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15 pages, 2172 KiB

Open AccessArticle

Characterization of Peptide Profiles and the Hypoallergenic and High Antioxidant Activity of Whey Protein Hydrolysate Prepared Using Different Hydrolysis Modes

by Qiang Cui, Yuting Li, Tingli Li, Jie Yu, Guanghui Shen, Xiaomeng Sun, Man Zhou and Zhiqing Zhang

Foods 2024, 13(18), 2978; https://doi.org/10.3390/foods13182978 (registering DOI) - 20 Sep 2024

Abstract

Food proteins and peptides are generally considered a source of dietary antioxidants. The aim of this study was to investigate the antioxidant activity, allergenicity, and peptide profiles of whey protein hydrolysates (WPHs) using different hydrolysis methods. The results demonstrated that the degrees of [...] Read more.

Food proteins and peptides are generally considered a source of dietary antioxidants. The aim of this study was to investigate the antioxidant activity, allergenicity, and peptide profiles of whey protein hydrolysates (WPHs) using different hydrolysis methods. The results demonstrated that the degrees of hydrolysis of the hydrolysates with one-step (O-AD) and two-step (T-AD) methods reached 16.25% and 17.64%, respectively. The size exclusion chromatography results showed that the O-AD had a higher content of >5 and <0.3 kDa, and the distribution of peptide profiles for the two hydrolysates was significantly different. Furthermore, 5 bioactive peptides and 15 allergenic peptides were identified using peptidomics. The peptide profiles and the composition of the master proteins of the O-AD and T-AD were different. The DPPH and ABTS radical scavenging abilities of WPHs were measured, and hydrolysates were found to exhibit a strong radical scavenging ability after being treated using different hydrolysis methods. An enzyme-linked immunosorbent assay showed that the sensitization of WPHs was significantly reduced. This study may provide useful information regarding the antioxidant properties and allergenicity of WPHs. Full article

(This article belongs to the Special Issue Novel Processing and Quality Assurance of Milk and Milk Products)

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9 pages, 1656 KiB

Open AccessArticle

Graphene-Based Dual-Band Metasurface Absorber with High Frequency Ratio

by Anjie Cao, Nengfu Chen, Weiren Zhu and Zhansheng Chen

Nanomaterials 2024, 14(18), 1522; https://doi.org/10.3390/nano14181522 (registering DOI) - 20 Sep 2024

Abstract

In this paper, we propose a novel dual-band metasurface absorber with a high frequency ratio based on graphene. By carefully designing a centrally symmetrical graphene pattern and positioning it on a glass medium, while utilizing ITO as a ground, the metasurface absorber achieves [...] Read more.

In this paper, we propose a novel dual-band metasurface absorber with a high frequency ratio based on graphene. By carefully designing a centrally symmetrical graphene pattern and positioning it on a glass medium, while utilizing ITO as a ground, the metasurface absorber achieves remarkable high frequency ratio microwave absorption. Specifically, this metasurface absorber exhibits two distinct resonance points at 3.7 GHz and 14 GHz, with an impressive frequency ratio over 3.5. It achieves over 90% absorption efficiency in the frequency ranges of 3.5–4.5 GHz and 13.5–14.5 GHz, highlighting its capability to effectively absorb microwaves across widely spaced frequency bands. Furthermore, the metasurface absorber demonstrates optical transparency and polarization insensitivity, adding to its versatility and potential applications. The measured results of the fabricated prototype validate its design and potential for practical use. Full article

(This article belongs to the Special Issue Metamaterials and Metasurfaces for Advanced Electromagnetic Wave Manipulation and Applications)

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19 pages, 3474 KiB

Open AccessArticle

Development of an Agent-Based Model to Evaluate Rural Public Policies in Medellín, Colombia

by Julian Andres Castillo Grisales, Yony Fernando Ceballos, Lina María Bastidas-Orrego, Natalia Isabel Jaramillo Gómez and Elizabeth Chaparro Cañola

Sustainability 2024, 16(18), 8185; https://doi.org/10.3390/su16188185 (registering DOI) - 20 Sep 2024

Abstract

Rural areas near large cities do not satisfy the food needs of the city’s population. In Medellín, Colombia, these areas satisfy only 2% of the city’s food needs, highlighting an urgent need to review and improve policies supporting agriculture. This study was conducted [...] Read more.

Rural areas near large cities do not satisfy the food needs of the city’s population. In Medellín, Colombia, these areas satisfy only 2% of the city’s food needs, highlighting an urgent need to review and improve policies supporting agriculture. This study was conducted over a ten-year period since the release of the Medellín policy related to land use. The model uses agent-based modelling, geographic analysis and dichotomous variables, combining these structures to create a decision-making element and thus identify changes to examine in relation to current land use and detect properties with a potential for conversion to agricultural use. By evaluating post-processed geographic layers, land use in agricultural rural environments is prioritized, setting up clusters of homogeneous zones and finding new areas of rural influence. The implications of this study extend beyond Medellín, offering a model that can be applied to other regions facing similar challenges in agricultural productivity and land use. This research supports informed and effective decision-making in agricultural policy, contributing to improved food security and sustainable development. The results show that some properties are susceptible to policy changes and provide a framework for the revision of local regulations, serving as a support tool for decision-making in rural public policies by giving the local administration key factors to update in the current policies. The findings are relevant to local stakeholders, including policymakers and rural landowners, suggesting that several properties are susceptible to policy changes promoting agriculture and supporting informed decision-making in agricultural policy, contributing to food security and sustainable development. Also, this approach promotes efficient and sustainable agriculture, highlighting the importance of geographic analysis and agent-based modelling in policy planning and evaluation. Full article

(This article belongs to the Section Sustainable Urban and Rural Development)

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13 pages, 2343 KiB

Open AccessArticle

Collagen I Increases Palmitate-Induced Lipotoxicity in HepG2 Cells via Integrin-Mediated Death

by Tumisang Edward Maseko, Eva Peterová, Moustafa Elkalaf, Darja Koutová, Jan Melek, Pavla Staňková, Veronika Špalková, Reem Matar, Halka Lotková, Zuzana Červinková and Otto Kučera

Biomolecules 2024, 14(9), 1179; https://doi.org/10.3390/biom14091179 (registering DOI) - 20 Sep 2024

Abstract

Various strategies have been employed to improve the reliability of 2D, 3D, and co-culture in vitro models of nonalcoholic fatty liver disease, including using extracellular matrix proteins such as collagen I to promote cell adhesion. While studies have demonstrated the significant benefits of [...] Read more.

