bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Acid Aging and Damage Pattern Recognition of Glass Fiber-Reinforced Plastic Oil and Gas Gathering Pipelines Based on Acoustic Emission
Authors: Bi Haisheng , Zhang Yuhong , Zhang Chen , Ma Chunxun , Li Yuxiang , Miao Jiaxu , Wang Guang , Cheng Haoran
Published: August 2024

Pipelines extend thousands of kilometers to transport and distribute oil and gas. Given the challenges often faced with corrosion, fatigue, and other issues in steel pipes, the demand for glass fiber-reinforced plastic (GFRP) pipes is increasing in oil and gas gathering and transmission systems. However, the medium that is transported through these pipelines contains multiple acid gases such as CO2 and H2S, as well as ions including Cl−, Ca2+, Mg2+, SO42−, CO32−, and HCO3−. These substances can cause a series of problems, such as aging, debonding, delamination, and fracture. In this study, a series of aging damage experiments were conducted on V-shaped defect GFRP pipes with depths of 2 mm and 5 mm. The aging and failure of GFRP were studied under the combined effects of external force and acidic solution using acoustic emission (AE) techniques. It was found that the acidic aging solution promoted matrix damage, fiber/matrix desorption, and delamination damage in GFRP pipes over a short period. However, the overall aging effect was relatively weak. Based on the experimental data, the SSA-LSSVM algorithm was proposed and applied to the damage pattern recognition of GFRP. An average recognition rate of up to 90% was achieved, indicating that this method is highly suitable for analyzing AE signals related to GFRP damage.
Polymer-Assisted Graphite Exfoliation: Advancing Nanostructure Preparation and Multifunctional Composites
Authors: Orellana Jaime , Araya-Hermosilla Esteban , Pucci Andrea , Araya-Hermosilla Rodrigo
Published: August 2024

Exfoliated graphite (ExG) embedded in a polymeric matrix represents an accessible, cost-effective, and sustainable method for generating nanosized graphite-based polymer composites with multifunctional properties. This review article analyzes diverse methods currently used to exfoliate graphite into graphite nanoplatelets, few-layer graphene, and polymer-assisted graphene. It also explores engineered methods for small-scale pilot production of polymer nanocomposites. It highlights the chemistry involved during the graphite intercalation and exfoliation process, particularly emphasizing the interfacial interactions related to steric repulsion forces, van der Waals forces, hydrogen bonds, π-π stacking, and covalent bonds. These interactions promote the dispersion and stabilization of the graphite derivative structures in polymeric matrices. Finally, it compares the enhanced properties of nanocomposites, such as increased thermal and electrical conductivity and electromagnetic interference (EMI) shielding applications, with those of neat polymer materials.
Improving Shale Stability through the Utilization of Graphene Nanopowder and Modified Polymer-Based Silica Nanocomposite in Water-Based Drilling Fluids
Authors: Ospanov Yerlan Kanatovich , Kudaikulova Gulzhan Abdullaevna , Moldabekov Murat Smanovich , Zhaksylykova Moldir Zhumabaevna
Published: August 2024

Shale formations present significant challenges to traditional drilling fluids due to fluid infiltration, cuttings dispersion, and shale swelling, which can destabilize the wellbore. While oil-based drilling fluids (OBM) effectively address these concerns about their environmental impact, their cost limits their widespread use. Recently, nanomaterials (NPs) have emerged as a promising approach in drilling fluid technology, offering an innovative solution to improve the efficiency of water-based drilling fluids (WBDFs) in shale operations. This study evaluates the potential of utilizing modified silica nanocomposite and graphene nanopowder to formulate a nanoparticle-enhanced water-based drilling fluid (NP-WBDF). The main objective is to investigate the impact of these nanoparticle additives on the flow characteristics, filtration efficiency, and inhibition properties of the NP-WBDF. In this research, a silica nanocomposite was successfully synthesized using emulsion polymerization and analyzed using FTIR, PSD, and TEM techniques. Results showed that the silica nanocomposite exhibited a unimodal particle size distribution ranging from 38 nm to 164 nm, with an average particle size of approximately 72 nm. Shale samples before and after interaction with the graphene nanopowder WBDF and the silica nanocomposite WBDF were analyzed using scanning electron microscopy (SEM). The NP-WBM underwent evaluation through API filtration tests (LTLP), high-temperature/high-pressure (HTHP) filtration tests, and rheological measurements conducted with a conventional viscometer. Experimental results showed that the silica nanocomposite and the graphene nanopowder effectively bridged and sealed shale pore throats, demonstrating superior inhibition performance compared to conventional WBDF. Post adsorption, the shale surface exhibited increased hydrophobicity, contributing to enhanced stability. Overall, the silica nanocomposite and the graphene nanopowder positively impacted rheological performance and provided favorable filtration control in water-based drilling fluids.
Thermal Safety Study of Emulsion Explosive Matrix under the Coupled Effects of Environmental Pressure and Bubble Content with Internal Heat Source
Authors: Zhang Yi-Bo , Liu Qian , Shi Xiao-Cen
Published: August 2024

