bluuebunny/crossref_metadata_2025 huggingface dataset:
CoCrFeMnNi0.8V/Cr3C2-Ni20Cr High-Entropy Alloy Composite Thermal Spray Coating: Comparison with Monolithic CoCrFeMnNi0.8V and Cr3C2-Ni20Cr Coatings
Authors: Kiape Stavros , Glava Maria , Georgatis Emmanuel , Kamnis Spyros , Matikas Theodore E. , Karantzalis Alexandros E.
Published: March 2024

High-entropy alloys (HEAs) are revolutionizing the field of surface engineering, challenging traditional alloy frameworks with their superior mechanical attributes and resistance to corrosion. This investigation delves into the properties of the CoCrFeMnNi0.8V HEAs, both as a standalone material and when blended with Cr3C2-Ni20Cr, to evaluate their efficacy as cutting-edge surface treatments. The addition of vanadium to the CoCrFeMnNi0.8V alloy results in a distinctive microstructure that improves hardness and resistance to abrasion. The incorporation of Cr3C2-Ni20Cr particles enhances the alloy’s toughness and longevity. Employing high-velocity oxy-fuel (HVOF) thermal spray methods, these coatings are deposited onto steel substrates and undergo detailed evaluations of their microstructural characteristics, abrasion, and corrosion resistance. Findings reveal the CoCrFeMnNi0.8V coating’s exceptional ability to withstand corrosion, especially in environments rich in chlorides. The hybrid coating benefits from the combination of the HEA’s inherent corrosion resistance and the enhanced wear and corrosion resistance provided by Cr3C2-Ni20Cr, delivering comprehensive performance for high-stress applications. Through the fine-tuning of the application process, the Cr3C2-Ni20Cr reinforced high-entropy alloy coating emerges as a significant advancement in protective surface technology, particularly for use in marine and corrosive settings. This study not only highlights the adaptability of HEAs in surface engineering but also prompts further investigation into innovative material pairings.
Mechanical Properties of Small Quasi-Square Graphene Nanoflakes
Authors: Serna-Gutiérrez Andrés , Cordero Nicolás A.
Published: March 2024

The rise of straintronics—the possibility of fine-tuning the electronic properties of nanosystems by applying strain to them—has enhanced the interest in characterizing the mechanical properties of these systems when they are subjected to tensile (or compressive), shear and torsion strains. Four parameters are customarily used to describe the mechanical behavior of a macroscopic solid within the elastic regime: Young’s and shear moduli, the torsion constant and Poisson’s ratio. There are some relations among these quantities valid for elastic continuous isotropic systems that are being used for 2D nanocrystals without taking into account the non-continuous anisotropic nature of these systems. We present in this work computational results on the mechanical properties of six small quasi-square (aspect ratio between 0.9 and 1.1) graphene nanocrystals using the PM7 semiempirical method. We use the results obtained to test the validity of two relations derived for macroscopic homogeneous isotropic systems and sometimes applied to 2D systems. We show they are not suitable for these nanostructures and pinpoint the origin of some discrepancies in the elastic properties and effective thicknesses reported in the literature. In an attempt to recover one of these formulas, we introduce an effective torsional thickness for graphene analogous to the effective bending thickness found in the literature. Our results could be useful for fitting interatomic potentials in molecular mechanics or molecular dynamics models for finite carbon nanostructures, especially near their edges and for twisted systems.
Combined Effect of Particle Reinforcement and T6 Heat Treatment on the Compressive Deformation Behavior of an A357 Aluminum Alloy at Room Temperature and at 350 °C
Authors: Hirsch Sarah Johanna , Berndt Nadja , Grund Thomas , Lampke Thomas
Published: March 2024

Solid state sintering of cast aluminum powders by resistance heating sintering (RHS), also known as spark plasma sintering or field-assisted sintering technique, creates a very fine microstructure in the bulk material. This leads to high performance material properties with an improved strength and ductility compared to conventional production routes of the same alloys. In this study, the mechanical behavior of an RHS-sintered age-hardenable A357 (AlSi7Mg0.6) cast alloy and a SiCp/A357 aluminum matrix composite (AMC) was investigated. Aiming for high strength and good wear behavior in tribological applications, the AMC was reinforced with a high particle content (35 vol.%) of a coarse particle fraction (d50 = 21 µm). Afterwards, separated and combined effects of particle reinforcement and heat treatment were studied under compressive load both at room temperature and at 350 °C. At room temperature compression, the strengthening effect of precipitation hardening was about twice as high as that for the particle reinforcement, despite the high particle content. At elevated temperatures, the compressive deformation behavior was characterized by simultaneously occurring temperature-activated recovery, recrystallisation and precipitation processes. The occurrence and interaction of these processes was significantly affected by the initial material condition. Moreover, a rearrangement of the SiC reinforcement particles was detected after hot deformation. This rearrangement lead to a homogenized dispersion of the reinforcement phase without considerable particle fragmentation, which offers the potential for secondary thermo-mechanical processing of highly reinforced AMCs.
Retinal Microcirculation Measurements in Response to Endurance Exercises Analysed by Adaptive Optics Retinal Camera
Authors: Żmijewska Maria Anna , Wawrzyniak Zbigniew M. , Janiszewski Maciej , Zaleska-Żmijewska Anna
Published: March 2024

