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12 pages, 1610 KiB

Open AccessArticle

Investigation of the Interfacial Fusion Bonding on Hybrid Additively Manufactured Components under Torsional Load

by Melike Kizak, Anna von Bartschikowski, Anna Trauth, Christian Heigl and Klaus Drechsler

Polymers 2024, 16(19), 2719; https://doi.org/10.3390/polym16192719 (registering DOI) - 26 Sep 2024

Hybrid manufacturing processes integrate multiple manufacturing techniques to leverage their respective advantages and mitigate their limitations. This study combines additive manufacturing and injection molding, aiming to efficiently produce components with extensive design flexibility and functional integration. The research explores the interfacial fusion bonding [...] Read more.

Hybrid manufacturing processes integrate multiple manufacturing techniques to leverage their respective advantages and mitigate their limitations. This study combines additive manufacturing and injection molding, aiming to efficiently produce components with extensive design flexibility and functional integration. The research explores the interfacial fusion bonding of hybrid additively manufactured components under torsional loading. Specifically, it examines the impact of various surface treatments on injection molded parts and the influence of different build chamber temperatures during additive manufacturing on torsional strength. Polycarbonate components, neat, with glass or carbon fiber-reinforcement, are produced and assessed for dimensional accuracy, torsional strength, and fracture behavior. The findings emphasize the critical role of surface treatment for the injection molded components before additive manufacturing. Additionally, the study identifies the influence of chamber temperatures on both dimensional accuracy and torsional strength. Among all investigated materials, plasma-treated neat samples exhibited the best torsional strength. The torsional strength was increased by up to

87 %

by actively heating the build chamber to 186 °C for neat polycarbonate. These insights aim to advance the quality and performance of hybrid additively manufactured components, broadening their application potential across diverse fields. Full article

(This article belongs to the Topic Advanced Composites Manufacturing and Plastics Processing)

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17 pages, 2323 KiB

Open AccessArticle

Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching

by Nahed Alowidi, Razan Ali, Munera Sadaqah and Fatmah M. A. Naemi

Diagnostics 2024, 14(19), 2119; https://doi.org/10.3390/diagnostics14192119 - 25 Sep 2024

Abstract

(1) Background: Globally, the kidney donor shortage has made the allocation process critical for patients awaiting a kidney transplant. Adopting Machine Learning (ML) models for donor–recipient matching can potentially improve kidney allocation processes when compared with traditional points-based systems. (2) Methods: This study [...] Read more.

(1) Background: Globally, the kidney donor shortage has made the allocation process critical for patients awaiting a kidney transplant. Adopting Machine Learning (ML) models for donor–recipient matching can potentially improve kidney allocation processes when compared with traditional points-based systems. (2) Methods: This study developed an ML-based approach for donor–recipient matching. A comprehensive evaluation was conducted using ten widely used classifiers (logistic regression, decision tree, random forest, support vector machine, gradient boosting, boost, CatBoost, LightGBM, naive Bayes, and neural networks) across three experimental scenarios to ensure a robust approach. The first scenario used the original dataset, the second used a merged version of the dataset, and the last scenario used a hierarchical architecture model. Additionally, a custom ranking algorithm was designed to identify the most suitable recipients. Finally, the ML-based donor–recipient matching model was integrated into a web-based platform called Nephron. (3) Results: The gradient boost model was the top performer, achieving a remarkable and consistent accuracy rate of 98% across the three experimental scenarios. Furthermore, the custom ranking algorithm outperformed the conventional cosine and Jaccard similarity methods in identifying the most suitable recipients. Importantly, the platform not only facilitated efficient patient selection and prioritisation for kidney allocation but can be flexibly adapted for other solid organ allocation systems built on similar criteria. (4) Conclusions: This study proposes an ML-based approach to optimize donor-recipient matching within the kidney allocation process. Successful implementation of this methodology demonstrates significant potential to enhance both efficiency and fairness in kidney transplantation. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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14 pages, 1541 KiB

Open AccessArticle

Heart Rate Variability Monitoring in Special Emergency Response Team Anaerobic-Based Tasks and Training

by Colin Tomes, Ben Schram, Elisa F. D. Canetti and Robin Orr

Safety 2024, 10(4), 84; https://doi.org/10.3390/safety10040084 - 25 Sep 2024

Abstract

The Law enforcement profession is known to impart high stress. Members of Special Weapons and Tactics (SWAT) teams are allocated particularly demanding law enforcement operations and may therefore attain high fitness levels but may accumulate excessive stress. Heart rate variability (HRV), an assessment [...] Read more.

The Law enforcement profession is known to impart high stress. Members of Special Weapons and Tactics (SWAT) teams are allocated particularly demanding law enforcement operations and may therefore attain high fitness levels but may accumulate excessive stress. Heart rate variability (HRV), an assessment of time differences between heartbeats, likely indicates holistic load in field settings. To date, though, little research measuring HRV has been conducted involving SWAT units. The purpose of this study was to explore HRV measurements following (1) annual firearms qualification and (2) potential stress exposure with respect to completion time on an anaerobically taxing obstacle course. Officers with greater obstacle course performance were hypothesized to also exhibit greater HRV. HRV was also expected to stratify personnel more effectively than heart rate. Prospective 3-lead ECGs were obtained from a cohort of male SWAT operators (n = 15) with 5.2 ± 4.3 years of experience at three time points throughout one training day. HRV was assessed by time, frequency, and non-linear domains. Differences between baseline and post-training values were significant as assessed by the Wilcoxon signed-ranks test for heart rate, SDRR, LF, HF, and SD2. An enter-method linear regression model predicted post-training HF HRV by obstacle course time; r² = 0.617, F (1,6) = 9.652, p = 0.021. Anaerobic performance may be highly valuable in SWAT units. HRV analysis may also be beneficial in measuring the psychophysiological impact of SWAT activities. Full article

(This article belongs to the Special Issue Occupational Health and Safety (OHS): Emerging Trends and Future Directions)

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21 pages, 8785 KiB

Open AccessArticle

Enhancing Unmanned Aerial Vehicle Path Planning in Multi-Agent Reinforcement Learning through Adaptive Dimensionality Reduction

by Haotian Shi, Zilin Zhao, Jiale Chen, Mengjie Zhou and Yang Liu

Drones 2024, 8(10), 521; https://doi.org/10.3390/drones8100521 - 25 Sep 2024

Abstract

Unmanned Aerial Vehicles (UAVs) have become increasingly important in various applications, including environmental monitoring, disaster response, and surveillance, due to their flexibility, efficiency, and ability to access hard-to-reach areas. Effective path planning for multiple UAVs exploring a target area is crucial for maximizing [...] Read more.