Emulsion explosives have become a hot topic in various studies due to their explosive combustion characteristics and detonation performance under different environmental pressures. The thermal safety of an emulsified matrix was studied with ignition energy as the characterization. A minimum ignition energy test experimental system for emulsion matrices was established in this research. The system simulated the occurrence of hot spots inside emulsion matrices using an electric heating wire. The effect of bubbles on the thermal safety of the emulsified matrix was studied by adding expanded perlite additive to the emulsified matrix. This study investigated the variation trend in the minimum ignition energy of the emulsion matrix under the coupled effect of bubbles and ambient pressure using the orthogonal experimental method. The impacts of two factors on the thermal safety of the emulsion matrix were studied at different hot-spot temperatures. Coupled analysis experiments were conducted on emulsion matrices containing 0%, 1.5%, and 3% expanded perlite under pressure environments of 1 atm, 2 atm, and 3 atm. The critical hot-spot temperature of the emulsion matrix significantly decreases with increasing bubble content at 1 atm and 2 atm pressures, as revealed by intuitive analysis and analysis of variance. However, at 3 atm of pressure, the bubble content in the emulsion matrix has no significant effect on its critical hot-spot temperature. The results show that the thermal safety of the emulsified matrix decreases with the increase in the content of expanded perlite and environmental pressure, and the influence of environmental pressure is more significant than that of the bubble content. This paper’s research content serves as a reference for a safe emulsified matrix and as an experimental basis for establishing a production line for developing new equipment.
Effects of Biochar-Amended Composts on Selected Enzyme Activities in Soils
Authors: Zaid Faraj , Al-Awwal Nasruddeen , Yang John , Anderson Stephen H. , Alsunuse Bouzeriba T. B.
Published: August 2024

This study examines the effect of biochar as an agricultural soil supplement on soil quality indicators, specifically enzyme activity in Missouri regions. While the benefits of biochar on soil bulk density, soil organic carbon, and infiltration have been established, its effect on soil enzyme activity has remained underexplored in this region. A three-year field investigation was conducted with six treatments (compost, biochar, compost + biochar, biochar + compost tea, fescue, and control) to evaluate the effects on enzymes such as β-glucosidase (BG), acid and alkaline phosphatases (ACP-ALP), arylsulfatase (ARS), dehydrogenases (DG), arylamidase (AMD), cellulase (CLS), and urease (URS). Furthermore, soil pH, organic matter (OM), and cation exchange capacity (CEC) were determined. The results showed that compost and biochar treatments considerably increased soil enzyme activity compared to other treatments, with nitrogen application further increasing enzyme activity. Soil pH, OM, and CEC were all important determinants in determining enzyme activity, with BG demonstrating strong positive associations with ACP and AMD (99.5%). This study shows that compost and biochar amendments significantly improve soil physicochemical and biological properties, thereby enhancing soil health and assisting farmers’ sustainable soil management practices.
Studies of TLC-Chromatographic Quantification of Astaxanthin in Dietary Supplements and Its Antioxidant Activity
Authors: Dymek Iwona , Żandarek Joanna , Starek Małgorzata , Dąbrowska Monika
Published: August 2024

Astaxanthin is a red carotenoid pigment known for its strong antioxidant and immune-supporting properties, which are higher than other carotenoids. The aim of this study was the qualitative and quantitative evaluation of dietary supplements containing astaxanthin. First, optimal conditions for conducting analyses using the TLC technique with densitometric detection were developed. The mobile phase consisting of methanol: ethyl acetate: 1,4-dioxane (1:3:6 v/v/v) was selected, while the stationary phase consisted of Silica gel 60 F254. Densitometric detection was performed at 460 nm. Next, the validation process of the developed method was carried out according to the guidelines of the International Conference on Harmonization (ICH). The range of linearity tested was 0.0026–0.0100 µg/spot, and the determined LOD and LOQ values were 0.85 and 2.57 ng/μL, respectively. The variation coefficient at the level of 4.75% proves good precision. The percentage of recovery was in the range of 95.25–104.94%. The obtained results confirmed the good accuracy of the method. Subsequently, quantitative analyses of the preparations were carried out. Analysis of dietary supplements showed significant deviations from the declared astaxanthin content. Astaxanthin solutions were stable in alkaline environments and when exposed to light and oxidizing substances; however, the substance degraded in acidic environments. The performed antioxidant capacity tests confirmed the high antioxidant activity of astaxanthin.
Fracture Evolution during CO2 Fracturing in Unconventional Formations: A Simulation Study Using the Phase Field Method
Authors: Yang Bing , Ren Qianqian , Huang Hai , Wang Haizhu , Zheng Yong , Dou Liangbin , He Yanlong , Zhang Wentong , Chen Haoyu , Qiao Ruihong
Published: August 2024