Various strategies have been employed to improve the reliability of 2D, 3D, and co-culture in vitro models of nonalcoholic fatty liver disease, including using extracellular matrix proteins such as collagen I to promote cell adhesion. While studies have demonstrated the significant benefits of culturing cells on collagen I, its effects on the HepG2 cell line after exposure to palmitate (PA) have not been investigated. Therefore, this study aimed to assess the effects of PA-induced lipotoxicity in HepG2 cultured in the absence or presence of collagen I. HepG2 cultured in the absence or presence of collagen I was exposed to PA, followed by analyses that assessed cell proliferation, viability, adhesion, cell death, mitochondrial respiration, reactive oxygen species production, gene and protein expression, and triacylglycerol accumulation. Culturing HepG2 on collagen I was associated with increased cell proliferation, adhesion, and expression of integrin receptors, and improved cellular spreading compared to culturing them in the absence of collagen I. However, PA-induced lipotoxicity was greater in collagen I-cultured HepG2 than in those cultured in the absence of collagen I and was associated with increased α2β1 receptors. In summary, the present study demonstrated for the first time that collagen I-cultured HepG2 exhibited exacerbated cell death following exposure to PA through integrin-mediated death. The findings from this study may serve as a caution to those using 2D models or 3D scaffold-based models of HepG2 in the presence of collagen I. Full article

(This article belongs to the Special Issue New Insights into Integrins)

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14 pages, 8735 KiB

Open AccessArticle

Knowledge Graph Construction Method for Commercial Aircraft Fault Diagnosis Based on Logic Diagram Model

by Huanchun Peng and Weidong Yang

Aerospace 2024, 11(9), 773; https://doi.org/10.3390/aerospace11090773 (registering DOI) - 20 Sep 2024

Abstract

Commercial aircraft fault diagnosis is an important means to ensure the reliability and safety of commercial aircraft. Traditional knowledge-driven and data-driven fault diagnosis methods lack interpretability in engineering mechanisms, making them difficult to promote and apply. To address the issue of lack of [...] Read more.

Commercial aircraft fault diagnosis is an important means to ensure the reliability and safety of commercial aircraft. Traditional knowledge-driven and data-driven fault diagnosis methods lack interpretability in engineering mechanisms, making them difficult to promote and apply. To address the issue of lack of interpretability, this paper conducts a fault knowledge graph for commercial aircraft fault diagnosis, using the fault logic in the logic diagram to increase the interpretability of diagnostic work. Firstly, to avoid the inefficiency of logic diagram applications, an executable logic diagram model is established, which can perform mathematical analysis and achieve fault diagnosis and localization using operational data as input. Then, the logic diagram is sorted out to obtain the hidden fault knowledge in the logic diagram, which is used to construct a fault knowledge graph to help achieve cause localization and rapid troubleshooting. The methods proposed in this paper are all validated through case studies of abnormal low-pressure faults in domestic commercial aircraft hydraulic systems. The results show that the logic diagram model can perform model simulation and fault diagnosis based on operational data, and the fault knowledge graph can quickly locate abnormal monitoring parameters and guide troubleshooting work based on existing information. Full article

(This article belongs to the Special Issue State Monitoring and Health Management of Complex Equipment (2nd Edition))

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16 pages, 11167 KiB

Open AccessArticle

AbFTNet: An Efficient Transformer Network with Alignment before Fusion for Multimodal Automatic Modulation Recognition

by Meng Ning, Fan Zhou, Wei Wang, Shaoqiang Wang, Peiying Zhang and Jian Wang

Electronics 2024, 13(18), 3725; https://doi.org/10.3390/electronics13183725 (registering DOI) - 20 Sep 2024

Abstract

Multimodal automatic modulation recognition (MAMR) has emerged as a prominent research area. The effective fusion of features from different modalities is crucial for MAMR tasks. An effective multimodal fusion mechanism should maximize the extraction and integration of complementary information. Recently, fusion methods based [...] Read more.

Multimodal automatic modulation recognition (MAMR) has emerged as a prominent research area. The effective fusion of features from different modalities is crucial for MAMR tasks. An effective multimodal fusion mechanism should maximize the extraction and integration of complementary information. Recently, fusion methods based on cross-modal attention have shown high performance. However, they overlook the differences in information intensity between different modalities, suffering from quadratic complexity. To this end, we propose an efficient Alignment before Fusion Transformer Network (AbFTNet) based on an in-phase quadrature (I/Q) and Fractional Fourier Transform (FRFT). Specifically, we first align and correlate the feature representations of different single modalities to achieve mutual information maximization. The single modality feature representations are obtained using the self-attention mechanism of the Transformer. Then, we design an efficient cross-modal aggregation promoting (CAP) module. By designing the aggregation center, we integrate two modalities to achieve the adaptive complementary learning of modal features. This operation bridges the gap in information intensity between different modalities, enabling fair interaction. To verify the effectiveness of the proposed methods, we conduct experiments on the RML2016.10a dataset. The experimental results show that multimodal fusion features significantly outperform single-modal features in classification accuracy across different signal-to-noise ratios (SNRs). Compared to other methods, AbFTNet achieves an average accuracy of 64.59%, with a 1.36% improvement over the TLDNN method, reaching the state of the art. Full article