Unmanned Aerial Vehicles (UAVs) have become increasingly important in various applications, including environmental monitoring, disaster response, and surveillance, due to their flexibility, efficiency, and ability to access hard-to-reach areas. Effective path planning for multiple UAVs exploring a target area is crucial for maximizing coverage and operational efficiency. This study presents a novel approach to optimizing collaborative navigation for UAVs using multi-agent reinforcement learning (MARL). To enhance the efficiency of this process, we introduce the Adaptive Dimensionality Reduction (ADR) framework, which includes Autoencoders (AEs) and Principal Component Analysis (PCA) for dimensionality reduction and feature extraction. The ADR framework significantly reduces computational complexity by simplifying high-dimensional state spaces while preserving crucial information. Additionally, we incorporate communication modules to facilitate inter-UAV coordination, further improving path planning efficiency. Our experimental results demonstrate that the proposed approach significantly enhances exploration performance and reduces computational complexity, showcasing the potential of combining MARL with ADR techniques for advanced UAV navigation in complex environments. Full article

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11 pages, 241 KiB

Open AccessArticle

Evaluation of Diagnostic Performance of Three Commercial Interferon-Gamma Release Assays for Mycobacterium tuberculosis

by Richard Kutame, Gifty Boateng, Yaw Adusi-Poku, Felix Sorvor, Lorreta Antwi, Florence Agyemang-Bioh, Bright Ayensu, Vincent Gyau-Boateng and Franklin Asiedu-Bekoe

Diagnostics 2024, 14(19), 2130; https://doi.org/10.3390/diagnostics14192130 (registering DOI) - 25 Sep 2024

Abstract

Interferon-gamma release assays (IGRAs) have gained attention for the diagnosis of latent tuberculosis infection (LTBI) due to their higher specificity compared to the tuberculin skin test (TST). However, the IGRA’s performance varies across different populations. This study evaluated the diagnostic performance of three [...] Read more.

Interferon-gamma release assays (IGRAs) have gained attention for the diagnosis of latent tuberculosis infection (LTBI) due to their higher specificity compared to the tuberculin skin test (TST). However, the IGRA’s performance varies across different populations. This study evaluated the diagnostic performance of three IGRAs (TBF-FIA, TBF-ELISA, and QFT-Plus) in Ghana, comparing them among individuals exposed and unexposed to MTB infection. Conducted in TB clinics across three regions, this prospective and cross-sectional study included healthy individuals with no known TB exposure (unexposed group) and patients with confirmed active TB (exposed group). Blood samples were tested using all three assays as per the manufacturers’ guidelines. The TBF-ELISA showed 3.4% higher sensitivity but 4.6% lower specificity compared to QFT-Plus. The TBF-FIA had sensitivity of 78.5–87.3% and specificity of 82.9–90.0%. These findings indicate that while the three IGRAs offer similar diagnostic accuracy, the variations in specificity and limited data on assays like TBF-FIA require further investigation. Full article

(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)

13 pages, 1953 KiB

Open AccessArticle

A Maize Mutant Impaired in SL Biosynthesis (zmccd8) Shows a Lower Growth, an Altered Response to Nitrogen Starvation, and a Potential Secondary Effect on Drought Tolerance

by Laura Ravazzolo, Andrea Chichi, Franco Meggio, Leonardo Buzzicotti, Benedetto Ruperti, Serena Varotto, Mario Malagoli and Silvia Quaggiotti

Stresses 2024, 4(4), 614-626; https://doi.org/10.3390/stresses4040039 (registering DOI) - 25 Sep 2024

Abstract

Strigolactones (SLs) are essential phytohormones involved in plant development and interaction with the rhizosphere, regulating shoot branching, root architecture, and leaf senescence for nutrient reallocation. The Zea mays L. zmccd8 mutant, defective in SL biosynthesis, shows various architectural changes and reduced growth. This [...] Read more.

Strigolactones (SLs) are essential phytohormones involved in plant development and interaction with the rhizosphere, regulating shoot branching, root architecture, and leaf senescence for nutrient reallocation. The Zea mays L. zmccd8 mutant, defective in SL biosynthesis, shows various architectural changes and reduced growth. This study investigates zmccd8 and wild-type (WT) maize plants under two nutritional treatments (N-shortage vs. N-provision as urea). Morphometric analysis, chlorophyll and anthocyanin indexes, drought-related parameters, and gene expression were measured at specific time points. The zmccd8 mutant displayed reduced growth, such as shorter stems, fewer leaves, and lower kernel yield, regardless of the nutritional regime, confirming the crucial role of SLs. Additionally, zmccd8 plants exhibited lower chlorophyll content, particularly under N-deprivation, indicating SL necessity for proper senescence and nutrient mobilization. Increased anthocyanin accumulation in zmccd8 under N-shortage suggested a stress mitigation attempt, unlike WT plants. Furthermore, zmccd8 plants showed signs of increased water stress, likely due to impaired stomatal regulation, highlighting SLs role in drought tolerance. Molecular analysis confirmed higher expression of SL biosynthesis genes in WT under N-shortage, while zmccd8 lacked this response. These findings underscore SL importance in maize growth, stress responses, and nutrient allocation, suggesting potential agricultural applications for enhancing crop resilience. Full article

(This article belongs to the Topic Plant Responses to Environmental Stress)

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50 pages, 8622 KiB

Open AccessReview

A Review of the Mechanical Properties of and Long-Term Behavior Research on Box Girder Bridges with Corrugated Steel Webs

by Yuanxun Zheng, Jiahao Wang, Pan Guo and Yong Zhang

Buildings 2024, 14(10), 3056; https://doi.org/10.3390/buildings14103056 - 25 Sep 2024

Abstract

Based on an analysis of the extant literature, this paper summarizes the research progress on the mechanical properties and long-term behavior of corrugated steel web (CSW) box girder bridges. First, the research results of CSW box girder bridges in terms of the shear [...] Read more.