This study aimed to precisely investigate the effects of intensive physical exercise on retinal microvascular regulation in healthy volunteers through adaptive optics retinal camera (AO) measurement. We included healthy volunteers (11 men and 14 women) aged 20.6 ± 0.9. The heart rate (HR) and systolic and diastolic blood pressures (SBP, DBP) were recorded before and after a submaximal physical exertion of continuously riding a training ergometer. The superior temporal retinal artery measurements were captured using the AO—rtx1TM (Imagine Eyes, Orsay, France) without pupil dilation. We compared measures of vessel diameter (VD), lumen diameter (LD), two walls (Wall 1, 2), wall-to-lumen ratio (WLR), and wall cross-sectional analysis (WCSA) before and immediately after the cessation of exercise. Cardiovascular parameter results: After exercise, SBP, DBP, and HR changed significantly from 130.2 ± 13.2 to 159.7 ± 15.6 mm Hg, 81.2 ± 6.3 to 77.1 ± 8.2 mm Hg, and 80.8 ± 16.1 to 175.0 ± 6.2 bpm, respectively (p < 0.002). Retinal microcirculation analysis showed no significant decrease in LD, Wall 1 after exercise: from 96.0 ± 6.8 to 94.9 ± 6.7 (p = 0.258), from 11.0 ± 1.5 to 10.4 ± 1.5 (p = 0.107), respectively, and significant reduction in VD from 118.5 ± 8.3 to 115.9 ± 8.3 (p = 0.047), Wall 2 from 11.5 ± 1.0 to 10.7 ± 1.3 (p = 0.017), WLR from 0.234 ± 0.02 to 0.222 ± 0.010 (p = 0.046), WCSA from 3802.8 ± 577.6 to 3512.3 ± 535.3 (p = 0.016). The AO is a promising technique for investigating the effects of exercise on microcirculation, allowing for the tracking of changes throughout the observation. Intensive dynamic physical exertion increases blood pressure and heart rate and causes the vasoconstriction of small retinal arterioles due to the autoregulation mechanism.
Medical Relevance, State-of-the-Art and Perspectives of “Sweet Metacode” in Liquid Biopsy Approaches
Authors: Pinkeova Andrea , Kosutova Natalia , Jane Eduard , Lorencova Lenka , Bertokova Aniko , Bertok Tomas , Tkac Jan
Published: March 2024

This review briefly introduces readers to an area where glycomics meets modern oncodiagnostics with a focus on the analysis of sialic acid (Neu5Ac)-terminated structures. We present the biochemical perspective of aberrant sialylation during tumourigenesis and its significance, as well as an analytical perspective on the detection of these structures using different approaches for diagnostic and therapeutic purposes. We also provide a comparison to other established liquid biopsy approaches, and we mathematically define an early-stage cancer based on the overall prognosis and effect of these approaches on the patient’s quality of life. Finally, some barriers including regulations and quality of clinical validations data are discussed, and a perspective and major challenges in this area are summarised.
Low Rate of Postoperative Pterygium Recurrence in Patients under Treatment with Low-Dose Oral Doxycycline for Chronic Blepharitis: A First Report
Authors: Catania Fiammetta , Vinciguerra Paolo , Di Maria Alessandra
Published: March 2024

Purpose: Low doses of systemic doxycycline (LD-SD) inhibit angiogenesis and the expression of matrix metalloproteases, which are determinants of pterygium progression. This study aimed to compare the recurrence rate and visual outcome of pterygium excision in patients undergoing chronic treatment with LD-SD for chronic refractory blepharitis and LD-SD-naive patients. Methods: A retrospective analysis of patients that underwent surgical excision and conjunctival graft apposition was conducted. Patients were divided in a TETRA group (under LD-SD treatment at the moment of surgery) and a control group. The main outcome was the rate of recurrence at 1 year postoperatively. Secondary outcomes were the comparisons of surface regularity, visual quality, and dry-eye symptoms at 6-week, 6-month, and 1-year follow-up in the two groups. Results: The TETRA group showed a significantly lower rate of 1-year recurrence both in primary (p = 0.034) and recurrent (p < 0.001) pterygia. The best corrected visual acuity (BCVA), astigmatic error, corneal total root mean square (RMS), and ocular surface disease index (OSDI) significantly reduced during the follow-up in both groups. The surface asymmetry index and high-order aberrations (HOAs) significantly reduced only in the TETRA group. The final BCVA was significantly higher, while the OSDI score and total RMS and HOAs were significantly lower in the TETRA group compared to the control. Conclusions: Patients under treatment with LD-SD showed a lower rate of recurrence at 1-year follow-up compared to controls. These patients also experienced higher BCVA and surface regularity and less dry-eye symptoms.
Radiomics-Based Machine Learning Model for Diagnosis of Acute Pancreatitis Using Computed Tomography
Authors: Bette Stefanie , Canalini Luca , Feitelson Laura-Marie , Woźnicki Piotr , Risch Franka , Huber Adrian , Decker Josua A. , Tehlan Kartikay , Becker Judith , Wollny Claudia , Scheurig-Münkler Christian , Wendler Thomas , Schwarz Florian , Kroencke Thomas
Published: March 2024

