bluuebunny/crossref_metadata_2025 huggingface dataset:
Nondestructive Identification of Internal Potato Defects Using Visible and Short-Wavelength Near-Infrared Spectral Analysis
Authors: Semyalo Dennis , Kim Yena , Omia Emmanuel , Arief Muhammad Akbar Andi , Kim Haeun , Sim Eun-Yeong , Kim Moon S. , Baek Insuck , Cho Byoung-Kwan
Published: November 2024

Potatoes are a staple food crop consumed worldwide, with their significance extending from household kitchens to large-scale food processing industries. Their market value and quality are often compromised by various internal defects such as pythium, bruising, internal browning, hollow heart, gangrene, blackheart, internal sprouting, and dry rot. This study aimed to classify internal-based defects and investigate the quantification of internal defective areas in potatoes using visible and short-wavelength near-infrared spectroscopy. The acquisition of the spectral data of potato tubers was performed using a spectrometer with a wavelength range of 400–1100 nm. The classification of internal-based defects was performed using partial least squares discriminant analysis (PLS-DA), while the quantification of the internal defective area was based on partial least squares regression (PLSR). The PLS-DA double cross-validation accuracy for the distinction between non-defective and all internally defective potatoes was 90.78%. The double cross-validation classification accuracy achieved for pythium, bruising, and non-defective categories was 91.03%. The internal defective area model based on PLSR achieved a correlation coefficient of double cross-validation of 0.91 and a root mean square error of double cross-validation of 0.85 cm2. This study makes a valuable contribution to advancing nondestructive techniques for evaluating internal defects in potatoes.
Biocontrol Potential of a Native Trichoderma Collection Against Fusarium oxysporum f. sp. cubense Subtropical Race 4
Authors: Correa-Delgado Raquel , Brito-López Patricia , Cardoza Rosa E. , Jaizme Vega María C. , Laich Federico , Gutiérrez Santiago
Published: November 2024

The Canary Islands lead banana (Musa acuminata) production in the EU. Different fungal pathogens affect this crop in subtropical areas, with Fusarium oxysporum f. sp. cubense subtropical race 4 (Foc-STR4) being the most important in the Canary Islands. With the aim of developing environmentally sustainable techniques for disease control, this study presents the results of the evaluation of the antifungal capacity of a native Trichoderma collection (12 species, 109 isolates) obtained from banana soils. The results demonstrate the diversity of biocontrol genes and the in vitro antagonistic potential of different native Trichoderma species/isolates against two Foc-STR4 strains obtained from plants with Panama disease symptoms. Trichoderma virens (TF18), a dominant species in banana soils in the Canary Islands, showed a high capacity to inhibit the growth of Foc-STR4 in different in vitro assays. Trichoderma atrobrunneum (TF01) showed mycoparasitism capacity through the spiral coil around the hyphae of the pathogen. In addition, the genome analysis of T. atrobrunneum (TF03) showed 69 putative biosynthetic gene clusters, with the notable presence of the trichothecene tri5 gene. Finally, our work demonstrates that the soils of the Canary Islands banana crops are a potential source of environmentally adapted biological control agents to control or reduce the incidence of Foc-STR4.
Structural Characterization and Bioactive Compound Evaluation of Fruit and Vegetable Waste for Potential Animal Feed Applications
Authors: Filip Miuța , Vlassa Mihaela , Petean Ioan , Țăranu Ionelia , Marin Daniela , Perhaiță Ioana , Prodan Doina , Borodi Gheorghe , Dragomir Cătălin
Published: November 2024

Agricultural waste from the fruit and vegetable industry is used as an alternative source of animal feed, but detailed investigations are required. The aim of this work was to conduct a physico-chemical characterization, through analytical techniques, of fruit and vegetable wastes such as those of golden apples, red apples, carrots, celery, beetroots, and red potato peels. The bioactive compounds in the samples indicated a high carbohydrate content of 50.38 g/100 g in golden apples and 59.38 mg/100 g of organic acids in celery. In addition, the total phenolic content (TPC, mg gallic acid equivalent/g dry weight) varied between 3.72 in celery and 15.51 in beetroots. The antioxidant capacity values were significant. A thermal analysis showed thermal stability and weight loss, underscoring the composition of the solid samples. An infrared spectroscopy (FTIR) analysis showed C-H, O-H, C=O, and N-H functional groups in non-starchy carbohydrates, organic acids, and proteins. Microscopic techniques revealed the microstructure, particle size, and semicrystalline profile of the samples. The ultrastructure (determined via atomic force microscopy (AFM)) of celery consisted of a smooth and uniform surface with a lignin and cellulose texture. These results highlight the importance of fruit and vegetable waste as an alternative source of essential nutrients and bioactive compounds for animal feed.
Enhancing Phenolic Profiles in ‘Cabernet Franc’ Grapes Through Chitooligosaccharide Treatments: Impacts on Phenolic Compounds Accumulation Across Developmental Stages
Authors: Qiang Wenle , Wang Hongjuan , Ma Tongwei , Li Kaian , Wang Bo , Ma Tengzhen , Jiang Yumei , Zhang Bo
Published: November 2024