Based on an analysis of the extant literature, this paper summarizes the research progress on the mechanical properties and long-term behavior of corrugated steel web (CSW) box girder bridges. First, the research results of CSW box girder bridges in terms of the shear buckling performance (local shear buckling, overall shear buckling, and interaction buckling), bending performance, bending capacity, torsional capacity, and coefficient of internal force increase are summarized, along with the main factors affecting the mechanical performance of CSW box girder bridges. Second, based on research on the self-oscillation characteristics and dynamic response of CSW box girder bridges, the influence of structural parameters on the self-oscillation characteristics is analyzed. Finally, the long-term mechanical behavior of the CSW box girder bridges is analyzed in terms of fatigue, creep, and temperature effects. The existing research results demonstrate that there still exist deficiencies in the mechanical properties and long-term behavior of CSW box girder bridges, and this paper thus suggests a future research focus on CSW box girder bridges to provide a reference for further improving their basic theoretical system. Full article

(This article belongs to the Section Building Structures)

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12 pages, 4086 KiB

Open AccessCommunication

Design and Assembly of a Miniature Catheter Imaging System for In Vivo Heart Endoscopic Imaging

by Walter Messina, Lorenzo Niemitz, Simon Sorensen, Claire O’Dowling, Piotr Buszman, Stefan Andersson-Engels and Ray Burke

Sensors 2024, 24(19), 6216; https://doi.org/10.3390/s24196216 (registering DOI) - 25 Sep 2024

Abstract

In this paper, we present the design and fabrication of a novel chip-on-tip catheter, which uses a microcamera and optical fibres to capture in vivo images in a beating porcine heart thanks to a saline flush to clear the blood field. Here, we [...] Read more.

In this paper, we present the design and fabrication of a novel chip-on-tip catheter, which uses a microcamera and optical fibres to capture in vivo images in a beating porcine heart thanks to a saline flush to clear the blood field. Here, we demonstrate the medical utility and mechanical robustness of this catheter platform system, which could be used for other optical diagnostic techniques, surgical guidance, and clinical navigation. We also discuss some of the challenges and system requirements associated with developing a miniature prototype for such a study and present assembly instructions. Methods of clearing the blood field are discussed, including an integrated flush channel at the distal end. This permits the capture of images of the endocardial walls. The device was navigated under fluoroscopic guiding, through a guiding catheter to various locations of the heart, where images were successfully acquired. Images were captured at the intra-atrial septum, in the left atrium after a trans-septal cross procedure, and in the left ventricle, which are, to the best of our knowledge, the first images captured in an in vivo beating heart using endoscopic techniques. Full article

(This article belongs to the Special Issue Sensing Functional Imaging Biomarkers and Artificial Intelligence)

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22 pages, 3241 KiB

Open AccessArticle

Fragile Egos and Broken Hearts: Narcissistic and Borderline Personality Traits Predict Reactions to Potential Infidelity

by Avi Besser and Virgil Zeigler-Hill

Int. J. Environ. Res. Public Health 2024, 21(10), 1272; https://doi.org/10.3390/ijerph21101272 - 25 Sep 2024

Abstract

We examined the connections that narcissistic and borderline personality traits had with hypothetical responses to romantic infidelity in a sample of Israeli community members (N = 997). We distinguished between four forms of narcissism: extraverted narcissism (characterized by assertive self-enhancement), antagonistic narcissism (characterized [...] Read more.

We examined the connections that narcissistic and borderline personality traits had with hypothetical responses to romantic infidelity in a sample of Israeli community members (N = 997). We distinguished between four forms of narcissism: extraverted narcissism (characterized by assertive self-enhancement), antagonistic narcissism (characterized by defensiveness and hostility), neurotic narcissism (characterized by emotional distress), and communal narcissism (characterized by attempts to emphasize superiority over others by exaggerating communal characteristics such as being extraordinarily helpful). We also measured levels of borderline personality traits. Results showed that neurotic narcissism was strongly associated with heightened negative emotional responses, particularly in high-threat infidelity scenarios, aligning with predictions regarding emotional volatility. Antagonistic and communal narcissism showed detrimental effects on relationship evaluations primarily under low-threat conditions, indicating distinct patterns of defensiveness and vulnerability. Extraverted narcissism showed no significant association with emotional responses. Borderline traits were linked to intense emotional reactions across conditions, emphasizing their broad impact on perceived relational threats. These findings suggest that while some personality traits exacerbate reactions in less severe conditions, infidelity trauma can overwhelm these differences, underscoring the potential need for personalized therapeutic approaches. Discussion is focused on the implications for understanding personality traits in relational contexts and future research directions exploring varied threat manipulations. Full article

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11 pages, 738 KiB

Open AccessArticle

Antioxidant Activity of Planar Catechin Conjugated with Trolox

by Wakana Shimizu, Yoshimi Shoji, Kei Ohkubo, Hiromu Ito, Ikuo Nakanishi and Kiyoshi Fukuhara

Antioxidants 2024, 13(10), 1165; https://doi.org/10.3390/antiox13101165 (registering DOI) - 25 Sep 2024

Abstract

Planar catechin (PCat), a natural antioxidant with a fixed 3D catechin structure on a plane, exhibits radical-scavenging activity approximately five times stronger than the conventional catechin. We synthesized a compound, PCat-TrOH, by binding Trolox (TrOH), an α-tocopherol analog, to PCat to enhance its [...] Read more.