(This article belongs to the Topic Advances in Integrative AI, Machine Learning, and Big Data for Transformative Applications)

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9 pages, 446 KiB

Open AccessArticle

Perfectionism and Emotion Regulation in the Study of Suicidal Ideation in Portuguese Young Adults

by Marta Brás, João Antunes, Ana Reis and Cláudia Carmo

Behav. Sci. 2024, 14(9), 846; https://doi.org/10.3390/bs14090846 (registering DOI) - 20 Sep 2024

Abstract

Suicide is a serious public health problem worldwide, being the culmination of a process that normally begins with suicidal ideation. Therefore, it is important to assess suicidal ideation and know its risk factors. The association between perfectionism and suicidal ideation has been widely [...] Read more.

Suicide is a serious public health problem worldwide, being the culmination of a process that normally begins with suicidal ideation. Therefore, it is important to assess suicidal ideation and know its risk factors. The association between perfectionism and suicidal ideation has been widely debated in the literature. However, knowledge about the role of emotion regulation in this relationship is scarce. The main objective of this investigation was thus to study the role of emotion regulation in the relationship between perfectionism and suicidal ideation in young adults. A sample of 224 Portuguese young adults was recruited through an online form which assessed suicidal ideation, perfectionism, and emotion regulation. The results showed a positive relationship between suicidal ideation and emotion regulation difficulties. There was also a positive association between emotion regulation difficulties and perfectionism, especially regarding the strategies and dimensions of maladaptive perfectionism. The relationship between perfectionism and suicidal ideation was fully mediated by emotion regulation difficulties. Increases in emotion regulation difficulties from increased perfectionism could contribute decisively to increasing the risk of suicidal ideation. Thus, the assessment of perfectionism and emotion regulation difficulties can promote the prevention and psychological interventions for suicidal behavior. Full article

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16 pages, 506 KiB

Open AccessReview

Chemerin in the Spotlight: Revealing Its Multifaceted Role in Acute Myocardial Infarction

by Andreas Mitsis, Elina Khattab, Michael Myrianthefs, Stergios Tzikas, Nikolaos P. E. Kadoglou, Nikolaos Fragakis, Antonios Ziakas and George Kassimis

Biomedicines 2024, 12(9), 2133; https://doi.org/10.3390/biomedicines12092133 (registering DOI) - 20 Sep 2024

Abstract

Chemerin, an adipokine known for its role in adipogenesis and inflammation, has emerged as a significant biomarker in cardiovascular diseases, including acute myocardial infarction (AMI). Recent studies have highlighted chemerin’s involvement in the pathophysiological processes of coronary artery disease (CAD), where it modulates [...] Read more.

Chemerin, an adipokine known for its role in adipogenesis and inflammation, has emerged as a significant biomarker in cardiovascular diseases, including acute myocardial infarction (AMI). Recent studies have highlighted chemerin’s involvement in the pathophysiological processes of coronary artery disease (CAD), where it modulates inflammatory responses, endothelial function, and vascular remodelling. Elevated levels of chemerin have been associated with adverse cardiovascular outcomes, including increased myocardial injury, left ventricular dysfunction, and heightened inflammatory states post-AMI. This manuscript aims to provide a comprehensive review of the current understanding of chemerin’s role in AMI, detailing its molecular mechanisms, clinical implications, and potential as a biomarker for diagnosis and prognosis. Additionally, we explore the therapeutic prospects of targeting chemerin pathways to mitigate myocardial damage and improve clinical outcomes in AMI patients. By synthesizing the latest research findings, this review seeks to elucidate the multifaceted role of chemerin in AMI and its promise as a target for innovative therapeutic strategies. Full article

(This article belongs to the Special Issue The Role of Chemerin in Human Disease—2nd Edition)

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12 pages, 595 KiB

Open AccessReview

RNAi-Induced Gene Silencing against Chikungunya and COVID-19: What Have We Learned So Far, and What Is the Way Forward?

by Kingshuk Panda, Kalichamy Alagarasu, Rajarshee Tagore, Mandar Paingankar, Satyendra Kumar, Manish Kumar Jeengar, Sarah Cherian and Deepti Parashar

Viruses 2024, 16(9), 1489; https://doi.org/10.3390/v16091489 (registering DOI) - 20 Sep 2024

Abstract

RNA interference (RNAi) is a process in which small RNA molecules (such as small interfering RNAs or siRNAs) bind to specific messenger RNAs (mRNAs), leading to its degradation and inhibition of protein synthesis. Our studies have shown that RNAi can effectively silence genes [...] Read more.

RNA interference (RNAi) is a process in which small RNA molecules (such as small interfering RNAs or siRNAs) bind to specific messenger RNAs (mRNAs), leading to its degradation and inhibition of protein synthesis. Our studies have shown that RNAi can effectively silence genes involved in the replication of the Chikungunya virus (CHIKV) in cells. However, these investigations were performed only in laboratory settings and have yet to be tested in human clinical trials. Researchers need to conduct more research to determine the safety and efficacy of RNAi-based therapies as a therapeutic agent to treat viral infections. In this review, the history of evolution of siRNA as an inhibitor of protein synthesis, along with its current developments, is discussed based on our experience. Moreover, this review examines the hurdles and future implications associated with siRNA based therapeutic approaches. Full article

(This article belongs to the Section Human Virology and Viral Diseases)

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31 pages, 1674 KiB

Open AccessArticle

Protection of Personal Data in the Context of E-Commerce

by Zlatan Morić, Vedran Dakic, Daniela Djekic and Damir Regvart

J. Cybersecur. Priv. 2024, 4(3), 731-761; https://doi.org/10.3390/jcp4030034 (registering DOI) - 20 Sep 2024

Abstract

This paper examines the impact of stringent regulations on personal data protection on customer perception of data security and online shopping behavior. In the context of the rapidly expanding e-commerce landscape, ensuring the security of personal data is a complex and crucial task. [...] Read more.

