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20 pages, 6402 KiB

Open AccessArticle

PGNN-Net: Parallel Graph Neural Networks for Hyperspectral Image Classification Using Multiple Spatial-Spectral Features

by Ningbo Guo, Mingyong Jiang, Decheng Wang, Yutong Jia, Kaitao Li, Yanan Zhang, Mingdong Wang and Jiancheng Luo

Remote Sens. 2024, 16(18), 3531; https://doi.org/10.3390/rs16183531 (registering DOI) - 23 Sep 2024

Abstract

Hyperspectral image (HSI) shows great potential for application in remote sensing due to its rich spectral information and fine spatial resolution. However, the high dimensionality, nonlinearity, and complex relationship between spectral and spatial features of HSI pose challenges to its accurate classification. Traditional [...] Read more.

Hyperspectral image (HSI) shows great potential for application in remote sensing due to its rich spectral information and fine spatial resolution. However, the high dimensionality, nonlinearity, and complex relationship between spectral and spatial features of HSI pose challenges to its accurate classification. Traditional convolutional neural network (CNN)-based methods suffer from detail loss in feature extraction; Transformer-based methods rely too much on the quantity and quality of HSI; and graph neural network (GNN)-based methods provide a new impetus for HSI classification by virtue of their excellent ability to handle irregular data. To address these challenges and take advantage of GNN, we propose a network of parallel GNNs called PGNN-Net. The network first extracts the key spatial-spectral features of HSI using principal component analysis, followed by preprocessing to obtain two primary features and a normalized adjacency matrix. Then, a parallel architecture is constructed using improved GCN and ChebNet to extract local and global spatial-spectral features, respectively. Finally, the discriminative features obtained through the fusion strategy are input into the classifier to obtain the classification results. In addition, to alleviate the over-fitting problem, the label smoothing technique is embedded in the cross-entropy loss function. The experimental results show that the average overall accuracy obtained by our method on Indian Pines, Kennedy Space Center, Pavia University Scene, and Botswana reaches 97.35%, 99.40%, 99.64%, and 98.46%, respectively, which are better compared to some state-of-the-art methods. Full article

(This article belongs to the Section Remote Sensing Image Processing)

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27 pages, 22334 KiB

Open AccessArticle

Continuously Learning Prediction Models for Smart Domestic Hot Water Management

by Raphaël Bayle, Marina Reyboz, Aurore Lomet, Victor Cook and Martial Mermillod

Energies 2024, 17(18), 4734; https://doi.org/10.3390/en17184734 (registering DOI) - 23 Sep 2024

Abstract

Domestic hot water (DHW) consumption represents a significant portion of household energy usage, prompting the exploration of smart heat pump technology to efficiently meet DHW demands while minimizing energy waste. This paper proposes an innovative investigation of models using deep learning and continual [...] Read more.

Domestic hot water (DHW) consumption represents a significant portion of household energy usage, prompting the exploration of smart heat pump technology to efficiently meet DHW demands while minimizing energy waste. This paper proposes an innovative investigation of models using deep learning and continual learning algorithms to personalize DHW predictions of household occupants’ behavior. Such models, alongside a control system that decides when to heat, enable the development of a heat-pumped-based smart DHW production system, which can heat water only when needed and avoid energy loss due to the storage of hot water. Deep learning models, and attention-based models particularly, can be used to predict time series efficiently. However, they suffer from catastrophic forgetting, meaning that when they dynamically learn new patterns, older ones tend to be quickly forgotten. In this work, the continuous learning of DHW consumption prediction has been addressed by benchmarking proven continual learning methods on both real dwelling and synthetic DHW consumption data. Task-per-task analysis reveals, among the data from real dwellings that do not present explicit distribution changes, a gain compared to the non-evolutive model. Our experiment with synthetic data confirms that continual learning methods improve prediction performance. Full article

(This article belongs to the Special Issue Smart Energy Systems: Learning Methods for Control and Optimization)

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10 pages, 217 KiB

Open AccessEditorial

Applications of Computer Vision, 2nd Edition

by Eva Cernadas

Electronics 2024, 13(18), 3779; https://doi.org/10.3390/electronics13183779 (registering DOI) - 23 Sep 2024

Abstract

Computer vision (CV) is a broad term mainly used to refer to processing image and video data [...] Full article

(This article belongs to the Special Issue Applications of Computer Vision, 2nd Edition)

13 pages, 4287 KiB

Open AccessArticle

Antibacterial Properties of Grape Seed Extract-Enriched Cellulose Hydrogels for Potential Dental Application: In Vitro Assay, Cytocompatibility, and Biocompatibility

by Karla Lizette Tovar-Carrillo, Lizett Trujillo-Morales, Juan Carlos Cuevas-González, Judith Virginia Ríos-Arana, León Francisco Espinosa-Cristobal and Erasto Armando Zaragoza-Contreras

Gels 2024, 10(9), 606; https://doi.org/10.3390/gels10090606 (registering DOI) - 23 Sep 2024

Abstract

Hydrogels elaborated from Dasylirion spp. and enriched with grape seed extract (GSE) were investigated for tentative use in dental treatment. Cellulose-GSE hydrogels were elaborated with varying GSE contents from 10 to 50 wt%. The mechanical and physical properties, antimicrobial effect, biocompatibility, and in [...] Read more.