With the introduction of China’s “dual carbon” goals, CO2 is increasingly valued as a resource and is being utilized in unconventional oil and gas development. Its application in fracturing operations shows promising prospects, enabling efficient extraction of oil and gas while facilitating carbon sequestration. The process of reservoir stimulation using CO2 fracturing is complex, involving coupled phenomena such as temperature variations, fluid behavior, and rock mechanics. Currently, numerous scholars have conducted fracturing experiments to explore the mechanisms of supercritical CO2 (SC-CO2)-induced fractures in relatively deep formations. However, there is relatively limited numerical simulation research on the coupling processes involved in CO2 fracturing. Some simulation studies have simplified reservoir and operational parameters, indicating a need for further exploration into the multi-field coupling mechanisms of CO2 fracturing. In this study, a coupled thermo-hydro-mechanical fracturing model considering the CO2 properties and heat transfer characteristics was developed using the phase field method. The multi-field coupling characteristics of hydraulic fracturing with water and SC-CO2 are compared, and the effects of different geological parameters (such as in situ stress) and engineering parameters (such as the injection rate) on fracturing performance in tight reservoirs were investigated. The simulation results validate the conclusion that CO2, especially in its supercritical state, effectively reduces reservoir breakdown pressures and induces relatively complex fractures compared with water fracturing. During CO2 injection, heat transfer between the fluid and rock creates a thermal transition zone near the wellbore, beyond which the reservoir temperature remains relatively unchanged. Larger temperature differentials between the injected CO2 fluid and the formation result in more complicated fracture patterns due to thermal stress effects. With a CO2 injection, the displacement field of the formation deviated asymmetrically and changed abruptly when the fracture formed. As the in situ stress difference increased, the morphology of the SC-CO2-induced fractures tended to become simpler, and conversely, the fracture presented a complicated distribution. Furthermore, with an increasing injection rate of CO2, the fractures exhibited a greater width and extended over longer distances, which are more conducive to reservoir volumetric enhancement. The findings of this study validate the authenticity of previous experimental results, and it analyzed fracture evolution through the multi-field coupling process of CO2 fracturing, thereby enhancing theoretical understanding and laying a foundational basis for the application of this technology.
Forest Fire Detection Based on Spatial Characteristics of Surface Temperature
Authors: Yao Houzhi , Yang Zhigao , Zhang Gui , Liu Feng
Published: August 2024

Amidst the escalating threat of global warming, which manifests in more frequent forest fires, the prompt and accurate detection of forest fires has ascended to paramount importance. The current surveillance algorithms employed for forest fire monitoring—including, but not limited to, fixed threshold algorithms, multi-channel threshold algorithms, and contextual algorithms—rely primarily upon the degree of deviation between the pixel temperature and the background temperature to discern pyric events. Notwithstanding, these algorithms typically fail to account for the spatial heterogeneity of the background temperature, precipitating the consequential oversight of low-temperature fire point pixels, thus impeding the expedited detection of fires in their initial stages. For the amelioration of this deficiency, the present study introduces a spatial feature-based (STF) method for forest fire detection, leveraging Himawari-8/9 imagery as the main data source, complemented by the Shuttle Radar Topography Mission (SRTM) DEM data inputs. Our proposed modality reconstructs the surface temperature information via selecting the optimally designated machine learning model, subsequently identifying the fire point through utilizing the difference between the reconstructed surface temperatures and empirical observations, in tandem with the spatial contextual algorithm. The results confirm that the random forest model demonstrates superior efficacy in the reconstruction of the surface temperature. Benchmarking the STF method against both the fire point datasets disseminated by the China Forest and Grassland Fire Prevention and Suppression Network (CFGFPN) and the Wild Land Fire (WLF) fire point product validation datasets from Himawari-8/9 yielded a zero rate of omission errors and a comprehensive evaluative index, predominantly surpassing 0.74. These findings show that the STF method proposed herein significantly augments the identification of lower-temperature fire point pixels, thereby amplifying the sensitivity of forest surveillance.
Underdetermined Blind Source Separation of Audio Signals for Group Reared Pigs Based on Sparse Component Analysis
Authors: Pan Weihao , Jiao Jun , Zhou Xiaobo , Xu Zhengrong , Gu Lichuan , Zhu Cheng
Published: August 2024

In order to solve the problem of difficult separation of audio signals collected in pig environments, this study proposes an underdetermined blind source separation (UBSS) method based on sparsification theory. The audio signals obtained by mixing the audio signals of pigs in different states with different coefficients are taken as observation signals, and the mixing matrix is first estimated from the observation signals using the improved AP clustering method based on the “two-step method” of sparse component analysis (SCA), and then the audio signals of pigs are reconstructed by L1-paradigm separation. Five different types of pig audio are selected for experiments to explore the effects of duration and mixing matrix on the blind source separation algorithm by controlling the audio duration and mixing matrix, respectively. With three source signals and two observed signals, the reconstructed signal metrics corresponding to different durations and different mixing matrices perform well. The similarity coefficient is above 0.8, the average recovered signal-to-noise ratio is above 8 dB, and the normalized mean square error is below 0.02. The experimental results show that different audio durations and different mixing matrices have certain effects on the UBSS algorithm, so the recording duration and the spatial location of the recording device need to be considered in practical applications. Compared with the classical UBSS algorithm, the proposed algorithm outperforms the classical blind source separation algorithm in estimating the mixing matrix and separating the mixed audio, which improves the reconstruction quality.
Capacity Building for Student Teachers in Learning, Teaching Artificial Intelligence for Quality of Education
Authors: Altinay Zehra , Altinay Fahriye , Sharma Ramesh Chander , Dagli Gokmen , Shadiev Rustam , Yikici Betul , Altinay Mehmet
Published: August 2024