In the early diagnostic workup of acute pancreatitis (AP), the role of contrast-enhanced CT is to establish the diagnosis in uncertain cases, assess severity, and detect potential complications like necrosis, fluid collections, bleeding or portal vein thrombosis. The value of texture analysis/radiomics of medical images has rapidly increased during the past decade, and the main focus has been on oncological imaging and tumor classification. Previous studies assessed the value of radiomics for differentiating between malignancies and inflammatory diseases of the pancreas as well as for prediction of AP severity. The aim of our study was to evaluate an automatic machine learning model for AP detection using radiomics analysis. Patients with abdominal pain and contrast-enhanced CT of the abdomen in an emergency setting were retrospectively included in this single-center study. The pancreas was automatically segmented using TotalSegmentator and radiomics features were extracted using PyRadiomics. We performed unsupervised hierarchical clustering and applied the random-forest based Boruta model to select the most important radiomics features. Important features and lipase levels were included in a logistic regression model with AP as the dependent variable. The model was established in a training cohort using fivefold cross-validation and applied to the test cohort (80/20 split). From a total of 1012 patients, 137 patients with AP and 138 patients without AP were included in the final study cohort. Feature selection confirmed 28 important features (mainly shape and first-order features) for the differentiation between AP and controls. The logistic regression model showed excellent diagnostic accuracy of radiomics features for the detection of AP, with an area under the curve (AUC) of 0.932. Using lipase levels only, an AUC of 0.946 was observed. Using both radiomics features and lipase levels, we showed an excellent AUC of 0.933 for the detection of AP. Automated segmentation of the pancreas and consecutive radiomics analysis almost achieved the high diagnostic accuracy of lipase levels, a well-established predictor of AP, and might be considered an additional diagnostic tool in unclear cases. This study provides scientific evidence that automated image analysis of the pancreas achieves comparable diagnostic accuracy to lipase levels and might therefore be used in the future in the rapidly growing era of AI-based image analysis.
Evaluation of Binding and Neutralizing Antibodies for Inactivated SARS-CoV-2 Vaccine Immunization
Authors: Zhao Heng , Jiang Guorun , Li Cong , Che Yanchun , Long Runxiang , Pu Jing , Zhang Ying , Li Dandan , Liao Yun , Yu Li , Zhao Yong , Yuan Mei , Li Yadong , Fan Shengtao , Liu Longding , Li Qihan
Published: March 2024

The circulating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variant presents an ongoing challenge for surveillance and detection. It is important to establish an assay for SARS-CoV-2 antibodies in vaccinated individuals. Numerous studies have demonstrated that binding antibodies (such as S-IgG and N-IgG) and neutralizing antibodies (Nabs) can be detected in vaccinated individuals. However, it is still unclear how to evaluate the consistency and correlation between binding antibodies and Nabs induced by inactivated SARS-CoV-2 vaccines. In this study, serum samples from humans, rhesus macaques, and hamsters immunized with inactivated SARS-CoV-2 vaccines were analyzed for S-IgG, N-IgG, and Nabs. The results showed that the titer and seroconversion rate of S-IgG were significantly higher than those of N-IgG. The correlation between S-IgG and Nabs was higher compared to that of N-IgG. Based on this analysis, we further investigated the titer thresholds of S-IgG and N-IgG in predicting the seroconversion of Nabs. According to the threshold, we can quickly determine the positive and negative effects of the SARS-CoV-2 variant neutralizing antibody in individuals. These findings suggest that the S-IgG antibody is a better supplement to and confirmation of SARS-CoV-2 vaccine immunization.
Research on Vision-Based Servoing and Trajectory Prediction Strategy for Capturing Illegal Drones
Authors: Ma Jinyu , Chen Puhui , Xiong Xinhan , Zhang Liangcheng , Yu Shengdong , Zhang Dongyuan
Published: March 2024

A proposed strategy for managing airspace and preventing illegal drones from compromising security involves the use of autonomous drones equipped with three key functionalities. Firstly, the implementation of YOLO-v5 technology allows for the identification of illegal drones and the establishment of a visual-servo system to determine their relative position to the autonomous drone. Secondly, an extended Kalman filter algorithm predicts the flight trajectory of illegal drones, enabling the autonomous drone to compensate in advance and significantly enhance the capture success rate. Lastly, to ensure system robustness and suppress interference from illegal drones, an adaptive fast nonsingular terminal sliding mode technique is employed. This technique achieves finite time convergence of the system state and utilizes delay estimation technology for the real-time compensation of unknown disturbances. The stability of the closed-loop system is confirmed through Lyapunov theory, and a model-based hardware-in-the-loop simulation strategy is adopted to streamline system development and improve efficiency. Experimental results demonstrate that the designed autonomous drone accurately predicts the trajectory of illegal drones, effectively captures them using a robotic arm, and maintains stable flight throughout the process.
Application and Assessment of an Experiential Deformation Approach as a Didactive Tool of Truss Structures in Architectural Engineering
Authors: Voutetaki Maristella E.
Published: March 2024

