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27 pages, 6627 KiB

Open AccessArticle

Chatter and Surface Waviness Analysis in Oerlikon Face Hobbing of Spiral Bevel Gears

by Jingchao Wang, Jun Qian, Kaifeng Huang, Zhentao Shang and Jianwu Yu

Aerospace 2024, 11(7), 535; https://doi.org/10.3390/aerospace11070535 (registering DOI) - 28 Jun 2024

A vectorized analytical model for the cutting dynamics in the spiral bevel gear face hobbing process has been developed, which is based on machine tool kinematics and vibration vectorization. The structural modal parameters of the cutter head spindle system are obtained through experimental [...] Read more.

A vectorized analytical model for the cutting dynamics in the spiral bevel gear face hobbing process has been developed, which is based on machine tool kinematics and vibration vectorization. The structural modal parameters of the cutter head spindle system are obtained through experimental modal analysis with hammer impact testing. The analytical model is utilized to simulate the generation of simulated vibration acceleration signals during spiral bevel gear hobbing. A wavelet threshold denoising method is applied to process the simulated vibration signals of the spiral bevel gear face hobbing with added white noise. Signal processing methods, including short-time Fourier transform are employed for time-domain analysis, frequency-domain analysis, and time–frequency-domain analysis of measured signals and simulated signals, thereby extracting the corresponding statistical features. In addition to the results of the experimental modal analysis, the causes of chatter in spiral bevel gear hobbing are discussed in detail, revealing that the main factor is cutter head vibration in the Y direction of the Hunan ZDCY CNC EQUIPMENT YKA2260 machine tool used in this research. The error in the time-domain characteristic parameters between simulated signals and measured vibration acceleration signals is within 15%, with a difference of 3.5% in spectral peak values. The predicted tooth surface morphology from simulation matches the actual morphology on the workpiece, comprehensively validating the reliability of the cutting dynamics model for the spiral bevel gear face hobbing process. Another conclusion drawn from numerical simulation experiments is that the amount of tooth surface waviness of the spiral bevel gears is the ratio of tool chatter frequency to cutting fundamental frequency. Full article

(This article belongs to the Special Issue Fatigue Damage and Fracture Analysis of Aerospace Metal Materials)

22 pages, 925 KiB

Open AccessReview

Factors, Prediction, and Explainability of Vehicle Accident Risk Due to Driving Behavior through Machine Learning: A Systematic Literature Review, 2013–2023

by Javier Lacherre, José Luis Castillo-Sequera and David Mauricio

Computation 2024, 12(7), 131; https://doi.org/10.3390/computation12070131 (registering DOI) - 28 Jun 2024

Abstract

Road accidents are on the rise worldwide, causing 1.35 million deaths per year, thus encouraging the search for solutions. The promising proposal of autonomous vehicles stands out in this regard, although fully automated driving is still far from being an achievable reality. Therefore, [...] Read more.

Road accidents are on the rise worldwide, causing 1.35 million deaths per year, thus encouraging the search for solutions. The promising proposal of autonomous vehicles stands out in this regard, although fully automated driving is still far from being an achievable reality. Therefore, efforts have focused on predicting and explaining the risk of accidents using real-time telematics data. This study aims to analyze the factors, machine learning algorithms, and explainability methods most used to assess the risk of vehicle accidents based on driving behavior. A systematic review of the literature produced between 2013 and July 2023 on factors, prediction algorithms, and explainability methods to predict the risk of traffic accidents was carried out. Factors were categorized into five domains, and the most commonly used predictive algorithms and explainability methods were determined. We selected 80 articles from journals indexed in the Web of Science and Scopus databases, identifying 115 factors within the domains of environment, traffic, vehicle, driver, and management, with speed and acceleration being the most extensively examined. Regarding machine learning advancements in accident risk prediction, we identified 22 base algorithms, with convolutional neural network and gradient boosting being the most commonly used. For explainability, we discovered six methods, with random forest being the predominant choice, particularly for feature importance analysis. This study categorizes the factors affecting road accident risk, presents key prediction algorithms, and outlines methods to explain the risk assessment based on driving behavior, taking vehicle weight into consideration. Full article

(This article belongs to the Section Computational Engineering)

2 pages, 147 KiB

Open AccessEditorial

Energy Storage and Applications—A New Open Access Journal

by Zhaoyang Dong

Energy Storage Appl. 2024, 1(1), 1-2; https://doi.org/10.3390/esa1010001 - 28 Jun 2024

Abstract

As sustainability and the adoption of renewable energy become increasingly prominent on the international agenda, energy storage plays an increasingly essential role in facilitating this transition while ensuring a secure and reliable energy supply [...] Full article

18 pages, 21597 KiB

Open AccessArticle

Enigmatic Discoid and Elliptical Structures from Brioverian (Ediacaran-Fortunian) Deposits of Brittany (Armorican Massif, NW of France)

by Didier Néraudeau, Marc Poujol, Alfredo Loi and Jules Charrondière

Foss. Stud. 2024, 2(3), 123-140; https://doi.org/10.3390/fossils2030006 - 28 Jun 2024

Abstract

The Ediacaran–Cambrian deposits of Brittany (Brioverian series) contain both a few isolated pluricentimetric discoid structures, dome-shaped or “donut”-shaped, and a multitude of centimetric to infracentimetric more or less elliptical fossils or pseudofossils. The discoid and elliptical Brioverian structures are compared to similar fossils [...] Read more.