Planar catechin (PCat), a natural antioxidant with a fixed 3D catechin structure on a plane, exhibits radical-scavenging activity approximately five times stronger than the conventional catechin. We synthesized a compound, PCat-TrOH, by binding Trolox (TrOH), an α-tocopherol analog, to PCat to enhance its antioxidant effect against oxidative stress, such as lipid peroxidation. TrOH shows radical-scavenging activity about 6.5 times greater than PCat, and PCat-TrOH exhibited a similar level of radical-scavenging activity to TrOH. Additionally, PCat-TrOH demonstrated twice the radical-scavenging activity against reactive oxygen species compared to PCat or TrOH. This compound is also expected to exhibit an excellent antioxidant effect against lipid peroxidation caused by radical chain reactions, through interactions with vitamin C, similar to that in the case of α-tocopherol. Full article

(This article belongs to the Special Issue Bioactive Compounds: Antioxidant, Antibacterial, Anti-inflammatory Modulation)

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27 pages, 9970 KiB

Open AccessArticle

Factors Controlling Differences in Morphology and Fractal Characteristics of Organic Pores of Longmaxi Shale in Southern Sichuan Basin, China

by Yuanlin Wang, Denglin Han, Wei Lin, Yunqian Jia, Jizhen Zhang, Chenchen Wang and Binyu Ma

Fractal Fract. 2024, 8(10), 555; https://doi.org/10.3390/fractalfract8100555 - 25 Sep 2024

Abstract

Shale gas is a prospective cleaner energy resource and the exploration and development of shale gas has made breakthroughs in many countries. Structure deformation is one of the main controlling factors of shale gas accumulation and enrichment in complex tectonic areas in southern [...] Read more.

Shale gas is a prospective cleaner energy resource and the exploration and development of shale gas has made breakthroughs in many countries. Structure deformation is one of the main controlling factors of shale gas accumulation and enrichment in complex tectonic areas in southern China. In order to estimate the shale gas capacity of structurally deformed shale reservoirs, it is necessary to understand the systematic evolution of organic pores in the process of structural deformation. In particular, as the main storage space of high-over-mature marine shale reservoirs, the organic matter pore system directly affects the occurrence and migration of shale gas; however, there is a lack of systematic research on the fractal characteristics and deformation mechanism of organic pores under the background of different tectonic stresses. Therefore, to clarify the above issues, modular automated processing system (MAPS) scanning, low-pressure gas adsorption, quantitative evaluation of minerals by scanning (QEMSCAN), and focused ion beam scanning electron microscopy (FIB-SEM) were performed and interpreted with fractal and morphology analyses to investigate the deformation mechanisms and structure of organic pores from different tectonic units in Silurian Longmaxi shale. Results showed that in stress concentration areas such as around veins or high-angle fractures, the organic pore length-width ratio and the fractal dimension are higher, indicating that the pore is more obviously modified by stress. Under different tectonic backgrounds, the shale reservoir in Weiyuan suffered severe denudation and stronger tectonic compression during burial, which means that the organic pores are dominated by long strip pores and slit-shaped pores with high fractal dimension, while the pressure coefficient in Luzhou is high and the structural compression is weak, resulting in suborbicular pores and ink bottle pores with low fractal dimension. The porosity and permeability of different forms of organic pores are also obviously different; the connectivity of honeycomb pores with the smallest fractal dimension is the worst, that of suborbicular organic pores is medium, and that of long strip organic pores with the highest fractal dimension is the best. This study provides more mechanism discussion and case analysis for the microscopic heterogeneity of organic pores in shale reservoirs and also provides a new analysis perspective for the mechanism of shale gas productivity differences in different stress–strain environments. Full article

(This article belongs to the Special Issue Pore Structure and Fractal Characteristics in Unconventional Oil and Gas Reservoirs)

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26 pages, 19476 KiB

Open AccessArticle

Fractal Dimension-Based Multi-Focus Image Fusion via Coupled Neural P Systems in NSCT Domain

by Liangliang Li, Xiaobin Zhao, Huayi Hou, Xueyu Zhang, Ming Lv, Zhenhong Jia and Hongbing Ma

Fractal Fract. 2024, 8(10), 554; https://doi.org/10.3390/fractalfract8100554 - 25 Sep 2024

Abstract

In this paper, we introduce an innovative approach to multi-focus image fusion by leveraging the concepts of fractal dimension and coupled neural P (CNP) systems in nonsubsampled contourlet transform (NSCT) domain. This method is designed to overcome the challenges posed by the limitations [...] Read more.

In this paper, we introduce an innovative approach to multi-focus image fusion by leveraging the concepts of fractal dimension and coupled neural P (CNP) systems in nonsubsampled contourlet transform (NSCT) domain. This method is designed to overcome the challenges posed by the limitations of camera lenses and depth-of-field effects, which often prevent all parts of a scene from being simultaneously in focus. Our proposed fusion technique employs CNP systems with a local topology-based fusion model to merge the low-frequency components effectively. Meanwhile, for the high-frequency components, we utilize the spatial frequency and fractal dimension-based focus measure (FDFM) to achieve superior fusion performance. The effectiveness of the method is validated through extensive experiments conducted on three benchmark datasets: Lytro, MFI-WHU, and MFFW. The results demonstrate the superiority of our proposed multi-focus image fusion method, showcasing its potential to significantly enhance image clarity across the entire scene. Our algorithm has achieved advantageous values on metrics

