Applied Sciences

17 pages, 8338 KiB

Open AccessArticle

Hybrid Huff-n-Puff Process for Enhanced Oil Recovery: Integration of Surfactant Flooding with CO₂ Oil Swelling

by Abhishek Ratanpara, Joshua Donjuan, Camron Smith, Marcellin Procak, Ibrahima Aboubakar, Philippe Mandin, Riyadh I. Al-Raoush, Rosalinda Inguanta and Myeongsub Kim

Appl. Sci. 2024, 14(24), 12078; https://doi.org/10.3390/app142412078 - 23 Dec 2024

Viewed by 577

Abstract

With increasing energy demands and depleting oil accessibility in reservoirs, the investigation of more effective enhanced oil recovery (EOR) methods for deep and tight reservoirs is imminent. This study investigates a novel hybrid EOR method, a synergistic approach of nonionic surfactant flooding with [...] Read more.

With increasing energy demands and depleting oil accessibility in reservoirs, the investigation of more effective enhanced oil recovery (EOR) methods for deep and tight reservoirs is imminent. This study investigates a novel hybrid EOR method, a synergistic approach of nonionic surfactant flooding with intermediate CO₂-based oil swelling. This study is focused on the efficiency of surfactant flooding and low-pressure oil swelling in oil recovery. We conducted a fluorescence-based microscopic analysis in a microchannel to explore the effect of sodium dodecyl sulfate (SDS) surfactant on CO₂ diffusion in Texas crude oil. Based on the change in emission intensity of oil, the results revealed that SDS enhanced CO₂ diffusion at low pressure in oil, primarily due to SDS aggregation and reduced interfacial tension at the CO₂ gas–oil interface. To validate the feasibility of our proposed EOR method, we adopted a ‘reservoir-on-a-chip’ approach, incorporating flooding tests in a polymethylmethacrylate (PMMA)-based micromodel. We estimated the cumulative oil recovery by comparing the results of two-stage surfactant flooding with intermediate CO₂ swelling at different pressures. This novel hybrid approach test consisted of a three-stage sequence: an initial flooding stage, followed by intermediate CO₂ swelling, and a second flooding stage. The results revealed an increase in cumulative oil recovery by nearly 10% upon a 2% (w/v) solution of SDS and water flooding compared to just water flooding. The results showed the visual phenomenon of oil imbibition during the surfactant flooding process. This innovative approach holds immense potential for future EOR processes, characterized by its unique combination of surfactant flooding and CO₂ swelling, yielding higher oil recovery. Full article

(This article belongs to the Special Issue Current Advances and Future Trend in Enhanced Oil Recovery)

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20 pages, 23391 KiB

Open AccessArticle

Full Life Cycle Evaluation of Stability Pile in High Slope with Multi-Layer Weak Interlayers

by Guie Shi, Jiaming Zhang, Mingzhi Lu, Fei Liu, Pengzheng Guo and Chenxi Wang

Appl. Sci. 2024, 14(24), 12077; https://doi.org/10.3390/app142412077 - 23 Dec 2024

Viewed by 393

Abstract

High slopes with multi-layer weak interlayers are a type of special slope that tends to fail due to the unfavorable mechanical properties of interlayers. In this study, the influence of the position, length, diameter, and ratio of on-center spacing to the pile diameter [...] Read more.

High slopes with multi-layer weak interlayers are a type of special slope that tends to fail due to the unfavorable mechanical properties of interlayers. In this study, the influence of the position, length, diameter, and ratio of on-center spacing to the pile diameter on the stability of such slopes is investigated using the three-dimensional strength reduction elastoplastic finite element method. Based on a high slope with multi-layer weak interlayers, two models were created, and three states (an initial state, a state with a safety factor of 1.35, and a limit equilibrium state) were considered. The pile can improve slope stability when the it is located at the lower to lower-middle part of a high slope. The resistance effect no longer has a strengthening property if it exceeds a critical pile length (28 m and 30 m in the two models); 30 m was found to be the optimal pile length for the high slope. As the diameter increased, the safety factor increased from 1.38 (1.37) to 1.41 (1.40) in Model 1 (or in Model 2), while the maximum compressive stress, the maximum shear stress of the pile, and the maximum displacement of the pile head decreased in the two models from 20.84 (81.24) MPa to 16.15 (18.8) MPa, 11.19 (42.02) MPa to 7.77 (10.43) MPa, and 714.1 (4585.00) mm to 396.3 (1272.00) mm, respectively. The pile diameter should be >1.4 m in such cases. When stress and displacement increased, the arching effect and the pile group effect weakened, and the safety factor decreased as the ratio of on-center spacing to diameter increased. The ratio should be <3 to ensure slope ability. Full article

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30 pages, 8481 KiB

Open AccessArticle

Sustainable Parking Space Management Using Machine Learning and Swarm Theory—The SPARK System

by Artur Janowski, Mustafa Hüsrevoğlu and Malgorzata Renigier-Bilozor

Appl. Sci. 2024, 14(24), 12076; https://doi.org/10.3390/app142412076 - 23 Dec 2024

Viewed by 580

Abstract

The utilization of contemporary technology enhances the efficiency of parking resource management, contributing to more liveable and sustainable cities. In response to the growing challenges of urbanization, intelligent parking systems have emerged as a crucial solution for optimizing parking management, reducing traffic congestion, [...] Read more.

The utilization of contemporary technology enhances the efficiency of parking resource management, contributing to more liveable and sustainable cities. In response to the growing challenges of urbanization, intelligent parking systems have emerged as a crucial solution for optimizing parking management, reducing traffic congestion, and minimizing pollution. The primary aim of this study is to present the concept of the developed web application that supports finding available parking spaces, embodied in the SPARK system (Smart Parking Assistance and Resource Knowledge). The integration of the YOLOv9 (You Only Look Once) segmentation algorithm with Artificial Bee Colony (ABC) optimization, combined with the use of crowdsourced data and deep learning for image analysis, significantly enhances the SPARK system’s operational efficiency. It enables rapid and precise detection of available parking spaces while ensuring robustness and continuous improvement. The accuracy of detecting available parking spaces in the presented system, estimated at 87.33%, is satisfactory compared to similar studies worldwide. Full article

(This article belongs to the Special Issue Crowd-Sourced Data and Deep Learning in Remote Sensing: Methods and Applications)

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21 pages, 5646 KiB

Open AccessArticle

A Fractal Prediction Model for the Friction Coefficient of Wet Clutch Friction Plates

by Jianfeng Cao, Sirui Yang, Zhigang Chen, Haoxuan Sun, Fenglian Ning and Heyun Bao

Appl. Sci. 2024, 14(24), 12075; https://doi.org/10.3390/app142412075 - 23 Dec 2024

Viewed by 497

Abstract

The motion state of the friction plate in a wet friction clutch is investigated by analyzing the causes of friction coefficient formation. This study establishes static and dynamic friction coefficient models for the friction plate based on a fractal model. The fractal dimension [...] Read more.