Hydrogels elaborated from Dasylirion spp. and enriched with grape seed extract (GSE) were investigated for tentative use in dental treatment. Cellulose-GSE hydrogels were elaborated with varying GSE contents from 10 to 50 wt%. The mechanical and physical properties, antimicrobial effect, biocompatibility, and in vitro cytotoxicity were studied. In all the cases, the presence of GSE affects the hydrogel’s mechanical properties. The elongation decreased from 12.67 mm for the hydrogel without GSE to 6.33 mm for the hydrogel with the highest GSE content. The tensile strength decrease was from 52.33 N/mm² (for the samples without GSE) and went to 40 N/mm² for the highest GSE content. Despite the adverse effects, hydrogels possess suitable properties for manipulation. In addition, all hydrogels exhibited excellent biocompatibility and no cytotoxicity, and the antibacterial performance was demonstrated against S. mutans, E. Faecalis, S. aureus, and P. aureginosa. Furthermore, the hydrogels with 30 wt% GSE inhibited more than 90% of the bacterial growth. Full article

(This article belongs to the Special Issue Advances in Cellulose-Based Hydrogels (3rd Edition))

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9 pages, 1459 KiB

Open AccessArticle

Variation in Accelerometer-Derived Instantaneous Acceleration Distribution Curves of Elite Male Soccer Players According to Playing Position: A Pilot Study

by Pedro Oliveira, Felipe Arruda Moura, Ivan Baptista, Fábio Yuzo Nakamura and José Afonso

Sports 2024, 12(9), 263; https://doi.org/10.3390/sports12090263 (registering DOI) - 23 Sep 2024

Abstract

The incorporation of triaxial accelerometers into Global Positioning Systems (GPS) has significantly advanced our understanding of accelerations in sports. However, inter-positional differences are unknown. This study aimed to explore the variability of acceleration and deceleration (Acc) distribution curves according to players’ positions during [...] Read more.

The incorporation of triaxial accelerometers into Global Positioning Systems (GPS) has significantly advanced our understanding of accelerations in sports. However, inter-positional differences are unknown. This study aimed to explore the variability of acceleration and deceleration (Acc) distribution curves according to players’ positions during soccer matches. Thirty-seven male players from a national-level Portuguese club were monitored using 10 Hz GPS with an embedded accelerometer during the 2021/2022 season. Resultant Acc was obtained from the x (lateral), y (frontal/back), and z (vertical) axes and expressed in gravitational units (g). Statistical Parametric Mapping was employed to compare playing positions: central defenders (CD), fullbacks (FB), central midfielders (CM), wide midfielders (WM), and strikers (ST). All positions exhibited a decreasing Acc distribution curve, very similar in shape, with a high frequency of events in the lower ranges (i.e., 0 to 1 g) and a lower frequency of events in the higher values (2 to 10 g). Post hoc comparisons revealed significant differences between all positions, except between FB and WM. Out of 1000 points in the curve, CD had 540, 535, 414, and 264 different points compared to FB, CM, WM, and ST, respectively. These findings indicate that players in different positions face distinct demands during matches, emphasizing the need for position-specific Acc analysis and training programming. By analyzing Acc as a continuous variable, this study highlights the importance of individualized monitoring to ensure the comprehensive and precise tracking of all player activities, without overlooking or omitting critical information. Full article

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17 pages, 1686 KiB

Open AccessArticle

A Study on Operator Allocation in Consideration of Fatigue in Cell Manufacturing System

by Moe Endo and Harumi Haraguchi

Appl. Syst. Innov. 2024, 7(5), 87; https://doi.org/10.3390/asi7050087 (registering DOI) - 23 Sep 2024

Abstract

In a labor-intensive cell production system, it is important to train operators effectively because their skills are essential for productivity. Our previous study proposed a method to classify these skills according to a “skill index” based on the time required for each task [...] Read more.

In a labor-intensive cell production system, it is important to train operators effectively because their skills are essential for productivity. Our previous study proposed a method to classify these skills according to a “skill index” based on the time required for each task and the allocated operators based on this method. However, in actual workplaces, it is assumed that operators accumulate fatigue due to the repetition of work, which affects the assembly time. In this study, we propose an operator allocation method that considers the effect of fatigue and verify its effectiveness compared with the results of the previous study by computer experiments. In addition, an assembly experiment with a toy is conducted based on the operator allocation method derived from the computer experiments. The experimental results show that the proposed method is effective and indicate that appropriate parameter setting is crucial when applying it in real-world scenarios. Full article

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10 pages, 282 KiB

Open AccessArticle

Topological Susceptibility of the Gluon Plasma in the Stochastic-Vacuum Approach

by Dmitry Antonov

Universe 2024, 10(9), 377; https://doi.org/10.3390/universe10090377 (registering DOI) - 23 Sep 2024

Abstract

Topological susceptibility of the SU(3) gluon plasma is calculated by accounting for both factorized and non-factorized contributions to the two-point correlation function of topological-charge densities. It turns out that, while the factorized contribution keeps this correlation function non-positive away from the origin, the [...] Read more.

