bluuebunny/crossref_metadata_2025 huggingface dataset:
Terahertz Nondestructive Measurement of Heat Radiation Performance of Thermal Barrier Coatings Based on Hybrid Artificial Neural Network
Authors: Xu Zhou , Yin Changdong , Wu Yiwen , Liu Houli , Zhou Haiting , Xu Shuheng , Xu Jianfei , Ye Dongdong
Published: May 2024

Effective control of the micro- and nanostructure of thermal barrier coatings is essential to enhance the thermal radiation performance of the coating, which helps to determine the remaining service life of the coating. This paper proposed a method to measure the radiation properties of thermal barrier coatings by terahertz nondestructive testing technique, using APS-prepared thermal barrier coatings as the object of study. Radiative properties were a comprehensive set of properties characterized by the diffuse reflectance, transmittance, and absorptance of the thermal barrier coating. The coating data in actual service were obtained by scanning electron microscopy and metallographic experiments, and the data were used as the simulation model critical value. The terahertz time-domain simulation data of coatings with different microstructural features were obtained using the finite-different time-domain (FDTD) method. In simulating the real test signals, white noise with a signal-to-noise ratio of 20 dB was added, and fast Fourier transform (FFT), short-time Fourier transform (STFT), and wavelet transform (WT) were used to reduce the noise and compare their noise reduction effects. Different machine learning methods were used to build the model, including support vector machine algorithm (SVM) and k-nearest neighbor algorithm (KNN). The principal component algorithm (PCA) was used to reduce the dimensionality of terahertz time-domain data, and the SVM algorithm and KNN algorithm were optimized using the particle swarm optimization algorithm (PSO) and the ant colony optimization algorithm (ACO), respectively, to improve the robustness of the system. The K-fold cross-validation method was used to construct the model to improve the adaptability of the model. It could be clearly seen that the novel hybrid PCA-ACO-SVM model had superior prediction performance. Finally, this work proposed a novel, convenient, nondestructive, online, safe and highly accurate method for measuring the radiation performance of thermal barrier coatings, which could be used for the judgment of the service life of thermal barrier coatings.
Wear Resistance Behavior of Low-, Mid-, and High-Phosphorus Electroless Ni-P Coatings Heat-Treated in the Air Environment
Authors: Dhakal Dhani Ram , Han Young Uk , Lee Byung Geon , Kim Tae Ho , Jang Gi Bum , Cho Sung Youl
Published: May 2024

The high-temperature heat treatment of electroless nickel–phosphorus (Ni-P) coatings in an air environment, and its consequences have scarcely been investigated. This work investigated tribological characteristics of the high-temperature, heat-treated, electroless Ni-P coatings on steel substrates with low-, mid-, and high-phosphorus content for which the average phosphorus content was 2.4 wt.%, 7.1 wt.%, and 10.3 wt.%, respectively. X-ray fluorescence and energy dispersive spectroscopy were implemented to determine the phosphorus content of the coatings. The oxidation of Ni and the formation of the NiO layer on the coating surface was confirmed by the X-ray diffraction technique. A reciprocating sliding method on a ball-on-flat system was utilized to evaluate the coating’s friction and wear behavior. Among the coatings with varying phosphorus content, a high hardness of 1086 HV was found for high-phosphorus coating when heat-treated at 400 °C in an air environment, and that was decreased to 691 HV when heat-treated at 650 °C. The oxidation of nickel in the electroless Ni-P coating occurred when heat-treated at 400 °C in an air environment, and this phenomenon was increased more when the temperature was increased to 650 °C. The characteristics of the NiO layer that formed on the surface of the heat-treated electroless Ni-P coating were influenced by the concentration of phosphorus, which caused different colors of NiO to be seen on the Ni-P coating surface. A greenish black NiO layer on the low-phosphorus and black NiO layer on the mid- and high-phosphorus Ni-P coating was developed during heat treatment at 650 °C in an air atmosphere. The adhesion and tribological characteristics of the Ni-P coatings were affected by the NiO layer developed on the heat-treated Ni-P coating surfaces. The Ni-P coatings with mid- and high-phosphorus content showed enhanced wear-resistance characteristics when they underwent heat treatment in an air atmosphere at the high temperature of 650 °C. The wear volume obtained for as-plated mid-phosphorus and high-phosphorus Ni-P coatings was 0.111 mm3 and 0.128 mm3, respectively, and that was reduced to 0.031 mm3 and 0.051 mm3, respectively, after the high-temperature heat treatment.
Modeling Density Waves and Circulations in Vertical Cross-Section in Adhesive Contacts
Authors: Filippov Aleksander E. , Lyashenko Iakov A. , Popov Valentin L.
Published: May 2024