The motion state of the friction plate in a wet friction clutch is investigated by analyzing the causes of friction coefficient formation. This study establishes static and dynamic friction coefficient models for the friction plate based on a fractal model. The fractal dimension and scaling coefficient are studied to understand the fractal characteristics and variation patterns of the surface morphology of friction pairs during engagement. The MM6000 friction and wear testing machine is utilized for experiments, measuring surface morphology changes due to wear and changes in the engagement motion state of the friction plate. The theoretical content is compared and analyzed to verify the accuracy of the friction coefficient prediction model for the friction pair. Experiments are conducted on paper-based friction materials under different bonding pressures, and the relationship between bonding times and surface morphology changes is established. A comparative experiment between the joint motion state and dynamic simulation is performed, concluding that the micro convex contact model has certain accuracy in predicting the contact state of friction plates under various working conditions. Full article

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9 pages, 210 KiB

Open AccessArticle

Exploring the Socio-Demographic Profile of Non-Completion in Public Oral Healthcare Services: A Cross-Sectional Study in Melbourne, Victoria

by Rodrigo Mariño, Kelsey Price and Ramini Shankumar

Appl. Sci. 2024, 14(24), 12074; https://doi.org/10.3390/app142412074 - 23 Dec 2024

Viewed by 497

Abstract

(1) Background: Completion of the full oral health course of care (CoC) is essential to prevent further deterioration of oral and overall health. Understanding these patterns, particularly in public oral healthcare services, is crucial for improving access to and the delivery of care. [...] Read more.

(1) Background: Completion of the full oral health course of care (CoC) is essential to prevent further deterioration of oral and overall health. Understanding these patterns, particularly in public oral healthcare services, is crucial for improving access to and the delivery of care. This study aims to identify the socio-demographic and clinical characteristics of adult patients who did not complete required dental treatments within a 12-month period at Monash Health Dental Services (MHDS), Melbourne, Victoria. (2) Methods: Data were collected on patients’ course of care (CoC), socio-demographic characteristics, and clinical information from the MHDS Titanium electronic database. This study represents a secondary data analysis from adult patients who attended MHDS between November 2022 and October 2023, excluding emergency dental care visits. Logistic regression analyzed the socio-demographic and clinical variables affecting CoC. (3) Results: Our findings identified several significant predictors of incomplete CoC; being a non-priority group, mental health clients, refugees, and identifying as Aboriginal or Torres Strait Islanders (OR = 1.41; 95% CI: 1.08–1.84). Conversely, speaking a language other than English increased the odds of completing treatment (OR = 0.85; 95% CI: 0.74–0.98). By age, patients in the 36-to-55- or the 56-to-75-year-old age groups were more likely to be in the incomplete group (OR = 1.65; 95% CI: 1.37–1.98; and OR = 1.43; 95% CI: 1.22–1.66, respectively). (4) Conclusions: This study identified predictors of discontinued care, emphasizing accessibility and equitable outcomes for users of public oral healthcare. The findings indicate that the predictors of course of care (CoC) completion differ from barriers to accessing care. This highlights key objectives in public health dentistry, focusing on improving accessibility and promoting equitable oral health outcomes for vulnerable populations. Full article

16 pages, 15762 KiB

Open AccessArticle

A LiDAR-Based Backfill Monitoring System

by Xingliang Xu, Pengli Huang, Zhengxiang He, Ziyu Zhao and Lin Bi

Appl. Sci. 2024, 14(24), 12073; https://doi.org/10.3390/app142412073 - 23 Dec 2024

Viewed by 413

Abstract

A backfill system in underground mines supports the walls and roofs of mined-out areas and improves the structural integrity of mines. However, there has been a significant gap in the visualization and monitoring of the backfill progress. To better observe the process of [...] Read more.

A backfill system in underground mines supports the walls and roofs of mined-out areas and improves the structural integrity of mines. However, there has been a significant gap in the visualization and monitoring of the backfill progress. To better observe the process of the paste backfill material filling the tunnels, a LiDAR-based backfill monitoring system is proposed. As long as the rising top surface of the backfill material enters the LiDAR range, the proposed system can compute the plane coefficient of this surface. The intersection boundary of the tunnel and the backfill material can be obtained by substituting the plane coefficient into the space where the initial tunnel is located. A surface point generation and slurry point determination algorithm are proposed to obtain the point cloud of the backfill body based on the intersection boundary. After Poisson surface reconstruction and volume computation, the point cloud model is reconstructed into a 3D mesh, and the backfill progress is digitized as the ratio of the backfill body volume to the initial tunnel volume. The volumes of the meshes are compared with the results computed by two other algorithms; the error is less than 1%. The time to compute a set of data increases with the amount of data, ranging from 8 to 20 s, which is sufficient to update a set of data with a tiny increase in progress. As the digitized results update, the visualization progress is transmitted to the mining control center, allowing unexpected problems inside the tunnel to be monitored and addressed based on the messages provided by the proposed system. Full article

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21 pages, 2619 KiB

Open AccessArticle

MIRA-ChatGLM: A Fine-Tuned Large Language Model for Intelligent Risk Assessment in Coal Mining

by Yi Sun, Chao Zhang, Chen Wang and Ying Han

Appl. Sci. 2024, 14(24), 12072; https://doi.org/10.3390/app142412072 - 23 Dec 2024

Viewed by 640

Abstract

Intelligent mining risk assessment (MIRA) is a vital approach for enhancing safety and operational efficiency in mining. In this study, we introduce MIRA-ChatGLM, which leverages pre-trained large language models (LLMs) for the domain of gas risk assessment in coal mines. We meticulously constructed [...] Read more.

Intelligent mining risk assessment (MIRA) is a vital approach for enhancing safety and operational efficiency in mining. In this study, we introduce MIRA-ChatGLM, which leverages pre-trained large language models (LLMs) for the domain of gas risk assessment in coal mines. We meticulously constructed a dataset specifically designed for mining risk analysis and performed parameter-efficient fine-tuning on the locally deployed GLM-4-9B-chat base model to develop MIRA-ChatGLM. By utilizing consumer-grade GPUs and employing LoRA and various levels of quantization algorithms such as QLoRA, we investigated the impact of different data scales and instruction settings on model performance. The evaluation results show that MIRA-ChatGLM achieved excellent performance with BLEU-4, ROUGE-1, ROUGE-2, and ROUGE-L scores of 84.47, 90.63, 86.88, and 90.63, respectively, highlighting its outstanding performance in coal mine gas risk assessment. Through comparative experiments with other large language models of similar size and manual evaluation, MIRA-ChatGLM demonstrated superior performance across multiple key metrics, fully demonstrating its tremendous potential in intelligent mine risk assessment and decision support. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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19 pages, 1844 KiB

Open AccessArticle

Coordination of Speaking Opportunities in Virtual Reality: Analyzing Interaction Dynamics and Context-Aware Strategies

by Jiadong Chen, Chenghao Gu, Jiayi Zhang, Zhankun Liu, Boxuan Ma and Shin‘ichi Konomi

Appl. Sci. 2024, 14(24), 12071; https://doi.org/10.3390/app142412071 - 23 Dec 2024

Viewed by 426

Abstract

This study explores the factors influencing turn-taking coordination in virtual reality (VR) environments, with a focus on identifying key interaction dynamics that affect the ease of gaining speaking opportunities. By analyzing VR interaction data through logistic regression and clustering, we identify significant variables [...] Read more.