This paper examines the impact of stringent regulations on personal data protection on customer perception of data security and online shopping behavior. In the context of the rapidly expanding e-commerce landscape, ensuring the security of personal data is a complex and crucial task. The study of several legal frameworks, including Malaysia’s compliance with EU regulations and Indonesia’s Personal Data Protection Law, provides valuable insights into consumer data protection. The challenges of balancing data safeguarding and unrestricted movement and tackling misuse by external entities are significant and require careful consideration. This research elucidates the pivotal role of trust in e-commerce environments and the deployment of innovative e-commerce models designed to minimize personal data sharing. By integrating advanced privacy-enhancing technologies and adhering to stringent regulatory standards such as the GDPR, this study demonstrates effective strategies for robust data protection. The paper contributes to the academic discourse by providing a comprehensive framework that synergizes legal, technological, and procedural elements to fortify data security and enhance consumer trust in digital marketplaces. This approach aligns with international data protection standards and offers a pragmatic blueprint for achieving sustainable data security in e-commerce. Full article

(This article belongs to the Special Issue Data Protection and Privacy)

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25 pages, 3047 KiB

Open AccessArticle

Hierarchical Dynamic Spatio-Temporal Graph Convolutional Networks with Self-Supervised Learning for Traffic Flow Forecasting

by Siwei Wei, Yanan Song, Donghua Liu, Sichen Shen, Rong Gao and Chunzhi Wang

Inventions 2024, 9(5), 102; https://doi.org/10.3390/inventions9050102 (registering DOI) - 20 Sep 2024

Abstract

It is crucial for both traffic management organisations and individual commuters to be able to forecast traffic flows accurately. Graph neural networks made great strides in this field owing to their exceptional capacity to capture spatial correlations. However, existing approaches predominantly focus on [...] Read more.

It is crucial for both traffic management organisations and individual commuters to be able to forecast traffic flows accurately. Graph neural networks made great strides in this field owing to their exceptional capacity to capture spatial correlations. However, existing approaches predominantly focus on local geographic correlations, ignoring cross-region interdependencies in a global context, which is insufficient to extract comprehensive semantic relationships, thereby limiting prediction accuracy. Additionally, most GCN-based models rely on pre-defined graphs and unchanging adjacency matrices to reflect the spatial relationships among node features, neglecting the dynamics of spatio-temporal features and leading to challenges in capturing the complexity and dynamic spatial dependencies in traffic data. To tackle these issues, this paper puts forward a fresh approach: a new self-supervised dynamic spatio-temporal graph convolutional network (SDSC) for traffic flow forecasting. The proposed SDSC model is a hierarchically structured graph–neural architecture that is intended to augment the representation of dynamic traffic patterns through a self-supervised learning paradigm. Specifically, a dynamic graph is created using a combination of temporal, spatial, and traffic data; then, a regional graph is constructed based on geographic correlation using clustering to capture cross-regional interdependencies. In the feature learning module, spatio-temporal correlations in traffic data are subjected to recursive extraction using dynamic graph convolution facilitated by Recurrent Neural Networks (RNNs). Furthermore, self-supervised learning is embedded within the network training process as an auxiliary task, with the objective of enhancing the prediction task by optimising the mutual information of the learned features across the two graph networks. The superior performance of the proposed SDSC model in comparison with SOTA approaches was confirmed by comprehensive experiments conducted on real road datasets, PeMSD4 and PeMSD8. These findings validate the efficacy of dynamic graph modelling and self-supervision tasks in improving the precision of traffic flow prediction. Full article

(This article belongs to the Special Issue Advanced Technologies and Artificial Intelligence for Sustainable and Intelligent Transportation Systems)

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16 pages, 6912 KiB

Open AccessArticle

Enhanced Photoelectrochemical Water Splitting Performance of Ce-Doped TiO₂ Nanorod Array Photoanodes for Efficient Hydrogen Production

by Bi-Li Lin, Rui Chen, Mei-Ling Zhu, Ao-Sheng She, Wen Chen, Bai-Tong Niu, Yan-Xin Chen and Xiu-Mei Lin

Catalysts 2024, 14(9), 639; https://doi.org/10.3390/catal14090639 (registering DOI) - 20 Sep 2024

Abstract

In this study, original titanium dioxide (TiO₂) and cerium (Ce)-doped TiO₂ nanorod array photoanodes are prepared by hydrothermal method combined with high-temperature annealing, and their morphology, photoelectrochemical properties, and photocatalytic hydrogen production ability are systematically evaluated. X-ray diffraction (XRD) analysis [...] Read more.