The Ediacaran–Cambrian deposits of Brittany (Brioverian series) contain both a few isolated pluricentimetric discoid structures, dome-shaped or “donut”-shaped, and a multitude of centimetric to infracentimetric more or less elliptical fossils or pseudofossils. The discoid and elliptical Brioverian structures are compared to similar fossils and pseudofossils found worldwide, and interpreted considering both sedimentary and biological hypotheses. This synthesis of more or less enigmatical fossils from the Ediacaran–Fortunian deposits of Brittany completes the previous descriptions of more well-known discoid and elliptical Brioverian structures such as Nimbia-like and Chuaria-like fossils. It provides a better understanding of the diversity of the Brioverian fossils and original sedimentary structures. Full article

(This article belongs to the Special Issue Advances in Palaeontology—Feature Papers to Celebrate the Inaugural Issue of Fossil Studies)

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13 pages, 7761 KiB

Open AccessArticle

Numerical Simulation for the Desired Compatibility between the Inside Slopes of Open Irrigation Canals, and the Used Type of Wing Walls for the Most Efficient Performance of Water Structures

by Mohamed A. Ashour, Haitham M. Abueleyon, M. Khairy Ali, Abdallah A. Abdou and Tarek S. Abu-Zaid

Limnol. Rev. 2024, 24(3), 192-204; https://doi.org/10.3390/limnolrev24030011 - 28 Jun 2024

Abstract

The design of water structures is crucial for efficient hydraulic performance. Open irrigation canals are designed with specific inside slopes to ensure maximum stability, while the wing walls of water structures constructed across the canal are designed to maximize hydraulic performance. Therefore, ensuring [...] Read more.

The design of water structures is crucial for efficient hydraulic performance. Open irrigation canals are designed with specific inside slopes to ensure maximum stability, while the wing walls of water structures constructed across the canal are designed to maximize hydraulic performance. Therefore, ensuring compatibility between the canal inside slopes and the wing wall types used on both the upstream and downstream sides is of great importance for achieving optimum hydraulic performance. However, our literature review indicates that this necessary compatibility between the canal inside slope and the wing wall type has not been adequately researched and studied. This present study aims to numerically investigate the relationship between open canals inside slopes and wing wall types, as well as examine the impact of using different wing wall types with varying canals inside slopes on hydraulic performance efficiency. Four canal inside slope ratios (Z) (H: V = 2:1, 1.5:1, 1:1, and 0.75:1) are simulated using the HEC-RAS program, along with two types of water structure wing walls (box and broken). The HEC-RAS numerical model provides accurate and reliable estimations of the hydraulic characteristics of flowing water through the structure, and the results are verified using previous experimental measurements available in the literature. The variation (ε%) between the measured and computed results is consistent for estimating specific energy, velocity, heading (afflux), and water depths. The simulation results demonstrate that changing the canal inside slope (Z) from 0.75:1 to 2:1 results in a relative increase of approximately 27.84% in heading up and 15.06% in velocity. Additionally, the broken wing wall proves to be more effective than the box type. The study confirms that the optimal configuration for the most efficient performance of water structures involves utilizing broken-type wing walls on the upstream side, along with a 1H:1V canal inside slope. This configuration reduces the relative velocity and relative heading by approximately 12% and 20%, respectively, which is considered highly favorable. Full article

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19 pages, 8483 KiB

Open AccessArticle

Genome-Wide Identification and Expression Analysis of BrBASS Genes in Brassica rapa Reveals Their Potential Roles in Abiotic Stress Tolerance

by Zhaojing Ji, Ruolan Wang, Meiqi Zhang, Luhan Chen, Yuexin Wang, Jiyun Hui, Shiya Hao, Bingcan Lv, Qiwei Jiang and Yunyun Cao

Curr. Issues Mol. Biol. 2024, 46(7), 6646-6664; https://doi.org/10.3390/cimb46070396 - 28 Jun 2024

Abstract

The bile acid sodium symporter (BASS) family plays an important role in transporting substances and coordinating plants’ salt tolerance. However, the function of BASS in Brassica rapa has not yet been elucidated. In this study, eight BrBASS genes distributed on five chromosomes were [...] Read more.

The bile acid sodium symporter (BASS) family plays an important role in transporting substances and coordinating plants’ salt tolerance. However, the function of BASS in Brassica rapa has not yet been elucidated. In this study, eight BrBASS genes distributed on five chromosomes were identified that belonged to four subfamilies. Expression profile analysis showed that BrBASS7 was highly expressed in roots, whereas BrBASS4 was highly expressed in flowers. The promoter element analysis also identified several typical homeopathic elements involved in abiotic stress tolerance and stress-related hormonal responses. Notably, under salt stress, the expression of BrBASS2 was significantly upregulated; under osmotic stress, that of BrBASS4 increased and then decreased; and under cold stress, that of BrBASS7 generally declined. The protein–protein interaction analysis revealed that the BrBASS2 homologous gene AtBASS2 interacted with Nhd1 (N-mediated heading date-1) to alleviate salt stress in plants, while the BrBASS4 homologous gene AtBASS3 interacted with BLOS1 (biogenesis of lysosome-related organelles complex 1 subunit 1) via co-regulation with SNX1 (sorting nexin 1) to mitigate an unfavorable growing environment for roots. Further, Bra-miR396 (Bra-microRNA396) targeting BrBASS4 and BrBASS7 played a role in the plant response to osmotic and cold stress conditions, respectively. This research demonstrates that BrBASS2, BrBASS4, and BrBASS7 harbor great potential for regulating abiotic stresses. The findings will help advance the study of the functions of the BrBASS gene family. Full article