This study explores the factors influencing turn-taking coordination in virtual reality (VR) environments, with a focus on identifying key interaction dynamics that affect the ease of gaining speaking opportunities. By analyzing VR interaction data through logistic regression and clustering, we identify significant variables impacting turn-taking success and categorize typical interaction states that present unique coordination challenges. The findings reveal that features related to interaction proactivity, individual status, and communication quality significantly impact turn-taking outcomes. Furthermore, clustering analysis identifies five primary interaction contexts: high competition, intense interaction, prolonged single turn, high-status role, and low activity, each with unique turn-taking coordination requirements. This work provides insights into enhancing turn-taking support systems in VR, emphasizing contextually adaptive feedback to reduce speaking overlap and turn-taking failures, thereby improving overall interaction flow in immersive environments. Full article

(This article belongs to the Special Issue Advancing Human–Machine Interaction Through Intelligent Sensors and Technology)

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15 pages, 2586 KiB

Open AccessArticle

SocialJGCF: Social Recommendation with Jacobi Polynomial-Based Graph Collaborative Filtering

by Heng Lu and Ziwei Chen

Appl. Sci. 2024, 14(24), 12070; https://doi.org/10.3390/app142412070 - 23 Dec 2024

Viewed by 412

Abstract

With the flourishing of social media platforms, data in social networks, especially user-generated content, are growing rapidly, which makes it hard for users to select relevant content from the overloaded data. Recommender systems are thus developed to filter user-relevant content for better user [...] Read more.

With the flourishing of social media platforms, data in social networks, especially user-generated content, are growing rapidly, which makes it hard for users to select relevant content from the overloaded data. Recommender systems are thus developed to filter user-relevant content for better user experiences and also the commercial needs of social platform providers. Graph neural networks have been widely applied in recommender systems for better recommendation based on past interactions between users and corresponding items due to the graph structure of social data. Users might also be influenced by their social connections, which is the focus of social recommendation. Most works on recommendation systems try to obtain better representations of user embeddings and item embeddings. Compared with recommendation systems only focusing on interaction graphs, social recommendation has an additional task of combining user embedding from the social graph and interaction graph. This paper proposes a new method called SocialJGCF to address these problems, which applies Jacobi-Polynomial-Based Graph Collaborative Filtering (JGCF) to the propagation of the interaction graph and social graph, and a graph fusion is used to combine the user embeddings from the interaction graph and social graph. Experiments are conducted on two real-world datasets, epinions and LastFM. The result shows that SocialJGCF has great potential in social recommendation, especially for cold-start problems. Full article

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11 pages, 4061 KiB

Open AccessArticle

Circular Catalytic Hydrogen/Methanol Plate Burner with Stackable Clover Channels Supporting Rapid Start-Up and Stable Operation for Highly Efficient Reformer System

by Fan-Gang Tseng, Wen-Hsin Hu, He-Jia Li and Xiang-Jun Wang

Appl. Sci. 2024, 14(24), 12069; https://doi.org/10.3390/app142412069 - 23 Dec 2024

Viewed by 385

Abstract

This study proposes a platinum catalytic plate burner with a clover-shaped microchannel design to reduce the maximum temperature difference (ΔT_max) and improve long-term hydrogen production (HP) performance in an autothermal methanol steam reforming (ATMSR) microreactor. The burner integrates with a plate [...] Read more.

This study proposes a platinum catalytic plate burner with a clover-shaped microchannel design to reduce the maximum temperature difference (ΔT_max) and improve long-term hydrogen production (HP) performance in an autothermal methanol steam reforming (ATMSR) microreactor. The burner integrates with a plate reformer within a cylindrical adiabatic container. By optimizing catalyst arrangement and incorporating a parallel clover-type microchannel design, thermal gradients inside the burner are minimized, enabling better operation conditions for the plate reformer. Three Pt catalyst gradients (50/50, 40/60, and 30/70) reduce ΔT_max from 48.2 °C and 38.3 °C to 25.8 °C. Additionally, the startup time to 250 °C is reduced from 35, 25, and 14 min, respectively. The integration of the plate burner and reformer with the 30/70 catalyst type shows a higher methanol conversion rate (98%), better hydrogen yield, and lower CO selectivity compared to the 50/50 type. Long-term testing for 30 h shows a low catalyst degradation rate, making it suitable for sustained operation. Full article

(This article belongs to the Special Issue Sustainable Alternative Fuels and Advanced Combustion Techniques)

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21 pages, 2460 KiB

Open AccessArticle

Multi-Agent System for Emulating Personality Traits Using Deep Reinforcement Learning

by Georgios Liapis and Ioannis Vlahavas

Appl. Sci. 2024, 14(24), 12068; https://doi.org/10.3390/app142412068 - 23 Dec 2024

Viewed by 428

Abstract

Conventional personality assessment methods depend on subjective input, while game-based AI predictive methods offer a dynamic and objective framework. However, training these models requires large and labeled datasets, which are challenging to obtain from real players with diverse personality traits. In this paper, [...] Read more.

Conventional personality assessment methods depend on subjective input, while game-based AI predictive methods offer a dynamic and objective framework. However, training these models requires large and labeled datasets, which are challenging to obtain from real players with diverse personality traits. In this paper, we propose a multi-agent system using Deep Reinforcement Learning in a game environment to generate the necessary labeled data. Each agent is trained with custom reward functions based on the HiDAC system that encourages trait-aligned behaviors to emulate specific personality traits based on the OCEAN personality trait model. The Multi-Agent Posthumous Credit Assignment (MA-POCA) algorithm facilitates continuous learning, allowing agents to emulate behaviors through self-play. The resulting gameplay data provide diverse, high-quality samples. This approach allows for robust individual and team assessments, as agent interactions reveal the impact of personality traits on team dynamics and performance. Ultimately, this methodology provides a scalable, unbiased methodology for human personality evaluation in various settings, establishing new standards for data-driven assessment methods. Full article

(This article belongs to the Special Issue Deep Reinforcement Learning for Multiagent Systems)

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26 pages, 3079 KiB

Open AccessArticle

Analyzing Student Behavioral Patterns in MOOCs Using Hidden Markov Models in Distance Education

by Vassilios S. Verykios, Nikolaos S. Alachiotis, Evgenia Paxinou and Georgios Feretzakis

Appl. Sci. 2024, 14(24), 12067; https://doi.org/10.3390/app142412067 - 23 Dec 2024

Viewed by 457

Abstract

The log files of Massive Open Online Courses (MOOCs) reveal useful information that can help interpret student behavior. In this study, we focus on student performance based on their access to course resources and the grades they achieve. We define states as the [...] Read more.