Q_{A B / F}

,

Q_{C B}

,

Q_{C V}

,

Q_{E}

,

Q_{F M I}

,

Q_{G}

,

Q_{M I}

, and

Q_{N C I E}

. Full article

(This article belongs to the Special Issue Fractional Order Complex Systems: Advanced Control, Intelligent Estimation and Reinforcement Learning Image Processing Algorithms)

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17 pages, 5302 KiB

Open AccessArticle

Unsupervised Machine Learning-Based Singularity Models: A Case Study of the Taiwan Strait Basin

by Yan Zhang, Li Zhang, Zhenyu Lei, Fan Xiao, Yongzhang Zhou, Jing Zhao and Xing Qian

Fractal Fract. 2024, 8(10), 553; https://doi.org/10.3390/fractalfract8100553 - 25 Sep 2024

Abstract

The identification of geochemical anomalies in oil and gas indicators is a fundamental task in oil and gas exploration, as the process of oil and gas accumulation is a low probability event. Machine learning algorithms for anomaly detection are applicable to the identification [...] Read more.

The identification of geochemical anomalies in oil and gas indicators is a fundamental task in oil and gas exploration, as the process of oil and gas accumulation is a low probability event. Machine learning algorithms for anomaly detection are applicable to the identification of oil and gas geochemical anomalies related to oil and gas accumulation. However, when using oil and gas indicators for anomaly detection, the diversity of these indicators often leads to the influence of the indicator redundancy on the identification of such features. Therefore, it is particularly important to select appropriate oil and gas indicators for anomaly detection. In this study, a hybrid model combining unsupervised machine learning methods and singularity analysis methods was used to evaluate oil and gas indicator anomalies using geochemical data from the Taiwan Strait Basin. The models used in this study include the singularity index model (LSP), the principal component model combined with the singularity index model (PCA and LSP), and the cluster analysis combined with the principal component model and the singularity index model (CLA-PCA-LSP). PCA models can reduce the dimensions of the data and retain as much information as possible. CLA divides data samples into different groups, so that samples within the same group are more similar and samples between different groups are less similar. LSP is mainly used for measuring the setting and singular degree of local anomalies in multi-scale geochemistry, geophysics, and other types of local anomalies, and it has a unique advantage in extracting low and weak anomalies and nonlinear characteristics. The results of the study show that the results obtained using the CLA-PCA-LSP hybrid model are very similar to those obtained by performing PCA on the entire index and then calculating the singularity index. This also verifies that, for the study areas of the Jiulongjiang Depression and Jinjiang Depression, we can select oil and gas indicators that are favorable for exploration analysis, without including all indicators in the analysis scope, thereby improving the computational efficiency. The application of a singularity analysis method and generalized self-similarity principle in extracting the geochemical information of oil and gas indicators in the Taiwan Strait Basin highlights key technologies such as the identification of weak anomalies, decomposition of composite anomalies, and integration of spatial information. The combination anomalies delineated by the singularity analysis method and S-A method not only reflect the spatial relationship with known oil and gas reservoir distribution, but also show the multiple combination anomalies in unknown areas, providing favorable guidance for the next exploration direction in the Taiwan Strait Basin. Full article

(This article belongs to the Special Issue Fractals in Geology and Geochemistry)

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7 pages, 187 KiB

Open AccessEditorial

Advances in Steel and Composite Steel—Concrete Bridges and Buildings

by Marco Bonopera

Infrastructures 2024, 9(10), 169; https://doi.org/10.3390/infrastructures9100169 - 25 Sep 2024

Abstract

Construction steel has widely been used worldwide for developing infrastructure, e [...] Full article

(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)

22 pages, 8159 KiB

Open AccessArticle

Sustainability of Asphalt Mixtures Containing 50% RAP and Recycling Agents

by Ibrahim Elnaml, Louay N. Mohammad, Gaylon Baumgardner, Samuel Cooper III and Samuel Cooper, Jr.

Recycling 2024, 9(5), 85; https://doi.org/10.3390/recycling9050085 - 25 Sep 2024

Abstract

The substitution of virgin asphalt binder with reclaimed asphalt pavement (RAP) has environmental and economic merits, however, cracking susceptibility arises due to the aged asphalt binder within RAP. The objectives of this study are to (1) enhance the cracking resistance of asphalt mixtures [...] Read more.

The substitution of virgin asphalt binder with reclaimed asphalt pavement (RAP) has environmental and economic merits, however, cracking susceptibility arises due to the aged asphalt binder within RAP. The objectives of this study are to (1) enhance the cracking resistance of asphalt mixtures containing 50% RAP utilizing recycling agents (RAs) derived from six petroleum-based and bio-based materials, (2) conduct an environmental impact assessment (represented by global warming potential “GWP”) for high-RAP mixtures including RAs, and (3) estimate the cost effectiveness of including high-RAP content in asphalt mixtures. Based on the RAP asphalt binder performance grade (PG), base asphalt binder PG, and RAP content, the RA contents were determined to achieve a target asphalt binder of PG 76-22. A control mixture was benchmarked for comparison, specified for high-traffic volume roads, and contained PG 76-22 polymer-modified asphalt binder. The engineering performance of studied asphalt mixtures was evaluated using the Hamburg wheel-tracking (HWT), semi-circular bend, Illinois flexibility index, Ideal cracking tolerance, and thermal stress-restrained specimen tensile strength tests. It was found that petroleum-derived aromatic oil, soy-based oil, and tall oil fatty acid-based RAs demonstrated a successful restoration of aged RAP asphalt binder without compromising the permanent deformation resistance. The 50% RAP mixtures emitted less GWP by 41% and 42.9% using petroleum- and bio-oil RAs, respectively, and achieved a 31% cost reduction compared to the control mixtures. Full article

(This article belongs to the Special Issue The Use of Recycled Materials to Promote Pavement Sustainability Performance II)

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27 pages, 3994 KiB

Open AccessFeature PaperArticle

From Weeds to Feeds: Exploring the Potential of Wild Plants in Horticulture from a Centuries-Long Journey to an AI-Driven Future

by Diego Rivera, Diego-José Rivera-Obón, José-Antonio Palazón and Concepción Obón

Horticulturae 2024, 10(10), 1021; https://doi.org/10.3390/horticulturae10101021 - 25 Sep 2024

Abstract

Given the increasing food needs of humanity and the challenges cultivated species face in adapting to the climatic uncertainties we experience, it is urgent to cultivate new species. A highly relevant repertoire for this purpose is offered by the array of edible wild [...] Read more.