Topological susceptibility of the SU(3) gluon plasma is calculated by accounting for both factorized and non-factorized contributions to the two-point correlation function of topological-charge densities. It turns out that, while the factorized contribution keeps this correlation function non-positive away from the origin, the non-factorized contribution makes it positive at the origin, in accordance with the reflection positivity condition. Matching the obtained result for topological susceptibility to its lattice value at the deconfinement critical temperature, we fix the parameters of the quartic cumulant of gluonic field strengths, and calculate the contribution of that cumulant to the string tension. This contribution reduces the otherwise too large value of the string tension, which stems from the quadratic cumulant, making it much closer to the standard phenomenological value. Full article

(This article belongs to the Special Issue Quantum Field Theory, 2nd Edition)

13 pages, 8494 KiB

Open AccessArticle

Effects of Different Photoperiods on the Transcriptome of the Ovary and Small White Follicles in Zhedong White Geese

by Tao Huang, Meina Fei, Xiaolong Zhou, Ke He, Songbai Yang and Ayong Zhao

Animals 2024, 14(18), 2747; https://doi.org/10.3390/ani14182747 (registering DOI) - 23 Sep 2024

Abstract

Photoperiod can regulate the broodiness of geese and thus increase their egg-laying rate. The laying performance of geese is mainly determined by ovary and follicle development. To understand the effect of photoperiod on the ovary and small white follicles, sixteen 220-day-old healthy female [...] Read more.

Photoperiod can regulate the broodiness of geese and thus increase their egg-laying rate. The laying performance of geese is mainly determined by ovary and follicle development. To understand the effect of photoperiod on the ovary and small white follicles, sixteen 220-day-old healthy female Zhedong white geese were randomly divided into two groups for long photoperiods (15L:9D) and short photoperiods (9L:15D). The geese were euthanized after two months of feeding, and their ovaries and follicles were collected for transcriptome sequencing. RNA-seq analysis identified 187 and 448 differentially expressed genes in ovaries and small white follicles of different photoperiod groups, respectively. A long photoperiod promotes high expression of SPP1, C6, MZB1, GP1BA, and FCGBP genes in the ovaries, and increases the expression of SPP1, ANGPTL5, ALPL, ZP1, and CHRNA4 genes in small white follicles. Functional enrichment analysis showed that photoperiod could affect respiratory system development, smooth muscle cell proliferation in ovaries, and extracellular matrix-related function in small white follicles. WGCNA revealed 31 gene modules, of which 2 were significantly associated with ovarian weight and 17 with the number of small white follicles. Our results provide a better understanding of the molecular regulation in the photoperiod affecting goose reproduction. Full article

(This article belongs to the Section Poultry)

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13 pages, 299 KiB

Open AccessArticle

Effects of Split-Attention and Task Complexity on Individual and Collaborative Learning

by John Guzmán and Jimmy Zambrano R.

Educ. Sci. 2024, 14(9), 1035; https://doi.org/10.3390/educsci14091035 (registering DOI) - 23 Sep 2024

Abstract

School tasks often include individual and collaborative activities supported by a wide variety of learning materials. These materials can elicit varied levels of attention and learning depending on the complexity (i.e., element interactivity level) and physical separation of the information elements in the [...] Read more.

School tasks often include individual and collaborative activities supported by a wide variety of learning materials. These materials can elicit varied levels of attention and learning depending on the complexity (i.e., element interactivity level) and physical separation of the information elements in the study material. The aim of this study was to explore the potential effects of the element interactivity level (i.e., high vs. low) and split attention (i.e., integrated vs. separated information) on individual and collaborative learning. An experimental design was implemented with 192 high school learners, with 64 working individually and 128 in dyads. The results revealed that in tasks with high element interactivity and integrated information, individual students learned more than groups. However, separated information benefited groups more than individual learners. It is concluded that the benefits of individual and group learning are mediated by task element interactivity and the physical separation of information sources in the study material, and recommendations for education professionals are presented. Full article

(This article belongs to the Special Issue Cognitive Load Theory: Emerging Trends and Innovations)

18 pages, 14791 KiB

Open AccessArticle

Effect of Substrate Bias on the Structure and Tribological Performance of (AlTiVCrNb)C_xN_y Coatings Deposited via Graphite Co-Sputtering

by Haichao Cai, Pengge Guo, Yujun Xue, Lulu Pei, Yinghao Zhang and Jun Ye

Lubricants 2024, 12(9), 325; https://doi.org/10.3390/lubricants12090325 (registering DOI) - 23 Sep 2024

Abstract

In the existing literature, there are few studies on the effect of deposition bias on the tribological properties of carbon-doped high-entropy alloy coatings. In order to further study the effect of the deposition bias on the properties of coatings, (AlTiVCrNb)C_xN_y [...] Read more.

In the existing literature, there are few studies on the effect of deposition bias on the tribological properties of carbon-doped high-entropy alloy coatings. In order to further study the effect of the deposition bias on the properties of coatings, (AlTiVCrNb)C_xN_y coatings were deposited via unbalanced RF magnetron sputtering. The microstructure and tribological properties of carbon-doped high-entropy alloy ceramic coatings under different deposition biases were studied. The composition, morphology, crystal structure, and chemical morphology of each element of the coating were analyzed using scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The hardness, elastic modulus, friction, and wear properties of the coating were further characterized using a nanoindentation instrument, reciprocating sliding friction, a wear tester, and a white light interferometer. The coating density reached the optimal level when the deposition bias value was 90 V. The hardness and elastic modulus of the (AlTiVCrNb)C_xN_y coating increased first and then decreased with an increase in deposition bias, and the maximum hardness was 23.98 GPa. When the deposition bias was 90 V, the coating formed a good-quality carbon transfer film on the surface of the counterbody due to sp2 clusters during the friction and wear process. The average friction coefficient and wear rate of the (AlTiVCrNb)C_xN_y coating were the lowest, 0.185 and 1.6 × 10⁻⁷ mm³/N·m, respectively. The microstructure, mechanical properties, and tribological performance of the (AlTiVCrNb)C_xN_y coating were greatly affected by the change in deposition bias, and an (AlTiVCrNb)C_xN_y coating with excellent structure and friction properties could be prepared using graphite co-sputtering. Full article

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17 pages, 289 KiB

Open AccessArticle

Indigeneity as a Post-Apocalyptic Genealogical Metaphor

by Arcia Tecun

Genealogy 2024, 8(3), 121; https://doi.org/10.3390/genealogy8030121 (registering DOI) - 23 Sep 2024

Abstract

This paper is a theoretical exploration that works through a global Indigenous consciousness. As a critically reflexive story work and auto-ethnographic contemplation it begins by confronting a presumed genealogy in a post-apocalyptic world of coloniality through a global Indigenous lens. Extending beyond racially [...] Read more.

