bluuebunny/crossref_metadata_2025 huggingface dataset:
Hays of Novel-Improved Legume Cultivars: Phytochemical Content and Nutritional Value
Authors: Myrtsi Eleni D. , Vlachostergios Dimitrios N. , Petsoulas Christos , Evergetis Epameinondas , Koulocheri Sofia D. , Haroutounian Serkos A.
Published: October 2024

The imperative need to produce safe foodstuffs using environmentally sustainable practices has highlighted the incorporation of legumes in human and animal diets as an emerging nutritional staple. Since legumes comprise a family of plants known to display an extensive agricultural diversity with significant bioactivities, we report herein the exploitation outcome of the nutritional and bio-functional content of hay, derived from the post-harvest aerial parts of eight novel-improved Greek cultivars belonging to the following six taxa: Larthyrus sativus L., Medicago sativa L., Cicer arietinum L., Pisum sativum L., Vicia faba L., and Phaseolus vulgaris L. In specific, the phytochemical content of their hay extracts was screened against the presence of 37 fatty acids and 67 polyphenols using, respectively, GC-FID and LC-MS/MS instruments, while the determination of their total phenolic and tannin contents was achieved with spectrophotometric methods. In this respect, the presence of 26 different fatty acids was detected of which the acids linoleic, linolenic and palmitic were traced in all extracts in concentrations exceeding the 10 mg/g, while the oleic acid was determined as the major component of C. arietinum (77.58 mg/g), V. faba (36.11 mg/g), and L. sativus (12.89 mg/g) extracts. In addition, 30 different phenolics were traced as extracts’ components with the most abundant the molecule of isoquercetin, which was present in six extracts and isoliquiritigenin, calycosin, and chlorogenic acid which were detected in five extracts. Finally, the antioxidant properties of the extracts were evaluated by performing both DPPH• and FRAP assays, which highlighted the V. faba extract as the most potent in both tests, followed by the extracts of P. sativum and P. vulgaris. Results herein are indicative of the significant advances achieved, for the improvement of investigated plant cultivars with respect to their utilization as nutritional crops, since these novel cultivars hays have been found to contain significant amounts of essential nutrients in the form of fatty acids along with bioactive ingredients in the form of polyphenols, while simultaneously they were determined as deprived of tannins that constitute essential anti-nutritional factors.
Innovative Materials for High-Performance Tin-Based Perovskite Solar Cells: A Review
Authors: Wang Xiansheng , Yang Jianjun , Zhong Jian , Yu Junsheng , Pan Xinjian
Published: October 2024

With the rapid development of lead-based perovskite solar cells, tin-based perovskite solar cells are emerging as a non-toxic alternative. Material engineering has been an effective approach for the fabrication of efficient perovskite solar cells. This paper summarizes the novel materials used in tin-based perovskite solar cells over the past few years and analyzes the roles of various materials in tin-based devices. It is found that self-assembling materials and fullerene derivatives have shown remarkable performance in tin-based perovskite solar cells. Finally, this article discusses design strategies for new materials, providing constructive suggestions for the development of innovative materials in the future.
On the Valorization of Olive Oil Pomace: A Sustainable Approach for Methylene Blue Removal from Aqueous Media
Authors: Saoudi Hassani El Mokhtar , Duarte Hugo , Brás João , Taleb Abdeslam , Taleb Mustapha , Rais Zakia , Eivazi Alireza , Norgren Magnus , Romano Anabela , Medronho Bruno
Published: October 2024

Currently, industrial water pollution represents a significant global challenge, with the potential to adversely impact human health and the integrity of ecosystems. The continuous increase in global consumption has resulted in an exponential rise in the use of dyes, which have become one of the major water pollutants, causing significant environmental impacts. In order to address these concerns, a number of wastewater treatment methods have been developed, with a particular focus on physicochemical approaches, such as adsorption. The objective of this study is to investigate the potential of a bio-based material derived from olive oil pomace (OOP) as an environmentally friendly bio-adsorbent for the removal of methylene blue (MB), a cationic dye commonly found in textile effluents. The biobased material was initially characterized by determining the point of zero charge (pHpzc) and using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). Subsequently, a comprehensive analysis was conducted, evaluating the impact of specific physicochemical parameters on MB adsorption, which included a thorough examination of the kinetic and thermodynamic aspects. The adsorption process was characterized using Langmuir, Freundlich, Brunauer-Emmett-Teller (BET), and Dubinin Radushkevich (D-R) isotherms. The results suggest that the equilibrium of adsorption is achieved within ca. 200 min, following pseudo-second-order kinetics. The optimal conditions, including adsorbent mass, temperature, bulk pH, and dye concentration, yielded a maximum adsorption capacity of ca. 93% (i.e., 428 mg g−1) for a pomace concentration of 450 mg L−1. The results suggest a monolayer adsorption process with preferential electrostatic interactions between the dye and the pomace adsorbent. This is supported by the application of Langmuir, BET, Freundlich, and D-R isotherm models. The thermodynamic analysis indicates that the adsorption process is spontaneous and exothermic. This work presents a sustainable solution for mitigating MB contamination in wastewater streams while simultaneously valorizing OOP, an agricultural by-product that presents risks to human health and the environment. In conclusion, this approach offers an innovative ecological alternative to synthetic adsorbents.
Ultrasonic Production of Chitosan Nanoparticles and Their Application Against Colletotrichum gloeosporioides Present in the Ataulfo Mango
Authors: Solis Vizcaino Ivana , Rubio Rosas Efraín , Águila Almanza Eva , Marín Castro Marco , Hernández Cocoletzi Heriberto
Published: October 2024