The future of education relies on the integration of information technologies, emphasizing the importance of equity and inclusiveness for quality education. Teacher education programs are essential for fostering qualified educators for the future. Integrating AI in education is crucial to ensure inclusivity and comprehensive services for all. This study aims to evaluate student teachers’ perceptions of using AI in learning and teaching, and to provide suggestions for enhancing sustainable education through information technologies. A qualitative research design was adopted to gather perceptions and experiences from 240 student teachers who participated in a seminar on AI usage and completed self-reflection tasks. These student teachers, enrolled in various teaching methods and principal courses, contributed to the thematic analysis. The study reveals that AI should be carefully planned and incorporated into lesson plans to enhance personalized learning. Student teachers reported that AI supports and motivates the learning process, effectively transforming students’ needs and learning experiences. However, they also noted potential drawbacks, such as AI imposing restrictions on the teaching profession, replacing teachers, and producing biased results. The study suggests that capacity-building strategies for student teachers should be enriched across different courses to raise awareness about AI’s applications.
A Comparison of the Plyometric Performance of Upper Limbs between Experienced and Non-Experienced Athletes
Authors: Dhote Sylvain , Eon Pauline , Grosprêtre Sidney
Published: August 2024

Although explosive upper-limb movements are far less studied than the equivalent lower-limb movements, they are important in many sports activities. The goal of this study was to explore, for the first time, the performance of street workout (SW) athletes who primarily focus on explosive and isometric strength in the upper limbs and to examine the effect of the contraction type on performance during a classical upper-body movement. Eighteen men took part in this study (age: 22.6 ± 2.1 years, height: 179.6 ± 7.1 cm, bodyweight: 71.9 ± 6.6 kg). Of these, nine practiced SW and nine practiced various team and individual sports—the latter serving as the control group. The athletes performed three different types of push-ups—one in a concentric way and two others in a plyometric way—and a fatigue-inducing push-up set. Jump heights, myoelectrical activities (through electromyography), muscle architecture, and hypertrophy (through ultrasonography) were measured. The results show no significant differences in jump height between the push-up types. Both groups confounded, but the SW athletes jumped on average 66 ± 21% higher than the control athletes (p < 0.05). There was no major difference in EMG between groups, regardless of the push-up type, but the SW athletes had a greater pectoralis major and anterior deltoid thickness as well as a greater pennation angle of the pectoralis major. The results suggest that the plyometric performance of the upper limbs does not follow the same pattern as that of the lower limbs. The SW group’s greater capacity in performing explosive push-ups could be attributed to greater upper-body muscle hypertrophy and more efficient execution of the movement.
Monitoring and Analysis of Eco-Environmental Quality in Daihai Lake Basin from 1985 to 2022 Based on the Remote Sensing Ecological Index
Authors: Ye Bowen , Sun Biao , Shi Xiaohong , Zhao Yunliang , Guo Yuying , Pang Jiaqi , Yao Weize , Hu Yaxin , Zhao Yunxi
Published: August 2024

Exploring eco-environmental quality dynamics in the Daihai Lake Basin has significant implications for the conservation of ecological environments in the semi-arid and arid regions of northern China. Based on the Google Earth Engine (GEE) platform, the remote sensing ecological index (RSEI) was constructed by coupling Landsat SR remote sensing data from 1985 to 2022. The spatial significance of the RSEI was analyzed using linear regression equations and an F-test. The spatial correlation, distribution characteristics, and driving factors behind the RSEI were explored using Moran’s index and a geodetector. The results indicated that (1) the RSEI was appropriate for evaluating eco-environmental quality in the Daihai Lake Basin. (2) From 1985 to 2022, the eco-environmental quality of the Daihai Lake Basin exhibited a positive trend but remained subpar. (3) A positive spatial autocorrelation was demonstrated for eco-environmental quality with increasing spatial aggregation. (4) Significant eco-environmental quality degradation (slope < 0) occurred primarily in Sanyiquan Town in the northeastern region of the basin and in Tiancheng Township in the southeastern region. Conversely, a notable improvement (slope > 0) was predominantly observed in Yongxing and Liusumu in southwestern Daihai. (5) The improvement in the ecological environment of the Daihai Lake Basin was primarily attributed to an increase in NDVI and WET and a decrease in NDBSI and LST. The interaction between NDVI and LST had the greatest explanatory power for the ecological environment. Among the external driving factors, DEM (elevation) was the dominant factor in the RSEI and had the strongest explanatory power. The interaction between DEM and LST was the most significant, and the driving factors were enhanced. This study provided a theoretical basis for the sustainable development of the Daihai Lake Basin, which is crucial for the local ecological environment and economic development.
Experimental Study on the Physical Properties of Autoclaved Bricks Made from Desert Sand and Their Resistance to Sulfate Attacks
Authors: Yang Cheng , Wang Luping , Zhang Ziyang , Wang Haifeng , Wu Dongge , Wang Yushan , Liang Lu , Liu Wenlong
Published: August 2024

