar antennas. Additionally, it has peculiar features when compared to materials that are easily obtained because of its negative permeability and permittivity, which results in a negative refractive index. Owing to the unique characteristics of Metamaterials, the antenna achieves 3.768 dB, 53.76 % overall efficiency, and a 1.6 VSWR at 5 GHz frequency using a single unit cell. These results are excellent for wireless LANs and point-to-point communication. Additionally, a different metamaterial antenna with three unit cells produces superior results at 5 GHz frequency, with a return loss of -13.51 dB, a gain of 5.19.17 dB, and an overall efficiency of 92.50% at 2.4 GHz, the results are 4.1830 dB, 60.78%, and -14.51 dB, respectively.
Experimental Testing of Rubber Materials for Enhancement of Suspension Bush Performance
Authors: Karthi Vinith K S , Sreenaveen S , Sarveshnarayanan G , Muthukumar S 
Published: October 2024

Abstract
In the ever-evolving automotive industry, the enhancement of vehicle performance hinges on fundamental components, with the rubber bush in vehicle suspension emerging as a critical element for transformative innovation. This research delves into the optimization of rubber bushes through vulcanization, a process renowned for augmenting rubber’s mechanical properties. The study scrutinizes the performance characteristics of various rubber materials, evaluating their suitability for incorporation into suspension rubber bushes. The research employs a rigorous three- stage testing methodology, including compression, tensile, and fatigue tests, utilizing a Universal Testing Machine (UTM). These stages provide comprehensive insights into the materials’ responses to compression forces, tensile strengths and weaknesses, and fatigue resistance. The findings aid in the informed selection of materials for suspension rubber bushes, contributing to the advancement of automotive suspension system technology. This study not only enhances our understanding of rubber material behaviour but also offers practical insights for applications in automotive engineering. Aligned with the goal of advancing suspension system technology, the research underscores the importance of material-specific properties in real-world scenarios. Ultimately, this research is poised to make a significant contribution to the continual evolution of automotive suspension systems, emphasizing durability, resilience, and overall performance. Neoprene rubber exhibits performance qualities in compression, tensile strength, and fatigue resistance that are equivalent to those of natural rubber, according to the extensive testing findings. This implies that neoprene rubber is a good substitute for using in suspension bushings, providing manufacturers and vehicle engineers with a tempting choice.
Structural, Optical, and Electrical Transformations in FexSi1−xO Thin Films: The Role of Iron and Annealing
Authors: Sudha M , Balamurugan A , Girisha L , Kalaiarasan S , Ravivarman G , Nanthakumar S , Girimurugan R 
Published: October 2024

Abstract
Thin films FexSi1−xO, with iron (Fe) content between 0 to 20% have been applied to substrates made of soda lime glass by means of the spray pyrolysis process. Annealing the films allowed us to test their thermal stability. Both the as-depositedFexSi1−xO thin film and annealed FexSi1−xOthin film were analyzed by. Researchers analyzed the structure of the films and its composition using these methods. The XRD study demonstrated that the FexSi1−xOthin films, even if they are deposited or annealed, have a wurtzite structure in the plane orientation. The result shows that the films’ crystalline structure is not affected by the heating process. In addition to that, the good indicator of film quality and consistency were no signs of pinholes or cracks in the films. An iron deficiency was identified by following the annealing process, according to the compositional analysis done by EDAX. Annealing affects the integration of Fe in the film’s matrix, according to these changes occur in the composition. The band gap changes to red for FexSi1−xOthin films was observed in the optical characteristics of these films while tested using Ultra Violet -Visible spectroscopy. Integrating Fe into films alters their electronic structure, and it is one important indicator for band gap change. The incorporation of Fe resulted in a reduction in resistance and it is measured by the electrical properties using the two-probe method which in turn indicates an improvement in the films’ electrical conductivity. In conclusion, the outcomes if this research supports the feasibility of incorporating iron into the silicon carbide thin films. There are major structural changes to the films’ electrical characteristics and optical properties due to this incorporation. The outcomes of this research have significant implications for the advancement of electronic and optoelectronic devices that could make use of these alterations to enhance their performance.