Given the increasing food needs of humanity and the challenges cultivated species face in adapting to the climatic uncertainties we experience, it is urgent to cultivate new species. A highly relevant repertoire for this purpose is offered by the array of edible wild plants. We analyzed data from Murcia (Spain), involving 61 species and 59 informants, and the Global Database of Wild Food Plants, which includes 15,000 species, 500 localities, and nearly 700 references. Using local consensus, global distribution, and GBIF occurrence data, we built simple unimodal or bimodal models to explore their limitations. Our study highlights that approximately 15,000 wild or feral plant species are consumed as food, underlining the urgent need to support existing crops with new species due to current food crises and climate irregularities. We examined wild plant diversity from a horticultural perspective, considering their relationships with weeds and invasive species. Partial criteria, such as local consensus or global use, were found insufficient for selecting candidate species. We propose developing a specific artificial intelligence to integrate various factors—ecological, nutritional, toxicological, agronomic, biogeographical, ethnobotanical, economic, and physiological—to accurately model a species’ potential for domestication and cultivation. We propose the necessary tools and a protocol for developing this AI-based model. Full article

(This article belongs to the Collection Prospects of Using Wild Plant Species in Horticulture)

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15 pages, 1723 KiB

Open AccessArticle

Prothioconazole Stress Reduces Bacterial Richness and Alters Enzyme Activity in Soybean Rhizosphere

by Ronggang Zhai, Mengchen Shi, Panpan Chen and Yi Wang

Toxics 2024, 12(10), 692; https://doi.org/10.3390/toxics12100692 - 25 Sep 2024

Abstract

Prothioconazole (PTC) is currently a popular triazole fungicide. In recent years, as the use of PTC has increased, there has been growing concern about its environmental and toxicological effects. Here, we studied the effect of PTC on the growth of soybean plants and [...] Read more.

Prothioconazole (PTC) is currently a popular triazole fungicide. In recent years, as the use of PTC has increased, there has been growing concern about its environmental and toxicological effects. Here, we studied the effect of PTC on the growth of soybean plants and further analyzed the enzyme activity and microbial community of rhizosphere soil after PTC treatment through 16S rRNA gene high-throughput sequencing and fungal ITS. Changes in structural diversity and species richness were measured using Simpson’s diversity index, Shannon’s diversity index and the Chao1 and ACE algorithms. The statistical t-test was applied to test whether the index values were significantly different between the two groups. The results showed that the contents of malondialdehyde (MDA) and H₂O₂ increased after the recommended dose of PTC, indicating that PTC has a strong toxic effect on plant growth, thus affecting the healthy growth of plants. In the presence of PTC, the species richness of fungi and bacteria decreased in all three soil types (black soil, yellow earth and red earth), and the community structure also changed significantly (the p-values were all less than 0.05). Proteobacteria, Actinomycetota, Bacteroidota and Acidobacteriota were the main bacteria, and the abundance of Acidobacteriota and Chloroflexi increased. The dominant fungal communities were Ascomycota and Mortierellomycota. The increased abundance of potentially beneficial microorganisms, such as Sphingomonadaceae, suggested that plants may be resistant to PTC stress by recruiting beneficial microorganisms. PICRUSt analysis showed that the metabolism-related functions and membrane transport pathway of rhizosphere bacterial community were inhibited after PTC stress. Spearman correlation analysis revealed a weak correlation between key fungal taxa and rhizosphere variables in the presence of PTC. Therefore, compared with those in the fungal community, the bacterial community was more likely to help plants resist PTC stress, indicating that these key fungal groups may indirectly help soybean growth under PTC stress by affecting the bacterial community. Full article

(This article belongs to the Special Issue Ecological Risk Assessment of Pesticides)

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15 pages, 3731 KiB

Open AccessArticle

Enhanced Tetracycline Adsorption Using KOH-Modified Biochar Derived from Waste Activated Sludge in Aqueous Solutions

by Jiazheng Ding, Jiahao Liang, Qinghong Wang, Xiang Tan, Wenyu Xie, Chunmao Chen, Changgang Li, Dehao Li, Jin Li and Xiaoqing Chen

Toxics 2024, 12(10), 691; https://doi.org/10.3390/toxics12100691 - 25 Sep 2024

Abstract

Antibiotic pollution poses a serious environmental concern worldwide, posing risks to ecosystems and human well-being. Transforming waste activated sludge into adsorbents for antibiotic removal aligns with the concept of utilizing waste to treat waste. However, the adsorption efficiency of these adsorbents is currently [...] Read more.