In this study, original titanium dioxide (TiO₂) and cerium (Ce)-doped TiO₂ nanorod array photoanodes are prepared by hydrothermal method combined with high-temperature annealing, and their morphology, photoelectrochemical properties, and photocatalytic hydrogen production ability are systematically evaluated. X-ray diffraction (XRD) analysis shows that as the Ce content increases, the diffraction peak of the rutile phase (110) shifts towards lower angles, indicating the successful doping of different contents of Ce into the TiO₂ lattice. Photoelectric performance test results show that Ce doping significantly improves the photocurrent density of TiO₂, especially for the 0.54wt% Ce-doped TiO₂ (denoted as CR5). The photocurrent density of CR5 reaches 1.98 mA/cm² at a bias voltage of 1.23 V (relative to RHE), which is 2.6 times that of undoped TiO₂ (denoted as R). Photoelectrochemical hydrolysis test results show that the hydrogen yield performance under full-spectrum testing conditions of Ce-doped TiO₂ photoanodes is better than that of original TiO₂ as well, which are 37.03 and 12.64 µmol·cm⁻²·h⁻¹ for CR5 and R, respectively. These results indicate that Ce doping can effectively promote charge separation and improve hydrogen production efficiency by reducing resistance, accelerating charge transfer, and introducing new electronic energy levels. Our findings provide a new strategy for designing efficient photocatalysts with enhanced photoelectrochemical (PEC) water-splitting performance. Full article

(This article belongs to the Section Photocatalysis)

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Graphical abstract

17 pages, 5564 KiB

Open AccessArticle

Modeling for Apple-Slice Drying in Carbon Dioxide Gas

by Tien Cong Do, Quoc Tuan Le and Thi Thu Hang Tran

Agriculture 2024, 14(9), 1642; https://doi.org/10.3390/agriculture14091642 (registering DOI) - 19 Sep 2024

Abstract

In this study, a numerical model of a modified air-drying process of apple slices that considers the conjugate heat and mass transfer in the drying chamber is developed. Inside the apple slice sample, the continuum model is incorporated to describe the non-isothermal two-phase [...] Read more.

In this study, a numerical model of a modified air-drying process of apple slices that considers the conjugate heat and mass transfer in the drying chamber is developed. Inside the apple slice sample, the continuum model is incorporated to describe the non-isothermal two-phase transport. The intra- and extra-sample heat, mass, and momentum transfer are coupled to simulate the transportation phenomena inside the drying chamber using the finite volume method implemented in computational fluid dynamic software (COMSOL Multiphysics 6.0). In this manner, temperature, velocity, moisture content of the drying agent inside the chamber, sample temperature, and moisture content distributions can be predicted. The validity of the proposed model is confirmed by a good agreement between the numerical and experimental data in terms of the overall evaporation rate and temperature. The simulation results indicate that the maldistribution of the convective heat and mass transfer resistance on the sample surface is significant. This can be explained by the nonuniform velocity distribution inside the drying chamber. Additionally, both experimental and numerical observations show that the drying process can be divided into two periods: the quasi-constant drying rate and falling drying rate periods. The impact of dryer operational conditions on the drying process is numerically investigated. Full article

(This article belongs to the Section Agricultural Product Quality and Safety)

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14 pages, 1585 KiB

Open AccessArticle

TAFENet: A Two-Stage Attention-Based Feature-Enhancement Network for Strip Steel Surface Defect Detection

by Li Zhang, Zhipeng Fu, Huaping Guo, Yan Feng, Yange Sun and Zuofei Wang

Electronics 2024, 13(18), 3721; https://doi.org/10.3390/electronics13183721 (registering DOI) - 19 Sep 2024

Abstract

Strip steel serves as a crucial raw material in numerous industries, including aircraft and automobile manufacturing. Surface defects in strip steel can degrade the performance, quality, and appearance of industrial steel products. Detecting surface defects in steel strip products is challenging due to [...] Read more.

Strip steel serves as a crucial raw material in numerous industries, including aircraft and automobile manufacturing. Surface defects in strip steel can degrade the performance, quality, and appearance of industrial steel products. Detecting surface defects in steel strip products is challenging due to the low contrast between defects and background, small defect targets, as well as significant variations in defect sizes. To address these challenges, a two-stage attention-based feature-enhancement network (TAFENet) is proposed, wherein the first-stage feature-enhancement procedure utilizes an attentional convolutional fusion module with convolution to combine all four-level features and then strengthens the features of different levels via a residual spatial-channel attention connection module (RSC). The second-stage feature-enhancement procedure combines three-level features using an attentional self-attention fusion module and then strengthens the features using a RSC attention module. Experiments on the NEU-DET and GC10-DET datasets demonstrated that the proposed method significantly improved detection accuracy, thereby confirming the effectiveness and generalization capability of the proposed method. Full article

(This article belongs to the Special Issue Enhancing Efficiency and Driving Innovation in the Semiconductor Industry through Artificial Intelligence Applications)

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18 pages, 2206 KiB

Open AccessArticle

Simultaneous Instance and Attribute Selection for Noise Filtering

by Yenny Villuendas-Rey, Claudia C. Tusell-Rey and Oscar Camacho-Nieto

Appl. Sci. 2024, 14(18), 8459; https://doi.org/10.3390/app14188459 (registering DOI) - 19 Sep 2024

Abstract

The existence of noise is inherent to most real data that are collected. Removing or reducing noise can help classification algorithms focus on relevant patterns, preventing them from being affected by irrelevant or incorrect information. This can result in more accurate and reliable [...] Read more.

The existence of noise is inherent to most real data that are collected. Removing or reducing noise can help classification algorithms focus on relevant patterns, preventing them from being affected by irrelevant or incorrect information. This can result in more accurate and reliable models, improving their ability to generalize and make accurate predictions on new data. For example, among the main disadvantages of the nearest neighbor classifier are its noise sensitivity and its high computational cost (for classification and storage). Thus, noise filtering is essential to ensure data quality and the effectiveness of supervised classification models. The simultaneous selection of attributes and instances for supervised classifiers was introduced in the last decade. However, the proposed solutions present several drawbacks because some are either stochastic or do not handle noisy domains, and the neighborhood selection of some algorithms allows very dissimilar objects to be considered as neighbors. In addition, the design of some methods is just for specific classifiers without generalization possibilities. This article introduces an instance and attribute selection model, which seeks to detect and eliminate existing noise while reducing the feature space. In addition, the proposal is deterministic and does not predefine any supervised classifier. The experiments allow us to establish the viability of the proposal and its effectiveness in eliminating noise. Full article