High-quality grape raw materials are fundamental for producing premium wine. Ensuring the quality of grape raw materials, particularly enhancing their phenolic profiles, significantly improves wine flavor. Therefore, this study focused on ‘Cabernet Franc’ grapes, where a 0.1% chitooligosaccharide (COS) solution was foliar sprayed during the green pea stage, the onset of veraison stage, and the mid-ripening stage to investigate the impact of exogenous COS treatment on the accumulation of phenolic compounds in grape berries. The results revealed that COS treatment during the green pea and the onset of veraison stages significantly increased the levels of total phenolic, total flavonoid, and total anthocyanin in grapes, with distinct effects on flavanols, phenolic acids, flavonols, and stilbenes, respectively. Eight key compounds most significantly influenced by the treatment were identified through orthogonal partial least squares discriminant analysis (OPLS-DA) and machine learning screening. Specifically, treatment during the green pea stage had a significant impact on total soluble solids, proanthocyanidin B1, catechin, and vanillic acid, while veraison treatment notably affected petunidin-3-O-(6″-O-p-coumaryl)-glucoside, cyanidin-3-O-(6″-O-p-coumaryl)-glucoside, cyanidin-3-O-glucoside and isorhamnetin. This study could provide valuable data references and theoretical support for applying COS in wine grapes and regulating high-quality raw materials.
Rice Production and Nitrogen Use Efficiency by Diverse Forms of Fertilization in Rice-Based Crop Rotation Systems
Authors: Kim Woojin , Lee Moon-Sub , Sung Jwakyung
Published: November 2024

The rising demand for climate change mitigation has brought attention to agricultural systems focused on carbon farming and reducing emissions. Composting food wastes and livestock manure not only mitigates environmental concerns but also boosts soil fertility and crop yields as an alternative fertilizer. In this experiment, we investigated the effects of different fertilizer types (chemical and organic waste compost) and crop rotations (rice–fallow, rice–Italian ryegrass, and rice–potato) on rice production, nitrogen use efficiency, and soil carbon stocks. In this experiment, soil carbon and nitrogen retention were more influenced by compost nutrient levels than by crop rotation types. Overall, as the nitrogen levels increased, the rice yields improved with both chemical and organic waste fertilizers. Among the crop rotations, the rice–Italian ryegrass rotation showed a higher nitrogen use efficiency. Optimal fertility levels, balancing nitrogen use efficiency, yield, and soil carbon were observed between 523 and 582 kg N ha−1 when combined with specific crop rotations. Moreover, soil total carbon and soil total nitrogen varied among crop rotation systems. Our results indicate that organic waste compost can be a potential alternative to chemical fertilizers, while crop rotations offer a viable approach for maximizing the environmental benefits.
An Incongruent 2-Minute Stroop Task Alters the Response Time Performance in Semi-Elite Soccer Players: A Pilot Study
Authors: Prieto-Sánchez Andrés , García-Ceberino Juan M. , Leon-Llamas Juan Luis , Villafaina Santos
Published: November 2024

Introduction: Mental fatigue is a key factor in soccer that can affect physical performance. Mental fatigue protocols based on the Stroop test used in soccer involve extensive time, ranging from 10 to 30 min. Offering a protocol with a shorter duration that is more applicable in ecological situations seems to be an exciting challenge. Objective: To analyze the effects of a mental fatigue induction protocol (2 min Stroop test in its incongruent mode) on decision-making, response time, and technical execution accuracy in soccer players. Methods: A total of 18 semi-elite soccer male players, 25.83 (4.71) years from a Spanish soccer team, participated in this cross-sectional study. The 2 min incongruent Stroop test was used like mental fatigue protocol, followed by a specific analytical soccer task. The Wilcoxon signed-rank and Chi-squared tests were used to analyze the statistical differences. Results: A significant increase in participants’ response time after the fatigue protocol (p < 0.001; r = 0.878) was observed. Regarding the variables of correct decision (p = 0.457; r = 0.031) and technical execution accuracy (p = 1; r < 0.001), no significant differences were found. Additionally, no differences were observed between the first and second attempts of the 2 min incongruent Stroop test, in terms of execution accuracy, errors, or total words. Conclusions: The 2 min Stroop incongruent task may induce some degree of mental fatigue, leading to slower response time during certain technical tasks in semi-elite soccer players. However, this Stroop task was insufficient to promote significant changes in the accuracy of technical execution and the effectiveness of decision-making.
Image–Text Matching Model Based on CLIP Bimodal Encoding
Authors: Zhu Yihuan , Xu Honghua , Du Ailin , Wang Bin
Published: November 2024