The log files of Massive Open Online Courses (MOOCs) reveal useful information that can help interpret student behavior. In this study, we focus on student performance based on their access to course resources and the grades they achieve. We define states as the Moodle resources and quiz grades for each student ID, considering participation in resources such as wikis and forums. We use efficient Hidden Markov Models to interpret the abundance of information provided in the Moodle log files. The transitions among certain resources for each student or groups of students are determined as behaviors. Other studies employ Machine Learning and Pattern Classification algorithms to recognize these behaviors. As an example, we visualize these transitions for individual learners. Additionally, we have created row and column charts to present our findings in a comprehensible manner. For implementing the proposed methodology, we use the R programming language. The dataset that we use was obtained from Kaggle and pertains to a MOOC of 4037 students. Full article

(This article belongs to the Special Issue Advances in Machine Learning and Data Mining: Emerging Trends and Applications)

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31 pages, 6688 KiB

Open AccessArticle

Study on the Interaction Mechanism Between Urbanization and Ecological Resilience—The Case of Urban Agglomeration on the North Slope of Tianshan Mountain

by Yanjun Tong, Tiange Shi, Shubao Zhang, Yunjie Cheng, Jiangyan Liang and Jun Lei

Appl. Sci. 2024, 14(24), 12066; https://doi.org/10.3390/app142412066 - 23 Dec 2024

Viewed by 476

Abstract

Although it promotes national economic development, urbanization causes regional ecosystems to suffer from disturbances and impacts that cannot be completely avoided. Ecosystems urgently need to improve their resilience; however, existing studies lack an analysis of the interaction between urbanization and ecological resilience. In [...] Read more.

Although it promotes national economic development, urbanization causes regional ecosystems to suffer from disturbances and impacts that cannot be completely avoided. Ecosystems urgently need to improve their resilience; however, existing studies lack an analysis of the interaction between urbanization and ecological resilience. In this study, the interaction between urbanization and ecological resilience is investigated, taking the urban agglomeration on the north slope of Tianshan Mountain (UANST) as a study area and using the entropy value method to construct an urbanization evaluation system. Based on land use change data, an ecological resilience evaluation model is constructed using the InVSET model, the landscape pattern index, and the unit area value equivalent factor method. The degree of coupling and coordination of the interaction coupling between urbanization and ecological resilience are measured for the years 1990–2020, and their internal action mechanisms are analyzed. The results show that (1) with the development of urbanization, ecological resilience shows a decreasing and then increasing double “U”-shaped change characteristic. (2) The coupling degree of urbanization and ecological resilience in the UANST increased from 0.6888 to 0.9485, and the coordination degree increased from 0.3367 to 0.4410. (3) There are three types of coupling coordination: basic coordination, basic dysfunction, and serious dysfunction. Basic coordination is mainly distributed in the central part of the urban agglomeration, and basic dysfunction and serious dysfunction are mainly concentrated on the east and west sides; the overall trend is to shift from dysfunction to coordination. (4) Economic urbanization plays a driving role, and population urbanization, spatial urbanization, and social urbanization have an inhibitory role in the degree of coupling coordination; base quality and structural stability have a driving role in the degree of coupling coordination, while ecological services have an inhibitory role; and the population density, the proportion of built-up area to the total land area of the city, and the value of ecosystem services have a stronger influence on the level of coupling coordination. Full article

(This article belongs to the Topic Sustainable Development and Coordinated Governance of Urban and Rural Areas under the Guidance of Ecological Wisdom)

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40 pages, 5219 KiB

Open AccessArticle

Adaptive Path Planning for UAV-Based Pollution Sampling

by Mateusz Kosior, Piotr Przystałka and Wawrzyniec Panfil

Appl. Sci. 2024, 14(24), 12065; https://doi.org/10.3390/app142412065 - 23 Dec 2024

Viewed by 382

Abstract

Unmanned Aerial Vehicles (UAVs) continue to gain popularity in applications such as military reconnaissance, environmental monitoring in remote locations, and package delivery. High-Altitude Long-Endurance (HALE) UAVs can remain airborne for extended periods, enabling air pollution measurements to be conducted across a wide range [...] Read more.

Unmanned Aerial Vehicles (UAVs) continue to gain popularity in applications such as military reconnaissance, environmental monitoring in remote locations, and package delivery. High-Altitude Long-Endurance (HALE) UAVs can remain airborne for extended periods, enabling air pollution measurements to be conducted across a wide range of altitudes, from a few hundred meters above ground level to the lower stratosphere. However, the challenges posed by dynamic environmental conditions and strict energy limitations necessitate the use of adaptive path planning algorithms that account for UAV and environmental models. To address these challenges, we propose a two-tier Adaptive Path Planner (APP), which comprises a Global Path Planner (GPP) and a Local Path Planner (LPP). The GPP, operating offline, generates obstacle-free, energy-efficient paths that adhere to the UAV’s kinematic constraints, while the LPP dynamically recalculates alternative routes in real time when obstacles arise. The APP leverages a novel data-driven environmental model, integrating terrain, wind, airspace, and measurement maps. Extensive Model-in-the-Loop testing was conducted to evaluate various single-objective optimization algorithms for the GPP. Subsequently, the APP was successfully validated in simulation scenarios inspired by real-world pollution monitoring missions conducted in Poland and the Arctic. Additionally, the proposed approach was tested under real-world conditions, demonstrating significant application potential. A comparative analysis of the generated paths demonstrated that the APP effectively replaces human operators. Further testing confirmed the APP’s capability for adaptive re-planning during mission execution. Full article

(This article belongs to the Special Issue Smart Manufacturing and Materials Ⅱ)

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20 pages, 1917 KiB

Open AccessArticle

Distributed Formation Control for Underactuated, Unmanned Surface Vehicles with Uncertainties and Disturbances

by Wenbin Huang, Yuxin Zheng, Lei Zhang, Yanhao Li and Xi Chen

Appl. Sci. 2024, 14(24), 12064; https://doi.org/10.3390/app142412064 - 23 Dec 2024

Viewed by 400

Abstract

This paper investigates the distributed formation control problem of underactuated unmanned surface vehicles (UUSVs) with uncertainties and disturbances and proposes a novel distributed formation controller. The proposed controller redefines the dynamic and kinematic models for each UUSV, which reduces the complexity of the [...] Read more.

This paper investigates the distributed formation control problem of underactuated unmanned surface vehicles (UUSVs) with uncertainties and disturbances and proposes a novel distributed formation controller. The proposed controller redefines the dynamic and kinematic models for each UUSV, which reduces the complexity of the underactuated controller design. Dynamic surface control (DSC) is employed to eliminate the repeated derivatives of the virtual control law, which is crucial for the generation of real-time control signals. The proposed controller integrates neural network approximation with MLP-based adaptive laws to enhance the model’s resistance to disturbances. Then, an auxiliary adaptive law is designed for each UUSV to obtain a continuous controller under the compensation of approximate errors and disturbances. The results demonstrate that the controller achieves the desired goals for the formation control, and all control signals are guaranteed to be semi-global uniformly ultimately bounded (SGUUB). The final simulation results thoroughly prove the effectiveness of the theoretical results. Full article

(This article belongs to the Special Issue Modeling, Guidance and Control of Marine Robotics)

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16 pages, 865 KiB

Open AccessReview

Radiotherapy for Rectal Cancer and Radiation-Induced Malignancies from Epidemiological and Dosimetric Data

by Stefanos Kachris and Michalis Mazonakis

Appl. Sci. 2024, 14(24), 12063; https://doi.org/10.3390/app142412063 - 23 Dec 2024

Viewed by 438

Abstract

Preoperative or postoperative radiation therapy is broadly employed in patients with rectal carcinoma. Radiotherapy directs high-energy beams of ionizing radiation toward the tumor area to destroy cancer cells. High radiation doses are needed for cell killing. The radiation exposure of the healthy tissues/organs [...] Read more.