(This article belongs to the Special Issue Applied and Innovative Computational Intelligence Systems: 3rd Edition)

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16 pages, 6522 KiB

Open AccessArticle

Experiment and Analysis of Physical Properties of Sweet Potato Varieties at Different Harvesting Periods

by Jiwen Peng, Haiyang Shen, Gongpu Wang, Zhilong Zhang, Baoliang Peng, Guangyu Xue, Sen Huang, Wenhao Zheng and Lianglong Hu

Agriculture 2024, 14(9), 1641; https://doi.org/10.3390/agriculture14091641 (registering DOI) - 19 Sep 2024

Abstract

To fill the research gap in the mechanical and physical properties of different varieties of sweet potatoes at different points in the harvest period and to provide a theoretical basis for the design of key components of the sweet potato harvester, the physical [...] Read more.

To fill the research gap in the mechanical and physical properties of different varieties of sweet potatoes at different points in the harvest period and to provide a theoretical basis for the design of key components of the sweet potato harvester, the physical properties of Su-Shu 16, Su-Shu 36, and Ning-Zi 4 during the harvest period were studied at three time points: 15 October, 25 October, and 4 November 2023. The moisture content of sweet potatoes was determined using the DGF30/7-IA electric hot air-drying oven. The results showed that the moisture content of sweet potatoes decreased with increasing growth time at three different time points during the harvest period. The moisture content of Su-Shu 16 was, on average, 12.74% higher than that of Su-Shu 36, while the moisture content of Ning-Zi 4 was, on average, 8.07% higher than that of Su-Shu 36. The density of Su-Shu 36 measured by the drainage method is greater than that of Su-Shu 16 and Ning-Zi 4, but the difference is relatively small, and the density tends to decrease slowly with the increase of growth time. Using an electronic universal testing machine, compression tests were conducted on Su-Shu 16, Su-Shu 36, and Ning-Zi 4 at loading speeds of 5 mm/min and 10 mm/min, respectively. The results showed that the compressive strength limit range of Su-Shu 36 was slightly higher than that of Su-Shu 16 and significantly higher than that of Ning-Zi 4. The Poisson’s ratio, elastic modulus, and shear modulus values of Su-Shu 16 and Su-Shu 36 were similar and much higher than those of Ning-Zi 4. Studying sweet potatoes’ growth and physical characteristics for different purposes can provide data references for the design of digging depth, working width, and conveyor chain gap of sweet potato harvesters, as well as data references for sweet potato simulation experiments. Full article

(This article belongs to the Special Issue From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation)

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7 pages, 2081 KiB

Open AccessCommunication

Improving the Performance of Bidirectional Communication System Using Second-Order Raman Amplifiers

by Zhongshuai Feng, Peili He, Wei Li, Kaijing Hu, Fei Tong and Xingrui Su

Photonics 2024, 11(9), 879; https://doi.org/10.3390/photonics11090879 (registering DOI) - 19 Sep 2024

Abstract

In order to achieve low-cost scalability, the same-wavelength bidirectional (SWB) fiber communication system is a better solution. We present a detailed investigation of the performance of the different orders Raman amplifiers in same-wavelength bidirectional fiber communication systems. We discuss how to suppress the [...] Read more.

In order to achieve low-cost scalability, the same-wavelength bidirectional (SWB) fiber communication system is a better solution. We present a detailed investigation of the performance of the different orders Raman amplifiers in same-wavelength bidirectional fiber communication systems. We discuss how to suppress the main factor affecting system performance which is Rayleigh scattering noise (RSN). By using different Raman amplifiers to construct different quasi-lossless transmission, the performance changes in the same-wavelength bidirectional fiber optic communication system were studied. On this basis, multi-channel and same-wavelength single fiber bidirectional system experiments were conducted to compare the performance of second-order Raman systems and first-order Raman systems. The results indicate that the Rayleigh scattering suppression effect of second-order Raman systems is better, and compared to first-order Raman systems, the average signal-to-noise ratio (SNR) can be increased by 2.88 dB. Full article

(This article belongs to the Special Issue Advancements in Optical Sensing and Communication Technologies)

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16 pages, 426 KiB

Open AccessArticle

Honey as a Sugar Substitute in Gluten-Free Bread Production

by Michela Cannas, Costantino Fadda, Pietro Paolo Urgeghe, Antonio Piga and Paola Conte

Foods 2024, 13(18), 2973; https://doi.org/10.3390/foods13182973 (registering DOI) - 19 Sep 2024

Abstract

In recent years, there has been a significant focus on enhancing the overall quality of gluten-free breads by incorporating natural and healthy compounds to meet consumer expectations regarding texture, flavor, and nutritional value. Considering the high glycemic index associated with gluten-free products, the [...] Read more.

In recent years, there has been a significant focus on enhancing the overall quality of gluten-free breads by incorporating natural and healthy compounds to meet consumer expectations regarding texture, flavor, and nutritional value. Considering the high glycemic index associated with gluten-free products, the use of honey, renowned for its numerous health benefits, may serve as an optimal alternative to sucrose. This study investigates the impact of substituting sucrose, either partially (50%) or entirely (100%), with five Sardinian honeys (commercial multifloral honey, cardoon, eucalyptus, and strawberry tree unifloral honeys, and eucalyptus honeydew honey), on the rheological properties of the doughs and the physico-chemical and technological properties of the resulting gluten-free breads. The results demonstrated that an optimal balance was achieved between the leavening and viscoelastic properties of the doughs and the physical and textural attributes of the resulting breads in gluten-free samples prepared with a partial substitution of cardoon and multifloral honeys. Conversely, the least favorable outcomes were observed in samples prepared with strawberry tree honey and eucalyptus honeydew honey at both substitution levels. Therefore, the different behavior observed among all honey-enriched gluten-free breads was likely attributable to the distinct botanical origins of honey rather than to the substitution percentages employed. Full article