Image–text matching is a fundamental task in the multimodal research field, connecting computer vision and natural language processing by aligning visual content with corresponding textual descriptions. Accurate matching is critical for applications such as image captioning and text-based image retrieval yet remains challenging due to the differences in data modalities. This paper addresses these challenges by proposing a robust image–text matching model inspired by Contrastive Language–Image Pre-training (CLIP). Our approach employs the Vision Transformer (ViT) model as the image encoder and Bidirectional Encoder Representations from Transformers (Bert) as the text encoder, integrating these into a shared vector space to measure semantic similarity. We enhance the model’s training efficiency using the LiT-tuning paradigm to optimize learning through a cosine decay strategy for dynamic adjustment of the learning rate. We validate our method on two benchmark datasets, WuKong and Flickr30k, demonstrating that our model achieves superior performance and significantly improves key evaluation metrics. The results underscore the model’s effectiveness in achieving accurate and robust image–text alignment.
The Effect Characterization of Lens on LNAPL Migration Based on High-Density Resistivity Imaging Technique
Authors: Zhao Guizhang , Cheng Jiale , Jia Menghan , Zhang Hongli , Li Hongliang , Zhang Hepeng
Published: November 2024

Light non-aqueous phase liquids (LNAPLs), which include various petroleum products, are a significant source of groundwater contamination globally. Once introduced into the subsurface, these contaminants tend to accumulate in the vadose zone, causing chronic soil and water pollution. The vadose zone often contains lens-shaped bodies with diverse properties that can significantly influence the migration and distribution of LNAPLs. Understanding the interaction between LNAPLs and these lens-shaped bodies is crucial for developing effective environmental management and remediation strategies. Prior research has primarily focused on LNAPL behavior in homogeneous media, with less emphasis on the impact of heterogeneous conditions introduced by lens-shaped bodies. To investigate the impact of lens-shaped structures on the migration of LNAPLs and to assess the specific effects of different types of lens-shaped structures on the distribution characteristics of LNAPL migration, this study simulates the LNAPL leakage process using an indoor two-dimensional sandbox. Three distinct test groups were conducted: one with no lens-shaped aquifer, one with a low-permeability lens, and one with a high-permeability lens. This study employs a combination of oil front curve mapping and high-density resistivity imaging techniques to systematically evaluate how the presence of lens-shaped structures affects the migration behavior, distribution patterns, and corresponding resistivity anomalies of LNAPLs. The results indicate that the migration rate and distribution characteristics of LNAPLs are influenced by the presence of a lens in the gas band of the envelope. The maximum vertical migration distances of the LNAPL are as follows: high-permeability lens (45 cm), no lens-shaped aquifer (40 cm), and low-permeability lens (35 cm). Horizontally, the maximum migration distances of the LNAPL to the upper part of the lens body decreases in the order of low-permeability lens, high-permeability lens, and no lens-shaped aquifer. The low-permeability lens impedes the vertical migration of the LNAPL, significantly affecting its migration path. It creates a flow around effect, hindering the downward migration of the LNAPL. In contrast, the high-permeability lens has a weaker retention effect and creates preferential flow paths, promoting the downward migration of the LNAPL. Under conditions with no lens-shaped aquifer and a high-permeability lens, the region of positive resistivity change rate is symmetrical around the axis where the injection point is located. Future research should explore the impact of various LNAPL types, lens geometries, and water table fluctuations on migration patterns. Incorporating numerical simulations could provide deeper insights into the mechanisms controlling LNAPL migration in heterogeneous subsurface environments.
A Workflow for Creating Gastric Computational Models from SPARC Scaffolds
Authors: Avci Recep , Athavale Omkar N. , Sangi Mehrdad , Di Natale Madeleine R. , Furness John B. , Liu Zhongming , Du Peng , Cheng Leo K.
Published: November 2024

In-silico studies are an ideal medium to model and improve our understanding of the mechanisms underlying gastric motility in health and disease. In this study, a workflow to create computational models of the stomach was developed using SPARC scaffolds. Three anatomically based finite element method (FEM) models of the rat stomach incorporating experimental measurements of muscle layer thickness and fiber orientations across the stomach were developed: (i) 2D (surface) FEM model with no thickness, (ii) 3D (volume) FEM model with a fixed thickness across the longitudinal and circular muscle layers, and (iii) 3D (volume) FEM model with varying thickness across the longitudinal and circular muscle layers. The three FEM models were subsequently used in whole-organ slow wave simulations and the impact of anatomical details on the simulation outcomes was investigated. The 3D FEM model with varying thickness was the most computationally expensive, while the 2D FEM model provided the fastest solution (a 200 s simulation took 8 min vs. 38 h to solve). The spatiotemporal profiles of the slow wave activation and propagation in the three FEM models were in good agreement. The largest temporal difference of 1 s in cellular activation was observed between the 2D FEM model and the varying thickness 3D FEM model in the most distal-stomach regions. These FEM models and developed workflow will be used in in-silico studies to improve our understanding of the structure-function relationship in the stomach and identify the optimal parameters of electrical therapies, an alternative treatment for the motility disorders in the stomach. In addition, the developed workflow can be readily used to generate computational models of other organs using SPARC scaffolds.
6G Technology for Indoor Localization by Deep Learning with Attention Mechanism
Authors: Chiu Chien-Ching , Wu Hung-Yu , Chen Po-Hsiang , Chao Chen-En , Lim Eng Hock
Published: November 2024