(This article belongs to the Special Issue Functional Genomics and Comparative Genomics Analysis in Plants, 2nd Edition)

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13 pages, 772 KiB

Open AccessReview

Potential Protective Factors for Allergic Rhinitis Patients Infected with COVID-19

by Jiaoyue Dong, Dingyuan Su, Binbin Zhao, Jiayang Han, Mengjie Tu, Kaifeng Zhang, Fengling Wang and Yang An

Curr. Issues Mol. Biol. 2024, 46(7), 6633-6645; https://doi.org/10.3390/cimb46070395 - 28 Jun 2024

Abstract

At the beginning of the 2019 coronavirus disease (COVID-19) pandemic, airway allergic diseases such as asthma and allergic rhinitis (AR) were considered as risk factors for COVID-19, as they would aggravate symptoms. With further research, more and more literature has shown that airway [...] Read more.

At the beginning of the 2019 coronavirus disease (COVID-19) pandemic, airway allergic diseases such as asthma and allergic rhinitis (AR) were considered as risk factors for COVID-19, as they would aggravate symptoms. With further research, more and more literature has shown that airway allergic disease may not be a high-risk factor, but may be a protective factor for COVID-19 infection, which is closely related to its low-level expression of the ACE2 receptor and the complex cytokines network as underlying molecular regulatory mechanisms. In addition, steroid hormones and age factors could not be ignored. In this review, we have summarized some current evidence on the relationship between COVID-19 and allergic rhinitis to highlight the underlying mechanisms of COVID-19 infection and provide novel insights for its prevention and treatment. The key findings show that allergic rhinitis and its related molecular mechanisms may have a protective effect against COVID-19 infection. Full article

(This article belongs to the Special Issue Molecular and Real-World Evidence Research of Respiratory Diseases and Infections)

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21 pages, 892 KiB

Open AccessArticle

Identification of Food Spoilage Fungi Using MALDI-TOF MS: Spectral Database Development and Application to Species Complex

by Nolwenn Rolland, Victoria Girard, Valérie Monnin, Sandrine Arend, Guillaume Perrin, Damien Ballan, Rachel Beau, Valérie Collin, Maëlle D’Arbaumont, Amélie Weill, Franck Deniel, Sylvie Tréguer, Audrey Pawtowski, Jean-Luc Jany and Jérôme Mounier

J. Fungi 2024, 10(7), 456; https://doi.org/10.3390/jof10070456 - 28 Jun 2024

Abstract

Fungi, including filamentous fungi and yeasts, are major contributors to global food losses and waste due to their ability to colonize a very large diversity of food raw materials and processed foods throughout the food chain. In addition, numerous fungal species are mycotoxin [...] Read more.

Fungi, including filamentous fungi and yeasts, are major contributors to global food losses and waste due to their ability to colonize a very large diversity of food raw materials and processed foods throughout the food chain. In addition, numerous fungal species are mycotoxin producers and can also be responsible for opportunistic infections. In recent years, MALDI-TOF MS has emerged as a valuable, rapid and reliable asset for fungal identification in order to ensure food safety and quality. In this context, this study aimed at expanding the VITEK^® MS database with food-relevant fungal species and evaluate its performance, with a specific emphasis on species differentiation within species complexes. To this end, a total of 380 yeast and mold strains belonging to 51 genera and 133 species were added into the spectral database including species from five species complexes corresponding to Colletotrichum acutatum, Colletotrichum gloeosporioides, Fusarium dimerum, Mucor circinelloides complexes and Aspergillus series nigri. Database performances were evaluated by cross-validation and external validation using 78 fungal isolates with 96.55% and 90.48% correct identification, respectively. This study also showed the capacity of MALDI-TOF MS to differentiate closely related species within species complexes and further demonstrated the potential of this technique for the routine identification of fungi in an industrial context. Full article

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34 pages, 4900 KiB

Open AccessReview

A Survey on Visual Mamba

by Hanwei Zhang, Ying Zhu, Dan Wang, Lijun Zhang, Tianxiang Chen, Ziyang Wang and Zi Ye

Appl. Sci. 2024, 14(13), 5683; https://doi.org/10.3390/app14135683 (registering DOI) - 28 Jun 2024

Abstract

State space models (SSM) with selection mechanisms and hardware-aware architectures, namely Mamba, have recently shown significant potential in long-sequence modeling. Since the complexity of transformers’ self-attention mechanism is quadratic with image size, as well as increasing computational demands, researchers are currently exploring how [...] Read more.

State space models (SSM) with selection mechanisms and hardware-aware architectures, namely Mamba, have recently shown significant potential in long-sequence modeling. Since the complexity of transformers’ self-attention mechanism is quadratic with image size, as well as increasing computational demands, researchers are currently exploring how to adapt Mamba for computer vision tasks. This paper is the first comprehensive survey that aims to provide an in-depth analysis of Mamba models within the domain of computer vision. It begins by exploring the foundational concepts contributing to Mamba’s success, including the SSM framework, selection mechanisms, and hardware-aware design. Then, we review these vision Mamba models by categorizing them into foundational models and those enhanced with techniques including convolution, recurrence, and attention to improve their sophistication. Furthermore, we investigate the widespread applications of Mamba in vision tasks, which include their use as a backbone in various levels of vision processing. This encompasses general visual tasks, medical visual tasks (e.g., 2D/3D segmentation, classification, image registration, etc.), and remote sensing visual tasks. In particular, we introduce general visual tasks from two levels: high/mid-level vision (e.g., object detection, segmentation, video classification, etc.) and low-level vision (e.g., image super-resolution, image restoration, visual generation, etc.). We hope this endeavor will spark additional interest within the community to address current challenges and further apply Mamba models in computer vision. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Visual Processing)

