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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 98-109页

作者： Namdari, Himan Moradikia, Majid Zekavat, Seyed Askari, Radwin Mangoubi, Oren Petkie, Doug Data Science Program WorcesterMA01609 United States Michigan Technological University Department of Geological and Mining Engineering and Sciences HoughtonMI48105 United States Physics Department WorcesterMA01609 United States

In this article, we investigate an intelligent ground penetrating radar (GPR) that facilitates root-zone soil moisture estimation, a key parameter in precision agriculture. To create an intelligent GPR, we must train machine learning (ML) methods applied to the GPR-received signal. This process requires a large number of labeled GPR data that would be time-consuming and labor-intensive if created via field measurements. This article uses gprMAX software to emulate drone-coupled GPR received signal to generate large-scale data for training ML models. The data are created via a 1.5 GHz Ricker waveform considering a three-layer soil consistent with a realistic soil horizon model. The approach is structured as follows: first, we generate a synthetic dataset using gprMAX. Feature engineering techniques are then employed to extract meaningful components from the GPR signals, followed by a rigorous selection process to identify the most effective ML model for soil moisture prediction. Finally, we validate our model by integrating synthetic data with real GPR data collected at the SoilX lab at Worcester Polytechnic Institute, enhancing prediction accuracy and generalization capability. Our proposed model achieves an overall average root-mean-squared error of 0.5%, and 1.56 cm for moisture and depth estimations, respectively. The proposed intelligent GPR, when installed on a drone, enables high horizontal (e.g., 10 m) and vertical (e.g., 1.5 cm) resolution and high penetration depth (beyond 2 m) megafarm root-zone 3-D moisture map creation. Thus, it offers much higher capabilities when compared to traditional methods, such as synthetic aperture radar and satellite imaging. These results facilitate efficient farming practices, such as optimizing irrigation models, for better crop yields and food security. © 2023 IEEE.

关键词： Soil moisture

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Post-Traumatic stress disorder and post-traumatic growth in firefighters: examining the moderating effects of resilience on occupational safety behaviors

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BMC Public Health 2025年第1期25卷 1-15页

作者： Bakirci, Ahmet Erhan Demirel, Nuray Sar, Vedat Cetin, Ali Department of Civil Defense and Firefighting Vocational School of Technical Science Cerrahpasa University-Istanbul Istanbul Turkey Mining Engineering Occupational Health and Safety Interdisciplinary Program Middle East Technical University Ankara Turkey Department of Psychiatry Koc University Faculty of Medicine Istanbul Turkey Department of Obstetrics and Gynecology Haseki Training and Research Hospital University of Health Sciences Istanbul Turkey

Background: Posttraumatic stress disorder (PTSD) and posttraumatic growth (PTG) represent divergent outcomes following trauma exposure in high-risk professions. This investigation examined the complex interplay between PTSD, PTG, and resilience in relation to occupational safety behaviors among Turkish firefighters. Methods: A multi-site cross-sectional study was conducted across five metropolitan fire departments in Turkey (N = 122). Participants completed validated psychometric instruments including the PTSD Checklist for DSM-5 (PCL-5), Posttraumatic Growth Inventory-Expanded Form (PTGI-X), Brief Resilience Scale, alongside detailed evaluations of safety practices, perceptions, and behaviors that assessed protocol adherence, equipment maintenance, training attendance, and safety communication metrics. Hierarchical multiple regression and chi-square analyses examined the relationships between psychological factors and safety outcomes, with particular attention to moderating effects. Results: Analyses revealed significant associations between psychological adaptation patterns and safety-critical behaviors. PTSD symptomatology demonstrated negative correlations with safety protocol adherence (r=-.24, p <.01) and safety awareness (r=-.21, p <.01). PTG manifested distinct cultural patterns, with Personal Strength emerging as the predominant domain (M = 3.10, SD = 1.08). A distinct disparity emerged between technical and psychological safety dimensions, with high adherence to equipment-related protocols (breathing apparatus maintenance: M = 4.00) contrasting markedly with poor implementation of psychological safety practices (comfort in communicating safety concerns: M = 1.66). Regression analyses indicated that psychological factors accounted for 28% of the variance in safety performance metrics, with resilience moderating the relationship between PTSD symptomatology and safety outcomes. Conclusions: This investigation identifies critical relationships between psycholo

关键词： Emergency services Firefighters Occupational safety Posttraumatic growth Posttraumatic stress disorder Psychological resilience

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Integrated mine closure planning adherence Index: a new approach for evaluating mine closure plans