Antibiotic pollution poses a serious environmental concern worldwide, posing risks to ecosystems and human well-being. Transforming waste activated sludge into adsorbents for antibiotic removal aligns with the concept of utilizing waste to treat waste. However, the adsorption efficiency of these adsorbents is currently limited. This study identified KOH modification as the most effective method for enhancing tetracycline (TC) adsorption by sludge biochar through a comparative analysis of acid, alkali, and oxidant modifications. The adsorption characteristics of TC upon unmodified sludge biochar (BC) as well as KOH-modified sludge biochar (BC-KOH) were investigated in terms of equilibrium, kinetics, and thermodynamics. BC-KOH exhibited higher porosity, greater specific surface area, and increased abundance of oxygen-based functional groups compared to BC. The TC adsorption on BC-KOH conformed the Elovich and Langmuir models, with a maximum adsorption capacity of 243.3 mg/g at 298 K. The adsorption mechanisms included ion exchange, hydrogen bonding, pore filling, and electrostatic adsorption, as well as π-π interactions. Interference with TC adsorption on BC-KOH was observed with HCO₃⁻, PO₄³⁻, Ca²⁺, and Mg²⁺, whereas Cl⁻, NO₃⁻, and SO₄²⁻ ions exhibited minimal impact on the adsorption process. Following three cycles of utilization, there was a slight 5.94% reduction in the equilibrium adsorption capacity, yet the adsorption capacity remained 4.5 times greater than that of unmodified sludge BC, underscoring its significant potential for practical applications. This research provided new insights to the production and application of sludge biochar for treating antibiotic-contaminated wastewater. Full article

(This article belongs to the Special Issue Advanced Processes for Wastewater Treatment)

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13 pages, 1235 KiB

Open AccessArticle

Australian and United States Consumer Acceptance of Beef Brisket Cooked Using the Low and Slow Barbeque Method

by Jarrod Lees, Nicholas Hardcastle, Justin Johnston, Rohen Wong, Holly Cuthbertson, Garth Tarr, Andrea Garmyn, Markus Miller, Rod Polkinghorne and Peter McGilchrist

Foods 2024, 13(19), 3049; https://doi.org/10.3390/foods13193049 - 25 Sep 2024

Abstract

Meat Standards Australia (MSA) sensory protocols have been effectively utilized in beef for international consumers employing several cooking methods. Our objective was to compare the consumer response of Australian and American consumers to paired beef brisket samples utilizing a newly developed low and [...] Read more.

Meat Standards Australia (MSA) sensory protocols have been effectively utilized in beef for international consumers employing several cooking methods. Our objective was to compare the consumer response of Australian and American consumers to paired beef brisket samples utilizing a newly developed low and slow cooking method. Briskets were collected from Australian carcasses with diverse eating quality. Half of the briskets (n = 24) were retained in Australia and their pair was exported to Texas for consumer sensory testing. Naïve consumers (Australia; n = 240) and familiar consumers (USA; n = 240) evaluated paired barbequed briskets for tenderness, juiciness, flavor liking, and overall liking from 0 to 100 using a visual analogue scale, and a weighted composite meat quality score was later calculated. Australian consumers scored briskets lower for tenderness (−4.84 ± 1.70 points) and juiciness (−4.44 ± 1.55 points) and higher for flavor liking (3.48 ± 1.58 points); however, there was no difference between the countries for overall liking (p = 0.75) and combined meat quality score (p = 0.88). Differences between Australian and US consumers’ evaluations indicate that there is an impact of cultural background, potentially driven by Australia’s naivety to the low and slow barbeque cooking method. Full article

(This article belongs to the Special Issue Meat Quality, Sensory and Consumer Preferences and Attitudes)

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22 pages, 7280 KiB

Open AccessArticle

A Multi-Pointer Network for Multiple Agile Optical Satellite Scheduling Problem

by Zheng Liu, Wei Xiong, Chi Han and Kai Zhao

Aerospace 2024, 11(10), 792; https://doi.org/10.3390/aerospace11100792 - 25 Sep 2024

Abstract

With the rapid growth in space-imaging demands, the scheduling problem of multiple agile optical satellites has become a crucial problem in the field of on-orbit satellite applications. Because of the considerable solution space and complicated constraints, the existing methods suffer from a huge [...] Read more.

With the rapid growth in space-imaging demands, the scheduling problem of multiple agile optical satellites has become a crucial problem in the field of on-orbit satellite applications. Because of the considerable solution space and complicated constraints, the existing methods suffer from a huge computation burden and a low solution quality. This paper establishes a mathematical model of this problem, which aims to maximize the observation profit rate and realize the load balance, and proposes a multi-pointer network to solve this problem, which adopts multiple attention layers as the pointers to construct observation action sequences for multiple satellites. In the proposed network, a local feature-enhancement strategy, a remaining time-based decoding sorting strategy, and a feasibility-based task selection strategy are developed to improve the solution quality. Finally, extensive experiments verify that the proposed network outperforms the comparison algorithms in terms of solution quality, computation efficiency, and generalization ability and that the proposed three strategies significantly improve the solving ability of the proposed network. Full article

(This article belongs to the Topic Techniques and Science Exploitations for Earth Observation and Planetary Exploration)

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12 pages, 3833 KiB

Open AccessArticle

Research on the Stability of Salt Cavern Hydrogen Storage and Natural Gas Storage under Long-Term Storage Conditions

by Zhongzhong Liu and Yuxuan Liu

Processes 2024, 12(10), 2080; https://doi.org/10.3390/pr12102080 - 25 Sep 2024

Abstract

The stability of salt cavern storage during prolonged operation is a crucial indicator of its safety. This study focuses on an operational underground gas storage facility, conducting comparative numerical simulations for the storage of natural gas and hydrogen. We investigated the evolution of [...] Read more.