In Mexico, the Ataulfo mango crop faces significant challenges due to anthracnose, a disease caused by the fungus Colletotrichum gloeosporioides. The need to use eco-friendly fungicides is crucial to avoid the use of harmful synthetic chemicals. This study aimed to prepare chitosan nanoparticles through a simple and effective ultrasound-assisted top-down method, with high antifungal efficiency. The nanoparticles were prepared from chitosan (DD = 85%, MW = 553 kDa) and Tween 20 under constant sonication. The formation of the nanoparticles was initially confirmed by Fourier-transform infrared (FTIR) spectroscopy; and their physicochemical properties were subsequently characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The antifungal potential of the chitosan nanoparticles against the phytopathogen Colletotrichum gloeosporioides was evaluated with isolated fungi obtained directly from mango tissues showing anthracnose symptoms in the state of Guerrero, Mexico. The fungus was identified through SEM imaging, showing a regular and smooth conidial layer, with cylindrical shape (r = 2 µm, h = 10 µm). In vitro tests were conducted with three different concentrations of chitosan nanoparticles to assess their inhibitory effects. After seven days of incubation, a maximum inhibition rate of 97% was observed with the 0.5% nanoparticle solution, corresponding to a fungal growth rate of 0.008 cm/h. At this time, the control mycelial growth was 7 cm, while the treated sample reached a radius of 0.55 mm. These results demonstrated the antifungal effect of the nanoparticles on the membrane and cell wall of the fungus, suggesting that their composition could induce a resistance response. The inhibitory effect was also influenced by the particle size (30 nm), as the small size facilitated penetration into fungal cells. Consequently, the parent compound could be formulated and applied as a natural antifungal agent in nanoparticle form to enhance its activity. The method described in this study offers a viable alternative for the preparation of chitosan nanoparticles, by avoiding the use of toxic reagents.
The Excellent Chemical Interaction Properties of Poloxamer and Pullulan with Alpha Mangostin on Amorphous Solid Dispersion System: Molecular Dynamics Simulation
Authors: Rusdin Agus , Muchtaridi Muchtaridi , Megantara Sandra , Wardhana Yoga Windhu , Fakih Taufik Muhammad , Budiman Arif
Published: October 2024

Background: Alpha mangostin (AM) has demonstrated significant potential as an anticancer agent, owing to its potent bioactivity. However, its clinical application is limited by poor solubility, which hampers its bioavailability and effectiveness. Amorphous solid dispersion (ASD) presents a promising technique to enhance the solubility and stability of AM. Molecular dynamics simulation offers a rapid, efficient, and precise method to evaluate and optimize ASD formulations before production. Aim of Study: In this study, we conducted molecular dynamics simulations to explore the ASD development of AM with poloxamer and pullulan. Result: Our results revealed that AM–poloxamer complexes exhibit superior interaction characteristics compared to AM–pullulan, with a 1:5 ratio of AM to poloxamer and a cooling rate of 1 °C/ns demonstrating the most favorable outcomes. This combination showed enhanced hydrogen bonding, a more compact molecular structure, and higher stability, making it the optimal choice for ASD formulation. Conclusion: The integration of molecular dynamics simulation into ASD development significantly accelerates the formulation process and provides critical insights into achieving a stable and effective AM dispersion. The AM–poloxamer complex, particularly at a 1:5 ratio with a 1 °C/ns cooling rate, offers the best potential for improving AM solubility and therapeutic efficacy.
Prevention and Control of Biofouling Coatings in Limnoperna fortunei: A Review of Research Progress and Strategies
Authors: Zhang Hailong , Ding Qingjie , Zhang Yonghui , Lu Guangyi , Liu Yangyu , Tong Yuping
Published: October 2024

The increasing environmental concerns of conventional antifouling coatings have led to the exploration of novel and sustainable solutions to address the biofouling caused by Limnoperna fortunei. As a rapidly expanding invasive species, the fouling process of Limnoperna fortunei is closely associated with microbial fouling, posing significant threats to the integrity of aquatic infrastructure and biodiversity. This review discusses recent progress in the development of non-toxic, eco-friendly antifouling coatings that are designed to effectively resist biofouling without using toxic chemicals. Recent research has focused on developing novel non-toxic coatings that integrate natural bioactive components with advanced material technologies. These formulations not only meet current environmental standards and exhibit minimal ecological impact, but also possess significant potential in preventing the attachment, growth, and reproduction of Limnoperna fortunei. This review aims to provide scientific guidance by proposing effective and sustainable solutions to address the ecological challenges presented by Limnoperna fortunei. The insights gained from current research not only reveal novel antifouling methods, but also identify key areas for further investigation aimed at enhancing performance and environmental compatibility.
A New Method for Compression Testing of Reinforced Polymers
Authors: Morăraș Ciprian Ionuț , Husaru Dorin , Goanță Viorel , Bârsănescu Paul Doru , Lupu Fabian Cezar , Munteanu Corneliu , Cimpoesu Nicanor , Cosau Elena Roxana
Published: October 2024