This paper is a theoretical exploration that works through a global Indigenous consciousness. As a critically reflexive story work and auto-ethnographic contemplation it begins by confronting a presumed genealogy in a post-apocalyptic world of coloniality through a global Indigenous lens. Extending beyond racially legalised genealogical ancestry, the metaphysics of indigeneity in the context of Western modernity can be re-positioned as a metaphor of past future human-being-ness or person/people-hood. Global Indigeneity and Indigenous metaphysics are framed as a portal and entry beyond coloniality through fugitive sociality and subversive relationality. Confronting the tensions of colonially purist and racially essentialist categories of indigenous identity, lineages of the post-post-apocalyptic world are forming in the enduring social connections embodied in an Indigenous genealogical consciousness of the present. Full article

(This article belongs to the Special Issue Decolonial (and Anti-Colonial) Interventions to Genealogy)

20 pages, 1768 KiB

Open AccessReview

Sesame, an Underutilized Oil Seed Crop: Breeding Achievements and Future Challenges

by Saeed Rauf, Taiyyibah Basharat, Adane Gebeyehu, Mohammed Elsafy, Mahbubjon Rahmatov, Rodomiro Ortiz and Yalcin Kaya

Plants 2024, 13(18), 2662; https://doi.org/10.3390/plants13182662 (registering DOI) - 23 Sep 2024

Abstract

Sesame seeds and their edible oil are highly nutritious and rich in mono- and polyunsaturated fatty acids. Bioactive compounds such as sterols, tocopherols, and sesamol provide significant medicinal benefits. The high oil content (50%) and favorable mono- and polyunsaturated fatty acid balance, as [...] Read more.

Sesame seeds and their edible oil are highly nutritious and rich in mono- and polyunsaturated fatty acids. Bioactive compounds such as sterols, tocopherols, and sesamol provide significant medicinal benefits. The high oil content (50%) and favorable mono- and polyunsaturated fatty acid balance, as well as resilience to water stress, make sesame a promising candidate crop for global agricultural expansion. However, sesame production faces challenges such as low yields, poor response to agricultural inputs, and losses due to capsule dehiscence. To enhance yield, traits like determinate growth, dwarfism, a high harvest index, non-shattering capsules, disease resistance, and photoperiod sensitivity are needed. These traits can be achieved through variation or induced mutation breeding. Crossbreeding methods often result in unwanted genetic changes. The gene editing CRISPR/Cas9 technology has the potential to suppress detrimental alleles and improve the fatty acid profile by inhibiting polyunsaturated fatty acid biosynthesis. Even though sesame is an orphan crop, it has entered the genomic era, with available sequences assisting molecular breeding efforts. This progress aids in associating single-nucleotide polymorphisms (SNPs) and simple sequence repeats (SSR) with key economic traits, as well as identifying genes related to adaptability, oil production, fatty acid synthesis, and photosynthesis. Additionally, transcriptomic research can reveal genes involved in abiotic stress responses and adaptation to diverse climates. The mapping of quantitative trait loci (QTL) can identify loci linked to key traits such as capsule size, seed count per capsule, and capsule number per plant. This article reviews recent advances in sesame breeding, discusses ongoing challenges, and explores potential strategies for future improvement. Hence, integrating advanced genomic tools and breeding strategies provides promising ways to enhance sesame production to meet global demands. Full article

(This article belongs to the Section Plant Genetic Resources)

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19 pages, 3381 KiB

Open AccessReview

Enhancing Crop Resilience: Insights from Labdane-Related Diterpenoid Phytoalexin Research in Rice (Oryza sativa L.)

by Shiquan Bian, Zhong Li, Shaojie Song, Xiao Zhang, Jintao Shang, Wanli Wang, Dewen Zhang and Dahu Ni

Curr. Issues Mol. Biol. 2024, 46(9), 10677-10695; https://doi.org/10.3390/cimb46090634 (registering DOI) - 23 Sep 2024

Abstract

Rice (Oryza sativa L.), as one of the most significant food crops worldwide, holds paramount importance for global food security. Throughout its extensive evolutionary journey, rice has evolved a diverse array of defense mechanisms to fend off pest and disease infestations. Notably, [...] Read more.