This work continues the study of the process of friction between a steel spherical indenter and a soft elastic elastomer previously published in our paper. It is done in the context of our previous experimental results obtained on systems with strongly pronounced adhesive interaction between the surfaces of contacting bodies during the process of friction between a steel spherical indenter and a soft elastic elastomer. In the present paper, we concentrate on the theoretical study of the processes developing in a vertical cross-section of the system. For continuity, here the case of indenter motion at a low speed at different indentation depths is considered as before. The analysis of the evolution of normal and tangential contact forces, mean normal pressure, tangential stresses, as well as the size of the contact area is performed. Despite its relative simplicity, a numerical two-dimensional (2D = 1 + 1) model, which is used here, satisfactorily reproduces experimentally observed effects. Furthermore, it allows direct visualization of the motion in the vertical cross-section of the system, which is currently invisible experimentally. Partially, it recalls two-dimensional (2D = 1 + 1) models recently proposed to describe the “turbulent” shear flow of solids under torsion and in cellular materials. The observations extracted from the model help us to understand better the adhesive processes that underlie the experimental results.
Reactive Magnetron Sputtering for Y-Doped Barium Zirconate Electrolyte Deposition in a Complete Protonic Ceramic Fuel Cell
Authors: Lescure Victoire , François Mélanie , Charleux Maëlys , Aubry Eric , Combemale Lionel , Briois Pascal , Caboche Gilles
Published: May 2024

Yttrium-doped barium zirconate is a commonly used electrolyte material for Protonic Ceramic Fuel Cells (PCFC) due to its high protonic conductivity and high chemical stability. However, it is also known for its poor sinterability and poor grain boundary conductivity. In this work, in response to these issues, reactive magnetron sputtering was strategically chosen as the electrolyte deposition technique. This method allows the creation of a 4 µm tick electrolyte with a dense columnar microstructure. Notably, this technique is not widely utilized in PCFC fabrication. In this study, a complete cell is elaborated without exceeding a sintering temperature of 1350 °C. Tape casting is used for the anode, and spray coating is used for the cathode. The material of interest is yttrium-doped barium zirconate with the formula BaZr0.8Y0.2O3−δ (BZY). The anode consists of a NiO-BZY cermet, while the cathode is composed of BZY and Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSFC) in a 50:50 weight ratio. The electrochemical impedance spectroscopy analysis reveals a global polarization resistance of 0.3 Ω cm2, indicating highly efficient interfaces between electrolytes and electrodes.
R-Phase Transformation Evolution in NiTi SMA Wires Studied via the Internal Friction Technique
Authors: Xu Yuhao , Chen Junlan , Wang Xinggang , Sun Meng , Wang Xianping , Jiang Weibin
Published: May 2024

The specific damping capacity variation of heat-treated NiTi was observed during a pseudoelasticity test. The detailed B2 → R-phase transformation process in cold-drawn NiTi wires undergoing middle-temperature aging was studied via X-ray diffraction, transmission electron microscope, and internal friction technique. Results show that, as aging time increased at 450 °C, the dynamic phase transition splitting from B2 → R to B2 → R1 and B2 → R2 became evident. However, such a splitting process was not observed for the sample after aging at 400 °C. The reason for R-phase generation is attributed to non-uniformly distributed stress fields. The splitting of the internal friction peak, in conjunction with high-resolution transmission electron microscope and mechanic results, suggests a substantial occurrence of short-range segregation of Ni atoms in the B2-NiTi matrix. Furthermore, the specific damping capacity (SDC) exhibits a gradual increase with prolonged annealing time. Specifically, the sample with significant dynamic phase transition splitting reaches an SDC value of 0.60.
Nanoscale Cu2ZnSnSxSe(4−x) (CZTS/Se) for Sustainable Solutions in Renewable Energy, Sensing, and Nanomedicine
Authors: Mohammadi Sayedmahdi , Kaur Navdeep , Radu Daniela R.
Published: May 2024