This paper explores 6G technology for indoor positioning, focusing on accuracy and reliability using convolutional neural networks (CNN) with channel state information (CSI). Indoor positioning is critical for smart applications and the Internet of Things (IoT). 6G is expected to significantly enhance positioning performance through the use of higher frequency bands, such as terahertz frequencies with wider bandwidth. Preliminary results show that 6G-based systems are expected to achieve centimeter-level positioning accuracy due to the integration of advanced artificial intelligence algorithms and terahertz frequencies. In addition, this paper also investigates the impact of self-attention (SA) and channel attention (CA) mechanisms on indoor positioning systems. The combination of these attention mechanisms with conventional CNNs has been proposed to further improve the accuracy and robustness of localization systems. CNN with SA demonstrates a 50% reduction in RMSE compared to CNN by capturing spatial dependencies more effectively.
Inclusion of Muscle Forces Affects Finite Element Prediction of Compression Screw Pullout but Not Fatigue Failure in a Custom Pelvic Implant
Authors: Zhu Yuhui , Babazadeh-Naseri Ata , Brake Matthew R. W. , Akin John E. , Li Geng , Lewis Valerae O. , Fregly Benjamin J.
Published: November 2024

Custom implants used for pelvic reconstruction in pelvic sarcoma surgery face a high complication rate due to mechanical failures of fixation screws. Consequently, patient-specific finite element (FE) models have been employed to analyze custom pelvic implant durability. However, muscle forces have often been omitted from FE studies of the post-operative pelvis with a custom implant, despite the lack of evidence that this omission has minimal impact on predicted bone, implant, and fixation screw stress distributions. This study investigated the influence of muscle forces on FE predictions of fixation screw pullout and fatigue failure in a custom pelvic implant. Specifically, FE analyses were conducted using a patient-specific FE model loaded with seven sets of personalized muscle and hip joint contact force loading conditions estimated using a personalized neuromusculoskeletal (NMS) model. Predictions of fixation screw pullout and fatigue failure—quantified by simulated screw axial forces and von Mises stresses, respectively—were compared between analyses with and without personalized muscle forces. The study found that muscle forces had a considerable influence on predicted screw pullout but not fatigue failure. However, it remains unclear whether including or excluding muscle forces would yield more conservative predictions of screw failures. Furthermore, while the effect of muscle forces on predicted screw failures was location-dependent for cortical screws, no clear location dependency was observed for cancellous screws. These findings support the combined use of patient-specific FE and NMS models, including loading from muscle forces, when predicting screw pullout but not fatigue failure in custom pelvic implants.
Oscillation Mechanism and Suppression of Variable-Speed Pumped Storage Unit with Full-Size Converter Based on the Measured Single-Input and Single-Output Impedances
Authors: Pan Pengyu , Chen Gang , Shi Huabo , Ding Lijie , Teng Yufei , Zha Xiaoming
Published: November 2024

As the penetration rate of clean energy gradually increases, the demand for flexible regulation resources in the power grid is increasing accordingly. The variable-speed pumped storage unit with a full-size converter (FSC-VSPSU) can provide fast and flexible regulation resources for the power grid, which assists in the stable operation of the clean-energy-dominated power systems. Thus, its application is gradually becoming widespread. FSC-VSPSU relies on the power electronic converter for grid connection. When the impedance mismatch between FSC-VSPSU and the power grid occurs, the grid-connected system will experience oscillations, which seriously threatens its safe and stable operation. Aiming at this, this article firstly relies on the SISO impedance measurement and an equivalent impedance analysis to obtain the stability analysis criterion. Furthermore, applying the impedance matching analysis with the Bode diagram, the influence rules of the parameters of the grid-connected FSC-VSPSU on oscillation are obtained. In addition, with the summarized oscillation analysis results, this study delves into an exploration of pertinent strategies for oscillation suppression. Finally, a grid-connected FSC-VSPSU simulation model is built in MATLAB/SIMULINK, and the simulation results verify the correctness of the oscillation analysis results and the effectiveness of the proposed oscillation suppression strategy.
Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization
Authors: Umar Muhammad , Siddique Muhammad Farooq , Ullah Niamat , Kim Jong-Myon
Published: November 2024

This paper presents a fault diagnosis technique for milling machines based on acoustic emission (AE) signals and a hybrid deep learning model optimized with a genetic algorithm. Mechanical failures in milling machines, particularly in critical components like cutting tools, gears, and bearings, account for a significant portion of operational breakdowns, leading to unplanned downtime and financial losses. To address this issue, the proposed method first acquires AE signals from the milling machine. AE signals, capturing the dynamic responses of machine components, are transformed into continuous wavelet transform (CWT) scalograms for further analysis. Gaussian filtering is applied to enhance the clarity of these scalograms, effectively reducing noise while maintaining essential features. A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. The optimized features are finally fed into a fully connected (FC) layer of the proposed hybrid model for fault classification. The proposed method achieves an accuracy of 99.6%, significantly outperforming traditional approaches. This method offers a highly accurate and efficient solution for fault detection in milling machines, allowing for more reliable predictive maintenance and operational efficiency in industrial settings.
Physicochemical and Antimicrobial Properties of Lactic Acid-Based Natural Deep Eutectic Solvents as a Function of Water Content
Authors: Pozharitskaya Olga N. , Obluchinskaya Ekaterina D. , Shikova Veronika A. , Flisyuk Elena V. , Vishnyakov Evgeny V. , Makarevich Elena V. , Shikov Alexander N.
Published: November 2024