Experiential learning methods are advantageous for students as they motivate them to comprehend structural concepts without complex calculations, enhancing their inherent understanding of static principles. This research introduces a novel, cost-effective haptic didactic tool to enhance the approach to teaching trusses to students in a School of Architecture. The primary goal is to address challenges associated with the complexities of teaching structural systems within the context of architectural education. The proposed approach is related to the most critical issue, which is the state in which the individual elements are under applied load, compression, or tension. The approach explores the deformation of the truss elements and establishes a connection between their visible deformation and the stress they develop under various loads. As a didactic tool, this approach offers an alternative perspective to help students understand truss function under various loads. Also, an assessment procedure of learning outcomes and satisfaction indices has been structured to validate the impact on students on the proposed educational procedure. The findings underscore the significant educational efficiency of the proposed procedure as a sustainable way to connect the structural engineering challenges arising during design courses and creative skills in architecture engineering.
An Integrative Systematic Approach to Supporting Student Wellness: An Applied Case Example
Authors: Brann Kristy L. , Gallagher Mark , Noltemeyer Amity , Bush Kyle
Published: March 2024

As schools work toward addressing the youth mental health crisis, Student Assistance Programs (SAPs) can serve as a service delivery model to proactively offer a continuum of support. A SAP involves education and building awareness, prevention, early identification, referral, intervention, and guided support services. With the rising mental health need that was exacerbated by COVID-19, describing one district’s efforts can assist other schools in planning their own continuum of support within a SAP. This article provides a case example of one district’s efforts to create a system that integrates universal screening data and school and community support structures supporting students’ wellness. We describe the district’s continuum of support and early identification and intervention efforts, their systematic approach to integrating systems, and their teaming process. We will also report the percentages of students who are identified on wellness benchmarking and screening tools in addition to the percentage referred for additional support. We conclude by reviewing the implications for practice and future research.
A Strategy to Reorient Parental Perceptions to Create Conditions for Successful Inclusive Education: A Case Study in A Small-Sized School
Authors: Narot Pennee , Kiettikunwong Narong
Published: March 2024

This study investigates parents’ perceptions on school management practices for children with special educational needs in a small-sized Indonesian school. Data from surveys and interviews with 53 parents revealed overall positive attitudes toward classroom management and teacher care. However, concerns arose regarding teachers’ ability to support special needs students effectively, leading to hesitancy in collaborating for inclusive classrooms. To reorient parental perceptions to create conditions for successful inclusive education, effective communication strategies emphasizing teacher development and district-based support are crucial. Future research should focus on improving communication between parents to foster inclusive educational practices. These findings shed light on challenges and solutions for cultivating inclusive classroom environments in special education.
The Moderating Effect of Body Appreciation on the Relationship between Self-Esteem and Life Satisfaction
Authors: Wodarz René , Rogowska Aleksandra M.
Published: March 2024

Background: Although positive associations between life satisfaction, self-esteem, and body image have previously been established, differences in these variables by gender and age have yielded mixed results. Moreover, little is known about the interplay between self-esteem and body appreciation on life satisfaction. This study aims to investigate the moderating effect of body appreciation on the relationship between self-esteem and life satisfaction, considering disparities between females and males and also between emerging adults (before the age of thirty) and older adults. Methods: A cross-sectional online survey was performed in Poland with a sample of 449 adults aged between 18 and 75 (M = 30.41, SD = 12.72), including 68% of women. The survey included the Satisfaction With Life Scale (SWLS), Rosenberg Self-Esteem Scale (RSES), and Body Appreciation Scale (BAS-2). Results: Men scored higher than women in terms of life satisfaction and self-esteem, while older participants (age > 30) scored higher than younger individuals (age ≤ 30) in terms of life satisfaction, self-esteem, and body appreciation. The study confirmed positive and moderate correlations between life satisfaction, self-esteem, and body appreciation. The interactive effect of self-esteem and body appreciation on life satisfaction was also found by controlling for age and gender. Conclusions: Some intervention programs focused on increasing levels of self-esteem and body appreciation should be implemented, especially among women and emerging adults, to improve their well-being.
Shape Sensing for Continuum Robotics Using Optoelectronic Sensors with Convex Reflectors
Authors: Osman Dalia , Du Xinli , Minton Timothy , Noh Yohan
Published: March 2024

Three-dimensional shape sensing in soft and continuum robotics is a crucial aspect for stable actuation and control in fields such as minimally invasive surgery, engine repairs and search and rescue operations, as the estimation of complex curvatures while using continuum robotic tools is required to manipulate through fragile paths. This challenge has been addressed using a range of different sensing techniques, for example, Fibre Bragg grating (FBG) technology, inertial measurement unit (IMU) sensor networks, or stretch sensors. Previously, an optics-based method using optoelectronic sensors was explored, offering a simple and cost-effective solution for shape sensing in a flexible tendon-actuated manipulator in two orientations. This was based on proximity-modulated angle estimation and has been the basis for the shape sensing method addressed in this paper. The improved and miniaturised technique demonstrated in this paper is based on the use of a convex shaped reflector with optoelectronic sensors integrated into a tendon-actuated robotic manipulator. Upgraded sensing capability is achieved using optimisation of the convex reflector shape in terms of sensor range and resolution, and improved calibration is achieved through the integration of spherical bearings for friction-free motion. Shape estimation is achieved in two orientations upon calibration of sensors, with a maximum Root-Mean-Square Error (RMS) of 3.37°.
Review of Methods for PCB Panel Depanelization and Methods for Correct Assembly of Electronic Components on PCB Panels
Authors: Łyczek Mateusz , Skarka Wojciech
Published: March 2024