(This article belongs to the Section Food Quality and Safety)

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14 pages, 1185 KiB

Open AccessArticle

After-Ripening and Stratification Improve the Germination of the Cakile maritima Scop. (Brassicaceae) from the Apulia Region, Italy

by Giulia Conversa, Lucia Botticella and Antonio Elia

Agronomy 2024, 14(9), 2127; https://doi.org/10.3390/agronomy14092127 - 19 Sep 2024

Abstract

Understanding seed germination is crucial for refining the propagation techniques of Cakile maritima, a wild halophyte species with significant potential for biosaline agriculture. However, research on seed germination within intact fruits of this species is limited. Four trials were conducted to study [...] Read more.

Understanding seed germination is crucial for refining the propagation techniques of Cakile maritima, a wild halophyte species with significant potential for biosaline agriculture. However, research on seed germination within intact fruits of this species is limited. Four trials were conducted to study the seed germination of a population from the Apulia region. The focus was on seeds that had undergone after-ripening for 3 years (20AR₃) or 2 years (20AR₂) (both collected in 2020), or 1 year (22AR₁) (collected in 2022), and freshly harvested seeds in 2022 (22AR₀) and 2023 (23AR₀). The seeds were either incubated as naked or moist-stratified within intact fruits. A portion of 2022 AR₀ siliques was submerged in saline water before stratification. The naked seeds collected in 2022 and 2020 (22AR₀ and 20AR₂) did not germinate, whereas a portion of the 23AR₀ (67%), 20AR₃, and 22AR₁ (45%, irrespective of after-ripening) lots quickly (T₅₀ = 3.5 days) germinated, underlining a lower dormancy level for seeds harvested or dry stored in 2023. Seed germination in the intact fruits was lower than the naked seeds, confirming the role of the pericarp in inducing seed dormancy. Stratification of the shelled seeds was much more effective in improving the germination time (140 days) and levels in the 23AR₀ (81%), 20AR₃, and 22AR₁ (66%, irrespective of after-ripening) lots than in the 22AR₀ (34%) and 20AR₂ (61%) ones, which required 240 days to germinate. The saline solution imbibition of fruit seems only to delay the occurrence of the maximum emergence. The physiological seed dormancy of this C. maritima population has been proven, which may be variable in depth according to the year of fruit collection, ranging from intermediate to non-deep. Full article

(This article belongs to the Special Issue Agro-Environmental Sustainable Exploitation of Halophyte, Medicinal and Aromatic Species from Marginal Areas)

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4 pages, 155 KiB

Open AccessEditorial

Chemical Sensors for Toxic Chemical Detection

by Marijo Buzuk

Sensors 2024, 24(18), 6072; https://doi.org/10.3390/s24186072 (registering DOI) - 19 Sep 2024

Abstract

Industrialization, modern agriculture, urbanization, and modern lifestyles are expected to have a strong impact on the environment [...] Full article

(This article belongs to the Special Issue Chemical Sensors for Toxic Chemical Detection)

18 pages, 5834 KiB

Open AccessArticle

Hydrogen-Ignited-Methanol Catalytic Co-Combustion of Aromatic Volatile Organic Compounds over PdPt/Al₂O₃ Bimetallic Catalyst

by Sehrish Munsif, Lutf Ullah, Long Cao, Palle Ramana Murthy, Jing-Cai Zhang and Wei-Zhen Li

Catalysts 2024, 14(9), 637; https://doi.org/10.3390/catal14090637 - 19 Sep 2024

Abstract

Electric heating is frequently employed to treat volatile organic compounds (VOCs) through catalytic combustion. However, it is associated with problems such as slow heating, high energy consumption, and low efficiency. This study explores PdPt/Al₂O₃ catalysts for igniting methanol (MeOH) through [...] Read more.

Electric heating is frequently employed to treat volatile organic compounds (VOCs) through catalytic combustion. However, it is associated with problems such as slow heating, high energy consumption, and low efficiency. This study explores PdPt/Al₂O₃ catalysts for igniting methanol (MeOH) through H₂ catalytic combustion, providing internal on-site heating of catalyst active sites. It also investigates VOCs’ abatement using H₂-ignited-MeOH combustion without H₂ and external heating. Bimetallic catalysts enhance activity and reduce thermal aging. Hydrogen gas (H₂) can initiate the MeOH combustion at room temperature with the addition of very small amounts, even below its low explosive limit of 4%. This process optimizes MeOH ignition at approximately 350 °C, even when the concentration of H₂ is as low as 0.01%. This method enhances combustion kinetics, converting MeOH and VOCs into CO₂ and water. Catalytic performance is independent of PdPt nanoparticle sizes in fresh and spent catalysts, represented in XRD and STEM. Using hydrogen as an igniting agent provides a clean, effective method to initiate catalytic reactions, addressing traditional challenges and enhancing VOCs’ decomposition efficiency. Full article

(This article belongs to the Special Issue Effect of the Modification of Catalysts on the Catalytic Performance, 2nd Edition)

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15 pages, 1409 KiB

Open AccessArticle

Exploring the Metabolism of Flubrotizolam, a Potent Thieno-Triazolo Diazepine, Using Human Hepatocytes and High-Resolution Mass Spectrometry

by Prince Sellase Gameli, Johannes Kutzler, Diletta Berardinelli, Jeremy Carlier, Volker Auwärter and Francesco Paolo Busardò

Metabolites 2024, 14(9), 506; https://doi.org/10.3390/metabo14090506 (registering DOI) - 19 Sep 2024

Abstract

Background: The abuse of psychoactive substances presents challenges in clinical and forensic toxicology. The emergence of novel and potent drugs that pose significant health risks, in particular towards frequent abusers and users unaware of the ingredients, further complicates the situation. Designer benzodiazepines have [...] Read more.