The interest in natural deep eutectic solvents (NADESs) in green technology as an alternative to organic solvents has grown over the past decades. In this work, for the first time, the effect of dilution with water on the physicochemical and antimicrobial properties of lactic acid-based NADES with choline chloride (NADES1), sorbitol (NADES2), and glucose (NADES3) was systematically studied. According to FTIR data, after the dilution of NADESs with water, the strong hydrogen bonds weakened, however, were not destroyed after dilution of up to 40% water. The dilution of NADES with water resulted in a linear decrease in density and refractive index and in a linear increase in pH. The equations for the prediction of NADES density, pH, and refractive index as a function of water content were calculated. The viscosity decreased by half after adding approximately 10% water. The initial viscosity of NADES2 and NADES3 was significantly different. However, after adding 20% of the water, the viscosity was almost the same. The most pronounced decrease in surface tension (by 46.7%) was found for NADES1. The water activity was decreased in the following order: NADES3 > NADES1 > NADES2. The dilution of NADES with water caused a gradual increase in water activity. NADES1 showed the lowest minimal inhibitory concentrations (MIC) (7.8, 3.9, and 0.98 mg/mL) and minimum bactericidal concentrations (MBC) (15.6, 7.8, and 1.95 mg/mL) for Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, respectively. The antimicrobial activity was decreased by 2–8 times after the addition of 40% water. The water activity for all tested NADES together with low pH could explain the antimicrobial effect. The revealed regularity can be useful for the prediction of NADES properties and for the selection of green solvents on a laboratory and industrial scale.
Reduction of Submicron-Sized Aerosols by Aerodynamically Assisted Electrical Attraction with Micron-Sized Aerosols
Authors: Choi Hyun-Sik , Hwang Jungho
Published: November 2024

A vortex generator was installed inside an electric agglomeration device to apply aerodynamic agglomeration in the same space as electric agglomeration. Computational fluid dynamics simulation was utilized to assess the combined effects of electric and aerodynamic agglomeration, and this was subsequently validated through experiments. The discrete phase model was used to track particle trajectories. The results showed that both the aerodynamic agglomeration through the vortex generator and the electric agglomeration through the electric field were effective. When these two agglomerations existed individually in series, the total removal efficiency for submicron particles was 32.5%. However, when they coexisted in the same space, the efficiency increased to 50%. This increase is attributed to the increase in residence time when the vortex generator was added to a space with an electric field. This led to particles being exposed to the electric field for a longer duration, thus generating a synergistic effect.
Life Cycle Cost Analysis and Deterioration Patterns of Limestone Paving
Authors: Wasserman Irena (Rina) , Shohet Igal M.
Published: November 2024

Stone is a durable and high-performance paving material in standard and in intensive service regimes. Stone is thus a preferable material for sidewalk and promenade paving under intensive service regimes, such as touristic promenades and historic sites. Recent studies on the weathering and degradation of stones in buildings have revealed differing analytical approaches among geologists, geo-engineers, and civil engineers. The present research aims to develop a structured analytical–empirical methodology for the assessment of stone pedestrian pavements’ life cycle and life cycle costs. This study presents an integrated methodology that combines diagnostic field surveys, core laboratory tests, and the characterization of deterioration patterns. This approach allows for evaluating how faulty construction methods impact the durability and degradation of natural stone pedestrian pavements. It also assesses their effect on the pavement’s life cycle and associated costs. The diagnostic field survey concentrates on specific construction details, including: (a) Cracks in the paving stones. (b) Peeling of stone layers. (c) Subsidence and cracking at the paving edges. (d) Cracking of filler materials in joints between stone slabs. The laboratory tests focus on five core physical properties for the stone deterioration: (1) apparent density, (2) Water absorption, (3) Compressive strength, (4) Flexural strength, and (5) Abrasion resistance. This study proposes linear and exponential patterns for deterioration. A case study carried out on a Capernaum promenade revealed excessive deterioration patterns caused by the poor core properties of the paving stone and defective construction. The consequences of excessive deterioration on life cycle costs result in additional expenses of 73%, indicating a reduction in the life cycle. The novelty of this research lies in developing and delivering an integrated methodology that enables the assessment of how defective construction methods impact the durability, deterioration, life cycle, and life cycle costs of natural stone pedestrian pavements.
Fusion Text Representations to Enhance Contextual Meaning in Sentiment Classification
Authors: Trisna Komang Wahyu , Huang Jinjie , Liang Hengyu , Dharma Eddy Muntina
Published: November 2024