The stability of salt cavern storage during prolonged operation is a crucial indicator of its safety. This study focuses on an operational underground gas storage facility, conducting comparative numerical simulations for the storage of natural gas and hydrogen. We investigated the evolution of stability for natural gas and hydrogen storage under long-term storage conditions. The main conclusions are as follows: (1) A new equation for stress equilibrium and constitutive relations are derived. (2) At the same storage pressure, the effective stress at the same position in the interlayer is greater for hydrogen storage compared to natural gas storage, signifying a higher level of danger. (3) At the same storage pressure, the displacement at the cavity top for hydrogen storage is greater than that for natural gas storage. The displacement difference between the two is greatest at 9 MPa, amounting to 0.026 m. (4) Due to hydrogen’s lower dynamic viscosity and higher permeability, the depth and extent of the plastic zones within the interlayers are greater compared to natural gas. When the storage pressure is 15 MPa, the depth of the plastic zone within the interlayer can be up to 2.1 m greater than when storing natural gas, occurring in the third interlayer from the top. These research findings may serve as a valuable reference for determining the operational parameters of on-site salt cavern hydrogen storage facilities. Full article

(This article belongs to the Section Energy Systems)

15 pages, 27831 KiB

Open AccessArticle

Wind Field Reconstruction Method Using Incomplete Wind Data Based on Vision Mamba Decoder Network

by Min Chen, Haonan Wang, Wantong Chen and Shiyu Ren

Aerospace 2024, 11(10), 791; https://doi.org/10.3390/aerospace11100791 - 25 Sep 2024

Abstract

Accurate meteorological information is crucial for the safety of civil aviation flights. Complete wind field information is particularly helpful for planning flight routes. To address the challenge of accurately reconstructing wind fields, this paper introduces a deep learning neural network method based on [...] Read more.

Accurate meteorological information is crucial for the safety of civil aviation flights. Complete wind field information is particularly helpful for planning flight routes. To address the challenge of accurately reconstructing wind fields, this paper introduces a deep learning neural network method based on the Vision Mamba Decoder. The goal of the method is to reconstruct the original complete wind field from incomplete wind data distributed along air routes. This paper proposes improvements to the Vision Mamba model to fit our mission, showing that the developed model can accurately reconstruct the complete wind field. The experimental results demonstrate a mean absolute error (MAE) of wind speed of approximately 1.83 m/s, a mean relative error (MRE) of around 7.87%, an R-square value of about 0.92, and an MAE of wind direction of 5.78 degrees. Full article

(This article belongs to the Section Air Traffic and Transportation)

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30 pages, 4047 KiB

Open AccessArticle

Advanced Data Augmentation Techniques for Enhanced Fault Diagnosis in Industrial Centrifugal Pumps

by Dong-Yun Kim, Akeem Bayo Kareem, Daryl Domingo, Baek-Cheon Shin and Jang-Wook Hur

J. Sens. Actuator Netw. 2024, 13(5), 60; https://doi.org/10.3390/jsan13050060 - 25 Sep 2024

Abstract

This study presents an advanced data augmentation framework to enhance fault diagnostics in industrial centrifugal pumps using vibration data. The proposed framework addresses the challenge of insufficient defect data in industrial settings by integrating traditional augmentation techniques, such as Gaussian noise (GN) and [...] Read more.

This study presents an advanced data augmentation framework to enhance fault diagnostics in industrial centrifugal pumps using vibration data. The proposed framework addresses the challenge of insufficient defect data in industrial settings by integrating traditional augmentation techniques, such as Gaussian noise (GN) and signal stretching (SS), with advanced models, including Long Short-Term Memory (LSTM) networks, Autoencoders (AE), and Generative Adversarial Networks (GANs). Our approach significantly improves the robustness and accuracy of machine learning (ML) models for fault detection and classification. Key findings demonstrate a marked reduction in false positives and a substantial increase in fault detection rates, particularly in complex operational scenarios where traditional statistical methods may fall short. The experimental results underscore the effectiveness of combining these augmentation techniques, achieving up to a 30% improvement in fault detection accuracy and a 25% reduction in false positives compared to baseline models. These improvements highlight the practical value of the proposed framework in ensuring reliable operation and the predictive maintenance of centrifugal pumps in diverse industrial environments. Full article

(This article belongs to the Special Issue Fault Diagnosis in the Internet of Things Applications)

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23 pages, 8683 KiB

Open AccessArticle

MicroGravity Explorer Kit (MGX): An Open-Source Platform for Accessible Space Science Experiments

by Waldenê de Melo Moura, Carlos Renato dos Santos, Moisés José dos Santos Freitas, Adriano Costa Pinto, Luciana Pereira Simões and Alison Moraes

Aerospace 2024, 11(10), 790; https://doi.org/10.3390/aerospace11100790 - 25 Sep 2024

Abstract

The study of microgravity, a condition in which an object experiences near-zero weight, is a critical area of research with far-reaching implications for various scientific disciplines. Microgravity allows scientists to investigate fundamental physical phenomena influenced by Earth’s gravitational forces, opening up new possibilities [...] Read more.

The study of microgravity, a condition in which an object experiences near-zero weight, is a critical area of research with far-reaching implications for various scientific disciplines. Microgravity allows scientists to investigate fundamental physical phenomena influenced by Earth’s gravitational forces, opening up new possibilities in fields such as materials science, fluid dynamics, and biology. However, the complexity and cost of developing and conducting microgravity missions have historically limited the field to well-funded space agencies, universities with dedicated government funding, and large research institutions, creating a significant barrier to entry. This paper presents the MicroGravity Explorer Kit’s (MGX) design, a multifunctional platform for conducting microgravity experiments aboard suborbital rocket flights. The MGX aims to democratize access to microgravity research, making it accessible to high school students, undergraduates, and researchers. To ensure that the tool is versatile across different scenarios, the authors conducted a comprehensive literature review on microgravity experiments, and specific requirements for the MGX were established. The MGX is designed as an open-source platform that supports various experiments, reducing costs and accelerating development. The multipurpose experiment consists of a Jetson Nano computer with multiple sensors, such as inertial sensors, temperature and pressure, and two cameras with up to 4k resolution. The project also presents examples of codes for data acquisition and compression and the ability to process images and run machine learning algorithms to interpret results. The MGX seeks to promote greater participation and innovation in space sciences by simplifying the process and reducing barriers to entry. The design of a platform that can democratize access to space and research related to space sciences has the potential to lead to groundbreaking discoveries and advancements in materials science, fluid dynamics, and biology, with significant practical applications such as more efficient propulsion systems and novel materials with unique properties. Full article

(This article belongs to the Section Astronautics & Space Science)

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