Currently, processes related to PCBs (printed circle board), such as depanelization and checking the correct functioning of the boards, are carried out in separate devices. The purpose of this article is to review the literature and analyze trends related to these aspects of PCB panel manufacturing. The purpose of this analysis is to indicate the currently used depanelization methods and methods for checking the correctness of the assembly of electronic circuits on PCB panels. The publications were found in such knowledge bases as Scopus, IEEE Xplore or Emerald insight. In the following article, a systematic literature analysis along with a mapping study is used. This publication provides a review of selected scientific papers found in the above-mentioned databases. Based on these analyses, insights related to future work on both aspects of PCBs were presented. These insights are part of the development of new integrated devices for depanelization and verification of PCBs.
Hybrid Spatial-Channel Attention Mechanism for Cross-Age Face Recognition
Authors: An Wenxin , Wu Gengshen
Published: March 2024

Face recognition techniques have been widely employed in real-world biomimetics applications. However, traditional approaches have limitations in recognizing faces correctly with large age differences because of significant changes over age in the same person, leading to unsatisfactory recognition performance. To address this, previous studies propose to decompose and identify age and identity features independently in facial images across diverse age groups when optimizing the discriminative model so as to improve the age-invariant face recognition accuracy. Nevertheless, the interrelationships between these features make it difficult for the decomposition to disentangle them properly, thus compromising the recognition accuracy due to the interactive impacts on both features. To this end, this paper proposes a novel deep framework that incorporates a novel Hybrid Spatial-Channel Attention Module to facilitate the cross-age face recognition task. Particularly, the proposed module enables better decomposition of the facial features in both spatial and channel dimensions with attention mechanisms simultaneously while mitigating the impact of age variation on the recognition performance. Beyond this, diverse pooling strategies are also combined when applying those spatial and channel attention mechanisms, which allows the module to generate discriminative face representations while preserving complete information within the original features, further yielding sounder recognition accuracy. The proposed model is extensively validated through experiments on public face datasets such as CACD-VS, AgeDB-30, and FGNET, where the results show significant performance improvements compared to competitive baselines.
Optimizing Performance of Hybrid Electrochemical Energy Storage Systems through Effective Control: A Comprehensive Review
Authors: Clemente Alejandro , Arias Paula , Gevorkov Levon , Trilla Lluís , Obrador Rey Sergi , Roger Xavier Sanchez , Domínguez-García José Luis , Filbà Martínez Àlber
Published: March 2024

The implementation of energy storage system (ESS) technology with an appropriate control system can enhance the resilience and economic performance of power systems. However, none of the storage options available today can perform at their best in every situation. As a matter of fact, an isolated storage solution’s energy and power density, lifespan, cost, and response time are its primary performance constraints. Batteries are the essential energy storage component used in electric mobility, industries, and household applications nowadays. In general, the battery energy storage systems (BESS) currently available on the market are based on a homogeneous type of electrochemical battery. However, a hybrid energy storage system (HESS) based on a mixture of various types of electrochemical batteries can potentially provide a better option for high-performance electric cars, heavy-duty electric vehicles, industries, and residential purposes. A hybrid energy storage system combines two or more electrochemical energy storage systems to provide a more reliable and efficient energy storage solution. At the same time, the integration of multiple energy storage systems in an HESS requires advanced control strategies to ensure optimal performance and longevity of the system. This review paper aims to provide a comprehensive overview of the control systems used in HESSs for a wide range of applications. An overview of the various control strategies used in HESSs is offered, including traditional control methods such as proportional–integral–derivative (PID) control, and advanced control methods such as model predictive control (MPC), droop control (DC), sliding mode control (SMC), rule-based control (RBC), fuzzy logic control (FLC), and artificial neural network (ANN) control are discussed. The paper also highlights the recent developments in HESS control systems, including the use of machine learning techniques such as deep reinforcement learning (DRL) and genetic algorithms (GA). The paper provides not only a description and classification of various control approaches but also a comparison between control strategies from the evaluation of performance point of view. The review concludes by summarizing the key findings and future research directions for HESS control systems, which is directly linked to the research on machine learning and the mix of different control type strategies.
Optimal Design of Relay Coil Inductance to Improve Transmission Efficiency of Four-Coil Magnetic Resonance Wireless Power Transmission Systems
Authors: Hwang Min-Wook , Kwon Young-Min , Ko Kwang-Cheol
Published: March 2024