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Resources Policy 2025年 105卷

作者： Santos, Cecília Santiago Praça Leite, Mariangela Garcia Mota de Lima, Hernani Federal University of Ouro Preto Socioeconomic and Environmental Sustainability Graduated Program. Ouro Preto Minas Gerais Brazil Federal University of Ouro Preto Mining Engineering Department. Ouro Preto Minas Gerais Brazil

The evaluation of adherence to Integrated Mine Closure Planning (IMCP) contributes to improved closure risk management and strategy development, facilitating the achievement of desired closure outcomes and intended post-mining land use. IMCP should provide mining companies with an early identification of risks, build a positive legacy to affected communities, encompassing physical and chemical stability, socio-economic transition, and financial considerations. Based on international best practices and legal requirements for mine closure, an Integrated Mine Closure Planning Adherence Index (IMCPAI) was developed and applied to 8 closure plans from iron mines located in Brazil. The IMCPAI is a weighted checklist comprising 21 requirements, distributed across four categories: (i) knowledge base, (ii) integrated mine closure planning, (iii) stakeholder engagement and economic and social transition, and (iv) execution of closure actions. The performance of each category was evaluated, and the respective adherence level was calculated. The majority of the mines demonstrated a moderate adherence to IMCP evaluated. The integrated closure planning category achieved the best overall performance, suggesting a significant gap between theoretical principles and practical application of mine closure on the other analyzed categories. The IMCPAI proposed in the present study has the potential to enhance the quality of mine closure plans. It enables mining companies and interested parties to assess the efficacy of their IMCP strategies at the outset of a mine's operations, allowing adjustments and improvements in time to ensure the achievement of closure objectives. © 2025

关键词： Cost estimating

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Discrete fracture network application to rock slope engineering

Journal of Industrial Safety

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Journal of Industrial Safety 2025年第1期2卷 47-64页

作者： Elvis Karikari Mensah Reginald Hammah Hassan Basahel Hani Mitri Department of Mining and Materials Engineering McGill University Montreal Quebec H3A 0E8 Canada Rocscience Ltd. 54 Saint Patrick Street Toronto Ontario M5T 1V1 Canada Geological Hazards Program Saudi Geological Survey Jeddah 21514 Saudi Arabia

The stability of rock slopes is a critical concern in rock engineering applications due to the potential safety hazards and economic repercussions associated with slope failures. Currently, slope stability analysis relies on various analytical and numerical modeling tools leading to a factor of safety. Parameters such as joint strength are assessed through probabilistic analysis. Despite the established effectiveness of these methods, they often lack the capability to provide a volumetric estimation of the failure zone, primarily because the joint frequency parameter is not considered. By incorporating this parameter, it becomes feasible to construct a three-dimensional discrete fracture network (DFN), which offers a more comprehensive representation of the rock slope structure. This study aims to validate the use of DFN in civil engineering applications using two road-cut case studies from Saudi Arabia. Both case studies are analyzed with the conventional methods and DFN approaches, allowing for a comparative assessment of results. DFN models optimize the utilization of statistical data related to discontinuity persistence and spacing, enabling the construction of both deterministic and stochastic fracture networks. The effects of joint spacing and persistence on the factor of safety and volume of failure are examined. Finally, the advantages and limitations of the DFN on rock slope stability are highlighted and areas for improvement and optimization are discussed.

关键词： Discrete fracture network Rock slope engineering Numerical modeling Rock mechanics Mathematical modeling Limit equilibrium Kinematic analysis

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Recent advances in natural fiber reinforced metal/ceramic/polymer composites: An overview of the structure-property relationship for engineering applications

Hybrid Advances

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Hybrid Advances 2025年 8卷

作者： Olanrewaju, Olajesu Oladele, Isiaka Oluwole Adelani, Samson Oluwagbenga Department of Materials Science and Engineering Iowa State University Ames IA United States Department of Metallurgical and Materials Engineering Federal University of Technology PMB Akure 704 Nigeria Centre for Nanomechanics and Tribocorrosion School of Metallurgy Chemical and Mining Engineering University of Johannesburg Johannesburg South Africa Materials Science and Engineering Program University of Colorado Boulder 80303 CO United States