Compressive testing of specimens taken from relatively thin composite plates is difficult, especially due to the occurrence of buckling. To prevent buckling, the central portion of the specimens used for the compression test has smaller dimensions, and the specimens can be guided along their entire length. For these reasons, optical methods, such as digital image correlation (DIC), cannot be used for the compression test and strain rosettes cannot be glued onto the samples to determine Poisson’s ratio. In this study, compression tests of a glass fiber-reinforced polymer (GFRP) were conducted using both the ASTM D695 (Boeing version) and a newly proposed method. The new method involves using special specimens that allow T-type rosettes to be bonded to determine Poisson’s ratio, whose value of 0.14 was thus determined. SEM images of the failure surfaces were presented and interpreted. A finite element analysis (FEA) of the specimens tested in compression is also presented. The first analyzed case considers the homogeneous and orthotropic composite, loaded with a uniformly distributed force. The normal stress in the central section of the specimen, determined with FEA, has an error of 6.52% compared to that determined experimentally. Additionally, the strain in the center of the strain gauge, determined with FEA, has an error of 4.76% compared to the measured one. In the second case studied with FEA, the sample is loaded with a quasi-concentrated force, which can move in the direction of the symmetry axes of the cross-section, to study the effect of the eccentricity of the compression force on the state of stress. It was shown that the eccentricity of the force has a great influence: the stress distribution in the section of the specimen becomes strongly non-uniform. For a force eccentricity of 0.4 mm in the direction of the OX axis, the minimum stress decreases by 53.7%, and the maximum stress increases by 55.4%. In order to analyze the influence of some manufacturing defects, two other cases were analyzed by FEA, in which it was assumed that the thicknesses of the outer resin layers were modified, making them asymmetrical. For this final FEA, the specimen was considered to be composed of laminates. These results demonstrate the special attention that must be paid to the centric application of force in compression testing.
Modeling the Dynamic Properties of Multi-Layer Glass Fabric Sandwich Panels
Authors: Charuk Arkadiusz , Irska Izabela , Dunaj Paweł
Published: October 2024

Sandwich panels are key components of many lightweight structures. They are often subjected to time-varying loads, which can cause various types of vibrations that adversely affect the functionality of the structure. That is why it is of such importance to predict the dynamic properties of both the panels and the structures made of them at the design stage. This paper presents finite element modeling of the dynamic properties (i.e., natural frequencies, mode shapes, and frequency response functions) of sandwich panels made of glass fabric impregnated with phenolic resin. The model reproducing the details of the panel structure was built using two-dimensional, quadrilateral, isoparametric plane elements. Afterwards, the model was subjected to an updating procedure based on experimentally determined frequency response functions. As a result, the average relative error for natural frequencies achieved numerically was 5.0%. Finally, a cabinet model consisting of the analyzed panels was built and experimentally verified. The relative error between the numerically and experimentally obtained natural frequencies was on average 5.9%.
Creation of Composite Aerogels Consisting of Activated Carbon and Nanocellulose Blended with Cross-Linked Biopolymers: Application as Ethylene Scavengers
Authors: Asadullah  , Ngiwngam Kittaporn , Han Jaejoon , Rachtanapun Pornchai , Auras Rafael , Karbowiak Thomas , Noiwan Duangjai , Thongngam Masubon , Tongdeesoontorn Wirongrong
Published: October 2024

This study involved producing aerogels using activated carbon (AC) and nanocellulose (NC). Two distinct structured composites, AC composite aerogel (ACCA) and NC composite aerogel (NCCA), were developed by separately mixing AC and NC with identical proportions of cross-linked biopolymers: hydroxypropyl methylcellulose (HPMC), methylcellulose (MC), and chitosan (C). These aerogels were evaluated for their capability to adsorb ethylene gas through batch experiments, while the physical and chemical characteristics were thoroughly examined to determine their feasibility of removing ethylene. The resulting ACCA and NCCA aerogels exhibited low densities of 0.094 g cm−3 and 0.077 g cm−3, respectively, coupled with high porosity ranging between 95 and 96%. During the ethylene adsorption test, NCCA exhibited superior ethylene removal rates (~14.88–16.77 mL kg−1) compared to ACCA (~13.57–14.97 mL kg−1). Specifically, NCCA achieved a removal efficiency of 83.86% compared to 74.64% for ACCA. Kinetic model fitting yielded high R2 values ranging from 0.97 to 0.98 with the Lagergren kinetic model. These findings suggest the potential of composite aerogels to be incorporated into food packaging materials for dynamic ethylene capture, independent of environmental conditions, thereby providing promising routes for further development.
Study on the Mechanical and Permeability Evolution of a Composite Rock Mass in an Aquifuge Under Hydraulic Coupling
Authors: Zhao Changzheng , Cao Shenggen , Du Shuyu , Che Chiyuan , Liu Yang , Wang Kaifei , Ma Ruiting
Published: October 2024