Rice (Oryza sativa L.), as one of the most significant food crops worldwide, holds paramount importance for global food security. Throughout its extensive evolutionary journey, rice has evolved a diverse array of defense mechanisms to fend off pest and disease infestations. Notably, labdane-related diterpenoid phytoalexins play a crucial role in aiding rice in its response to both biotic and abiotic stresses. This article provides a comprehensive review of the research advancements pertaining to the chemical structures, biological activities, and biosynthetic pathways, as well as the molecular regulatory mechanisms, underlying labdane-related diterpenoid phytoalexins discovered in rice. This insight into the molecular regulation of labdane-related diterpenoid phytoalexin biosynthesis offers valuable perspectives for future research aimed at improving crop resilience and productivity. Full article

(This article belongs to the Special Issue Latest Review Papers in Molecular Biology 2024)

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26 pages, 3533 KiB

Open AccessSystematic Review

Energy-Efficient Industrial Internet of Things in Green 6G Networks

by Xavier Fernando and George Lăzăroiu

Appl. Sci. 2024, 14(18), 8558; https://doi.org/10.3390/app14188558 (registering DOI) - 23 Sep 2024

Abstract

The research problem of this systematic review was whether green 6G networks can integrate energy-efficient Industrial Internet of Things (IIoT) in terms of distributed artificial intelligence, green 6G pervasive edge computing communication networks and big-data-based intelligent decision algorithms. We show that sensor data [...] Read more.

The research problem of this systematic review was whether green 6G networks can integrate energy-efficient Industrial Internet of Things (IIoT) in terms of distributed artificial intelligence, green 6G pervasive edge computing communication networks and big-data-based intelligent decision algorithms. We show that sensor data fusion can be carried out in energy-efficient IoT smart industrial urban environments by cooperative perception and inference tasks. Our analyses debate on 6G wireless communication, vehicular IoT intelligent and autonomous networks, and energy-efficient algorithm and green computing technologies in smart industrial equipment and manufacturing environments. Mobile edge and cloud computing task processing capabilities of decentralized network control and power grid system monitoring were thereby analyzed. Our results and contributions clarify that sustainable energy efficiency and green power generation together with IoT decision support and smart environmental systems operate efficiently in distributed artificial intelligence 6G pervasive edge computing communication networks. PRISMA was used, and with its web-based Shiny app flow design, the search outcomes and screening procedures were integrated. A quantitative literature review was performed in July 2024 on original and review research published between 2019 and 2024. Study screening, evidence map visualization, and data extraction and reporting tools, machine learning classifiers, and reference management software were harnessed for qualitative and quantitative data, collection, management, and analysis in research synthesis. Dimensions and VOSviewer were deployed for data visualization and analysis. Full article

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22 pages, 12133 KiB

Open AccessArticle

Abiotic Stress Effect on Agastache mexicana subsp. mexicana Yield: Cultivated in Two Contrasting Environments with Organic Nutrition and Artificial Shading

by Judith Morales-Barrera, Juan Reséndiz-Muñoz, Blas Cruz-Lagunas, José Luis Fernández-Muñoz, Flaviano Godínez-Jaimes, Tania de Jesús Adame-Zambrano, Mirna Vázquez-Villamar, Teollincacihuatl Romero-Rosales, María Teresa Zagaceta-Álvarez, Karen Alicia Aguilar-Cruz, Jorge Estrada-Martínez and Miguel Angel Gruintal-Santos

Plants 2024, 13(18), 2661; https://doi.org/10.3390/plants13182661 (registering DOI) - 23 Sep 2024

Abstract

Research on medicinal plants is essential for their conservation, propagation, resistance to environmental stress, and domestication. The use of organic nutrition has been demonstrated to improve soil fertility and plant quality. It is also important to study the effects of the Basic Cation [...] Read more.

Research on medicinal plants is essential for their conservation, propagation, resistance to environmental stress, and domestication. The use of organic nutrition has been demonstrated to improve soil fertility and plant quality. It is also important to study the effects of the Basic Cation Saturation Ratio (BCSR) approach, which is a topic where there is currently controversy and limited scientific information. Evaluating the growth and yields of Agastache mexicana subsp. mexicana (Amm) in different environments is crucial for developing effective propagation and domestication strategies. This includes examining warm and subhumid environments with rain in summer in comparison to mild environments with summer rain. Significant differences were observed in the effects of cold, waterlogging, and heat stresses on the plant’s biomass yield and the morphometric-quantitative modeling by means of isolines. The biomass yield was 56% higher in environment one compared to environment two, 19% higher in environment one with organic nutrition, and 48% higher in environment two with organic nutrition compared to using only BCSR nutrition. In the second harvesting cycle, the plants in environment one did not survive, while the plants in environment two managed to survive without needing additional nutrition. Statistical and mathematical analyses provided information about the population or sample. Additionally, further analysis using isolines as a new approach revealed new insights into understanding phenology and growth issues. Full article

(This article belongs to the Special Issue Abiotic Stress Responses in Plants)

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15 pages, 1766 KiB

Open AccessArticle

Parallel Attention-Driven Model for Student Performance Evaluation

by Deborah Olaniyan, Julius Olaniyan, Ibidun Christiana Obagbuwa, Bukohwo Michael Esiefarienrhe and Olorunfemi Paul Bernard

Computers 2024, 13(9), 242; https://doi.org/10.3390/computers13090242 (registering DOI) - 23 Sep 2024

Abstract

This study presents the development and evaluation of a Multi-Task Long Short-Term Memory (LSTM) model with an attention mechanism for predicting students’ academic performance. The research is motivated by the need for efficient tools to enhance student assessment and support tailored educational interventions. [...] Read more.