Sentiment classification plays a crucial role in evaluating user feedback. Today, online media users can freely provide their reviews with few restrictions. User reviews on social media are often disorganized and challenging to classify as positive or negative comments. This task becomes even more difficult when dealing with large amounts of data, making sentiment classification necessary. Automating sentiment classification involves text classification processes, commonly performed using deep learning methods. The classification process using deep learning models is closely tied to text representation. This step is critical as it affects the quality of the data being processed by the deep learning model. Traditional text representation methods often overlook the contextual meaning of sentences, leading to potential misclassification by the model. In this study, we propose a novel fusion text representation model, GloWord_biGRU, designed to enhance the contextual understanding of sentences for sentiment classification. Firstly, we combine the advantages of GloVe and Word2Vec to obtain richer and more meaningful word representations. GloVe provides word representations based on global frequency statistics within a large corpus, while Word2Vec generates word vectors that capture local contextual relationships. By integrating these two approaches, we enhance the quality of word representations used in our model. During the classification stage, we employ biGRU, considering the use of fewer parameters, which consequently reduces computational requirements. We evaluate the proposed model using the IMDB dataset. Several scenarios demonstrate that our proposed model achieves superior performance, with an F1 score of 90.21%.
Improvement of Stockbridge Damper Design for Cable-Stayed Bridges
Authors: Olosz Adél , Kövesdi Balázs , Hegyi Péter , Dunai László
Published: November 2024

Stockbridge dampers are widely used to mitigate the vibrations of cable-stayed bridges and of many other cable-suspended or cable structures exposed to the action of pedestrians, traffic or wind load. Within the current research work, one of the most effective and likely used damper types, the Stockbridge damper, was investigated to support its design and application within the daily engineering praxis. The Stockbridge damper has a relatively simple structural layout, which ensures its modular design allows it to easily adapt the damper to cables having different dynamic properties (eigenfrequencies, mass, etc.). This paper focuses on two main research areas: (i) to understand the static and dynamic behaviour of the damper and the stay cable interaction to investigate the effectiveness of its damping; (ii) to study the sensitivity of the natural frequencies of the damper to the design parameters. The final aim of the research is to develop a simple design method that is easy to apply in engineering practice and allows the efficient adaptation of the Stockbridge damper to different cable-stayed bridges. Key findings include the recommendation to position the damper at approximately 20% of the cable length for optimal attenuation, the importance of detuning to maintain effectiveness under varying cable forces, and the observation that increasing the damper mass improves efficiency, particularly for detuned elements.
Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities
Authors: Sirbiladze Gia , Midodashvili Bidzina , Manjafarashvili Teimuraz
Published: November 2024

The article deals with the definitions of the distance, divergence, and similarity characteristics between two finite fuzzy measures, which are generalizations of the same definitions between two finite probability distributions. As is known, a fuzzy measure can be uniquely represented by the so-called its associated probability class (APC). The idea of generalization is that new definitions of distance, divergence, and similarity between fuzzy measures are reduced to the definitions of distance, divergence, and similarity between the APCs of fuzzy measures. These definitions are based on the concept of distance generator. The proof of the correctness of generalizations is provided. Constructed distance, similarity, and divergence relations can be used in such applied problems as: determining the difference between Dempster-Shafer belief structures; Constructions of collaborative filtering similarity relations; non-additive and interactive parameters of machine learning in phase space metrics definition, object clustering, classification and other tasks. In this work, a new concept is used in the fuzzy measure identification problem for a certain multi-attribute decision-making (MADM) environment. For this, a conditional optimization problem with one objective function representing the distance, divergence or similarity index is formulated. Numerical examples are discussed and a comparative analysis of the obtained results is presented.
Multivariate Approximation Using Symmetrized and Perturbed Hyperbolic Tangent-Activated Multidimensional Convolution-Type Operators
Authors: Anastassiou George A.
Published: November 2024

In this article, we introduce, for the first time, multivariate symmetrized and perturbed hyperbolic tangent-activated convolution-type operators in three forms. We present their approximation properties, that is, their quantitative convergence to the unit operator via the multivariate modulus of continuity. We continue with the multivariate global smoothness preservation of these operators. We present, in detail, the related multivariate iterative approximation, as well as, multivariate simultaneous approximation, and their combinations. Using differentiability in our research, we produce higher rates of approximation, and multivariate simultaneous global smoothness preservation is also achieved.
Biotechnological and Biomedical Applications of Enzymes Involved in the Synthesis of Nucleosides and Nucleotides—2nd Edition
Authors: Fernández-Lucas Jesús
Published: November 2024

The study of nucleic acid derivatives and their role in cellular processes, first addressed in our previous Special Issue (https://www [...]
Effectiveness of Watching a Kumagai Method Video for Long-Nipple Bottle-Feeding for Children with Cleft Lip and Palate: A Pilot Experimental Before–After Trial Study
Authors: Ueki Shingo , Kumagai Yukari , Hirai Yumi , Nagatomo Eri , Miyauchi Shoko , Inoue Takuro , An Qi , Tashiro Eri , Miyata Junko
Published: November 2024