The lithology and composition type of an aquifuge in overburden play a crucial role in influencing the crack evolution and permeability changes of the aquifuge. This study utilized the high-temperature and high-pressure rock triaxial seepage test system to conduct triaxial compression tests on mudstone, sandstone, and their combined rock samples. The mechanical characteristics and permeability evolution of each lithology law during the failure were investigated. Furthermore, computed tomography (CT) scanning technology was utilized for the three-dimensional (3D) reconstruction and theoretical permeability calculation of single and combined rock samples. The results indicated that the stress–strain curves for single and combined rock samples exhibited similar patterns, which were divided into four stages: pore compaction, linear elasticity, yield deformation, and post-peak residual deformation. The peak strength of rock samples positively correlated with confining pressure. Permeability trends for mudstone and sandstone exhibited an “N”-type pattern characterized by “slow decrease–gradual stabilization–sudden increase–rebound decrease”, while the permeability of mudstone–sandstone combined rock followed a “U”-type pattern of “initial decrease–stabilization–subsequent increase”. Notably, the permeability of the combined rock samples was significantly lower compared to the single rock samples. The failure mode indicated that fractures in a single rock sample transversed the entire sample, whereas failures in the combined rock samples were confined to the mudstone component. This observation accounted for the differences in the permeability changes between the rock sample types. Additionally, the theoretical permeability results from the 3D reconstruction correlated with the experimental results.
Quantitative Risk Analysis with the Possibility of Stochastic and Deterministic Simulation of Failure Trends from the Point of View of Expressing the Probability of Two Parameters
Authors: Breznická Alena , Kohutiar Marcel , Krbata Michal , Eckert Maroš , Mikuš Pavol
Published: October 2024

The aim of this paper is to present theoretical starting points in the field of risk analysis. This paper is formulated as a systematic overview of the latest knowledge and trends, which are supported by the simulation of selected risk parameters intended for the prediction of adverse events. The analysis and assessment of technical risk allow not only for indicating negative events detected in a process but also for taking corrective measures based on systematic reductions in technical system failures. This article refers to the use of mathematical experiments of risk modelling and simulation because mathematical modelling and simulation are very suitable methods for the analysis, modelling, and prediction of random phenomena in risk theory and assessment. The analytical approach is based on stochastic and deterministic risk modelling procedures and on the principle of risk evaluation through the effects of two factors: the probability of occurrence of negative events and consequences and their impact from the point of view of malfunctions. The analytical approach is based on a mathematical model that considers the intersection of two phenomena in terms of expressing the probability of two different statistical distributions in a stochastic expression. The analysis and assessment of technical risk allow not only for indicating negative events detected in a process but also for taking corrective measures. The aim of this article is to formulate a method that can be used to set and evaluate the technical risk of the cutting process from an organizational point of view.
Quantitative Evaluation of Deformation in High-Speed Magnetic Flux Leakage Signals for Weld Defects in Oil and Gas Pipelines
Authors: Ren Lemei , Liu Wenlong , Zhu Bo , Tian Guansan , Lu Hui , Yan Linkai
Published: October 2024

Complex multiphase flow in oil and gas pipelines raises safety risks. Magnetic flux leakage (MFL) detection effectively identifies pipeline defects. However, the high-speed movement of MFL inspection tools induces motion-induced eddy currents (MIECs), complicating defect recognition and quantification. Most prior research has primarily focused on rectangular defects, leaving a gap in understanding the impact of MIECs on weld defects. This paper proposes the amplitude and shape deformation coefficients to analyze the influence of velocity on various weld defects, including internal reinforcement, lack of penetration, crack, external corrosion, internal corrosion, porosity, and lack of fusion. Utilizing these coefficients, this study examines the influence of the defect size and magnetizer configuration on these velocity-induced effects. The results show that the shape deformation coefficients range from 2.75 to 3.57 for Bx and from −0.13 to −0.3 for By, indicating a significant change in the MFL signal shape at 10 m/s compared to 0 m/s. The amplitude deformation coefficients for lack of penetration, internal corrosion, and porosity range from −0.01 to 0.1 for Bx, and from 0.86 to 0.98 for By, suggesting a decrease in peak-to-peak values. In contrast, other defects exhibit an increase in peak-to-peak values, indicating that the velocity effect may enhance the MFL signal. Also, the defect size and magnetizer configuration can affect the velocity effect on signals. These findings provide essential guidance for quantifying defect sizes and a solid foundation for designing more effective magnetization devices.
Towards Sustainable Transportation: Adaptive Trajectory Tracking Control Strategies of a Four-Wheel-Steering Autonomous Vehicle for Improved Stability and Efficacy
Authors: Al-saedi Mazin I. , AL-bawi Hiba Mohsin Abd Ali
Published: October 2024