This study presents the development and evaluation of a Multi-Task Long Short-Term Memory (LSTM) model with an attention mechanism for predicting students’ academic performance. The research is motivated by the need for efficient tools to enhance student assessment and support tailored educational interventions. The model tackles two tasks: predicting overall performance (total score) as a regression task and classifying performance levels (remarks) as a classification task. By handling both tasks simultaneously, it improves computational efficiency and resource utilization. The dataset includes metrics such as Continuous Assessment, Practical Skills, Presentation Quality, Attendance, and Participation. The model achieved strong results, with a Mean Absolute Error (MAE) of 0.0249, Mean Squared Error (MSE) of 0.0012, and Root Mean Squared Error (RMSE) of 0.0346 for the regression task. For the classification task, it achieved perfect scores with an accuracy, precision, recall, and F1 score of 1.0. The attention mechanism enhanced performance by focusing on the most relevant features. This study demonstrates the effectiveness of the Multi-Task LSTM model with an attention mechanism in educational data analysis, offering a reliable and efficient tool for predicting student performance. Full article

(This article belongs to the Special Issue Present and Future of E-Learning Technologies (2nd Edition))

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18 pages, 5611 KiB

Open AccessEssay

Expression of Cystathionine-β-Synthase (CBS) Genes in Grape under Various Abiotic Stresses and Subcellular Localization of VvCBS27

by Xingyun Shi, Shanshan Xu, Yandong Li and Yiming Yin

Horticulturae 2024, 10(9), 1009; https://doi.org/10.3390/horticulturae10091009 (registering DOI) - 23 Sep 2024

Abstract

The cystathionine-β-synthase (CBS) domain is present in the proteins of all living organisms and functions as an energy sensor, regulating protein activity through the binding capacity of its adenosine ligands. The role of the CBS gene in plant growth and development, as well [...] Read more.

The cystathionine-β-synthase (CBS) domain is present in the proteins of all living organisms and functions as an energy sensor, regulating protein activity through the binding capacity of its adenosine ligands. The role of the CBS gene in plant growth and development, as well as tolerance to abiotic stresses, remains largely unknown, especially in grapevine. In our study, 32 members of the CBS gene family were obtained that were distributed on 15 chromosomes. The results of the structural and evolutionary tree analyses indicated that the VvCBS gene family exhibits diverse intron-exon patterns and highly conserved motifs. Furthermore, the phylogenetic classification of the VvCBS genes revealed the presence of three subfamilies. Subcellular localization analyses showed that the VvCBS genes are mainly located in the plasma membrane region. The secondary structure of the VvCBS protein mainly consists of α-helices, extended strands, β-turns, and random coils. The VvCBS gene family exhibited four co-linear gene pairs, while the numbers for Arabidopsis thaliana and rice were 21 and 7, respectively. The promoter cis-acting element analysis revealed the presence of light-responsive, hormone-responsive, stress-responsive, and growth- and development-related elements in the VvCBS family. The expression characterization demonstrated that 12 VvCBS genes exhibited high expression levels in all grape tissues. Additionally, the RT-qPCR expression analyses showed that the 32 VvCBS exhibited different responses to a variety of abiotic stresses (cold, drought, salt), suggesting that they were functionally differentiated. VvCBS27 was cloned from ‘Pinot Noir’ of grapevine with a coding sequence of 624 bp. Subcellular localization showed that VvCBS27 protein was mainly located in the cytoplasm, cell membrane, and nucleus. This study lays a foundation for elucidating the function of grape CBS protein. Full article

(This article belongs to the Section Viticulture)

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21 pages, 6642 KiB

Open AccessArticle

Investigating the Impact of Fasting and Refeeding on Blood Biochemical Indicators and Transcriptional Profiles in the Hypothalamus and Subcutaneous Adipose Tissue in Geese

by Yi Liu, Xianze Wang, Guangquan Li, Shufang Chen, Huiyan Jia, Jiuli Dai and Daqian He

Animals 2024, 14(18), 2746; https://doi.org/10.3390/ani14182746 (registering DOI) - 23 Sep 2024

Abstract

Fasting and refeeding systems can cause significant short-term fluctuations in nutrient and energy levels, triggering adaptive physiological responses in animals. This study examines the effects of fasting and refeeding on blood biochemical indicators and transcriptional profiles in the hypothalamus and subcutaneous adipose tissue [...] Read more.

Fasting and refeeding systems can cause significant short-term fluctuations in nutrient and energy levels, triggering adaptive physiological responses in animals. This study examines the effects of fasting and refeeding on blood biochemical indicators and transcriptional profiles in the hypothalamus and subcutaneous adipose tissue of geese. Biochemical assays reveal that fasting significantly increases levels of free fatty acids and glucagon, while reducing concentrations of triglycerides, leptin, and insulin. Transcriptomic analyses identify a complex transcriptional response in both the hypothalamus and subcutaneous adipose tissue, affecting several metabolic pathways and key genes associated with feed intake and energy metabolism. In subcutaneous adipose tissue, fasting downregulates genes involved in fatty acid synthesis (LPL, SCD, and ACSL1) and upregulates PLIN2, a gene promoting lipid droplet degradation. Fasting affects a variety of metabolic pathways and critical genes in the hypothalamus, including Apelin, insulin, and mTOR signaling pathways. After fasting, the mRNA expression of NOG, GABRD, and IGFBP-1 genes in the hypothalamus are significantly upregulated, while proopiomelanocortin (POMC) gene expression is markedly downregulated. This study highlights the intricate biological responses to nutritional changes in geese, which adds to our understanding of energy balance and metabolic regulation in avian species. Full article

(This article belongs to the Section Animal Physiology)

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22 pages, 1101 KiB

Open AccessReview

Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways

by Jinping Feng, Xinan Zhang and Tianhai Tian

Int. J. Mol. Sci. 2024, 25(18), 10204; https://doi.org/10.3390/ijms251810204 (registering DOI) - 23 Sep 2024

Abstract

The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in [...] Read more.