The importance and breadth of applications of the family of quaternary chalcogenides with the formula Cu2ZnSnSxSe(4−x) (CZTS/Se) where x = 0–4 are steadily expanding due to the tunable optoelectronic properties of these compounds and the Earth abundance of the elements in their composition. These p-type semiconductors are viewed as a viable alternative to Si, gallium arsenide, CdTe, and CIGS solar cells due to their cost effectiveness, Earth’s crust abundance, and non-toxic elements. Additionally, CZTS/Se compounds have demonstrated notable capabilities beyond solar cells, such as photoelectrochemical CO2 reduction, solar water splitting, solar seawater desalination, hydrogen production, and use as an antibacterial agent. Various routes have been explored for synthesizing pure CZTS/Se nanomaterials and significant efforts have been dedicated to reducing the occurrence of secondary phases. This review focuses on synthetic approaches for CZTS/Se nanomaterials, with emphasis on controlling the size and morphology of the nanoparticles and their recent application in solar energy harvesting and beyond, highlighting challenges in achieving the desired purity required in all these applications.
Generation and Validation of Normative, Age-Specific Reference Curves for Bone Strain Index in Women
Authors: Rinaudo Luca , Cuttone Sofia , Messina Carmelo , Magni Veronica , Capra Davide , Sconfienza Luca Maria , Sardanelli Francesco , Ulivieri Fabio Massimo
Published: May 2024

Bone Strain Index (BSI), based on dual-energy X-ray absorptiometry (DXA), is a densitometric index of bone strength of the femur and lumbar spine. Higher BSI values indicate a higher strain applied to bone, predisposing to higher fracture risk. This retrospective, multicentric study on Italian women reports the BSI normative age-specific reference curves. A cohort of Caucasian Italian women aged 20 to 90 years was selected from three different clinical centres. Bone mineral density (BMD) and BSI measurements were obtained for the lumbar spine vertebrae (L1–L4) and for the femur (neck, trochanter and intertrochanter) using Hologic densitometers scans. The data were compared with BMD normative values provided by the densitometer manufacturer. Then, the age-specific BSI curve for the femur and lumbar spine was generated. No significant difference was found between the BMD of the subjects in this study and BMD reference data provided by Hologic (p = 0.68 for femur and p = 0.90 for lumbar spine). Spine BSI values (L1–L4) increase by 84% between 20 and 90 years of age. The mean BSI of the total femur increases about 38% in the same age range. The BSI age-specific reference curve could help clinicians improve osteoporosis patient management, allowing an appropriate patient classification according to the bone resistance to the applied loads and fragility fracture risk assessment.
Identifying Autism Gaze Patterns in Five-Second Data Records
Authors: Lencastre Pedro , Lotfigolian Maryam , Lind Pedro G.
Published: May 2024

One of the most challenging problems when diagnosing autism spectrum disorder (ASD) is the need for long sets of data. Collecting data during such long periods is challenging, particularly when dealing with children. This challenge motivates the investigation of possible classifiers of ASD that do not need such long data sets. In this paper, we use eye-tracking data sets covering only 5 s and introduce one metric able to distinguish between ASD and typically developed (TD) gaze patterns based on such short time-series and compare it with two benchmarks, one using the traditional eye-tracking metrics and one state-of-the-art AI classifier. Although the data can only track possible disorders in visual attention and our approach is not a substitute to medical diagnosis, we find that our newly introduced metric can achieve an accuracy of 93% in classifying eye gaze trajectories from children with ASD surpassing both benchmarks while needing fewer data. The classification accuracy of our method, using a 5 s data series, performs better than the standard metrics in eye-tracking and is at the level of the best AI benchmarks, even when these are trained with longer time series. We also discuss the advantages and limitations of our method in comparison with the state of the art: besides needing a low amount of data, this method is a simple, understandable, and straightforward criterion to apply, which often contrasts with “black box” AI methods.
The Role of T2 Mapping in Cardiac Amyloidosis
Authors: Grazzini Giulia , Pradella Silvia , Bani Rossella , Fornaciari Chiara , Cappelli Francesco , Perfetto Federico , Cozzi Diletta , Giovannelli Simona , Sica Giacomo , Miele Vittorio
Published: May 2024

Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy divided into two types: light-chain (LA) and transthyretin (ATTR) CA. Cardiac magnetic resonance (CMR) has emerged as an important diagnostic tool in CA. While late gadolinium enhancement (LGE), T1 mapping and extracellular volume (ECV) have a consolidate role in the assessment of CA, T2 mapping has been less often evaluated. We aimed to test the value of T2 mapping in the evaluation of CA. This study recruited 70 patients with CA (51 ATTR, 19 AL). All the subjects underwent 1.5 T CMR with T1 and T2 mapping and cine and LGE imaging. Their QALE scores were evaluated. The myocardial T2 values were significantly (p < 0.001) increased in both types of CA compared to the controls. In the AL-CA group, increased T2 values were associated with a higher QALE score. The myocardial native T1 values and ECV were significantly (p < 0.001) higher in the CA patients than in the healthy subjects. Left ventricular (LV) mass, QALE score and ECV were higher in ATTR amyloidosis compared with AL amyloidosis, while the LV ejection fraction was lower (p < 0.001). These results support the concept of the presence of myocardial edema in CA. Therefore, a CMR evaluation including not only myocardial T1 imaging but also myocardial T2 imaging allows for more comprehensive tissue characterization in CA.
The Value of Contrast-Enhanced Ultrasound (CEUS) in the Evaluation of Central Lung Cancer with Obstructive Atelectasis
Authors: Safai Zadeh Ehsan , Huber Katharina Paulina , Görg Christian , Prosch Helmut , Findeisen Hajo
Published: May 2024

Purpose: To assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) alongside contrast-enhanced computed tomography (CECT) in evaluating central lung cancer (CLC). Materials and Methods: From 2006 to 2022, 54 patients with CLC and obstructive atelectasis (OAT) underwent standardized examinations using CEUS in addition to CECT. The ability to differentiate CLC from atelectatic tissue in CECT and CEUS was categorized as distinguishable or indistinguishable. In CEUS, in distinguishable cases, the order of enhancement (time to enhancement) (OE; categorized as either an early pulmonary arterial [PA] pattern or a delayed bronchial arterial [BA] pattern of enhancement), the extent of enhancement (EE; marked or reduced), the homogeneity of enhancement (HE; homogeneous or inhomogeneous), and the decrease in enhancement (DE; rapid washout [<120 s] or late washout [≥120 s]) were evaluated. Results: The additional use of CEUS improved the diagnostic capability of CECT from 75.9% to 92.6% in differentiating a CLC from atelectatic tissue. The majority of CLC cases exhibited a BA pattern of enhancement (89.6%), an isoechoic reduced enhancement (91.7%), and a homogeneous enhancement (91.7%). Rapid DE was observed in 79.2% of cases. Conclusions: In cases of suspected CLC with obstructive atelectasis, the application of CEUS can be helpful in differentiating tumor from atelectatic tissue and in evaluating CLC.
Interpreting Prostate MRI Reports in the Era of Increasing Prostate MRI Utilization: A Urologist’s Perspective
Authors: Miszewski Kevin , Skrobisz Katarzyna , Miszewska Laura , Matuszewski Marcin
Published: May 2024

Multi-parametric prostate MRI (mpMRI) is crucial for diagnosing, staging, and assessing treatment response in individuals with prostate cancer. Radiologists, through an accurate and standardized interpretation of mpMRI, stratify patients who may benefit from more invasive treatment or exclude patients who may be harmed by overtreatment. The integration of prostate MRI into the diagnostic pathway is anticipated to generate a substantial surge in the demand for high-quality mpMRI, estimated at approximately two million additional prostate MRI scans annually in Europe. In this review we examine the immediate impact on healthcare, particularly focusing on the workload and evolving roles of radiologists and urologists tasked with the interpretation of these reports and consequential decisions regarding prostate biopsies. We investigate important questions that influence how prostate MRI reports are handled. The discussion aims to provide insights into the collaboration needed for effective reporting.
The Challenges of Blood Sample Delivery via Drones in Urban Environment: A Feasibility Study through Specific Operation Risk Assessment Methodology
Authors: Molinari Sara , Patriarca Riccardo , Ducci Marco
Published: May 2024

In recent years, Unmanned Aircraft System (UAS) usage in the medical sector as an alternative to traditional means of goods transport has grown significantly. Even though the reduced response time achieved with UASs can be lifesaving in critical situations, their usage must comply with technological constraints such as range, speed and capacity, while minimizing potential risks. In this paper, the feasibility of a drone operation dedicated to the transport of blood samples in an urban area is studied through a safety risk analysis. The assessment utilizes the Specific Operation Risk Assessment (SORA) framework, in line with current European regulations, and extends it to define flight trajectories with minimal risk. A case study in the Helsinki urban area is used as a reference, with an exemplary case of commercial drone transportation of blood samples between the Töölö and Malmi Hospitals. By leveraging the drone performance capabilities and minimizing the risk for people on the ground, this approach demonstrates that medical delivery using drones in densely populated urban environments remains challenging. Nonetheless, it argues that the proposed method can enhance risk awareness and support the planning of feasible operations.
Comparative Analysis between Quality of Life and Human Labor in Countries Belonging to G7 and BRICS Blocks: Proposition of Discriminant Analysis Model
Authors: Girardi Gustavo Carolino , Rubbo Priscila , Broday Evandro Eduardo , Arnold Maik , Picinin Claudia Tania
Published: May 2024