The objective of continuous increase in the evolution of autonomous and intelligent vehicles is to attain a trustworthy, economical, and safe transportation system. Four-wheel steering (4WS) vehicles are favored over traditional front-wheel steering (FWS) vehicles because they have excellent dynamic characteristics. This paper exhibits the trajectory tracking task of a two degree of freedom (2DOF) underactuated 4WS Autonomous Vehicle (AV). Because the system is underactuated, MIMO, and has a nontriangular form, the traditional adaptive backstepping control scheme cannot be utilized to control it. For the purpose of rectifying this issue, two-state feedback-based methods grounded on the hierarchical steps of the block backstepping controller are proposed and compared in this paper. In the first strategy, a modified block backstepping is applied for the entire dynamic system. Global stability of the overall system is manifested by Lyapunov theory and Barbalat’s Lemma. In the second strategy, a block backstepping controller has been applied after a reduction of the high-order model into various first-order subsystems, consisting of Lyapunov-based design and stability warranty. A trajectory tracking controller that can follow a double lane change path with high accuracy is designed, and then simulation experiments of the CarSim/Simulink connection are carried out against various vehicle longitudinal speeds and road surface roughness to demonstrate the effectiveness of the presented controllers. Furthermore, a PID driver model is introduced for comparison with the two proposed controllers. Simulation outcomes show that the proposed controllers can attain good response implementation and enhance the 4WS AV performance and stability. Indeed, enhancement of the stability and efficacy of 4WS autonomous vehicles would afford a sustainable transportation system by lessening fuel consumption and gas emissions.
The Great Versatility of Supercritical Fluids in Industrial Processes: A Focus on Chemical, Agri-Food and Energy Applications
Authors: Kamjam Manita , Ngamprasertsith Somkiat , Sawangkeaw Ruengwit , Charoenchaitrakool Manop , Privat Romain , Jaubert Jean-Noël , Molière Michel
Published: October 2024

Long a thermodynamic curiosity, supercritical fluids (SCFs) have gradually gained ground in today’s life, generating an increasing number of new, efficient processes in diverse industrial sectors and fueling active R&D programs. Indeed, the versatility of SCFs allows them to serve a wide variety of applications. The list includes not only food processing, biofuel production, extraction of biomolecules marketable as medicines, cosmetics and nutraceuticals, but also emerging technologies for the production of electrical power, based on supercritical or transcritical thermodynamic cycles. This jointly authored article will provide a review of important applications covered by our laboratories in the agri-food, chemical and energy sectors. We will then try to detect recent trends and outline future prospects.
Utilizing Herbal Dust: Ultrasound-Assisted Extraction of Green Tea, Hibiscus, and Lemon Balm Filter Tea Industry Waste
Authors: Simić Siniša , Vidović Senka , Lubura Stošić Jelena , Filipović Katarina , Aladić Krunoslav , Jokić Stela , Gavarić Aleksandra
Published: October 2024

The rise of the global tea industry market, influenced by the growing demands for healthier diet options, resulted in the constant increase in herbal tea production. In accordance, increased production leads to increased waste generation, especially in the area of filter tea production, which generates waste in the form of powdered plant material with particle sizes lower than 0.315 mm. The generated amount of this powdered plant material, also called herbal dust, can vary in the range from 10 to 40% of the total processed plant, and it is often considered waste only due to its size. Therefore, within this study, ultrasound-assisted extraction (UAE) was utilized for the extraction of green tea (Camellia sinensis L.), lemon balm (Melissa officinalis L.), and hibiscus (Hibiscus sabdariffa L.) herbal dust, and the quality of the obtained extracts was evaluated in terms of total phenolic content (TPC) and phenolic profile. In addition, UAE was conducted on the three different amplitudes (20, 60, and 100%) and two different extraction times (5 and 10 min) in order to investigate and compare the influence of different extraction parameters. The results showed that the maximum TPC for green tea, hibiscus, and lemon balm herbal dust was 152.91 ± 0.74, 60.63 ± 0.10, and 356.22 ± 3.13 mg GAE/g DE, respectively. HPLC analysis conducted for all of the obtained extracts confirmed the presence of several phenolic compounds, with the highest concentrations of epigallocatechin gallate (EGCG) for the extracts of green tea, and neochlorogenic acid for hibiscus herbal dust extracts. The HPLC analysis of the lemon balm extracts recorded the highest concentration of rosmarinic acid for all of the UAE conditions. The results reported within this study indicate that previously considered waste, herbal dust plant material can be successfully extracted by application of UAE and that the obtained extracts exhibit concentrations of bioactive compounds comparable to the extracts of the commercially available plant material.
Study on Non-Isothermal Three-Phase Flow Characteristics in Large-Diameter Drilling Annular
Authors: Ma Yingwen , Cui Yueqi , Zhou Mengmeng , Song Xianzhi , Xu Zhengming , Wang Gaosheng , Zhu Zhaopeng , Yang Jin , Zhou Jianliang
Published: October 2024