In order to optimize the application of desert sand autoclaved bricks in rural construction in Xinjiang, this study focuses on the research and development of MU15-grade desert sand autoclaved bricks. Experimental investigations were conducted to examine the relationship between the water absorption rate of desert sand autoclaved bricks and the duration of water absorption while analyzing the impact of the water absorption rate on the compressive strength of these bricks. Additionally, experimental research was carried out to evaluate the appearance, compressive strength, and pore structure of autoclaved bricks after sulfate erosion. The results indicate the following. (1) With an increasing immersion time, the water absorption rate of desert sand-based autoclaved bricks initially rises and then declines, reaching approximately 14.74% when immersed for 4 h, which is close to the saturation water absorption rate. (2) The compressive strength of desert sand-based autoclaved bricks gradually decreases with an increasing water absorption rate, reaching its lowest point when saturation is attained, with a strength loss rate of approximately 33.18%. (3) Finally, after sulfate erosion, cracks and detachment appear on the surface of desert sand-based autoclaved bricks, and these cracks extend and propagate with the continuous accumulation of eroded products. Simultaneously, this process leads to an increase in the proportion of harmful pores by 0.96%, thereby causing a deterioration in strength. Through data analysis, a decay curve of the compressive strength erosion coefficient of desert sand-based autoclaved bricks with the number of sulfate erosion cycles was established, with good accuracy. This study provides theoretical references and technical support for the performance characteristics of desert sand-based autoclaved bricks and their application in rural construction in Xinjiang.
Research on the Optimal Trajectory Planning Method for the Dual-Attitude Adjustment Mechanism Based on an Improved Multi-Objective Salp Swarm Algorithm
Authors: Liu Xu , Wang Lei , Shen Chengwu , Ma Wenjia , Liu Shaojin , Han Yan , Wang Zhiqian
Published: August 2024

In this study, an optimization method for the motion trajectory of attitude actuators was investigated in order to improve assembly efficiency in the automatic docking process of large components. The self-developed dual-attitude adjustment mechanism (2-PPPR) is used as the research object, and the structure is symmetrical. Based on the modified Denavit–Hartenberg (MDH) parameter description method, a kinematic model of the attitude mechanism is established, and its end trajectory is parametrically expressed using a five-order B-spline curve. Based on the constraints of the dynamics and kinematics of the dual-posture mechanism, the total posturing time, the degree of urgency of each joint, and the degree of difficulty of the mechanism’s posturing are selected as the optimization objectives. The Lévy flight and Cauchy variation algorithms are introduced into the salp swarm algorithm (SSA) to solve the parameters of the multi-objective trajectory optimization model. By combining the evaluation method of the multi-objective average optimal solution, the optimal trajectory of the dual-tuning mechanism and the motion trajectory of each joint are obtained. The simulation and experiment results show that the trajectory planning method proposed in this paper is effective and feasible and can ensure that the large-part dual-posture mechanism can complete the automatic docking task smoothly and efficiently.
Multi-Task Multi-Objective Evolutionary Search Based on Deep Reinforcement Learning for Multi-Objective Vehicle Routing Problems with Time Windows
Authors: Deng Jianjun , Wang Junjie , Wang Xiaojun , Cai Yiqiao , Liu Peizhong
Published: August 2024

The vehicle routing problem with time windows (VRPTW) is a widely studied combinatorial optimization problem in supply chains and logistics within the last decade. Recent research has explored the potential of deep reinforcement learning (DRL) as a promising solution for the VRPTW. However, the challenge of addressing the VRPTW with many conflicting objectives (MOVRPTW) still remains for DRL. The MOVRPTW considers five conflicting objectives simultaneously: minimizing the number of vehicles required, the total travel distance, the travel time of the longest route, the total waiting time for early arrivals, and the total delay time for late arrivals. To tackle the MOVRPTW, this study introduces the MTMO/DRP-AT, a multi-task multi-objective evolutionary search algorithm, by making full use of both DRL and the multitasking mechanism. In the MTMO/DRL-AT, a two-objective MOVRPTW is constructed as an assisted task, with the objectives being to minimize the total travel distance and the travel time of the longest route. Both the main task and the assisted task are simultaneously solved in a multitasking scenario. Each task is decomposed into scalar optimization subproblems, which are then solved by an attention model trained using DRL. The outputs of these trained models serve as the initial solutions for the MTMO/DRL-AT. Subsequently, the proposed algorithm incorporates knowledge transfer and multiple local search operators to further enhance the quality of these promising solutions. The simulation results on real-world benchmarks highlight the superior performance of the MTMO/DRL-AT compared to several other algorithms in solving the MOVRPTW.
Roles of Micropillar Topography and Surface Energy on Cancer Cell Dynamics
Authors: Vu Hoang Huy , Nguyen Nam-Trung , Yadav Sharda , Nguyen Thi Thanh Ha , Kashaninejad Navid
Published: August 2024