Aim: This study aimed to determine whether the Kumagai method could be followed by watching an instructional video and to compare the feeding actions of specialists and the general population. Materials and Methods: Eleven adults from diverse backgrounds were recruited and asked to feed a baby doll using a bottle feeder with a long nipple, and their actions were recorded. Then, they watched a 2.5-min instructional video of the Kumagai method and were asked to bottle-feed again. Video recordings of the participants were used to evaluate whether their actions followed the Kumagai method. Differences in the feeding actions of the specialists and participants were determined from still images in the videos. The McNemar test was used to analyze the differences between the participants’ actions before and after. The Kruskal–Wallis test was also used to determine differences between the actions of participants and specialists. Results: Feeding movements significantly improved after watching the video. Participants’ actions, which differed significantly from those of the specialists, were evident in “the angle of the nipple at the moment the nipple was brought close to the lips” and “the angle change of the nipple from the lip to the mouth”. Conclusions: Watching our short instructional video was effective in improving the technique of the Kumagai method; however, it is insufficient for feeding a real child with cleft lip and palate. Including the rationale of each action in the video and adding direct instruction as a supplement is required.
Harnessing Bacillus subtilis Spore Surface Display (BSSD) Technology for Mucosal Vaccines and Drug Delivery: Innovations in Respiratory Virus Immunization
Authors: Bahrulolum Howra , Beyranvand Parisa , Ahmadian Gholamreza
Published: November 2024

Respiratory viruses present significant global health challenges due to their rapid evolution, efficient transmission, and zoonotic potential. These viruses primarily spread through aerosols and droplets, infecting respiratory epithelial cells and causing diseases of varying severity. While traditional intramuscular vaccines are effective in reducing severe illness and mortality, they often fail to induce sufficient mucosal immunity, thereby limiting their capacity to prevent viral transmission. Mucosal vaccines, which specifically target the respiratory tract’s mucosal surfaces, enhance the production of secretory IgA (sIgA) antibodies, neutralize pathogens, and promote the activation of tissue-resident memory B cells (BrMs) and local T cell responses, leading to more effective pathogen clearance and reduced disease severity. Bacillus subtilis spore surface display (BSSD) technology is emerging as a promising platform for the development of mucosal vaccines. By harnessing the stability and robustness of Bacillus subtilis spores to present antigens on their surface, BSSD technology offers several advantages, including enhanced stability, cost-effectiveness, and the ability to induce strong local immune responses. Furthermore, the application of BSSD technology in drug delivery systems opens new avenues for improving patient compliance and therapeutic efficacy in treating respiratory infections by directly targeting mucosal sites. This review examines the potential of BSSD technology in advancing mucosal vaccine development and explores its applications as a versatile drug delivery platform for combating respiratory viral infections.
Editorial Board Members’ Collection Series: Smart Energy System Design
Authors: Salkuti Surender Reddy
Published: November 2024

The collection series presents various emerging approaches for designing growing renewable energy (RE), energy storage (ES), and smart transportation with electric vehicles (EVs) in the power and automobile industries [...]
Parental Burnout—A Model of Risk Factors and Protective Resources Among Mothers of Children with/Without Special Needs
Authors: Findling Yifat , Itzhaki Michal , Barnoy Sivia
Published: November 2024

Parents of children With Special Needs and Disabilities (W-SND) who require long-term healthcare are at high risk of Parental Burnout (PB). However, most studies have focused on PB among parents of children Without Special Needs (WO-SN). This study aimed to develop a new model explaining PB of mothers of children W-SND/WO-SN. The main hypothesis was that the nexus of correlations between risk factors of PB (severity of child’s disability/challenge, perceived caregiver burden) and protective resources (social support, learned resourcefulness, deep emotion work) will explain the variance of PB of mothers of children W-SND and WO-SN. A questionnaire assessing PB, its risk factors, and protective resources was completed by 352 Israeli mothers of children W-SND (mean age 36.9) or WO-SN (mean age 32.3). The child’s disabilities were communicative, physical, intellectual and developmental. The main results are that mothers of children W-SND reported higher PB, higher caregiver burden, and a higher severity of disability. About 50% of PB variance was significantly explained by the nexus of correlations between selected risk and protective factors. Among all mothers, the more social support they received, the higher their learned-resourcefulness. However, learned resourcefulness mediates the correlation between caregiver burden and PB among mothers of children W-SND. Accordingly, it is important to increase awareness among healthcare professionals regarding the risk factors and symptoms of PB, and to develop workshops on protective resources in order to prevent PB and promote mothers’ well-being. Further research should be conducted among fathers and parents from diverse cultures.
A Q-Learning-Based Approach to Design an Energy-Efficient MAC Protocol for UWSNs Through Collision Avoidance
Authors: Gang Qiao , Rahman Wazir Ur , Zhou Feng , Bilal Muhammad , Ali Wasiq , Khan Sajid Ullah , Khattak Muhammad Ilyas
Published: November 2024