20 pages, 805 KiB

Open AccessArticle

Identification of Novel GANT61 Analogs with Activity in Hedgehog Functional Assays and GLI1-Dependent Cancer Cells

by Dina Abu Rabe, Lhoucine Chdid, David R. Lamson, Christopher P. Laudeman, Michael Tarpley, Naglaa Elsayed, Ginger R. Smith, Weifan Zheng, Maria S. Dixon and Kevin P. Williams

Molecules 2024, 29(13), 3095; https://doi.org/10.3390/molecules29133095 (registering DOI) - 28 Jun 2024

Abstract

Aberrant activation of hedgehog (Hh) signaling has been implicated in various cancers. Current FDA-approved inhibitors target the seven-transmembrane receptor Smoothened, but resistance to these drugs has been observed. It has been proposed that a more promising strategy to target this pathway is at [...] Read more.

Aberrant activation of hedgehog (Hh) signaling has been implicated in various cancers. Current FDA-approved inhibitors target the seven-transmembrane receptor Smoothened, but resistance to these drugs has been observed. It has been proposed that a more promising strategy to target this pathway is at the GLI1 transcription factor level. GANT61 was the first small molecule identified to directly suppress GLI-mediated activity; however, its development as a potential anti-cancer agent has been hindered by its modest activity and aqueous chemical instability. Our study aimed to identify novel GLI1 inhibitors. JChem searches identified fifty-two compounds similar to GANT61 and its active metabolite, GANT61-D. We combined high-throughput cell-based assays and molecular docking to evaluate these analogs. Five of the fifty-two GANT61 analogs inhibited activity in Hh-responsive C3H10T1/2 and Gli-reporter NIH3T3 cellular assays without cytotoxicity. Two of the GANT61 analogs, BAS 07019774 and Z27610715, reduced Gli1 mRNA expression in C3H10T1/2 cells. Treatment with BAS 07019774 significantly reduced cell viability in Hh-dependent glioblastoma and lung cancer cell lines. Molecular docking indicated that BAS 07019774 is predicted to bind to the ZF4 region of GLI1, potentially interfering with its ability to bind DNA. Our findings show promise in developing more effective and potent GLI inhibitors. Full article

(This article belongs to the Special Issue Small-Molecule Modulators Targeting Emerging Therapeutic Pathways: Design, Synthesis and Biological Evaluation)

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9 pages, 528 KiB

Open AccessArticle

Population Growth Parameters of Scymnus nubilus Fed Single-Aphid Diets of Aphis fabae or Myzus persicae

by Isabel Borges, Guillaume J. Dury and António O. Soares

Insects 2024, 15(7), 486; https://doi.org/10.3390/insects15070486 (registering DOI) - 28 Jun 2024

Abstract

Life tables are an important tool to forecast the performance of biological control agents used in pest management programs, and they are often assessed in terms of population growth. In the present study, the suitability of the aphids Aphis fabae Scopoli and Myzus [...] Read more.

Life tables are an important tool to forecast the performance of biological control agents used in pest management programs, and they are often assessed in terms of population growth. In the present study, the suitability of the aphids Aphis fabae Scopoli and Myzus persicae (Sulzer) for the ladybird predator Scymnus nubilus Mulsant was assessed for the first time. For this, we evaluated and compared the life history traits of immature individuals and adults of the predator fed single-aphid diets and the consequences of the single-aphid diets for the demographic parameters. Scymnus nubilus that were fed A. fabae were significantly more fecund and presented a shorter immature development time than those fed M. persicae. The predators fed A. fabae had a significantly higher net reproductive rate, an intrinsic and finite rate of increase, while their doubling time was significantly lower than that of those fed M. persicae. The aphid species used in this study are new additions to the essential prey list of the ladybird, with the predator presenting a better biological performance than that found on the previously known essential prey species. Full article

(This article belongs to the Special Issue Advances in Understanding of the Ecology and Biodiversity of Coleoptera: Coccinellidae)

32 pages, 14477 KiB

Open AccessArticle

De Novo Design of Inhibitors of DNA Methyltransferase 1: A Critical Comparison of Ligand- and Structure-Based Approaches

by Diana L. Prado-Romero, Fernanda I. Saldívar-González, Iván López-Mata, Pedro A. Laurel-García, Adrián Durán-Vargas, Enrique García-Hernández, Norberto Sánchez-Cruz and José L. Medina-Franco

Biomolecules 2024, 14(7), 775; https://doi.org/10.3390/biom14070775 (registering DOI) - 28 Jun 2024

Abstract

Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in [...] Read more.

Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in combination with similarity searching to identify a novel DNMT inhibitor with a novel chemical scaffold and warrants further exploration. This study aimed to continue exploring the potential of de novo design to build epigenetic-focused libraries targeted toward DNMT1. Herein, we report the results of an in-depth and critical comparison of ligand- and structure-based de novo design of screening libraries focused on DNMT1. The newly designed chemical libraries focused on DNMT1 are freely available on GitHub. Full article

(This article belongs to the Special Issue Chemoinformatics and Molecular Modeling of Pharmacologically Active Biomolecules: A Themed Issue in Honor of Prof. José L. Medina-Franco)

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20 pages, 1048 KiB

Open AccessArticle

Container Yard Layout Design Problem with an Underground Logistics System

by Bin Lu, Mengxia Zhang, Xiaojie Xu, Chengji Liang, Yu Wang and Hongchen Liu

J. Mar. Sci. Eng. 2024, 12(7), 1103; https://doi.org/10.3390/jmse12071103 (registering DOI) - 28 Jun 2024

Abstract

In recent years, underground logistics systems have attracted more and more attention from scholars and are considered to be a promising new green and intelligent transportation mode. This paper proposes a yard design problem considering an underground container logistics system. The structure and [...] Read more.