Magnetic resonance wireless power transmission consists of a source coil and relay coil (transmission coil (Tx-coil), receiving coil (Rx-coil)). The relay coil is designed with windings and a series capacitor, which are resonant with the input voltage frequency. Magnetic resonant wireless power transmission by a relay coil enables the transmission of power from a few centimeters to several meters. Recently, research has been conducted on the shape and material of each coil to increase the transmission distance. However, limitations remain with respect to increasing the transmission distance. Specifically, the optimization of the electrical characteristics of the relay coil is necessary to increase the transmission distance and improve efficiency. In this study, we configured the inductance of the relay coil to be approximately 95 μH, 270 μH, and 630 μH. Accordingly, we designed the series capacitors to have the same resonant frequency and analyzed the transmission characteristics of each relay coil. We confirmed that as the inductance increased, the transmission efficiency increased by up to 10%. The relay coil was designed to have an inductance of approximately three to six times that of the source coil (load coil). Thus, the optimal design of the relay coil is believed to be the most efficient and economical coil design.
An Image Retrieval Method for Lunar Complex Craters Integrating Visual and Depth Features
Authors: Zhang Yingnan , Kang Zhizhong , Cao Zhen
Published: March 2024

In the geological research of the Moon and other celestial bodies, the identification and analysis of impact craters are crucial for understanding the geological history of these bodies. With the rapid increase in the volume of high-resolution imagery data returned from exploration missions, traditional image retrieval methods face dual challenges of efficiency and accuracy when processing lunar complex crater image data. Deep learning techniques offer a potential solution. This paper proposes an image retrieval model for lunar complex craters that integrates visual and depth features (LC2R-Net) to overcome these difficulties. For depth feature extraction, we employ the Swin Transformer as the core architecture for feature extraction and enhance the recognition capability for key crater features by integrating the Convolutional Block Attention Module with Effective Channel Attention (CBAMwithECA). Furthermore, a triplet loss function is introduced to generate highly discriminative image embeddings, further optimizing the embedding space for similarity retrieval. In terms of visual feature extraction, we utilize Local Binary Patterns (LBP) and Hu moments to extract the texture and shape features of crater images. By performing a weighted fusion of these features and utilizing Principal Component Analysis (PCA) for dimensionality reduction, we effectively combine visual and depth features and optimize retrieval efficiency. Finally, cosine similarity is used to calculate the similarity between query images and images in the database, returning the most similar images as retrieval results. Validation experiments conducted on the lunar complex impact crater dataset constructed in this article demonstrate that LC2R-Net achieves a retrieval precision of 83.75%, showcasing superior efficiency. These experimental results confirm the advantages of LC2R-Net in handling the task of lunar complex impact crater image retrieval.
Digital Twin-Enabled Internet of Vehicles Applications
Authors: Gao Junting , Peng Chunrong , Yoshinaga Tsutomu , Han Guorong , Guleng Siri , Wu Celimuge
Published: March 2024

The digital twin (DT) paradigm represents a groundbreaking shift in the Internet of Vehicles (IoV) landscape, acting as an instantaneous digital replica of physical entities. This synthesis not only refines vehicular design but also substantially augments driver support systems and streamlines traffic governance. Diverging from the prevalent research which predominantly examines DT’s technical assimilation within IoV infrastructures, this review focuses on the specific deployments and goals of DT within the IoV sphere. Through an extensive review of scholarly works from the past 5 years, this paper provides a fresh and detailed perspective on the significance of DT in the realm of IoV. The applications are methodically categorized across four pivotal sectors: industrial manufacturing, driver assistance technology, intelligent transportation networks, and resource administration. This classification sheds light on DT’s diverse capabilities to confront and adapt to the intricate challenges in contemporary vehicular networks. The intent of this comprehensive overview is to catalyze innovation within IoV by providing an essential reference for researchers who aspire to swiftly grasp the complex dynamics of this evolving domain.
Deep Convolutional Dictionary Learning Denoising Method Based on Distributed Image Patches
Authors: Yin Luqiao , Gao Wenqing , Liu Jingjing
Published: March 2024

To address susceptibility to noise interference in Micro-LED displays, a deep convolutional dictionary learning denoising method based on distributed image patches is proposed in this paper. In the preprocessing stage, the entire image is partitioned into locally consistent image patches, and a dictionary is learned based on the non-local self-similar sparse representation of distributed image patches. Subsequently, a convolutional dictionary learning method is employed for global self-similarity matching. Local constraints and global constraints are combined for effective denoising, and the final denoising optimization algorithm is obtained based on the confidence-weighted fusion technique. The experimental results demonstrate that compared with traditional denoising methods, the proposed denoising method effectively restores fine-edge details and contour information in images. Moreover, it exhibits superior performance in terms of PSNR and SSIM. Particularly noteworthy is its performance on the grayscale dataset Set12. When evaluated with Gaussian noise σ=50, it outperforms DCDicL by 3.87 dB in the PSNR and 0.0012 in SSIM.
4H-SiC/SiO2 Interface Degradation in 1.2 kV 4H-SiC MOSFETs Due to Power Cycling Tests
Authors: Yoo Dahui , Kim MiJin , Kang Inho , Lee Ho-Jun
Published: March 2024