Advances in the material science world drive the birth of a new generation of sustainable materials. Natural fiber (NFs) biocomposites are emerging as valuable alternatives to conventional materials for engineering applications such as construction, automobiles, and aerospace due to their exceptional mechanical properties, lightweight, low carbon footprint, energy efficiency, and cost-effectiveness. These outstanding properties have made them more desirable for engineering applications. However, the focus has been on lignocellulosic fibers, neglecting other sources, such as keratinous, fibrinous, and microorganism fibers. Only a few reviews have considered the structure-property relationship of all classes of natural fibers, such as lignocellulosic (plant), keratinous and fibrinous (animal), and microorganism (mycelium) fibers. Although NFs have outstanding potential from an economic, technical, environmental, and green credentials perspective, they have limitations, such as fiber-matrix incompatibility and moisture damage. These limitations make using NFs as reinforcement for different material systems challenging. Surface alterations are usually necessary to improve the adherence between fiber and matrix. With the upgrade, NFs have the potential as sustainable replacement for conventional materials for engineering applications. Future research should aim at reconciling the mechanical properties of NFs to improve composite quality and fiber-matrix adherence and performance. © 2025 The Authors

关键词： Biocomposites Fibrinous Keratinous Lignocellulosic Microorganism Natural fiber

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A Comprehensive Review on plant and animal fiber reinforced composites: Experimental and theoretical approaches to interfacial strength optimization and potential applications

Hybrid Advances

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Hybrid Advances 2025年 10卷

Natural fiber-reinforced composites (NFRCs) have become vital in various engineering applications due to their exceptional properties and ease of manufacturing. Properties such as lightweight, sustainability, design flexibility, microstructure, durability, and advanced fabrication techniques have expanded their use across industries. Also, NFRCs are preferred because the extensive reliance on synthetic fibers presents significant challenges in recycling and waste management. Despite their excellent properties, NFRCs have three main challenges: fiber degradation, water degradation, and weak interfacial strength (incompatibility of fibers with the matrix). Consequently, research efforts have been directed at combating these challenges using different surface treatment techniques. However, research has been skewed towards experimental approaches for improving the interfacial strength in plant fiber polymer matrix composites (PMCs). Hence, there exists a dearth of information on the computational approaches for optimizing the interfacial properties of NFRCs. Hence, this review provides experimental and computational approaches (machine learning) for comprehensive optimizing strategies for different natural fibers (plant, animal, and microorganism) and matrices (polymers, metals, and ceramics). This review also highlights the importance of theoretical approaches and numerical modeling in analyzing and optimizing NFRCs. Finally, the review highlights recent advancements in NFRCs, their mechanical properties, potential applications, and future directions. © 2025 The Authors

关键词： Animal fiber Interfacial shear strength Machine-learning Natural fiber-reinforced composites Plant fiber

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Optimization of the catch bench design using a genetic algorithm

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International Journal of mining Science and Technology 2016年第6期26卷 1011-1016页

作者： Ruvin Wijesinghe Dakshith You Greg Mining Engineering Program Faculty of Science and Technology Federation University Australia Ballarat 3350 Australia

Rockfalls are one of the hazards that may be associated with open pit mining. The majority of rockfalls occur due to the existing conditions of slopes, such as back break, fractures and joints. Constructing a berm on the catch bench is a popular method for the mitigation of rockfall hazards in open pit *** width of the catch bench and the height of the berm play a major role in the open pit bench ***, there is no systematic method currently available to optimize the size of these parameters. This study proposes a novel methodology which calculates the optimum catch bench width by integrating the rockfall simulation model and genetic algorithm into a Simulation-Optimization Model. The proposed methodology is useful when used to determine the minimum catch bench width, or the maximum overall slope angle, insuring that a sufficient factor of safety of the slope is included while maximizing the overall profitability of the open pit mine.

关键词： Catch bench width RocFall Genetic algorithm Simulation-Optimization model

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Female entrepreneurship and sustainability: Behavioral insights and sustainable development goals

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Sustainable Futures 2025年 9卷

作者： Sánchez-Limón, Mónica Severino-González, Pedro Rebolledo-Aburto, Guipsy Dote-Pardo, Jairo Scott-Kinney, Ian Faculty of Commerce and Administration Autonomous University of Tamaulipas Victoria Mexico Department of Economics and Administration Faculty of Social and Economics Catholic University of Maule Talca Chile Engineering Program Faculty of Engineering and Business Adventist University of Chile Chillán Chile Department of Economic and Administrative Sciences Faculty of Legal Economic and Administrative Sciences Catholic University of Temuco Temuco Chile Mining Engineering Department Faculty of Engineering University of Santiago of Chile (USACH) Central Station Santiago Chile

The study of sustainable female entrepreneurship emerges as a critical research area, integrating gender and sustainability perspectives in the business context. The study aims to analyze the current state of scientific research on female entrepreneurship and sustainability over the last 15 years. A bibliometric analysis is performed for the method, reaching 733 publications between 2010 and 2024. The findings show an exponential growth in the number of publications, reflecting the growing interest in the subject. In addition, four main thematic groupings and a geographical diversity in research production were identified, although with unequal representation. This study provides an overview of the evolution and different perspectives on women's sustainable entrepreneurship. It also offers important opportunities, gaps and future directions for research and policy formulation by public and private, national and international organizations. © 2025 The Authors