In recent years, underground logistics systems have attracted more and more attention from scholars and are considered to be a promising new green and intelligent transportation mode. This paper proposes a yard design problem considering an underground container logistics system. The structure and workflow of the underground container logistics system are analyzed, and key features are recognized for the yard design problem, such as the container block layout direction, the lane configuration in the yard, and the number of container blocks. We formulate the problem into mathematical models under different scenarios of the key features with the comprehensive objective of maximizing the total throughput and minimizing the total operation cost simultaneously. An improved tabu search algorithm is designed to solve the problem. Experimental results show that the proposed algorithm can generate a satisfactory layout design solution for a real-size instance. Our research studies different container yard design options for introducing the underground logistics system into port terminals, which provides an important scientific foundation for promoting the application of underground container logistics systems. Full article

(This article belongs to the Section Ocean Engineering)

12 pages, 1745 KiB

Open AccessArticle

Data Mining Paths for Standard Weekly Training Load in Sub-Elite Young Football Players: A Machine Learning Approach

by José E. Teixeira, Samuel Encarnação, Luís Branquinho, Ryland Morgans, Pedro Afonso, João Rocha, Francisco Graça, Tiago M. Barbosa, António M. Monteiro, Ricardo Ferraz and Pedro Forte

J. Funct. Morphol. Kinesiol. 2024, 9(3), 114; https://doi.org/10.3390/jfmk9030114 (registering DOI) - 28 Jun 2024

Abstract

The aim of this study was to test a machine learning (ML) model to predict high-intensity actions and body impacts during youth football training. Sixty under-15, -17, and -19 sub-elite Portuguese football players were monitored over a 6-week period. External training load data [...] Read more.

The aim of this study was to test a machine learning (ML) model to predict high-intensity actions and body impacts during youth football training. Sixty under-15, -17, and -19 sub-elite Portuguese football players were monitored over a 6-week period. External training load data were collected from the target variables of accelerations (ACCs), decelerations (DECs), and dynamic stress load (DSL) using an 18 Hz global positioning system (GPS). Additionally, we monitored the perceived exertion and biological characteristics using total quality recovery (TQR), rating of perceived exertion (RPE), session RPE (sRPE), chronological age, maturation offset (MO), and age at peak height velocity (APHV). The ML model was computed by a feature selection process with a linear regression forecast and bootstrap method. The predictive analysis revealed that the players’ MO demonstrated varying degrees of effectiveness in predicting their DEC and ACC across different ranges of IQR. After predictive analysis, the following performance values were observed: DEC (

\bar{x}

_predicted = 41, β = 3.24, intercept = 37.0), lower IQR (IQR_predicted = 36.6, β = 3.24, intercept = 37.0), and upper IQR (IQR_predicted = 46 decelerations, β = 3.24, intercept = 37.0). The player’s MO also demonstrated the ability to predict their upper IQR (IQR_predicted = 51, β = 3.8, intercept = 40.62), lower IQR (IQR_predicted = 40, β = 3.8, intercept = 40.62), and ACC (

\bar{x}

_predicted = 46 accelerations, β = 3.8, intercept = 40.62). The ML model showed poor performance in predicting the players’ ACC and DEC using MO (MSE = 2.47–4.76; RMSE = 1.57–2.18: R² = −0.78–0.02). Maturational concerns are prevalent in football performance and should be regularly checked, as the current ML model treated MO as the sole variable for ACC, DEC, and DSL. Applying ML models to assess automated tracking data can be an effective strategy, particularly in the context of forecasting peak ACC, DEC, and bodily effects in sub-elite youth football training. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Sports Medicine, Physical Activity, Posture, and Rehabilitation)

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29 pages, 3181 KiB

Open AccessArticle

Biodiversity and Vegetation Succession in Vineyards, Moravia (Czech Republic)

by Erika Hurajová, Petra Martínez Barroso, Igor Děkanovský, Yentriani Rumeta Lumbantobing, Martin Jiroušek, Amir Mugutdinov, Ladislav Havel and Jan Winkler

Agriculture 2024, 14(7), 1036; https://doi.org/10.3390/agriculture14071036 (registering DOI) - 28 Jun 2024

Abstract

Maintaining biodiversity in agricultural landscapes is a major challenge for environmental protection in Europe. Vineyards rely heavily on agrotechnical interventions such as herbicide use and tillage for weed control, which affect biodiversity and can lead to soil erosion and resistant weed populations. The [...] Read more.