Preoperative or postoperative radiation therapy is broadly employed in patients with rectal carcinoma. Radiotherapy directs high-energy beams of ionizing radiation toward the tumor area to destroy cancer cells. High radiation doses are needed for cell killing. The radiation exposure of the healthy tissues/organs may lead to carcinogenesis. This study describes the evolving role of radiotherapy in rectal cancer management. The present report also reviews epidemiological and dosimetric studies related to the radiation-induced second malignancies from pelvic radiotherapy. Some epidemiological studies have concluded that the second-cancer risk in patients subjected to radiation therapy does not increase compared to unexposed rectal cancer patients. Other researchers found an elevated or a marginally increased probability for second-cancer induction. Dosimetric studies reported cancer risk estimates for critical organs or tissues in the near and far periphery of the treatment volume. Useful information about the effect of the treatment parameters such as the irradiation technique, photon beam energy, and fractionation schedule on the organ-specific second-cancer risk was derived from the dose data analysis. The knowledge of these effects is needed for the selection of the optimal treatment parameters enabling a reduction in the resultant risk of carcinogenesis. Full article

(This article belongs to the Special Issue Feature Review Papers in Section Applied Biosciences and Bioengineering)

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46 pages, 3509 KiB

Open AccessArticle

Migrating from Developing Asynchronous Multi-Threading Programs to Reactive Programs in Java

by Andrei Zbarcea and Cătălin Tudose

Appl. Sci. 2024, 14(24), 12062; https://doi.org/10.3390/app142412062 - 23 Dec 2024

Viewed by 502

Abstract

Modern software application development imposes standards regarding high performance, scalability, and minimal system latency. Multi-threading asynchronous programming is one of the standard solutions proposed by the industry for achieving such objectives. However, the recent introduction of the reactive programming interface in Java presents [...] Read more.

Modern software application development imposes standards regarding high performance, scalability, and minimal system latency. Multi-threading asynchronous programming is one of the standard solutions proposed by the industry for achieving such objectives. However, the recent introduction of the reactive programming interface in Java presents a potential alternative approach for addressing such challenges, promising performance improvements while minimizing resource utilization. The research examines the migration process from the asynchronous paradigm to the reactive paradigm, highlighting the implications, benefits, and challenges resulting from this transition. To this end, the architecture, technologies, and design of a support application are presented, outlining the practical aspects of this experimental process while closely monitoring the phased migration. The results are examined in terms of functional equivalence, testing, and comparative analysis of response times, resource utilization, and throughput, as well as the cases where the reactive paradigm proves to be a solution worth considering. Across multiple scenarios, the reactive paradigm demonstrated advantages such as up to 12% reduction in memory usage, 56% faster 90th percentile response times, and a 33% increase in throughput under high-concurrency conditions. However, the results also reveal cases, such as data-intensive scenarios, where asynchronous programming outperforms reactive approaches. Additionally, possible directions for further research and development are presented. This paper not only investigates the design and implementation process but also sets a foundation for future research and innovation in dependable systems, collaborative technologies, sustainable solutions, and distributed system architecture. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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16 pages, 10659 KiB

Open AccessArticle

Research on the Method for Solving the Safety Factor of Rock Slope Based on Deformation Monitoring Warning Threshold

by Xiaoyan Wei and Xiuli Zhang

Appl. Sci. 2024, 14(24), 12061; https://doi.org/10.3390/app142412061 - 23 Dec 2024

Viewed by 351

Abstract

In view of the fact that field monitoring information can more intuitively and accurately reflect the stability state of slopes, this paper takes the warning threshold of slope deformation rate monitoring as the slope stability evaluation standard, and puts forward a method for [...] Read more.

In view of the fact that field monitoring information can more intuitively and accurately reflect the stability state of slopes, this paper takes the warning threshold of slope deformation rate monitoring as the slope stability evaluation standard, and puts forward a method for solving the safety coefficient of rocky slopes. The discrete element method (3DEC), which is suitable for rocky slopes, is selected as the numerical calculation tool, the convergence criterion of its strength reduction method is modified to the slope deformation rate threshold, and the method is realized by the bifurcation method through its built-in FISH programming language. The results of the classical case show that, by selecting the slope deformation rate threshold in the appropriate interval, the results of this paper’s method are very close to those of the finite unit stress method and the limit equilibrium method, verifying the reliability of this paper’s method. Further, the method of this paper is applied to an open-pit mine slope project, based on the slope deformation on-site monitoring data and through the time series prediction method to determine the slope deformation rate warning threshold, using the threshold as an evaluation criterion to solve the slope’s coefficient of safety. The calculation results show that the slope’s coefficient of safety in natural working conditions is 1.086, being basically stable. However, with continuous rainfall, the slope’s body gradually becomes saturated, the slope’s coefficient of safety is reduced to 0.987, and the slope’s safety is reduced to 0.987. After continuous rainfall and gradual saturation of the slope, the coefficient of safety decreases to 0.987, resulting in destabilization and destruction, which is consistent with the site conditions. Full article

(This article belongs to the Section Civil Engineering)

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21 pages, 1891 KiB

Open AccessArticle

Preliminary Studies on the Use of an Electrical Method to Assess the Quality of Honey and Distinguish Its Botanical Origin

by Aleksandra Wilczyńska, Joanna Katarzyna Banach, Natalia Żak and Małgorzata Grzywińska-Rąpca

Appl. Sci. 2024, 14(24), 12060; https://doi.org/10.3390/app142412060 - 23 Dec 2024

Viewed by 404

Abstract

This study aimed to determine the possibility of deploying an innovative electrical method and to establish the usefulness of conductivity and dielectric parameters for assessing the quality of Polish honeys, as well as for distinguishing their botanical origin. An attempt was also made [...] Read more.

This study aimed to determine the possibility of deploying an innovative electrical method and to establish the usefulness of conductivity and dielectric parameters for assessing the quality of Polish honeys, as well as for distinguishing their botanical origin. An attempt was also made to determine which standard physicochemical parameter could be replaced by conductivity and dielectric parameters. The experimental material consisted of seven varieties of honey (linden, rapeseed, buckwheat, goldenrod, phacelia, multifloral, acacia), obtained from beekeepers from northern Poland. Their quality was assessed based on their physicochemical parameters, biological activity, and color. Electrical parameters were measured using a measuring system consisting of an LCR meter, and own-construction sensor. Conductivity (Z, G) and dielectric (Cs, Cp) parameters were measured. Statistical analysis of the results of measurements of electrical parameters of the seven types of honey tested allowed classifying them in terms of their conductivity properties into two groups of single-flower honeys and one group of multi-flower honeys. This proves the feasibility of identifying their botanical origin using the electrical method, which is characterized by non-invasiveness, measurement speed, and high sensitivity. The usefulness of parameters Z and G in replacing quality parameters was confirmed mainly for single-flower honeys: buckwheat, linden, rapeseed, and phacelia. Full article

(This article belongs to the Special Issue Antioxidants: Discovery, Analysis, Medicinal Prospects and Potential Applications)

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21 pages, 19647 KiB

Open AccessArticle

Large-Scale Urban 3D Geological Modeling Based on Multi-Method Coupling Under Multi-Source Heterogeneous Data Conditions

by Jixiang Zhu, Xiaoyuan Zhou and Lizhong Zhang

Appl. Sci. 2024, 14(24), 12059; https://doi.org/10.3390/app142412059 - 23 Dec 2024

Viewed by 400

Abstract

The development and utilization of urban underground space represents a crucial strategy for achieving sustainable urban development. Three-dimensional (3D) geological models provide a data foundation and technical support for research in urban planning and construction, as well as the prevention and control of [...] Read more.