Microstructured surfaces are renowned for their unique properties, such as waterproofing and low adhesion, making them highly applicable in the biomedical field. These surfaces play a crucial role in influencing cell response by mimicking the native microenvironment of biological tissues. In this study, we engineered a series of biomimetic micropatterned surfaces using polydimethylsiloxane (PDMS) to explore their effects on primary breast cancer cell lines, contrasting these effects with those observed on conventional flat surfaces. The surface topography was varied to direct cells’ attachment, growth, and morphology. Our findings elucidate that surface-free energy is not merely a background factor but plays a decisive role in cell dynamics, strongly correlating with the spreading behaviour of breast cancer cells. Notably, on micropillar surfaces with high surface-free energy, an increase in the population of cancer cells was observed. Conversely, surfaces characterised by lower surface-free energies noted a reduction in cell viability. Moreover, the structural parameters, such as the gaps and diameters of the pillars, were found to critically influence cellular dispersion and adherence, underscoring the importance of the microstructures’ topography in biomedical applications. These insights pave the way for designing advanced microstructured surfaces tailored to specific cellular responses, opening new avenues for targeted cancer therapies and tissue engineering.
Sources and Specified Health Risks of 12 PM2.5-Bound Metals in a Typical Air-Polluted City in Northern China during the 13th Five-Year Plan
Authors: Yang Deai , Li Mingjun , Geng Xingyi , Feng Zhihui
Published: August 2024

The continuous monitoring of PM2.5 (including 12 metal elements) was conducted in Jinan, a city with poor air quality in China, during the 13th Five-Year Plan (2016–2020). Positive matrix factorization (PMF) was used to identify emission sources of PM2.5-bound metals, and the health risks of the metals and their emission sources were assessed. During the study period, the concentration of most metals showed a decreasing trend (except Al and Be), and a significant seasonal difference was found: winter > fall > spring > summer. The PMF analysis showed that there were four main sources of PM2.5-bound metals, and their contributions to the total metals (TMs) were dust emissions (54.3%), coal combustion and industrial emissions (22.3%), vehicle emissions (19.3%), and domestic emissions (4.1%). The results of the health risk assessment indicated that the carcinogenic risk of metals (Cr and As) exceeded the acceptable level (1 × 10−6), which was of concern. Under the influence of emission reduction measures, the contribution of emission sources to health risks changes dynamically, and the emission sources that contribute more to health risks were coal combustion and industrial emissions, as well as vehicle emissions. In addition, our findings suggest that a series of emission reduction measures effectively reduced the health risk from emission sources of PM2.5-bound metals.
Effects of Fallen Posidonia Oceanica Seagrass Leaves on Wave Energy at Sandy Beaches
Authors: Sevim Ogan , Otay Emre N.
Published: August 2024

Posidonia Oceanica (PO) is an endemic marine plant in the Mediterranean Sea. In an experimental study conducted in the Eastern Mediterranean, the effects of natural PO leaves on reducing the height of incident waves impacting a beach were measured. The transmission coefficient (Kt) was found to vary between 0.73 and 0.94, which is equivalent to a wave height decay of 6–27%. The results show that in their natural environment, free-floating dead PO leaves dissipate incoming wave energy and have the capacity to protect beaches against erosion. Further analysis in separate frequency bands showed that waves with periods between 4.5–6.2 s were more sensitive to PO leaves in terms of energy dissipation. The transmission coefficient for medium-period waves, calculated using the medium-frequency part of the wave spectrum, delivered a maximum transmission coefficient of 0.5, corresponding to a 50% decay in wave height due to PO leaves.
Pore-Scale Formation Characteristics of Impermeable Frozen Walls for Shallow Groundwater Contamination Remediation
Authors: Zhang Yunfeng , Zhao Zhiqiang , Ding Guantao , Hu Caiping , Wang Yuan , Gao Shuai
Published: August 2024

Impermeability and water blocking are crucial for remediating shallow groundwater contamination. Traditional methods often employ curtain-grouting technology to create impermeable layers. However, cement slurry curing is irreversible, leading to permanent closure of underground aquifers and secondary pollution. This study employs an innovative approach by fabricating cylindrical models that simulate actual strata and utilizing a high-temperature and high-pressure displacement device. It systematically analyzes the variations in soil pore structure, distribution, porosity, and permeability under different temperatures, pressures, and freezing durations. The microscopic characteristics of the freezing process in water-bearing soils were studied. Results demonstrate that longer freezing time improves the effectiveness of soil freezing, reaching complete freezing at temperatures as low as −4 °C for samples with low water content. For water-saturated samples, freezing below −6 °C results in nearly zero porosity. Increased pressure at a certain freezing temperature significantly reduces permeability. When freezing temperature falls below −4 °C, water permeability in saturated samples after freezing reaches near-zero levels, while unsaturated samples experience complete freezing. These findings provide a theoretical foundation for constructing freezing curtains in remediating shallow groundwater pollution.
Towards Non-Region Specific Large-Scale Inundation Modelling with Machine Learning Methods
Authors: Tychsen-Smith Lachlan , Armin Mohammad Ali , Karim Fazlul
Published: August 2024