Maintaining biodiversity in agricultural landscapes is a major challenge for environmental protection in Europe. Vineyards rely heavily on agrotechnical interventions such as herbicide use and tillage for weed control, which affect biodiversity and can lead to soil erosion and resistant weed populations. The fragmentation of agricultural landscapes affects biodiversity by altering community composition and often reducing plant population sizes and genetic diversity. However, it can also increase the abundance of certain species and enhance population resilience to environmental change. Vineyards can support high levels of biodiversity and provide ecosystem services due to their semi-natural habitat structure. This research evaluates vegetation biodiversity using phytosociological relevés in different vineyards. Our results show that species richness and biodiversity are significantly influenced by vineyard age and management type. This study highlights differences in the representation of plant functional groups, with perennial taxa in grassy inter-row contributing to anti-erosion functions and serving as food sources for pollinators. The root zone around vine trunks shows an increase in invasive species with vineyard age, posing a risk to the agroecosystem. Vineyards predominantly follow a ruderal ecological strategy, using nutrients and light efficiently, while tolerating management disturbances. Understanding these dynamics is critical for developing sustainable vineyard management practices that support biodiversity and ecological resilience, counteract the homogenization of agricultural landscapes, and promote the coexistence of viticulture and species-rich ecosystems. Full article

(This article belongs to the Section Agricultural Systems and Management)

16 pages, 1920 KiB

Open AccessArticle

Estimation of Prediction Intervals for Performance Assessment of Building Using Machine Learning

by Khurram Shabbir, Muhammad Umair, Sung-Han Sim, Usman Ali and Mohamed Noureldin

Sensors 2024, 24(13), 4218; https://doi.org/10.3390/s24134218 (registering DOI) - 28 Jun 2024

Abstract

This study utilizes artificial neural networks (ANN) to estimate prediction intervals (PI) for seismic performance assessment of buildings subjected to long-term ground motion. To address the uncertainty quantification in structural health monitoring (SHM), the quality-driven lower upper bound estimation (QD-LUBE) has been opted [...] Read more.

This study utilizes artificial neural networks (ANN) to estimate prediction intervals (PI) for seismic performance assessment of buildings subjected to long-term ground motion. To address the uncertainty quantification in structural health monitoring (SHM), the quality-driven lower upper bound estimation (QD-LUBE) has been opted for global probabilistic assessment of damage at local and global levels, unlike traditional methods. A distribution-free machine learning model has been adopted for enhanced reliability in quantifying uncertainty and ensuring robustness in post-earthquake probabilistic assessments and early warning systems. The distribution-free machine learning model is capable of quantifying uncertainty with high accuracy as compared to previous methods such as the bootstrap method, etc. This research demonstrates the efficacy of the QD-LUBE method in complex seismic risk assessment scenarios, thereby contributing significant enhancement in building resilience and disaster management strategies. This study also validates the findings through fragility curve analysis, offering comprehensive insights into structural damage assessment and mitigation strategies. Full article

(This article belongs to the Special Issue Sensor Systems Empowered by AI, Big Data Processing, and Platform Technology)

16 pages, 1423 KiB

Open AccessArticle

Investigating Magnetohydrodynamic Motions of Oldroyd-B Fluids through the Application of a Circular Cylinder Filled with Porous Medium

by Constantin Fetecau and Dumitru Vieru

Processes 2024, 12(7), 1354; https://doi.org/10.3390/pr12071354 (registering DOI) - 28 Jun 2024

Abstract

We analytically investigated the magnetohydrodynamic motions of electrically conductive, incompressible Oldroyd-B fluids through an infinite circular cylinder filled with a porous medium. A general expression was established for the dimensionless velocity of fluid as a cylinder moves along its symmetry axis with an [...] Read more.

We analytically investigated the magnetohydrodynamic motions of electrically conductive, incompressible Oldroyd-B fluids through an infinite circular cylinder filled with a porous medium. A general expression was established for the dimensionless velocity of fluid as a cylinder moves along its symmetry axis with an arbitrary velocity; the expression can generate exact solutions for any motion of this fluid type, solving the discussed problem. Special cases were considered and validated through graphical investigation to illustrate important characteristics of fluid behavior. In application, this is the first presentation of an exact general expression for non-trivial shear stress related to the magnetohydrodynamic motions of Oldroyd-B fluids when a longitudinal time-dependent shear stress is applied to the fluid by a cylinder. Solutions for the motions of rate-type fluids are lacking. The graphical representations show that in the presence of a magnetic field or porous medium, fluids flow more slowly and the steady state is reached earlier. Full article

(This article belongs to the Special Issue Transport Processes in Porous Material and Porous Media: Latest Developments and New Approaches)

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21 pages, 374 KiB

Open AccessArticle

Generalized Linear Model (GLM) Applications for the Exponential Dispersion Model Generated by the Landau Distribution

by Shaul K. Bar-Lev, Xu Liu, Ad Ridder and Ziyu Xiang

Mathematics 2024, 12(13), 2021; https://doi.org/10.3390/math12132021 (registering DOI) - 28 Jun 2024

Abstract

The exponential dispersion model (EDM) generated by the Landau distribution, denoted by EDM-EVF (exponential variance function), belongs to the Tweedie scale with power infinity. Its density function does not have an explicit form and, as of yet, has not been used for statistical [...] Read more.