The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in single-cell proteomic technologies have provided unprecedented opportunities to investigate the heterogeneity and noise within complex, multi-signaling networks across diverse cells and cell types. Mathematical modeling has become a powerful interdisciplinary tool that bridges mathematics and experimental biology, providing valuable insights into these intricate cellular processes. In addition, statistical methods have been developed to infer pathway topologies and estimate unknown parameters within dynamic models. This review presents a comprehensive analysis of how mathematical modeling of the MAPK pathway deepens our understanding of its regulatory mechanisms, enhances the prediction of system behavior, and informs experimental research, with a particular focus on recent advances in modeling and inference using single-cell proteomic data. Full article

(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)

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14 pages, 939 KiB

Open AccessArticle

Stepwise Corrected Attention Registration Network for Preoperative and Follow-Up Magnetic Resonance Imaging of Glioma Patients

by Yuefei Feng, Yao Zheng, Dong Huang, Jie Wei, Tianci Liu, Yinyan Wang and Yang Liu

Bioengineering 2024, 11(9), 951; https://doi.org/10.3390/bioengineering11090951 (registering DOI) - 23 Sep 2024

Abstract

The registration of preoperative and follow-up brain MRI, which is crucial in illustrating patients’ responses to treatments and providing guidance for postoperative therapy, presents significant challenges. These challenges stem from the considerable deformation of brain tissue and the areas of non-correspondence due to [...] Read more.

The registration of preoperative and follow-up brain MRI, which is crucial in illustrating patients’ responses to treatments and providing guidance for postoperative therapy, presents significant challenges. These challenges stem from the considerable deformation of brain tissue and the areas of non-correspondence due to surgical intervention and postoperative changes. We propose a stepwise corrected attention registration network grounded in convolutional neural networks (CNNs). This methodology leverages preoperative and follow-up MRI scans as fixed images and moving images, respectively, and employs a multi-level registration strategy that establishes a precise and holistic correspondence between images, from coarse to fine. Furthermore, our model introduces a corrected attention module into the multi-level registration network that can generate an attention map at the local level through the deformation fields of the upper-level registration network and pathological areas of preoperative images segmented by a mature algorithm in BraTS, serving to strengthen the registration accuracy of non-correspondence areas. A comparison between our scheme and the leading approach identified in the MICCAI’s BraTS-Reg challenge indicates a 7.5% enhancement in the target registration error (TRE) metric and improved visualization of non-correspondence areas. These results illustrate the better performance of our stepwise corrected attention registration network in not only enhancing the registration accuracy but also achieving a more logical representation of non-correspondence areas. Thus, this work contributes significantly to the optimization of the registration of brain MRI between preoperative and follow-up scans. Full article

(This article belongs to the Section Biosignal Processing)

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17 pages, 3303 KiB

Open AccessArticle

Research on the Design Method of Camellia oleifera Fruit Picking Machine

by Shan Hu, Jing Xin, Dong Zhang and Geqi Xing

Appl. Sci. 2024, 14(18), 8537; https://doi.org/10.3390/app14188537 (registering DOI) - 23 Sep 2024

Abstract

Camellia oleifera fruit pickers are essential for improving picking efficiency and promoting the Camellia oleifera industry. However, it is challenging to develop pickers that meet user needs. Current design tools and methods have limitations, such as a single model, poor synergy between integrated [...] Read more.

Camellia oleifera fruit pickers are essential for improving picking efficiency and promoting the Camellia oleifera industry. However, it is challenging to develop pickers that meet user needs. Current design tools and methods have limitations, such as a single model, poor synergy between integrated models, and subjective bias when analysing user requirements and translating them into product attributes. To solve these problems, this study proposes a new design decision model based on the Fuzzy Analytic Hierarchy Process (FAHP), Function Analysis System Technique (FAST), Theory of Inventive Problem Solving (TRIZ Theory), and extension transformation theory. The model was developed and applied to design an Camellia oleifera fruit picker. In this paper, an empirical investigation of an Camellia oleifera base in Wuhan was carried out, and multi-level demand analysis was used to identify the design demands in the behavioural process; FAHP was used to calculate the demand weights to clarify the design focus; expert knowledge was used to convert the demands into specific product functional features, and FAST was used to decompose these features to find the contradictory conflicts; TRIZ theory was used to determine the principles of resolving the contradictions, and the extension transformation theory were used to generate the creative design solutions for the products. By integrating FAHP, FAST, TRIZ theory and the extension transformation theory, the subjective bias in product design is eliminated, the design decision-making process is improved, and new methods and ideas are provided for the design of oleaginous tea fruit pickers and similar products. Finally, the conceptual design of an Camellia oleifera fruit picking machine was produced. However, the conceptual design has yet to be subjected to exhaustive simulation experiments and prototype testing. Future research will focus on conducting the necessary simulations, prototypes, and field tests to fully assess the feasibility and effectiveness of the design and make the required iterative improvements accordingly to commercialize the product eventually. Full article

(This article belongs to the Special Issue Practical Applications of New Optimization Methods and Intelligent Control)

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23 pages, 6636 KiB

Open AccessArticle

High-Precision Bi-Directional Beam-Pointing Measurement Method Based on Space Solar Power Station System

by Xinyue Hou, Xue Li, Shun Zhao, Yinsen Zhang and Lulu Wang

Sensors 2024, 24(18), 6135; https://doi.org/10.3390/s24186135 (registering DOI) - 23 Sep 2024

Abstract

In the process of wireless energy transmission from a Space Solar Power Station (SSPS) to a satellite, the efficiency of energy transmission is closely related to the accuracy of beam control. The existing methods commonly ignore the impact of array position, structural deviation [...] Read more.