关键词： Entrepreneurial behavior Entrepreneurs Female Gender Sustainable development goals (SDGS) Women

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Axisymmetric alternating direction explicit scheme for efficient coupled simulation of hydro-mechanical interaction in geotechnical engineering-Application to circular footing and deep tunnel in saturated ground

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Journal of Rock Mechanics and Geotechnical engineering 2018年第2期10卷 259-279页

作者： Simon Heru Prassetyo Marte Gutierrez Department of Civil and Environmental Engineering Colorado School of MinesGoldenUSA Mining Engineering Program Institut Teknologi BandungBandungIndonesia

Explicit solution techniques have been widely used in geotechnical engineering for simulating the coupled hydro-mechanical(H-M) interaction of fluid flow and deformation induced by structures built above and under saturated ground, i.e. circular footing and deep tunnel. However, the technique is only conditionally stable and requires small time steps, portending its inefficiency for simulating large-scale H-M problems. To improve its efficiency, the unconditionally stable alternating direction explicit(ADE)scheme could be used to solve the flow problem. The standard ADE scheme, however, is only moderately accurate and is restricted to uniform grids and plane strain flow conditions. This paper aims to remove these drawbacks by developing a novel high-order ADE scheme capable of solving flow problems in nonuniform grids and under axisymmetric conditions. The new scheme is derived by performing a fourthorder finite difference(FD) approximation to the spatial derivatives of the axisymmetric fluid-diffusion equation in a non-uniform grid configuration. The implicit Crank-Nicolson technique is then applied to the resulting approximation, and the subsequent equation is split into two alternating direction sweeps,giving rise to a new axisymmetric ADE scheme. The pore pressure solutions from the new scheme are then sequentially coupled with an existing geomechanical simulator in the computer code fast Lagrangian analysis of continua(FLAC). This coupling procedure is called the sequentially-explicit coupling technique based on the fourth-order axisymmetric ADE scheme or SEA-4-AXI. Application of SEA-4-AXI for solving axisymmetric consolidation of a circular footing and of advancing tunnel in deep saturated ground shows that SEA-4-AXI reduces computer runtime up to 42%-50% that of FLAC’s basic scheme without numerical instability. In addition, it produces high numerical accuracy of the H-M solutions with average percentage difference of only 0.5%-1.8%.

关键词： Hydro-mechanical(H-M) interaction Explicit coupling technique Alternating direction explicit(ADE) scheme High-order finite difference(FD) Non-uniform grid Axisymmetric consolidation Circular footing Deep tunnel in saturated ground

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Novel robust Elman neural network-based predictive models for bubble point oil formation volume factor and solution gas–oil ratio using experimental data

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Neural Computing and Applications 2024年第23期36卷 14503-14526页

作者： Kohzadvand, Kamyab Mahmoudi Kouhi, Maryam Ghasemi, Mehdi Shafiei, Ali Tehran Iran Petroleum Engineering Program School of Mining and Geosciences Nazarbayev University Astana010000 Kazakhstan

Bubble point oil formation volume factor (Bob) and solution gas–oil ratio (Rs) are two crucial PVT parameters used for modeling and volumetric calculations in petroleum industry. They are usually determined in laboratory or estimated using empirical correlations. Experimental methods are time-consuming and expensive where empirical correlations have limitations. Artificial intelligence can be sued overcome these limitations to develop more accurate, robust, and quick predictive tools. In this paper, we used three artificial neural network algorithms to develop intelligent models to predict Bob and Rest using 465 experimental data. Application of the Elman neural network (ENN) for this purpose is being reported for the first time. A variety of input parameters were selected based on a sensitivity analysis which include reservoir temperature (T), oil API gravity (°API), bubble point pressure (Pb), gas-specific gravity (γg), and Rs was used to predict the Bob. T, °API, Pb, γg, and Bob was used to predict the Rs. The ENN model was found superior to the other developed smart models and the empirical correlations with coefficient of determination (R2) of 0.993, root mean square error (RMSE) of 0.0093, and average absolute percent relative error (AAPRE) of 0.93% for the Bob and 0.999, 0.016, and 6.72% for the Rs, respectively. The ENN network has fewer adjustable parameters and provides faster training capabilities using fewer neurons and hidden layers compared to other ANN algorithms. The developed smart predictive tools can be safely used instead of laboratory methods and empirical correlations for a much wider ranges of input parameters and with higher accuracy and confidence. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Mean square error

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