Deploying and effectively utilizing wireless sensor networks (WSNs) in underwater habitats remains a challenging task. In underwater wireless sensors networks (UWSNs), the availability of a continuous energy source for communicating with nodes is either very costly or is prohibited due to the marine life law enforcement agencies. So, in order to address this issue, we present a Q-learning-based approach to designing an energy-efficient medium access control (MAC) protocol for UWSNs through collision avoidance. The main goal is to prolong the network’s lifespan by optimizing the communication methods, specifically focusing on improving the energy efficiency of the MAC protocols. Factors affecting the energy consumption in communication are adjustments to the interference ranges, i.e., changing frequencies repeatedly to obtain optimal communication; data packet retransmissions in case of a false acknowledgment; and data packet collision occurrences in the channel. Our chosen protocol stands out by enabling sensor (Rx) nodes to avoid collisions without needing extra communication or prior interference knowledge. According to the results obtained through simulations, our protocol may increase the network’s performance in terms of network throughput by up to 23% when compared to benchmark protocols depending on the typical traffic load. It simultaneously decreases end-to-end latency, increases the packet delivery ratio (PDR), boosts channel usage, and lessens packet collisions by over 38%. All these gains result in minimizing the network’s energy consumption, with a proportional gain.
Learning A-Share Stock Recommendation from Stock Graph and Historical Price Simultaneously
Authors: Chen Hanyang , Wang Tian , Konpang Jessada , Sirikham Adisorn
Published: November 2024

The Chinese stock market, marked by rapid growth and significant volatility, presents unique challenges for investors and analysts. A-share stocks, traded on the Shanghai and Shenzhen exchanges, are crucial to China’s financial system and offer opportunities for both domestic and international investors. Accurate stock recommendation tools are vital for informed decision making, especially given the ongoing regulatory changes and economic reforms in China. Current stock recommendation methods often fall short, as they typically fail to capture the complex inter-company relationships and rely heavily on financial reports, neglecting the potential of unlabeled data and historical price trends. In response, we propose a novel approach that combines graph-based structures with historical price data to develop self-learned stock embeddings for A-share recommendations. Our method leverages self-supervised learning, bypassing the need for human-generated labels and autonomously uncovering latent relationships and patterns within the data. This dual-input strategy enhances the understanding of market dynamics, leading to more accurate stock predictions. Our contributions include a novel framework for label-free stock recommendations with modeling stock connections and pricing information, and empirical evidence demonstrating the robustness and adaptability of our approach in the volatile Chinese stock market.
Triple-Stacked FET Distributed Power Amplifier Using 28 nm CMOS Process
Authors: Kim Jihoon , Sung Youngje
Published: November 2024

A broadband 28 nm complementary metal–oxide–semiconductor (CMOS) power amplifier was implemented using a distributed amplification design. To develop a model library for high-frequency design, various test patterns for active and passive elements were fabricated and compared through measurements. As a result, a symmetrical n-channel field-effect transistor (NFET) was used as the active device, and a co-planar waveguide (CPW) with floating bottom metal layers was chosen as the transmission line for the passive element. These choices demonstrated superior radio frequency (RF) characteristics at high frequencies compared to other device candidates. Furthermore, to address the low breakdown voltage of CMOS, a triple-stacked FET structure was designed as the gain cell of the distributed power amplifier (DPA). The fabricated DPA showed a maximum small-signal gain of 22 dB and a minimum of 10 dB from DC to 56 GHz, with a maximum saturated output power of 20 dBm and a minimum of 13 dBm from 1 to 39 GHz. Notably, these results were achieved on the first attempt by designing solely based on measurement data from the test patterns.
Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon
Authors: Ponis Emanuele , Cacciatore Federica , Bernarello Valentina , Boscolo Brusà Rossella , Novello Marta , Sfriso Adriano , Strazzabosco Fabio , Cornello Michele , Bonometto Andrea
Published: November 2024

The Transitional Water Eutrophication Assessment Method (TWEAM) is a multi-index set up for assessing the eutrophication risk and trend in transitional waters. It includes a selection of environmental variables, an ecological status indicator (i.e., Macrophyte Quality Index, MaQI) and the Transitional Water Quality Index (TWQI). Possible outcomes of the TWEAM include three trophic classes in terms of eutrophication risk: (i) eutrophic; (ii) non-eutrophic; (iii) mesotrophic. The method was applied on data collected at 28 stations in the Venice Lagoon over four triennial monitoring cycles (MC I-IV) in the period 2011–2022. The spatial variability and medium-term trend of eutrophication risk were investigated, highlighting a general improvement in trophic conditions over time, with a decrease in mesotrophic stations (representing 46% of total in MC-I and 25% in MC-IV) in favor of non-eutrophic stations (46% of total in MC-I and 73% in MC-IV). The main driver of observed positive changes is related to the colonization of sensitive macroalgae and aquatic angiosperms, resulting in an increase in the percentage of stations with MaQI in good/high ecological status from 25% in MC-I to 54% in MC-IV. Eutrophic sites showed a non-linear trend, particularly in choked areas of the central lagoon, with anthropogenic disturbances and low water renewal.