The aim of the present research is to identify and analyze the variables which help to effectively differentiate Quality of Life (QoL) and human labor in the G7 (Germany, France, Italy, Canada, Japan, United Kingdom, and United States of America—USA) and BRICS countries (Brazil, Russia, India, China, and South Africa) through a discriminant analysis. A discriminant analysis model is developed to classify countries as having a low, mid, or high QoL based on QoL and human labor variables. The variables used in the discriminant analysis were obtained between 2010 and 2022 from two platforms: NUMBEO variables capable of relating QoL to socioeconomic aspects and OECD’s (Organization for Economic Cooperation and Development) human-labor-related variables. Based on the results, the three variables that most discriminate the groups in order of importance are employed women in relation to the female population, the female labor force participation rate, and the female unemployment rate. Countries are classified as having a low, mid, or high QoL. The adopted technique will allow researchers and managers to classify and draw goals for action reorganization and investment in QoL and labor.
Exploring Education as a Complex System: Computational Educational Research with Multi-Level Agent-Based Modeling
Authors: Vulic John , Jacobson Michael J. , Levin James A.
Published: May 2024

Our study employs multi-level agent-based modeling and computational techniques to explore education as a complex system. With an underlying focus that education should be underpinned by a scientific understanding of student learning, we created computational models that simulated learning dynamics in classrooms, integrating both quantitative and qualitative insights. Through these models, we conducted experiments aligned with real classroom data to address key questions, such as “How can we effectively support the academic progress of underperforming students, who are disproportionately from low socio-economic status (SES) backgrounds, to close their multi-year achievement gap in mathematics?” Our study analyzes various instructional approaches for mathematical learning, and our findings highlight the potential effectiveness of Productive Failure as an instructional approach. Considerations of the broader applicability of computational methods in advancing educational research are also provided.
Experimental Approach for Reliability Analysis of Medium-Power Zener Diodes under DC Switching Surge Degradation
Authors: van Niekerk Daniel , Venter Johan
Published: May 2024

This study investigated the reliability of Zener diodes subjected to a gradually increasing DC switching surge amplitude with delay internals between surges to avoid thermal degradation from different manufacturers with similar specifications. The analysis involved applying occasional 3 ms direct current (DC) switching surges with a gradual increasing surge voltage, followed by a constant current test to verify device functionality for three different selected manufacturer 5.1 V Zener diodes. This experimental approach was used to identify the maximum surge current that each Zener diode could handle before failing to clamp the surge voltage at the specified Zener reference voltage. Statistical analysis revealed significant differences in the maximum average surge current between different manufacturers. The maximum average surge current findings just before failure were 1.98 A, 3.18 A, and 3.33 A, respectively, and associated 95% confidence interval ranges can be used as a reliable metric to compare Zener diode population reliability against occasional DC switching surges. The findings revealed variations in the DC switching surge current handling capabilities between Zener diodes from different manufacturers with similar electrical specifications. The statistically measured maximum average surge current just before device failure can be considered an effective metric to compare the reliability of Zener diodes against DC switching surge degradation.
A Survey on AI-Empowered Softwarized Industrial IoT Networks
Authors: Rojas Elisa , Carrascal David , Lopez-Pajares Diego , Alvarez-Horcajo Joaquin , Carral Juan A. , Arco Jose Manuel , Martinez-Yelmo Isaias
Published: May 2024

The future generation of mobile networks envision Artificial Intelligence (AI) and the Internet of Things (IoT) as key enabling technologies that will foster the emergence of sophisticated use cases, with the industrial sector being one to benefit the most. This survey reviews related works in this field, with a particular focus on the specific role of network softwarization. Furthermore, the survey delves into their context and trends, categorizing works into several types and comparing them based on their contribution to the advancement of the state of the art. Since our analysis yields a lack of integrated practical implementations and a potential desynchronization with current standards, we finalize our study with a summary of challenges and future research ideas.
Waveform Optimization Control of an Active Neutral Point Clamped Three-Level Power Converter System
Authors: Zhou Jinghua , Li Jin
Published: May 2024