Traditional flood inundation modelling methods are computationally expensive and not suitable for near-real time inundation prediction. In this study we explore a data-driven machine learning method to complement and, in some cases, replace existing methods. Given sufficient training data and model capacity, our design enables a single neural network instance to approximate the flow characteristics of any input region, opening the possibility of applying the model to regions without available training data. To demonstrate the method we apply it to a very large >8000 km2 region of the Fitzroy river basin in Western Australia with a spatial resolution of 30 m × 30 m, placing an emphasis on efficiency and scalability. In this work we identify and address a range of practical limitations, e.g., we develop a novel water height regression method and cost function to address extreme class imbalances and by carefully constructing the input data, we introduce some natural physical constraints. Furthermore, a compact neural network design and training method was developed to enable the training problem to fit within GPU memory constraints and a novel dataset was constructed from the output of a calibrated two-dimensional hydrodynamic model. A good correlation between the predicted and groundtruth water heights was observed.
Predictive Functional Profiling Reveals Putative Metabolic Capacities of Bacterial Communities in Drinking Water Resources and Distribution Supply in Mega Manila, Philippines
Authors: Castro Arizaldo E. , Obusan Marie Christine M.
Published: August 2024

Assessing bacterial communities across water resources is crucial for understanding ecological dynamics and improving water quality management. This study examines the functional profiles of bacterial communities in drinking water resources in Mega Manila, Philippines, including Laguna Lake tributaries, pre-treatment plant sites, groundwater sources, and post-treatment plant sites. Using eDNA sequencing, flux balance analysis, and taxonomy-to-phenotype mapping, we identified metabolic pathways involved in nutrient metabolism, pollutant degradation, antibio- tic synthesis, and nutrient cycling. Despite site variations, there are shared metabolic pathways, suggesting the influence of common ecological factors. Site-specific differences in pathways like ascorbate, aldarate, and phenylalanine metabolism indicate localized environmental adaptations. Antibiotic synthesis pathways, such as streptomycin and polyketide sugar unit biosynthesis, were detected across sites. Bacterial communities in raw and pre-treatment water showed potential for pollutant degradation such as for endocrine-disrupting chemicals. High levels of ammonia-oxidizing and sulfate-reducing bacteria in pre- and post-treatment water suggest active nitrogen removal and pH neutralization, indicating a need to reassess existing water treatment approaches. This study underscores the adaptability of bacterial communities to environmental factors, as well as the importance of considering their functional profiles in assessing drinking water quality resources in urban areas.
Inhibitory Effect of Combined Exposure to Copper Ions and Polystyrene Microplastics on the Growth of Skeletonema costatum
Authors: Liu Haoyuan , Zhen Yu , Zhang Xiuli , Dou Lianyu
Published: August 2024

As two significant pollutants, the increased concentrations of copper ions and microplastics in coastal waters pose a substantial threat to the health of marine ecosystems. This study explored the individual and combined toxic effects of copper ions and microplastics on the marine diatom Skeletonema costatum. The results indicated that copper ions at a concentration of 0.05 mg/L exerted a negative impact on the growth of S. costatum; however, the influence of microplastics on algal cell growth was more complex: there was no significant inhibition of algal cell growth observed within the first 72 h of cultivation, but a pronounced negative effect on cell growth was noted between 72 and 96 h, with high concentrations (10.00 mg/L) of microplastics even causing a premature stagnation phase in algal cell growth. When both pollutants were present simultaneously, their impact on cell growth was similar to that of the microplastic pollution group, yet the growth condition was better than that of the copper ion pollution group. Through investigation of adsorption rates and toxicity mitigation rates, it was found that the adsorption of copper ions by microplastics was a significant reason for the improved growth condition of algal cells in the mixed pollution group compared to the copper ion pollution group. However, in the later stages of cultivation, the inhibitory effect of microspheres on algal cell growth counteracted their mitigating effect on copper ion toxicity. This study provides a reference for evaluating the impact of microplastics and heavy metals on coastal ecosystem health and for revealing the interactions between different pollutants.
Incremental Learning for LiDAR Attack Recognition Framework in Intelligent Driving Using Gaussian Processes
Authors: Miao Zujia , Shao Cuiping , Li Huiyun , Cui Yunduan
Published: August 2024