As oil and gas exploration extends into ultra-deep land and sea environments, developing accurate and efficient hydraulic computation models is essential for improving safe and effective drilling techniques. This paper presents a non-isothermal transient hydraulic computational model developed in MATLAB, which integrates the wellbore temperature and flow fields to simulate temperature, pressure, and phase distributions during gas-liquid-solid three-phase flow in deep wells with large annular ratios. Through example calculations, we examine the effects of the annular ratio and convective heat transfer coefficient on wellbore flow. Results indicate that increasing the annular ratio decreases bottom-hole temperature and pressure; specifically, increasing the annular ratio from 1.5 to 3.5 results in approximately a 10% reduction in pressure and a temperature drop of over 50 K. Additionally, when considering convective heat transfer in the drilling fluid, wellbore temperature increases gradually with depth, peaking at about 1/8 of the total well depth. These findings provide theoretical guidance for designing drilling programs and selecting well control strategies for ultra-deep wells.
The Molecular Modeling, Simulation, and Design of Base Oils and Additives in Lubricating Oils: A Review
Authors: Zhou Kang , Che Xinhao , Wei Chaoliang , Tang Zhongping , Yu Hai , Wang Dong , Wang Jianxin , Zhang Lei
Published: October 2024

Lubricating oils play a crucial role in modern industrial production, mechanical manufacturing, aerospace, and other fields. This paper provides a review and summary of the entire workflow for molecular simulations of lubricating oils, from molecular modeling, especially the molecular representation of base oils, to simulation calculation methods and result analysis. The application prospects and values of the relevant simulation techniques are discussed in detail. The simulation methods, force fields, and software involved in the modeling and simulation process are also introduced, aiming to provide guidance and insights for more rigorous, rational, and accurate lubricant molecular simulations, so as to accelerate the modification and development of new high-quality lubricants.
Spread Option Pricing Under Finite Liquidity Framework
Authors: Pirvu Traian A. , Zhang Shuming
Published: October 2024

This work explores a finite liquidity model to price spread options and assess the liquidity impact. We employ Kirk approximation for computing the spread option price and its delta. The latter is needed since the liquidity impact is caused by the delta hedging of a large investor. Our main contribution is a novel methodology to price spread options in this paradigm. Kirk approximation in conjunction with Monte Carlo simulations yields the spread option prices. Moreover, the antithetic and control variates variance reduction techniques improve the performance of our method. Numerical experiments reveal that the finite liquidity causes a liquidity value adjustment in option prices ranging from 0.53% to 2.81%. The effect of correlation on prices is also explored, and as expected the option price increases due to the diversification effect, but the liquidity impact decreases slightly.
Terahertz Emission Modeling of Lunar Regolith
Authors: Wang Suyun
Published: October 2024

We investigate the terahertz (THz) scattering and emission properties of lunar regolith by modeling it as a random medium with rough top and bottom boundaries and a host medium situated beneath. The total scattering and emission arise from three sources: the rough boundaries, the volume, and the interactions between the boundaries and the volume. To account for these sources, we model their respective phase matrices and apply the matrix doubling approach to couple these phase matrices to compute the total emission. The model is then used to explore insights into lunar regolith scattering and emission processes. The simulations reveal that surface roughness is the primary contributor to total scattering, while dielectric contrasts between the volume and the boundaries dominate total emission. The THz emissivity is highly sensitive to the regolith dielectric constant, particularly its imaginary part, making it a promising alternative for identifying previously undetected water ice in the lunar polar regions. The THz emissivity model developed in this study can be readily applied to invert the surface parameters of lunar regolith using THz observations.
The Time Difference of Arrival Estimation Method Utilizing an Inexact Reconstruction Within the Framework of Compressed Sensing
Authors: Wang Shanhe , Xiang Yu , Gao Yuanyuan , Hua Yu , Huang Changjiang , Zhao Xian
Published: October 2024

The time difference of arrival (TDOA) estimation plays a crucial role in emitter localization and time synchronization applications. When time among multiple sensors is synchronized, the TDOAs between the sensors and the emitter can be measured to achieve hyperbolic positioning of the emitter. Conversely, if the positions of both the sensors and the emitter are known, TDOAs can be utilized to synchronize the clocks across the sensors. Given that compressed sensing (CS) can reduce both the sampling rate and data volume, thereby enhancing the efficiency of TDOA estimation, there has been growing interest among researchers in exploring TDOA estimation within the CS framework. In scenarios such as passive positioning, the signals received by sensors are often non-cooperative, and the underlying signal system is unknown, making it difficult to obtain a sparse representation of the signal. This paper introduces an incomplete reconstruction-based TDOA estimation method along with an improved variant. By selecting a partial Fourier transform matrix as the measurement matrix and a Fourier transform matrix as the projection matrix, the orthogonal matching pursuit (OMP) algorithm is employed to reconstruct the compressed measurement data. Through subsequent processing steps, such as conjugate mirroring, TDOA estimation between two signals can be performed. Although the reconstructed signal may substantially differ from the original, the accuracy of TDOA estimation remains reliable. Simulation results demonstrate that when the signal-to-noise ratio (SNR) of the received signal is at least 0 dB and the compressed sampling length exceeds one-tenth of the original signal length, the TDOA estimation error of the proposed method is nearly identical to that of the cross-correlation method.
Hierarchical Mixed-Precision Post-Training Quantization for SAR Ship Detection Networks
Authors: Wei Hang , Wang Zulin , Ni Yuanhan
Published: October 2024