The exponential dispersion model (EDM) generated by the Landau distribution, denoted by EDM-EVF (exponential variance function), belongs to the Tweedie scale with power infinity. Its density function does not have an explicit form and, as of yet, has not been used for statistical aspects. Out of all EDMs belonging to the Tweedie scale, only two EDMs are steep and supported on the whole real line: the normal EDM with constant variance function and the EDM-EVF. All other absolutely continuous steep EDMs in the Tweedie scale are supported on the positive real line. This paper aims to accomplish an overall picture of all generalized linear model (GLM) applications belonging to the Tweedie scale by including the EDM-EVF. This paper introduces all GLM ingredients needed for its analysis, including the respective link function and total and scaled deviance. We study its analysis of deviance, derive the asymptotic properties of the maximum likelihood estimation (MLE) of the covariate parameters, and obtain the asymptotic distribution of deviance, using saddlepoint approximation. We provide numerical studies, which include estimation algorithm, simulation studies, and applications to three real datasets, and demonstrate that GLM using the EDM-EVF performs better than the linear model based on the normal EDM. An R package accompanies all of these. Full article

(This article belongs to the Section Probability and Statistics)

11 pages, 1194 KiB

Open AccessArticle

A Culture of Early Mobilization in Adult Intensive Care Units: Perspective and Competency of Physicians

by Ali Albarrati, Monira I. Aldhahi, Turki Almuhaid, Ali Alnahdi, Ahmed S. Alanazi, Abdulfattah S. Alqahtani and Rakan I. Nazer

Healthcare 2024, 12(13), 1300; https://doi.org/10.3390/healthcare12131300 (registering DOI) - 28 Jun 2024

Abstract

Background: Early mobility (EM) is vital in the intensive care unit (ICU) to counteract immobility-related effects. A multidisciplinary approach is key, as it requires precise initiation knowledge. However, physicians’ understanding of EM in adult ICU settings remains unexplored. This study was conducted to [...] Read more.

Background: Early mobility (EM) is vital in the intensive care unit (ICU) to counteract immobility-related effects. A multidisciplinary approach is key, as it requires precise initiation knowledge. However, physicians’ understanding of EM in adult ICU settings remains unexplored. This study was conducted to investigate the knowledge and clinical competency of physicians working in adult ICUs toward EM. Methods: This cross-sectional study enrolled 236 physicians to assess their knowledge of EM. A rigorously designed survey comprising 30 questions across the demographic, theoretical, and clinical domains was employed. The criteria for knowledge and competency were aligned with the minimum passing score (70%) stipulated for physician licensure by the medical regulatory authority in Saudi Arabia. Results: Nearly 40% of the respondents had more than 5 years of experience. One-third of the respondents received theoretical knowledge about EM as part of their residency training, and only 4% of the respondents attended formal courses to enhance their knowledge. Almost all the respondents (95%) stated their awareness of EM benefits and its indications and contraindications and considered it safe to mobilize patients on mechanical ventilators. However, 62.3% of the respondents did not support EM for critically ill patients on mechanical ventilators until weaning. In contrast, 51.7% of respondents advised EM for agitated patients with RASS > 2. Only 113 (47.9%) physicians were competent in determining the suitability of ICU patients for EM. For critically ill patients who should be mobilized, nearly 60% of physicians refused to initiate EM. Conclusions: This study underscores insufficient practical knowledge of ICU physicians about EM criteria, which leads to suboptimal decisions, particularly in complex ICU cases. These findings emphasize the need for enhanced training and education of physicians working in adult ICU settings to optimize patient care and outcomes in critical care settings. Full article

(This article belongs to the Section Critical Care)

11 pages, 1002 KiB

Open AccessSystematic Review

The Effect of Lumbopelvic Manipulation for Pain Reduction in Patellofemoral Pain Syndrome: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

by Long-Huei Lin, Ting-Yu Lin, Ke-Vin Chang, Wei-Ting Wu and Levent Özçakar

Life 2024, 14(7), 831; https://doi.org/10.3390/life14070831 (registering DOI) - 28 Jun 2024

Abstract

Patellofemoral pain syndrome (PFPS) is one of the most common etiologies of knee pain and might be relieved with lumbopelvic manipulation (LPM). This meta-analysis aimed to investigate the effects of LPM on pain reduction in patients with PFPS. Electronic databases were searched from [...] Read more.

Patellofemoral pain syndrome (PFPS) is one of the most common etiologies of knee pain and might be relieved with lumbopelvic manipulation (LPM). This meta-analysis aimed to investigate the effects of LPM on pain reduction in patients with PFPS. Electronic databases were searched from inception to December 2023 for randomized controlled trials (RCTs) investigating the effects of LPM on PFPS. The primary outcome was the change in visual analog or numeric rating scale scores assessing pain. Ten studies comprising 346 participants were included. Significant pain reduction was noted in the LPM group (Hedges’ g = −0.706, 95% confidence interval [CI] = −1.197 to −0.214, p = 0.005, = 79.624%) compared with the control group. Moreover, pain relief was more pronounced when LPM was combined with other physical therapies (Hedges’ g = −0.701, 95% CI = −1.386 to −0.017, p = 0.045, = 73.537%). No adverse events were reported during the LPM. The LPM appears to be a safe and effective adjuvant therapy for pain reduction in patients with PFPS. Clinicians should consider adding LPM to other physical therapies (e.g., quadriceps muscle strengthening) during the management of these patients. Full article

(This article belongs to the Special Issue Recent Advances in Diagnosis and Management of Musculoskeletal Pain)

3 pages, 609 KiB

Open AccessShort Note

5(S)-((3aR,4R,6aR)-2,2-Dimethyltetrahydrofuro[3,4-d][1,3]dioxol-4-yl)-2-phenyl-4,5-dihydrooxazole

by Liliana Boiaryna, Stéphane Guillarme and Christine Saluzzo

Molbank 2024, 2024(3), M1843; https://doi.org/10.3390/M1843 (registering DOI) - 28 Jun 2024

Abstract

5(S)-((3aR,4R,6aR)-2,2-Dimethyltetrahydrofuro[3,4-d][1,3]dioxol-4-yl)-2-phenyl-4,5-dihydrooxazole was synthesized from isosorbide in a three-step sequence, with an overall yield of 46%. The first reaction step involves a single regioselective ring-opening reaction of isosorbide with Me₃SiI in the presence of [...] Read more.