In the process of wireless energy transmission from a Space Solar Power Station (SSPS) to a satellite, the efficiency of energy transmission is closely related to the accuracy of beam control. The existing methods commonly ignore the impact of array position, structural deviation of the transmitting antenna, and modulation errors, which leads to the deviation error in actual energy transmission beams and the reduction of energy transmission efficiency. This paper innovatively proposes a high-precision bi-directional beam-pointing measurement method, which provides a technical basis for advancing the beam-pointing control accuracy from the perspective of improving the beam-pointing measurement accuracy. The method consists of (1) the interferometer goniometry method to realize high-precision guiding beam pointing measurement; and (2) the power field reconstruction method to realize offset angle measurement of the energy-transmitting beam. Simulation results demonstrate that under dynamic conditions, the guiding beam-pointing measurement accuracy of this method reaches 0.05°, which is better than the traditional 0.1° measurement accuracy based on the guiding beam. The measurement accuracy of the offset distance of the energy center is better than 0.11 m, and the measurement accuracy of the offset angle is better than 0.012°. Full article

(This article belongs to the Section Physical Sensors)

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16 pages, 9338 KiB

Open AccessArticle

Effects of Cooling Media on Microstructure and Mechanical Properties in Friction Stir Welded SA516 Gr.70 Cryogenic Steel Joints

by Xiuying Wang, Yu Wang, Jiujun Xu, Juncai Sun, Yuqian Wang and Guangming Xie

Materials 2024, 17(18), 4661; https://doi.org/10.3390/ma17184661 (registering DOI) - 23 Sep 2024

Abstract

SA516 Gr.70 steels were welded by friction stir welding (FSW) under various media of air, water, and water + CO₂ cooling, and the effect of the cooling media on the microstructure and mechanical properties of joints was systematically analyzed. The nugget zone [...] Read more.

SA516 Gr.70 steels were welded by friction stir welding (FSW) under various media of air, water, and water + CO₂ cooling, and the effect of the cooling media on the microstructure and mechanical properties of joints was systematically analyzed. The nugget zone (NZ) under the air-cooling condition contained coarse bainite + martensite. Martensite was obtained by decreasing the cooling media temperature. Furthermore, tensile fracturing of the joints occurred in the basal metal (BM), and the ultimate tensile strength of the joints under various cooling media was similar to that of the BM. However, with decreasing cooling media temperature, the total elongation of the joints noticeably increased. Good strength (545 MPa) and elongation (16.8%) were obtained in the joints under the water + CO₂ cooling condition since the fine martensite microstructure enhanced the plastic deformation capacity of the joints. In addition, in the NZ under water + CO₂ cooling condition, good toughness of 110 J/cm² was obtained due to a high fraction of high-angle boundaries and fine martensite. Full article

(This article belongs to the Special Issue Advances in Mechanical Properties and Structure of Metal and Metal Composites)

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22 pages, 6833 KiB

Open AccessArticle

Identification of Spatial Distribution of Afforestation, Reforestation, and Deforestation and Their Impacts on Local Land Surface Temperature in Yangtze River Delta and Pearl River Delta Urban Agglomerations of China

by Zhiguo Tai, Xiaokun Su, Wenjuan Shen, Tongyu Wang, Chenfeng Gu, Jiaying He and Chengquan Huang

Remote Sens. 2024, 16(18), 3528; https://doi.org/10.3390/rs16183528 (registering DOI) - 23 Sep 2024

Abstract

Forest change affects local and global climate by altering the physical properties of the land surface. Accurately assessing urban forest changes in local land surface temperature (LST) is a scientific and crucial strategy for mitigating regional climate change. Despite this, few studies have [...] Read more.

Forest change affects local and global climate by altering the physical properties of the land surface. Accurately assessing urban forest changes in local land surface temperature (LST) is a scientific and crucial strategy for mitigating regional climate change. Despite this, few studies have attempted to accurately characterize the spatial and temporal pattern of afforestation, reforestation, and deforestation to optimize their effects on surface temperature. We used the China Land Cover Dataset and knowledge criterion-based spatial analysis model to map urban forestation (e.g., afforestation and reforestation) and deforestation. We then analyzed the impacts of these activities on LST from 2010 to 2020 based on the moving window strategy and the spatial–temporal pattern change analysis method in the urban agglomerations of the Yangtze River Delta (YRD) and Pearl River Delta (PRD), China. The results showed that forest areas declined in both regions. Most years, the annual deforestation area is greater than the yearly afforestation areas. Afforestation and reforestation had cooling effects of −0.24 ± 0.19 °C and −0.47 ± 0.15 °C in YRD and −0.46 ± 0.10 °C and −0.86 ± 0.11 °C in PRD. Deforestation and conversion of afforestation to non-forests led to cooling effects in YRD and warming effects of 1.08 ± 0.08 °C and 0.43 ± 0.19 °C in PRD. The cooling effect of forests is more evident in PRD than in YRD, and it is predominantly caused by reforestation. Moreover, forests demonstrated a significant seasonal cooling effect, except for December in YRD. Two deforestation activities exhibited seasonal warming impacts in PRD, mainly induced by deforestation, while there were inconsistent effects in YRD. Overall, this study provides practical data and decision-making support for rational urban forest management and climate benefit maximization, empowering policymakers and urban planners to make informed decisions for the benefit of their communities. Full article

(This article belongs to the Section Forest Remote Sensing)

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