Power cycling tests (PCTs) assess the reliability of power devices by closely simulating their operating conditions. A PCT was performed on commercially available 1.2 kV 4H-SiC power metal–oxide–semiconductor field-effect transistors to observe its impact on the 4H-SiC/SiO2 interface. High-resolution transmission electron microscopy and electron energy loss spectroscopy measurements showed variations in the length of the 4H-SiC/SiO2 transition layer, depending on whether the device was power cycled. Moreover, the total resistance at Vg≫ Vt in Rtot − (Vg-Vt)−1 graph increased to 16.5%, while it changed more radically to 47.3% at Vg≈ Vt. The threshold voltage shifted negatively. These variations cannot be expected solely through the wearout of the package.
Application of Neural Networks on Carbon Emission Prediction: A Systematic Review and Comparison
Authors: Feng Wentao , Chen Tailong , Li Longsheng , Zhang Le , Deng Bingyan , Liu Wei , Li Jian , Cai Dongsheng
Published: March 2024

The greenhouse effect formed by the massive emission of carbon dioxide has caused serious harm to the Earth’s environment, in which the power sector constitutes one of the primary contributors to global greenhouse gas emissions. Reducing carbon emissions from electricity plays a pivotal role in minimizing greenhouse gas emissions and mitigating the ecological, economic, and social impacts of climate change, while carbon emission prediction provides a valuable point of reference for the formulation of policies to reduce carbon emissions from electricity. The article provides a detailed review of research results on deep learning-based carbon emission prediction. Firstly, the main neural networks applied in the domain of carbon emission forecasting at home and abroad, as well as the models combining other methods and neural networks, are introduced, and the main roles of different methods, when combined with neural networks, are discussed. Secondly, neural networks were used to predict electricity carbon emissions, and the performance of different models on carbon emissions was compared. Finally, the application of neural networks in the realm of the prediction of carbon emissions is summarized, and future research directions are discussed. The article provides a reference for researchers to understand the research dynamics and development trend of deep learning in the realm of electricity carbon emission forecasting.
Analysis of Sediment Erosion in Pelton Nozzles and Needles Affected by Particle Size
Authors: Liu Jie , Zhu Yilin , Liang Quanwei , Xiao Yexiang , Liu Zhengshu , Li Haijun , Ye Jian , Yang Nianhao , Deng Haifeng , Du Qingpin
Published: March 2024

The sediment erosion of Pelton turbine components is a major challenge in the operation and development of high-head water resources, especially in mountainous areas with high sediment yield. In this paper, a study using numerical simulation was conducted with different sediment particle sizes in the fine sand range. And the erosion mechanism of the Pelton turbine injector was analyzed. The Eulerian Lagrange method was adopted to simulate the gas–liquid–solid flow. The Mansouri’s model was applied to estimate the injector erosion. The predicted erosion results were in accord with field erosion photographs. In particular, the asymmetrical erosion distribution on the needle surface was physically reproduced. With the sediment particle size increasing from 0.05 mm, the needle erosion rate decreased, while the nozzle casing erosion rate increased dramatically. In order to clarify this tendency, the characteristics of the three-phase flow were analyzed. Interestingly, the results show that with the rise in particle size, the separation of particles and water streamlines became more serious in the contraction section of the nozzle mouth. Consequently, it caused the enhancement of erosion of the nozzle surfaces and weakened the erosion of the needle surfaces. Significant engineering insights may be provided for weakening Pelton injector erosion with needle guides in the current study.
Identification and Analysis of Expression Patterns of the Caleosin Genes in Hickory (Carya cathayensis Sarg.)
Authors: Cao Yueyinglun , Zhan Yang , Liu Jiale , Tang Tianyu , Li Juan , Zhao Rui , Zhang Qixiang , Hu Shuai , Cao Wenhan , Gao Yanli
Published: March 2024

The deciduous tree hickory (Carya cathayensis) holds economic significance in China due to its high oil content, particularly in unsaturated fatty acids. Oil bodies are crucial for storing triacylglycerol (TAG), with caleosin serving as a predominant oil body protein that aids in oil body formation and stability maintenance. Our study utilized bioinformatics techniques to identify caleosin genes within Carya cathayensis, Carya illinoinensis, and Juglans regia. Three caleosin genes were discovered in the genomes of Carya cathayensis, Carya illi-noinensis, and Juglans regia. These genes encode hydrophilic proteins. Additionally, all caleosin proteins feature a single Ca2+-binding EF-hand, a conserved “proline knot” motif, and a C-terminal hydrophilic region with four potential phosphorylation sites. The caleosin proteins in Carya cathayensis consist of α-helix, β-corner, extended chain, and random curl structures. Cis-acting elements related to stress response and hormone signaling were identified in Carya cathayensis, Carya illinoinensis, and Juglans regia, with distinct cis-acting elements implicated in seed-specific regulation in Carya cathayensis. Additionally, subcellular localization analysis confirmed that CcaCLO1 and CcaCLO2 were localized within oil bodies. Transcriptome analysis and quantitative real-time polymerase chain reaction (qRT-PCR) data demonstrated a significant up-regulation of CcaCLO1 expression during the developmental stages of the Carya cathayensis embryo. Furthermore, qPCR findings indicated that caleosins from Carya cathayensis were responsive to salt stress, with a significant up-regulation of CcaCLO1 following exposure to salt stress treatment. Consequently, caleosin genes in Carya cathayensis, Carya illinoinensis, and Juglans regia share similar physicochemical characteristics and conserved motifs. Specifically, CcaCLO1 in Carya cathayensis primarily responds to embryo development and salt stress. These findings offer foundational insights for future investigations into the regulatory mechanisms of oil accumulation and response to salt stress in hickory.
Variability in Pine Pitch Canker Susceptibility among Scots Pine (Pinus sylvestris) Provenances in Eastern Europe
Authors: Davydenko Kateryna , Łukaszewska-Skrzypniak Natalia , Sadowska Katarzyna , Nowakowska Justyna Anna , Raitelaitytė Kristina , Markovskaja Svetlana , Burokienė Daiva , Shcherbak Olena , Martín-García Jorge , Diez Casero Julio Javier , Hsiang Tom , Oszako Tomasz
Published: March 2024