Background: The abuse of psychoactive substances presents challenges in clinical and forensic toxicology. The emergence of novel and potent drugs that pose significant health risks, in particular towards frequent abusers and users unaware of the ingredients, further complicates the situation. Designer benzodiazepines have become a fast-growing subgroup of these new psychoactive substances (NPSs), and their overdose may potentially turn fatal, especially when combined with other central nervous system depressants. In 2021, flubrotizolam, a potent thieno-triazolo designer benzodiazepine, emerged on the illicit market, available online as a “research chemical”. The identification of markers of consumption for this designer benzodiazepine is essential in analytical toxicology, especially in clinical and forensic cases. Methods: We therefore aimed to identify biomarkers of flubrotizolam uptake in ten-donor-pooled human hepatocytes, applying liquid chromatography high-resolution mass spectrometry and software-aided data mining supported by in silico prediction tools. Results: Prediction studies resulted in 10 and 13 first- and second-generation metabolites, respectively, mainly transformed through hydroxylation and sulfation, methylation, and glucuronidation reactions. We identified six metabolites after 3 h human hepatocyte incubation: two hydroxylated metabolites (α- and 6-hydroxy-flubrotizolam), two 6-hydroxy-glucuronides, a reduced-hydroxy-N-glucuronide, and an N-glucuronide. Conclusions: We suggest detecting flubrotizolam and its hydroxylated metabolites as markers of consumption after the glucuronide hydrolysis of biological samples. The results are consistent with the in vivo metabolism of brotizolam, a medically used benzodiazepine and a chloro-phenyl analog of flubrotizolam. Full article

(This article belongs to the Special Issue Metabolite Profiling of Novel Psychoactive Substances)

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14 pages, 5069 KiB

Open AccessArticle

Optimizing Vertical Zone Refining for Ultra-High-Purity Tin: Numerical Simulations and Experimental Analyses

by Yu Yao, Jiajun Wen, Qi He, Meizhen Wu, Lishi Chen, Yuxu Bao and Hongxing Zheng

Separations 2024, 11(9), 273; https://doi.org/10.3390/separations11090273 (registering DOI) - 19 Sep 2024

Abstract

This study investigates the application of the vertical zone refining process to produce ultra-high-purity tin. Computational fluid dynamics (CFD) simulations were conducted using an Sn-1 wt.%Bi binary alloy to assess the effects of two key parameters—heater temperature and pulling rate—on Bi impurity segregation. [...] Read more.

This study investigates the application of the vertical zone refining process to produce ultra-high-purity tin. Computational fluid dynamics (CFD) simulations were conducted using an Sn-1 wt.%Bi binary alloy to assess the effects of two key parameters—heater temperature and pulling rate—on Bi impurity segregation. The simulations revealed a dynamic evolution in molten zone height, characterized by an initial rapid rise, followed by a gradual increase and ending with a sharp decline. Despite these fluctuations, the lower solid–liquid interface consistently remained slightly convex. After nine zone passes, impurities accumulated at the top of the sample, with dual vortices forming a rhombus- or gate-shaped negative segregation zone. The simulations demonstrated that lower heater temperatures and slower pulling rates enhanced impurity segregation efficiency. Based on these results, experiments were performed using 6N-grade tin as the starting material. Glow discharge mass spectrometry (GDMS) analysis showed that the effective partition coefficients (k_eff) for impurities such as Ag, Pb, Co, Al, Bi, Cu, Fe, and Ni were significantly less than 1, while As was slightly below but very close to 1, and Sb was above 1. Under optimal conditions—405 °C heater temperature and a pulling rate of 5 μm/s—over 60% of impurities were removed after nine zone passes, approaching 6N9-grade purity. These findings provide valuable insights into optimizing the vertical zone refining process and demonstrate its potential for achieving 7N-grade ultra-high-purity tin. Full article

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25 pages, 1571 KiB

Open AccessArticle

Unfolding Prosody Guides the Development of Word Segmentation

by Sónia Frota, Cátia Severino and Marina Vigário

Languages 2024, 9(9), 305; https://doi.org/10.3390/languages9090305 - 19 Sep 2024

Abstract

Prosody is known to scaffold the learning of language, and thus understanding prosodic development is vital for language acquisition. The present study explored the unfolding prosody model of prosodic development (proposed in Frota’s et al. study in 2016) beyond early production data, to [...] Read more.

Prosody is known to scaffold the learning of language, and thus understanding prosodic development is vital for language acquisition. The present study explored the unfolding prosody model of prosodic development (proposed in Frota’s et al. study in 2016) beyond early production data, to examine whether it predicted the development of early segmentation abilities. European Portuguese-learning infants aged between 5 and 17 months were tested in a series of word segmentation experiments. Developing prosodic structure was evidenced in word segmentation as proposed by the unfolding model: (i) a simple monosyllabic word shape crucially placed at a major prosodic edge was segmented first, before more complex word shapes under similar prosodic conditions; (ii) the segmentation of more complex words was easier at a major prosodic edge than in phrase-medial position; and (iii) the segmentation of complex words with an iambic pattern preceded the segmentation of words with a trochaic pattern. These findings demonstrated that word segmentation evolved with unfolding prosody, suggesting that the prosodic units developed in the unfolding process are used both as speech production planning units and to extract word-forms from continuous speech. Therefore, our study contributes to a better understanding of the mechanisms underlying word segmentation, and to a better understanding of early prosodic development, a cornerstone of language acquisition. Full article

(This article belongs to the Special Issue Phonetic and Phonological Complexity in Romance Languages)

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