The development and utilization of urban underground space represents a crucial strategy for achieving sustainable urban development. Three-dimensional (3D) geological models provide a data foundation and technical support for research in urban planning and construction, as well as the prevention and control of environmental geological issues. However, current urban 3D geological modeling generally faces the challenge of multi-source heterogeneous modeling data. This often necessitates varying degrees of generalization in data processing, resulting in the majority of current urban 3D geological models being relatively coarse and insufficient to fulfill the demand for detailed geological information in contemporary urban development and management. Therefore, determining how to formulate or optimize the 3D geological modeling schemes to enhance the utilization of multi-source heterogeneous data is a key challenge in current urban 3D geological modeling. This study, taking the 3D geological structure modeling of Wuhan’s metropolitan development area (MDA) as an example, develops an automated scheme for standardizing modeling data based on multi-scale geological chronostratigraphy. By utilizing the standardized stratigraphy as a unified and independent geological framework for layered modeling, a high-precision 3D geological model of Wuhan’s MDA, characterized by large-scale and ultra-complex geological conditions, is constructed through a methodology that integrates the global discrete constrained points modeling approach with the global layered modeling approach, without generalizing the multi-source heterogeneous modeling data. This research not only holds significant practical implications for the prevention and control of comprehensive urban geological issues in Wuhan but also provides novel technical insights into the methodology of 3D urban geological modeling. Full article

(This article belongs to the Special Issue New Challenges in Urban Underground Engineering)

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12 pages, 2147 KiB

Open AccessArticle

Two-Dimensional Scanning of Circularly Polarized Beams via Array-Fed Fabry–Perot Cavity Antennas

by Mikhail Madji, Edoardo Negri, Walter Fuscaldo, Davide Comite, Alessandro Galli and Paolo Burghignoli

Appl. Sci. 2024, 14(24), 12058; https://doi.org/10.3390/app142412058 - 23 Dec 2024

Viewed by 446

Abstract

In this paper, we present an array-fed Fabry–Perot cavity antenna (FPCA) based on a partially reflecting sheet (PRS) capable of generating a circularly polarized (CP), highly directive, far-field radiation pattern in the 27–28.5 GHz frequency range. The PRS, the cavity, and the array [...] Read more.

In this paper, we present an array-fed Fabry–Perot cavity antenna (FPCA) based on a partially reflecting sheet (PRS) capable of generating a circularly polarized (CP), highly directive, far-field radiation pattern in the 27–28.5 GHz frequency range. The PRS, the cavity, and the array of feeders serve to different purposes in this original structure. The PRS is engineered to produce a circular polarization from a linearly polarized source placed inside the cavity. The cavity is optimized to obtain a directive conical beam from the dipole-like pattern of the simple source, and allows for a frequency scan of the beam along the elevation plane. The array of feeders is designed to obtain a pencil beam whose azimuthal pointing direction can be controlled by properly phasing the sources. The radiation performance is studied with a specific application of the reciprocity theorem in a full-wave solver along with the pattern multiplication principle. A number of array-pattern configurations in terms of operation frequency and phase shift are investigated and presented to show the potential of the proposed solution in terms of design flexibility and radiation performance. Full article

(This article belongs to the Special Issue Feature Paper Collection in the Section ‘Electrical, Electronics and Communications Engineering’)

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17 pages, 18579 KiB

Open AccessArticle

Re-Understanding the Sedimentary Environment of the Wufeng–Longmaxi Shales in the Sichuan Basin

by Xiaoping Mao, Xiurong Chen, Fan Yang, Shuxian Li, Zhen Li and Yuexing Yang

Appl. Sci. 2024, 14(24), 12057; https://doi.org/10.3390/app142412057 - 23 Dec 2024

Viewed by 439

Abstract

The current understanding of organic matter enrichment in marine shales remains highly controversial. Most scholars argue that deeper water environments and warmer climates facilitate the enrichment of organic matter. However, this perspective contradicts the principles of carbon sequestration in environmental science, necessitating a [...] Read more.

The current understanding of organic matter enrichment in marine shales remains highly controversial. Most scholars argue that deeper water environments and warmer climates facilitate the enrichment of organic matter. However, this perspective contradicts the principles of carbon sequestration in environmental science, necessitating a more in-depth discussion of its underlying mechanisms. This article utilizes the Wufeng–Longmaxi shales in the Sichuan Basin as a case study and integrates the primary productivity and carbon sequestration patterns observed in modern water bodies to analyze the processes governing organic matter enrichment in shales. The findings indicate that the Wufeng–Longmaxi shales in the Sichuan Basin did not form in a deep-water shelf environment during a period of large-scale transgression; rather, they developed in a highly enclosed shallow-water environment during a regressive phase. The proximity to ancient land correlates with higher organic matter abundance and gas production, suggesting that the mineralization model closely resembles that of coal, thereby highlighting the significance of proximity to land and the supply of terrigenous materials. It can be concluded that the depositional environment of organic-matter-rich marine shales is characterized by four key attributes: a shallow water depth, proximity to land (with a supply of terrestrial materials), a high enclosure, and a cold climate. Full article

(This article belongs to the Special Issue Technologies and Methods for Exploitation of Geological Resources)

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28 pages, 7597 KiB

Open AccessReview

AI-Powered Digital Twins and Internet of Things for Smart Cities and Sustainable Building Environment

by Aljawharah A. Alnaser, Mina Maxi and Haytham Elmousalami

Appl. Sci. 2024, 14(24), 12056; https://doi.org/10.3390/app142412056 - 23 Dec 2024

Viewed by 1082

Abstract

This systematic literature review explores the intersection of AI-driven digital twins and IoT in creating a sustainable building environment. A comprehensive analysis of 125 papers focuses on four major themes. First, digital twins are examined in construction, facility management, and their role in [...] Read more.