Pine pitch canker, caused by the ascomycete Fusarium circinatum, poses a substantial threat to pine trees and Douglas firs (Pseudotsuga menziesii), and has been identified as a pervasive issue in forests and nurseries worldwide, particularly in regions where susceptible conifers are cultivated. Given its prevalence in the Iberian Peninsula, assessments of the susceptibility of diverse European provenances of Scots pine (Pinus sylvestris)—specifically those from Poland, Lithuania, and Ukraine—have been conducted. Preliminary evaluations of Polish provenances have raised concerns about the potential threat to Scots pine stands in Poland posed by pitch canker. Under controlled conditions, we examined the impact of F. circinatum inoculation on the survival of seeds and seedlings from ten provenances of Scots pine. In response, the initial assessment of F. circinatum pathogenicity was undertaken in a controlled greenhouse environment. This evaluation uncovered a heightened susceptibility of pine seedlings to pitch canker among the tested provenances. Notably, one Lithuanian provenance demonstrated superior resistance to pitch canker, while two Polish provenances exhibited a higher prevalence of symptomless seedlings. These findings underscore the need for further exploration and identification of resilient individuals within these provenances, offering valuable insights for developing strategies to mitigate the impact of pitch canker on Scots pine in Europe.
The Optimization of the Steam-Heat-Treated Process of Rattan (Calamus simplicifolius) Based on the Response Surface Analysis and Its Chemical Changes
Authors: Xu Minmin , Wang Zhihui , Li Zhenrui , Sun Zhenbing , Shang Lili , Tian Genlin , Ma Jianfeng , Liu Xing’e
Published: March 2024

The objective of this study is to investigate the impacts of steam heat treatment parameters (e.g., temperature, time, and pressure) on the impact toughness of rattan (Calamus simplicifolius). The Box–Behnken design response surface analysis was employed to optimize the steam heat treatment parameters. Impact toughness was selected as the evaluation index, with single-factor tests conducted as a baseline for comparison. Changes in chemical composition, cellulose crystallinity, and pyrolysis properties were analyzed using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectra, Thermogravimetry–Fourier transform infrared (TG-FTIR) spectra, and wet-chemistry methods for both untreated control samples and the heat-treated samples. The results show that a 1 h steam heat treatment at 160 °C under 0.1 MPa pressure has the optimal process parameters for the rattan. The achieved impact toughness value closely matches the predicted value at 71.29 kJ/m2. After the steam heat treatment, hemicellulose and cellulose contents decrease, whereas relative lignin content increases significantly, leading to improved toughness characteristics in Calamus simplicifolius samples. The TG results indicate that maximum weight loss occurs at temperatures of 352 °C, 354 °C, and 361 °C, respectively, for three different samples. This suggests that the thermal stability is enhanced as a result of the heat treatment. These findings will help optimize the heat treatments of the rattan material.
Forestry Ergonomics Publications in the Last Decade: A Review
Authors: Bačić Marin , Landekić Matija , Pandur Zdravko , Šušnjar Marijan , Šporčić Mario , Nevečerel Hrvoje , Lepoglavec Kruno
Published: March 2024

Compiling the research on forestry ergonomics, which is still a marginal field in terms of the sheer volume of published forestry-related articles, gives a good foundation and guidance for future research and publishing. This review aims to compile, classify, and analyze forestry ergonomics publications in JIF (Journal Impact Factor) journals regarding their spatial and temporal distribution, observed operations, machines and tools, and risk factors. A reference period from 2014 to 2023 was observed in this study. The Web of Science Core Collection database was used to filter publications in the field of forestry and ergonomics. A total number of 102 articles were selected. After selection, data regarding publishing year, journal name, main field, country of origin, forest operation, machine/tool, and risk factor were noted. The number of articles is ever-increasing with the last four years having above average numbers of articles. Countries from Europe and South America (Brazil) have the most publications. Most of the journals are ranked in the top 50%. Harvesting, wood extraction, and pre-harvesting operations have the highest number of records. Chainsaw, skidder, and pre-harvesting tools are the most observed means of work. The risk factors with the highest percentage of records are workload (23%), noise (20%), vibration (20%), postural load (16%), and MSD (Musculoskeletal Disorder) occurrence (7%).