5(S)-((3aR,4R,6aR)-2,2-Dimethyltetrahydrofuro[3,4-d][1,3]dioxol-4-yl)-2-phenyl-4,5-dihydrooxazole was synthesized from isosorbide in a three-step sequence, with an overall yield of 46%. The first reaction step involves a single regioselective ring-opening reaction of isosorbide with Me₃SiI in the presence of acetone followed by an intramolecular nucleophilic substitution to transform the iodoalcohol into its corresponding epoxide. The last reaction allows the formation of the oxazoline ring directly from the epoxide with benzonitrile in the presence of BF₃·Et₂O. Full article

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Scheme 1

19 pages, 3374 KiB

Open AccessArticle

SARS-CoV-2 Nucleocapsid Protein Induces Tau Pathological Changes That Can Be Counteracted by SUMO2

by Franca Orsini, Marco Bosica, Annacarla Martucci, Massimiliano De Paola, Davide Comolli, Rosaria Pascente, Gianluigi Forloni, Paul E. Fraser, Ottavio Arancio and Luana Fioriti

Int. J. Mol. Sci. 2024, 25(13), 7169; https://doi.org/10.3390/ijms25137169 (registering DOI) - 28 Jun 2024

Abstract

Neurologic manifestations are an immediate consequence of SARS-CoV-2 infection, the etiologic agent of COVID-19, which, however, may also trigger long-term neurological effects. Notably, COVID-19 patients with neurological symptoms show elevated levels of biomarkers associated with brain injury, including Tau proteins linked to Alzheimer’s [...] Read more.

Neurologic manifestations are an immediate consequence of SARS-CoV-2 infection, the etiologic agent of COVID-19, which, however, may also trigger long-term neurological effects. Notably, COVID-19 patients with neurological symptoms show elevated levels of biomarkers associated with brain injury, including Tau proteins linked to Alzheimer’s pathology. Studies in brain organoids revealed that SARS-CoV-2 alters the phosphorylation and distribution of Tau in infected neurons, but the mechanisms are currently unknown. We hypothesize that these pathological changes are due to the recruitment of Tau into stress granules (SGs) operated by the nucleocapsid protein (NCAP) of SARS-CoV-2. To test this hypothesis, we investigated whether NCAP interacts with Tau and localizes to SGs in hippocampal neurons in vitro and in vivo. Mechanistically, we tested whether SUMOylation, a posttranslational modification of NCAP and Tau, modulates their distribution in SGs and their pathological interaction. We found that NCAP and Tau colocalize and physically interact. We also found that NCAP induces hyperphosphorylation of Tau and causes cognitive impairment in mice infected with NCAP in their hippocampus. Finally, we found that SUMOylation modulates NCAP SG formation in vitro and cognitive performance in infected mice. Our data demonstrate that NCAP induces Tau pathological changes both in vitro and in vivo. Moreover, we demonstrate that SUMO2 ameliorates NCAP-induced Tau pathology, highlighting the importance of the SUMOylation pathway as a target of intervention against neurotoxic insults, such as Tau oligomers and viral infection. Full article

(This article belongs to the Special Issue Abnormal Organelles and Protein Expression in Acute and Chronic Neurodegeneration)

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Graphical abstract

15 pages, 513 KiB

Open AccessArticle

Geometry Interaction Embeddings for Interpolation Temporal Knowledge Graph Completion

by Xuechen Zhao, Jinfeng Miao, Fuqiang Yang and Shengnan Pang

Mathematics 2024, 12(13), 2022; https://doi.org/10.3390/math12132022 (registering DOI) - 28 Jun 2024

Abstract

Knowledge graphs (KGs) have become a cornerstone for structuring vast amounts of information, enabling sophisticated AI applications across domains. The progression to temporal knowledge graphs (TKGs) introduces time as an essential dimension, allowing for a dynamic representation of entity relationships. Despite their potential, [...] Read more.

Knowledge graphs (KGs) have become a cornerstone for structuring vast amounts of information, enabling sophisticated AI applications across domains. The progression to temporal knowledge graphs (TKGs) introduces time as an essential dimension, allowing for a dynamic representation of entity relationships. Despite their potential, TKGs often suffer from incompleteness, necessitating the development of temporal knowledge graph completion (TKGC) techniques. These methods, particularly focusing on interpolation within the known timeframe, aim to infer missing temporal facts and enhance the predictive capabilities of TKGs. The prevalent reliance on Euclidean space modeling in TKGC methods presents challenges in capturing the complex, hierarchical, and time-varying nature of TKGs. To overcome these limitations, we introduced the attention-based geometry interaction embedding (ATGIE) method, a novel approach that leverages the strengths of multiple geometric spaces, i.e., Euclidean, hyperbolic, and hypersphere, to model the intricacies of TKGs more effectively. ATGIE employs an attention mechanism to dynamically weigh the contributions of different geometric spaces, allowing it to adaptively form reliable spatial structures based on interactive geometric information. This multi-space modeling not only captures the diverse relationships within TKGs but also facilitates a nuanced understanding of how entities and their relationships evolve over time. Through extensive experiments, we demonstrate ATGIE’s superiority in TKGC tasks, showcasing its improvement over existing methods, robustness to noise, and sensitivity to temporal dynamics. The results highlight ATGIE’s potential to advance the state-of-the-art in TKGC, offering a promising direction for research and application in the field. Full article

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