Convolutional neural network (CNN)-based synthetic aperture radar (SAR) ship detection models operating directly on satellites can reduce transmission latency and improve real-time surveillance capabilities. However, limited satellite platform resources present a significant challenge. Post-training quantization (PTQ) provides an efficient method for pre-training neural networks to effectively reduce memory and computational resources without retraining. Despite this, PTQ faces the challenge of maintaining model accuracy, especially at low-bit quantization (e.g., 4-bit or 2-bit). To address this challenge, we propose a hierarchical mixed-precision post-training quantization (HMPTQ) method for SAR ship detection neural networks to reduce quantization error. This method encompasses a layerwise precision configuration based on reconstruction error and an intra-layer mixed-precision quantization strategy. Specifically, our approach initially utilizes the activation reconstruction error of each layer to gauge the sensitivity necessary for bit allocation, considering the interdependencies among layers, which effectively reduces the complexity of computational sensitivity and achieves more precise quantization allocation. Subsequently, to minimize the quantization error of the layers, an intra-layer mixed-precision quantization strategy based on probability density assigns a greater number of quantization bits to regions where the probability density is low for higher values. Our evaluation on the SSDD, HRSID, and LS-SSDD-v1.0 SAR Ship datasets, using different detection CNN models, shows that the YOLOV9c model with mixed-precision quantization at 4-bit and 2-bit for weights and activations achieves only a 0.28% accuracy loss on the SSDD dataset, while reducing the model size by approximately 80%. Compared to state-of-the-art methods, our approach maintains competitive accuracy, confirming the superior performance of the HMPTQ method over existing quantization techniques.
A Knowledge Base Driven Task-Oriented Image Semantic Communication Scheme
Authors: Guo Chang , Xi Junhua , He Zhanhao , Liu Jiaqi , Yang Jungang
Published: October 2024

With the development of artificial intelligence and computer hardware, semantic communication has been attracting great interest. As an emerging communication paradigm, semantic communication can reduce the requirement for channel bandwidth by extracting semantic information. This is an effective method that can be applied to image acquisition of unmanned aerial vehicles, which can transmit high-data-volume images within the constraints of limited available bandwidth. However, the existing semantic communication schemes fail to adequately incorporate the guidance of task requirements into the semantic communication process and are difficult to adapt to the dynamic changes of tasks. A task-oriented image semantic communication scheme driven by knowledge base is proposed, aiming at achieving high compression ratio and high quality image reconstruction, and effectively solving the bandwidth limitation. This scheme segments the input image into several semantic information unit under the guidance of task requirements by Yolo-World and Segment Anything Model. The assigned bandwidth for each unit is according to the task relevance scores, which enables high-quality transmission of task-related information with lower communication overheads. An improved metric weighted learned perceptual image patch similarity (LPIPS) is proposed to evaluate the transmission accuracy of the novel scheme. Experimental results show that our scheme achieves a notable performance improvement on weighted LPIPS while the same compression ratio compared with traditional image compression schemes. Our scheme has a higher target capture ratio than traditional image compression schemes under the task of target detection.
Relative Radiometric Normalization for the PlanetScope Nanosatellite Constellation Based on Sentinel-2 Images
Authors: Dias Rafael Luís Silva , Amorim Ricardo Santos Silva , da Silva Demetrius David , Fernandes-Filho Elpídio Inácio , Veloso Gustavo Vieira , Macedo Ronam Henrique Fonseca
Published: October 2024

Detecting and characterizing continuous changes on Earth’s surface has become critical for planning and development. Since 2016, Planet Labs has launched hundreds of nanosatellites, known as Doves. Despite the advantages of their high spatial and temporal resolution, these nanosatellites’ images still present inconsistencies in radiometric resolution, limiting their broader usability. To address this issue, a model for radiometric normalization of PlanetScope (PS) images was developed using Multispectral Instrument/Sentinel-2 (MSI/S2) sensor images as a reference. An extensive database was compiled, including images from all available versions of the PS sensor (e.g., PS2, PSB.SD, and PS2.SD) from 2017 to 2022, along with data from various weather stations. The sampling process was carried out for each band using two methods: Conditioned Latin Hypercube Sampling (cLHS) and statistical visualization. Five machine learning algorithms were then applied, incorporating both linear and nonlinear models based on rules and decision trees: Multiple Linear Regression (MLR), Model Averaged Neural Network (avNNet), Random Forest (RF), k-Nearest Neighbors (KKNN), and Support Vector Machine with Radial Basis Function (SVM-RBF). A rigorous covariate selection process was performed for model application, and the models’ performance was evaluated using the following statistical indices: Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Lin’s Concordance Correlation Coefficient (CCC), and Coefficient of Determination (R2). Additionally, Kruskal–Wallis and Dunn tests were applied during model selection to identify the best-performing model. The results indicated that the RF model provided the best fit across all PS sensor bands, with more accurate results in the longer wavelength bands (Band 3 and Band 4). The models achieved RMSE reflectance values of approximately 0.02 and 0.03 in these bands, with R2 and CCC ranging from 0.77 to 0.90 and 0.87 to 0.94, respectively. In summary, this study makes a significant contribution to optimizing the use of PS sensor images for various applications by offering a detailed and robust approach to radiometric normalization. These findings have important implications for the efficient monitoring of surface changes on Earth, potentially enhancing the practical and scientific use of these datasets.
AFA–Mamba: Adaptive Feature Alignment with Global–Local Mamba for Hyperspectral and LiDAR Data Classification
Authors: Li Sai , Huang Shuo
Published: October 2024