Currently, the escalating integration of renewable energy sources is causing a steady weakening of grid strength. When grid strength is weak, interactions between inverters or those between inverters and grid line impedance can provoke widespread oscillations in the power system. Additionally, the diverse DC voltage application characteristics of power converter systems (PCS) may lead to over-modulation, generating narrow pulse issues that further impact control of the midpoint potential balance. Existing dead-time elimination methods are highly susceptible to current polarity judgments, rendering them ineffective in practical use. PCS, due to inherent dead-time effects, midpoint potential imbalances in three-level topologies, and narrow pulses, can elevate low-order harmonic content in the output voltage, ultimately distorting grid-connected currents. This is particularly susceptible to causing resonance in weak grids. To enhance the output voltage waveform of PCS, this article introduces a comprehensive compensation control strategy that combines dead-time elimination, midpoint potential balance, and narrow pulse suppression, all based on an active neutral point clamped (ANPC) three-level topology. This strategy gives precedence to dead-time elimination and calculates the upper and lower limits of the zero-sequence available for midpoint potential balance while fully compensating for narrow pulses. By prioritizing dead-time elimination, followed by narrow pulse suppression and finally midpoint potential balance, this method decouples the coupling between these three factors. The effectiveness of the proposed method is validated through semi-physical simulations.
Nonlinear Robust Control of Vehicle Stabilization System with Uncertainty Based on Neural Network
Authors: Wang Yimin , Yuan Shusen , Wang Xiuye , Yang Guolai
Published: May 2024

To effectively suppress the effects of uncertainties including unmodeled dynamics and external disturbances in the vehicle stabilization system, a nonlinear robust control strategy based on a multilayer neural network is proposed in this paper. First, the mechanical and electrical coupling dynamics model of the vehicle stabilization system, considering model uncertainty and actuator dynamics, is refined. Second, the lumped uncertainty of the vehicle stabilization system is estimated by a multi-layer neural network and compensated by feedforward control. The high robustness of the system is ensured by constructing the sliding mode feedback control law. The proposed control method overcomes the limitations of sliding mode technology and the neural network and is naturally applied to the vehicle stabilization system, avoiding the adverse effects of high-gain feedback. Based on Lyapunov theory, it is demonstrated that the proposed controller is able to achieve the desired stability tracking performance. Finally, the effectiveness of the proposed control strategy is verified by co-simulation and comparative experiments.
Research on Aspect-Level Sentiment Analysis Based on Adversarial Training and Dependency Parsing
Authors: Xu Erfeng , Zhu Junwu , Zhang Luchen , Wang Yi , Lin Wei
Published: May 2024

Aspect-level sentiment analysis is used to predict the sentiment polarity of a specific aspect in a sentence. However, most current research cannot fully utilize semantic information, and the models lack robustness. Therefore, this article proposes a model for aspect-level sentiment analysis based on a combination of adversarial training and dependency syntax analysis. First, BERT is used to transform word vectors and construct adjacency matrices with dependency syntactic relationships to better extract semantic dependency relationships and features between sentence components. A multi-head attention mechanism is used to fuse the features of the two parts, simultaneously perform adversarial training on the BERT embedding layer to enhance model robustness, and, finally, to predict emotional polarity. The model was tested on the SemEval 2014 Task 4 dataset. The experimental results showed that, compared with the baseline model, the model achieved significant performance improvement after incorporating adversarial training and dependency syntax relationships.
TACA-RNet: Tri-Axis Based Context-Aware Reverse Network for Multimodal Brain Tumor Segmentation
Authors: Kim Hyunjin , Jo Youngwan , Lee Hyojeong , Park Sanghyun
Published: May 2024

Brain tumor segmentation using Magnetic Resonance Imaging (MRI) is vital for clinical decision making. Traditional deep learning-based studies using convolutional neural networks have predominantly processed MRI data as two-dimensional slices, leading to the loss of contextual information. While three-dimensional (3D) convolutional layers represent an advancement, they have not fully exploited pathological information according to the three-axis nature of 3D MRI data—axial, coronal, and sagittal. Recognizing these limitations, we introduce a Tri-Axis based Context-Aware Reverse Network (TACA-RNet). This innovative approach leverages the unique 3D spatial orientations of MRI, learning crucial information on brain anatomy and pathology. We incorporated three specialized modules: a Tri-Axis Channel Reduction module for optimizing feature dimensions, a MultiScale Contextual Fusion module for aggregating multi-scale features and enhancing spatial discernment, and a 3D Axis Reverse Attention module for the precise delineation of tumor boundaries. The TACA-RNet leverages three specialized modules to enhance the understanding of tumor characteristics and spatial relationships within MRI data by fully utilizing its tri-axial structure. Validated on the Brain Tumor Segmentation Challenge 2018 and 2020 datasets, the TACA-RNet demonstrated superior performances over contemporary methodologies. This underscores the critical role of leveraging the three-axis structure of MRI to enhance segmentation accuracy.
AC Direct Charging for Electric Vehicles via a Reconfigurable Cascaded Multilevel Converter
Authors: Tresca Giulia , Zanchetta Pericle
Published: May 2024