This systematic literature review explores the intersection of AI-driven digital twins and IoT in creating a sustainable building environment. A comprehensive analysis of 125 papers focuses on four major themes. First, digital twins are examined in construction, facility management, and their role in fostering sustainability and smart cities. The integration of IoT and AI with digital twins and energy optimization for zero-energy buildings is discussed. Second, the application of AI and automation in manufacturing, particularly in Industry 4.0 and cyber-physical systems, is evaluated. Third, emerging technologies in urban development, including blockchain, cybersecurity, and EEG-driven systems for sustainable buildings, are highlighted. The study underscores the role of data-driven approaches in flood resilience and urban digital ecosystems. This review contributes to sustainability by identifying how digital technologies and AI can optimize energy use and enhance resilience in both urban and industrial contexts. Full article

(This article belongs to the Section Civil Engineering)

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14 pages, 1294 KiB

Open AccessArticle

Listeria monocytogenes Challenge Testing of Ready-to-Eat Uncured Vacuum-Packed Pork Bars with Dried Plasma

by Paweł Pniewski, Krzysztof Anusz, Michał Tracz, Martyna Puchalska, Jan Wiśniewski, Joanna Zarzyńska, Kinga Domrazek, Ireneusz Białobrzewski, Dorota Chrobak-Chmiel and Agnieszka Jackowska-Tracz

Appl. Sci. 2024, 14(24), 12055; https://doi.org/10.3390/app142412055 - 23 Dec 2024

Viewed by 467

Abstract

Newly developed formulas of ready-to-eat (RTE) products, despite conforming to the latest nutritional trends involving low-processed and high-protein products, may pose a risk of promoting the growth of Listeria monocytogenes during shelf life. Food safety experts recommend challenge tests to assess the growth [...] Read more.

Newly developed formulas of ready-to-eat (RTE) products, despite conforming to the latest nutritional trends involving low-processed and high-protein products, may pose a risk of promoting the growth of Listeria monocytogenes during shelf life. Food safety experts recommend challenge tests to assess the growth potential of L. monocytogenes, which will ultimately provide microbiological evidence to determine the food safety limit. The present study evaluated whether RTE uncured vacuum-packed pork bars with dried plasma met the 100 CFU/g safety level at the end of shelf life under certain storage conditions and aimed to develop predictive models for the growth of L. monocytogenes in the above product. The bars were artificially inoculated with a mixture of three strains of L. monocytogenes at two different inoculum densities of 2 log CFU/g and 5 log CFU/g and stored at three different temperatures (2, 4, and 6 °C) and then subjected to microbiological evaluation at specific time intervals up to 21 storage days. The growth potential (Δ-value) for RTE pork bars contaminated with 2 log CFU/g L. monocytogenes inoculum was 0.36, 0.14, and 0.91 log CFU/g at 2, 4, and 6 °C, respectively, while for bars contaminated with 5 log CFU/g inoculum, they were −0.36, −0.40, and 0.64 at 2, 4, and 6 °C, respectively. Statistically higher growth potential (p < 0.05) was detected for RTE bars contaminated with 2 log CFU/g inoculum than with 5 log CFU/g. The results indicate that this type of product must be classified as a food category: “Ready-to-eat foods able to support the growth of L. monocytogenes, other than those intended for infants and for special medical purposes” (Category 1.2. according to EU Regulation 2073/2005). The newly created models can also describe L. monocytogenes growth in an environment where factors, such as temperature, pH, and a_w, change with time. The results showed that a higher inoculum density statistically reduced the growth potential values of L. monocytogenes compared to a lower density. Full article

(This article belongs to the Special Issue Advanced Technologies for Food Packaging and Preservation)

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19 pages, 8495 KiB

Open AccessArticle

Design and Development of a Precision Defect Detection System Based on a Line Scan Camera Using Deep Learning

by Byungcheol Kim, Moonsun Shin and Seonmin Hwang

Appl. Sci. 2024, 14(24), 12054; https://doi.org/10.3390/app142412054 - 23 Dec 2024

Viewed by 522

Abstract

The manufacturing industry environment is rapidly evolving into smart manufacturing. It prioritizes digital innovations such as AI and digital transformation (DX) to increase productivity and create value through automation and intelligence. Vision systems for defect detection and quality control are being implemented across [...] Read more.

The manufacturing industry environment is rapidly evolving into smart manufacturing. It prioritizes digital innovations such as AI and digital transformation (DX) to increase productivity and create value through automation and intelligence. Vision systems for defect detection and quality control are being implemented across industries, including electronics, semiconductors, printing, metal, food, and packaging. Small and medium-sized manufacturing companies are increasingly demanding smart factory solutions for quality control to create added value and enhance competitiveness. In this paper, we design and develop a high-speed defect detection system based on a line-scan camera using deep learning. The camera is positioned for side-view imaging, allowing for detailed inspection of the component mounting and soldering quality on PCBs. To detect defects on PCBs, the system gathers extensive images of both flawless and defective products to train a deep learning model. An AI engine generated through this deep learning process is then applied to conduct defect inspections. The developed high-speed defect detection system was evaluated to have an accuracy of 99.5% in the experiment. This will be highly beneficial for precision quality management in small- and medium-sized enterprises Full article

(This article belongs to the Special Issue Future Information & Communication Engineering 2024)

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29 pages, 10480 KiB

Open AccessArticle

Multi-Scale Information Collaborative Management Method in Hierarchical Construction Projects Based on Building Information Modeling

by Xuefeng Zhao, Wenkai Yan, Yu Xia, Zhe Sun, Mengxuan Li, Yan Bao and Qiankun Guo

Appl. Sci. 2024, 14(24), 12053; https://doi.org/10.3390/app142412053 - 23 Dec 2024

Viewed by 472

Abstract

Building Information Modeling (BIM) has been widely adopted in the Architecture, Engineering, and Construction (AEC) industry for information modeling and project-level based on information collected from multiple sources. Unfortunately, multi-scale building information is often organized in different formats according to different data management [...] Read more.

Building Information Modeling (BIM) has been widely adopted in the Architecture, Engineering, and Construction (AEC) industry for information modeling and project-level based on information collected from multiple sources. Unfortunately, multi-scale building information is often organized in different formats according to different data management protocols, making it a challenge to extract the data needed for effective decision-making by different project participants. This study proposed a method for the effective exchanges of multi-scale information through BIM, This method includes establishing an information management protocol between microscale and mesoscale through format conversion, standard unification, and contract constraint, and establishing an information management protocol between mesoscale and macroscale through model analysis, data integration, and institutional guarantee. The three paths of model, data, and management are used to link up the collaborative management of information in the three dimensions of individual, group, and region. The authors validated the proposed method using a case study of a project in Xiong’an New District in China as an example. Results show that the proposed method could help with the transmission and utilization of multi-scale building information using BIM for effective project management, which in turn enables the urban planners to have overall control over the information of urban construction projects. Full article

(This article belongs to the Special Issue Advances in the Building Information Modelling)

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18 pages, 1149 KiB

Open AccessArticle

Postharvest Evaluations of Blackcurrant Fruits with Chitosan and Ultraviolet A Treatments

by Zhuoyu Wang, Andrej Svyantek, Zachariah Miller, Aude A. Watrelot and Venkateswara Rao Kadium

Appl. Sci. 2024, 14(24), 12052; https://doi.org/10.3390/app142412052 - 23 Dec 2024

Viewed by 506

Abstract

The blackcurrant (Ribes nigrum L.) is a small fruit known for its health benefits, but treatment effects on postharvest storage for fresh markets remain understudied compared with other berries, such as blueberries (Vaccinium spp.). This work aimed to identify the effects [...] Read more.