The joint classification of hyperspectral imagery (HSI) and LiDAR data is an important task in the field of remote sensing image interpretation. Traditional classification methods, such as support vector machine (SVM) and random forest (RF), have difficulty capturing the complex spectral–spatial–elevation correlation information. Recently, important progress has been made in HSI-LiDAR classification using Convolutional Neural Networks (CNNs) and Transformers. However, due to the large spatial extent of remote sensing images, the vanilla Transformer and CNNs struggle to effectively capture global context. Moreover, the weak misalignment between multi-source data poses challenges for their effective fusion. In this paper, we introduce AFA–Mamba, an Adaptive Feature Alignment Network with a Global–Local Mamba design that achieves accurate land cover classification. It contains two main core designs: (1) We first propose a Global–Local Mamba encoder, which effectively models context through a 2D selective scanning mechanism while introducing local bias to enhance the spatial features of local objects. (2) We also propose an SSE Adaptive Alignment and Fusion (A2F) module to adaptively adjust the relative positions between multi-source features. This module establishes a guided subspace to accurately estimate feature-level offsets, enabling optimal fusion. As a result, our AFA–Mamba consistently outperforms state-of-the-art multi-source fusion classification approaches across multiple datasets.
Floodwater Extraction from UAV Orthoimagery Based on a Transformer Model
Authors: Wu Zhihong , Dong Zhe , Yang Kun , Liu Qingjie , Wang Wei
Published: October 2024

In recent years, remote sensing has experienced a significant transformation due to rapid advancements in deep learning technology, which have greatly outpaced traditional methodologies. This integration has attracted substantial interest within the academic community. To address the complex challenges of extracting data on intricate water bodies during disaster scenarios, this study developed a post-disaster floodwater body dataset and an enhanced multi-scale transformer model architecture. Through end-to-end training, the precision of the model in extracting floodwater contours has been significantly improved. Additionally, by utilizing the vast amounts of unannotated data in remote sensing through an unsupervised pre-training task, the model’s backbone network has been fortified, greatly enhancing its performance in remote sensing applications. Experimental analyses have shown that the multi-scale transformer-based algorithm for floodwater contour extraction proposed in this study is not only widely applicable but also excels in delivering precise segmentation results in complex environments. This refined approach ensures that the model adeptly handles the intricacies of floodwater body delineation, providing a robust solution for accurate extraction, even in disaster-stricken areas. This innovation represents a substantial leap forward in remote sensing, offering valuable insights and tools for disaster management and environmental monitoring.
Intelligent Monitoring Applications of Landslide Disaster Knowledge Graphs Based on ChatGLM2
Authors: Wu Zhengrong , Yang Haibo , Cai Yingchun , Yu Bo , Liang Chuangheng , Duan Zheng , Liang Qiuhua
Published: October 2024

Over the years, the field of landslide disaster research has amassed a wealth of data and specialized knowledge. However, these resources originate from a wide array of sources and often feature complex data structures, highlighting a persistent lack of methods to integrate multi-source, heterogeneous data. Traditional landslide monitoring methods typically focus on singular monitoring targets and data sources, which limits a comprehensive understanding of the complex processes involved in landslides. This paper introduces a landslide monitoring model based on a knowledge graph. This model employs P-Tuning to fine-tune ChatGLM2 for the extraction of triples. Differential InSAR (D-InSAR) is utilized to extract ground deformation data, which is then integrated with the knowledge graph for landslide monitoring and analysis. This study focuses on the co-seismic landslide in Jishishan, Gansu, China. By analyzing the landslide knowledge graph and the spatiotemporal deformation map, the results are as follows: (1) For this event, 106 entities and attributes were constructed, along with two recommended calculation routes. (2) The deformation at the earthquake’s central region reached up to 8.784 cm, with a slightly smaller deformation zone to the northwest peaking at 9.662 cm. Significant unilateral subsidence was observed in the mountain range to the southwest. (3) The area affected by the co-seismic landslide primarily includes farmland and villages, covering an area of 0.3408 square kilometers. (4) Analysis based on the knowledge graph indicates that this landslide was primarily caused by the rapid liquefaction of water-saturated soil layers due to the earthquake, resulting in instability. This study contributes to the analysis of post-disaster losses, attribution, and impacts.