This paper presents a charging architecture for the Reconfigurable Cascaded Multilevel converter, which was specifically designed for electric vehicle (EV) powertrain applications. The RCMC topology is capable of executing power conversion and actively managing battery systems concurrently. The active battery management is achieved using the Reconfigurable Battery Module, which regulates the serial connection of cells via a switch pattern. In this paper, the RCMC is directly interfaced with an AC three-phase power system, facilitating the dynamic control over battery cells charging. Its inherent design allows for the implementation of various charging algorithms, customizable to specific requirements, without necessitating additional intermediary power stages. Firstly, an overview of the RCMC topology is given, and an analysis to define the optimal filter inductance is carried out. Subsequently, after the AC system characteristics are explained, two charging algorithms are presented and described: one prioritizes State of Charge (SOC) balancing among battery cells, while the other focuses on minimizing power losses. Moreover, a time estimation computation for the RCMC is carried out considering a two-level AC charging station. The result is compared with the time required for a conventional battery pack. The results show a reduction of 10 s in charging time for a mere 20% increase in SOC. Finally, the experimental setup is presented and used to validate the efficacy of the proposed algorithms.
The Effect of Non-Saccharomyces Cerevisiae Torulaspora delbrueckii on the Aroma Composition of Munage Grape Base-Wine and the Mechanism of the Effect
Authors: Yin Xuefeng , Liu Bingze , Maimaitiyiming Ruxianguli , Wang Liang , Zhao Lei , Zhang Huimin , Chen Keping , Aihaiti Aihemaitijiang
Published: May 2024

To enhance comprehension of the impact of mixed fermentation using Torulaspora delbrueckii Bio-119667 (TD) on the aroma composition of Munage grape base-wine (MGBW), we analysed the aroma composition of MGBW using HS-SPME-GC-MS widely targeted metabolomics. The levels of volatile aroma components, including terpenes, higher alcohols, aldehydes, heterocyclic compounds, and esters, were significantly higher in MGBW produced by mixed fermentation compared to the pure Saccharomyces yeast control fermentation. The study found that the content of esters increased by 26.3% after mixed fermentation, indicating the contribution of TD to the formation of ester flavour components during the fermentation of MGBW. After analysing aroma activity values, we discovered that 49 out of 115 esters (25.5% of the total) significantly contributed to the aroma profile of MGBW (rOAV > 1). Of these esters, 16 were identified as key aroma compounds (rOAV > 1, VIP > 1) produced by mixed fermentation with the participation of TD. This finding further supports the contribution of TD to the improvement of MGBW’s aroma composition. This study reveals the role of non-Saccharomyces yeast strain Torulaspora delbrueckii Bio-119667 in improving the aroma composition of MGBW produced by mixed culture fermentation and the biosynthetic pathways of key aroma components therein.
Near-Infrared Spectroscopy Analysis of the Phytic Acid Content in Fuzzy Cottonseed Based on Machine Learning Algorithms
Authors: Yin Hong , Mo Wenlong , Li Luqiao , Ma Yiting , Chen Jinhong , Zhu Shuijin , Zhao Tianlun
Published: May 2024

Cottonseed is rich in oil and protein. However, its antinutritional factor content, of phytic acid (PA), has limited its utilization. Near-infrared (NIR) spectroscopy, combined with chemometrics, is an efficient and eco-friendly analytical technique for crop quality analysis. Despite its potential, there are currently no established NIR models for measuring the PA content in fuzzy cottonseeds. In this research, a total of 456 samples of fuzzy cottonseed were used as the experimental materials. Spectral pre-treatments, including first derivative (1D) and standard normal variable transformation (SNV), were applied, and the linear partial least squares (PLS), nonlinear support vector machine (SVM), and random forest (RF) methods were utilized to develop accurate calibration models for predicting the content of PA in fuzzy cottonseed. The results showed that the spectral pre-treatment significantly improved the prediction performance of the models, with the RF model exhibiting the best prediction performance. The RF model had a coefficient of determination in prediction (R2p) of 0.9114, and its residual predictive deviation (RPD) was 3.9828, which indicates its high accuracy in measuring the PA content in fuzzy cottonseed. Additionally, this method avoids the costly and time-consuming delinting and crushing of cottonseeds, making it an economical and environmentally friendly alternative.
Enhancing Fresh-Cut Apple Preservation: Impact of Slightly Acidic Electrolyzed Water and Chitosan–Apple Essence Microencapsulation Coating on Browning and Flavor
Authors: Luo Zhenyu , Li Guijing , Du Yanlin , Yi Junjie , Hu Xiaosong , Jiang Yongli
Published: May 2024