The blackcurrant (Ribes nigrum L.) is a small fruit known for its health benefits, but treatment effects on postharvest storage for fresh markets remain understudied compared with other berries, such as blueberries (Vaccinium spp.). This work aimed to identify the effects of postharvest storage conditions including chitosan coating, ultraviolet a (UVA) light, and combined UVA–chitosan treatments on the physicochemical and microbial properties of blackcurrant. Blackcurrants were harvested, stored under the three conditions, and analyzed at every three days of storage throughout this experiment for a total of 15 days. The results indicated that chitosan treatments had positive effects on reducing berry weight loss, maintaining berry firmness, and reducing mold populations. UVA influenced certain bioactive compounds, such as cyanidin-3-galactoside and rutin. The interaction effects from these two treatments were minimal. This study provides important information for blackcurrant postharvest storage and further small fruit storage work, considering both UVA and chitosan had differential beneficial effects on blackcurrant berries’ physical and chemical attributes. Full article

(This article belongs to the Section Food Science and Technology)

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16 pages, 1015 KiB

Open AccessReview

Sirtuin 1 and Hormonal Regulations in Aging

by Milena Keremidarska-Markova, Iliyana Sazdova, Mitko Mladenov, Bissera Pilicheva, Plamen Zagorchev and Hristo Gagov

Appl. Sci. 2024, 14(24), 12051; https://doi.org/10.3390/app142412051 - 23 Dec 2024

Viewed by 450

Abstract

Aging affects the structure and functions of all organs and systems in the organism. In the elderly, significant changes in hormonal levels are observed. These translate to a predisposition for chronic diseases, including cardiovascular, neurodegenerative, and metabolic disorders. Therefore, tremendous scientific effort is [...] Read more.

Aging affects the structure and functions of all organs and systems in the organism. In the elderly, significant changes in hormonal levels are observed. These translate to a predisposition for chronic diseases, including cardiovascular, neurodegenerative, and metabolic disorders. Therefore, tremendous scientific effort is focused on investigating molecular mechanisms and drugs with the potential to reduce hormonal changes in old age and their impact. Sirtuin 1 (SIRT1), a member of the sirtuin family of deacetylases, has been extensively studied as a regulator of multiple pathways related to antioxidant properties, optimal immune response, and metabolism. SIRT1 plays a key role in regulating various hormonal pathways and maintaining homeostasis. In the present study, we review the interplay between SIRT1 and hormonal regulations, including the endocrine role of the hypothalamic–pituitary–thyroid, –adrenal, –gonadal, and –liver axes, of other endocrine glands, and of non-endocrine tissues in the aging organism. The application of natural SIRT1 activators, such as resveratrol, curcumin, paeonol, and Buyang Huanwu Decoction, for the treatment of aging and senescence is discussed. SIRT1 activators improve mitochondrial function, reduce oxidative stress, and promote longevity, but their clinical application is limited by low bioavailability and poor permeability across biological barriers. For this reason, advanced delivery strategies are being considered, including nose-to-brain drug delivery and nanotechnology-based formulations. Full article

(This article belongs to the Special Issue Antioxidants: Discovery, Analysis, Medicinal Prospects and Potential Applications)

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21 pages, 4816 KiB

Open AccessArticle

Deep Learning-Based Postural Asymmetry Detection Through Pressure Mat

by Iker Azurmendi, Manuel Gonzalez, Gustavo García, Ekaitz Zulueta and Elena Martín

Appl. Sci. 2024, 14(24), 12050; https://doi.org/10.3390/app142412050 - 23 Dec 2024

Viewed by 484

Abstract

Deep learning, a subfield of artificial intelligence that uses neural networks with multiple layers, is rapidly changing healthcare. Its ability to analyze large datasets and extract relevant information makes it a powerful tool for improving diagnosis, treatment, and disease management. The integration of [...] Read more.

Deep learning, a subfield of artificial intelligence that uses neural networks with multiple layers, is rapidly changing healthcare. Its ability to analyze large datasets and extract relevant information makes it a powerful tool for improving diagnosis, treatment, and disease management. The integration of DL with pressure mats—which are devices that use pressure sensors to continuously and non-invasively monitor the interaction between patients and the contact surface—is a promising application. These pressure platforms generate data that can be very useful for detecting postural anomalies. In this paper we will discuss the application of deep learning algorithms in the analysis of pressure data for the detection of postural asymmetries in 139 patients aged 3 to 20 years. We investigated several main tasks: patient classification, hemibody segmentation, recognition of specific body parts, and generation of automated clinical reports. For this purpose, convolutional neural networks in their classification and regression modalities, the object detection algorithm YOLOv8, and the open language model LLaMa3 were used. Our results demonstrated high accuracy in all tasks: classification achieved 100% accuracy; hemibody division obtained an MAE of approximately 7; and object detection had an average accuracy of 70%. These results demonstrate the potential of this approach for monitoring postural and motor disabilities. By enabling personalized patient care, our methodology contributes to improved clinical outcomes and healthcare delivery. To our best knowledge, this is the first study that combines pressure images with multiple deep learning algorithms for the detection and assessment of postural disorders and motor disabilities in this group of patients. Full article

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18 pages, 10058 KiB

Open AccessArticle

Characterization of Dolomite Stone Broken Under Axial Impact

by Ran Ji, Han Chen, Huaizhong Shi, Wenhao He, Dong Liu and Yongqi Wang

Appl. Sci. 2024, 14(24), 12049; https://doi.org/10.3390/app142412049 - 23 Dec 2024

Viewed by 307

Abstract

As the extraction of oil and gas progresses into deeper and ultra-deep geological formations, the enhancement of rock-breaking efficiency in drill bits has emerged as a critical factor in ensuring energy security. Among the various techniques employed, vibratory percussion drilling technology is widely [...] Read more.

As the extraction of oil and gas progresses into deeper and ultra-deep geological formations, the enhancement of rock-breaking efficiency in drill bits has emerged as a critical factor in ensuring energy security. Among the various techniques employed, vibratory percussion drilling technology is widely recognized for its ability to improve both the efficiency and speed of penetrating hard rock formations. This study examined the effects of varying loading conditions on the characteristics of rock fracture and damage, maintaining a constant cutting speed and lead angle. By designing a small polycrystalline diamond compact (PDC) drill bit and incorporating simulation results, the research sought to analyze the influence of axial impact components on the efficiency of breaking dolomite samples, as well as the effects of impact frequency and amplitude on drilling pressure and rock-breaking energy. The findings revealed that an increase in the axial impact amplitude significantly enhanced rock-breaking efficiency, elevated von Mises stress, and increased principal compressive stress. An increase in impact frequency effectively reduced the overall stress and frictional work. These results underscored that the stress analysis revealed that the peak stress increased at lower impact amplitudes, with notable changes occurring at an amplitude of 1.5, leading to a 100% increase in Mises peak stress compared with an amplitude of 1.0. Axial impact drilling promoted deep crack formation and the development of a tensile damage zone beneath the cutter, indicating its effective rock-breaking capabilities. Axial impact drilling significantly reduced the threshold drilling pressure compared with conventional rotation, with an impact amplitude of 0.3 mm decreasing the static load by 44.1%. Additionally, increasing the axial impact amplitude enhanced the rate of penetration (ROP) while maintaining a constant static load, resulting in remarkable efficiency improvements. The results of the study are expected to provide theoretical guidance for the mechanism of impact rock breaking and the design of impact rock-breaking tool parameters. Full article

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