Fresh-cut apple preservation is a critical concern in the food industry due to the rapid deterioration of texture, color, and flavor. While our previous study introduced apple essence microencapsulation (AEM) to enhance flavor during storage, its impact on overall storage quality was minimal. Thus, this study explores the application of two preservation techniques, namely, slightly acidic electrolyzed water (SAEW) and chitosan–apple essence microencapsulation (CH–AEM) coating, to enhance the quality of fresh-cut apples. Our findings reveal that SAEW treatment significantly reduces the browning index (from 65.38 to 57.36) and respiratory rate (from 5.10% to 4.30% of CO2), and maintains a desirable aroma profile compared to uncoated treatment during 10 days of storage. Additionally, the CH–AEM coating acts as a protective barrier, further preserving the sensory characteristics of fresh-cut apples. Notably, the SAEW–CH–AEM group exhibits superior performance in firmness (8.14 N), respiratory rate (3.37% of CO2), ion leakage (34.86%), and juice yield (47.52%) after 10 days. Our research highlights the synergistic effect of combining these preservation strategies, providing a promising approach for extending the shelf life of fresh-cut apples while maintaining their visual appeal and aromatic quality. These results offer valuable insights for the fresh-cut produce industry, contributing to improved apple product preservation and consumer satisfaction.
Quality Evaluation of Polygonatum cyrtonema Hua Based on UPLC-Q-Exactive Orbitrap MS and Electronic Sensory Techniques with Different Numbers of Steaming Cycles
Authors: Wang Mengjin , Hu Jiayi , Hai Xiaoya , Cao Tianzhuo , Zhou An , Han Rongchun , Xing Lihua , Yu Nianjun
Published: May 2024

In this study, electronic sensory techniques were employed to comprehensively evaluate the organoleptic quality, chemical composition and content change rules for Polygonatum cyrtonema Hua (PCH) during the steaming process. The results were subjected to hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). These analyses revealed, from a sensory product perspective, overall differences in colour, odour and taste among the samples of PCH with different numbers of steaming cycles. Using the UPLC-Q-Exactive Orbitrap MS technique, 64 chemical components, including polysaccharides, organic acids, saponins and amino acids were detected in PCH before and after steaming. The sensory traits were then correlated with the chemical composition. From the perspectives of sensory traits, chemical composition, and multi-component index content, it was preliminarily deduced that carrying out five cycles of steaming and sun-drying was optimal, providing evidence for the quality evaluation of PCH during the steaming process.
Augmenting the Stability of Automatic Voltage Regulators through Sophisticated Fractional-Order Controllers
Authors: Mohamed Emad A. , Aly Mokhtar , Alhosaini Waleed , Ahmed Emad M.
Published: May 2024

The transition from traditional to renewable energy sources is a critical issue in current energy-generation systems, which aims to address climate change and the increased demand for energy. This shift, however, imposes additional burdens on control systems to maintain power system stability and quality within predefined limits. Addressing these challenges, this paper proposes an innovative Modified Hybrid Fractional-Order (MHFO) automatic voltage regulator (AVR) equipped with a fractional-order tilt integral and proportional derivative with a filter plus a second-order derivative with a filter FOTI-PDND2N2 controller. This advanced controller combines the benefits of a (FOTI) controller, known for enhancing dynamic performance and steady-state response, with a (PDND2N2) controller to improve system robustness and adaptability. The proposed MHFO controller stands out with its nine tunable parameters, providing more extensive control options than the conventional three-parameter PID controller and the five-parameter FOPID controller. Furthermore, a recent optimization approach using a growth optimizer (GO) has been formulated and applied to optimally adjust the MHFO controller’s parameters simultaneously. The performance of the proposed AVR based on the MHFO-GO controller is scrutinized by contrasting it with various established and developed optimization algorithms. The comparative study shows that the AVR based on the MHFO-GO controller surpasses other AVR controllers from the stability, robustness, and dynamic response speed points of view.