The perception system plays a crucial role by integrating LiDAR and various sensors to perform localization and object detection, which ensures the security of intelligent driving. However, existing research indicates that LiDAR is vulnerable to sensor attacks, which lead to inappropriate driving strategies and need effective attack recognition methods. Previous LiDAR attack recognition methods rely on fixed anomaly thresholds obtained from depth map data distributions in specific scenarios as static anomaly boundaries, which lead to reduced accuracy, increased false alarm rates, and a lack of performance stability. To address these problems, we propose an adaptive LiDAR attack recognition framework capable of adjusting to different driving scenarios. This framework initially models the perception system by integrating the vehicle dynamics model and object tracking algorithms to extract data features, subsequently employing Gaussian Processes for the probabilistic modeling of these features. Finally, the framework employs sparsification computing techniques and a sliding window strategy to continuously update the Gaussian Process model with window data, which achieves incremental learning that generates uncertainty estimates as dynamic anomaly boundaries to recognize attacks. The performance of the proposed framework has been evaluated extensively using the real-world KITTI dataset covering four driving scenarios. Compared to previous methods, our framework achieves a 100% accuracy rate and a 0% false positive rate in the localization system, and an average increase of 3.43% in detection accuracy in the detection system across the four scenarios, which demonstrates superior adaptive capabilities.
Relationship between Mother's Knowledge and Status of Advanced Immunization Completeness in Children Under 2 Years in Karangpandan Community Health Center Working Area
Authors: Darsi Darsi , Wijayanti Wijayanti , Umarianti Tresia
Published: August 2024

Mother's knowledge about immunization influences the provision of immunization to babies. If the mother's knowledge about immunization is lacking and the mother feels that she does not need immunization, this will affect the schedule, administration and completeness of immunizations for babies, which will have an impact on the emergence of disease in babies.
This research uses quantitative methods with a retrospective approach.   The population of this research is all female orphans who are in the Karangpandan Health Center Working Area for the period March 2024, namely 44 toddler’s mom with the sampling technique used Total Sampling. The instruments used were a maternal knowledge questionnaire about advanced immunizations and a KIA book to see the completeness of immunization status.
The statical test using Chi Square test results show the Asymp value. Sig. (2-sided) 0.001 < 0.05, meaning that Ha is accepted and Ho is rejected, so there is a relationship between the mother's level of knowledge about Advanced Immunization and the Completeness Status of Advanced Immunization for Children Under 2 Years in Karangpandan Community Health Center Working Area.
The THE EFFECT OF RED GUAVA JUICE ON HEMOGLOBIN LEVELS IN PREGNANT WOMEN DURING THE SECOND TRIMESTER AT PANCASILA PRIMARY CLINIC ,BATURETNO WONOGIRI
Authors: Afriani Maria , Wijayanti Wijayanti , Maharani P Ajeng
Published: August 2024

Background : The prevalance of anemia in Indonesia reaches 48.9%, attributed to various factors such as iron malabssorption. Therefore, additional vitamin C is required to improve the absorption of FE tablet consumption.Research Objective: The study aimed to examine the effect of red guava juice on improving hemoglobin levels during the second trimester of pregnant women at Pancasila Primary Clinic Wonogiri.
Research Method : The research employed an experimental method with a pretest-posttest design with the control group. The sampling technique used total sampling involving 44 responden, divided into experimental groups (22 respondents) and control group (22 respondents).Research Results: The sstatistical analysis using the paired sample t -test revealed a Pvalue of 0,004 < 0.005 in the control group and 0.000 < 0.005 in the experimental group. In addition , the independepnt t-test demonstrated a P value of 0.002 < 0.005, indicatinga significant effect of red guava juice on improving hemoglobin levels.
Conclusion: Based on the study development, red guava juice evoled as valuable therapeutic option for increasing hemoglobin levels during pregnancy, wether used independenly or in combination with iron ( FE ) tablets.
Influence Individual Nutrition Counseling with Booklet Media on Hb Levels of Pregnant Women in the Wedi Regency Health Center Area Klaten
Authors: Mariyana Anna , Sandi Ulya Pramitha , Prastyoningsih Aris
Published: August 2024

Background​ Incident maternal anemia in Indonesia is a consequence deficiency iron Still figure 48.9% (Riskesdas, 2018). Anemia is circumstances No sufficient erythrocytes For deliver need oxygen marked network​ with low Hb concentration <11gr/dl (Wibowo et al., 2021). Causative factor incident that's one of them is pattern consumption food Mother pregnant who is not various.
Subjects and methods : Type of research used is quasi experiment with design Pre-post Control Design and data is collected with use questionnaire with amount sample as many as 60 mothers pregnant . Taking sample in study This will use purposive sampling. Data analysis used the Paired T- Test for paired and Unpaired T-Test for those who don't pair.
Results : There is influence significant in a way statistics counseling nutrition individual with booklet media enhancement Hb levels of pregnant women with p value < 0.05 (0.000), in group intervention, the average increase in Hb was more than 0.50 gr/dl big from group control 0.20 gr/dl.
Giving a Herbal Drink “Hot Ginger” to Relieve Menstrual Pain to Students at the Islamic Boarding School Kediri
Authors: Margareta Andini Dwi , Rosita Dewi Ayu
Published: August 2024

Menstruation is a natural physiological change that occurs in every woman and is influenced by reproductive hormones, FSH (estrogen) or LH (progesterone). When you are menstruating, usually women will experience pain or cramps in the lower abdomen; this is called dysmenorrhea. One of the treatments for menstrual pain is traditional medicine using ginger ale. To analyze the effectiveness of giving ginger wedang to reduce the intensity of dysmenorrhea pain in female students in islamic boarding schools. This study uses a type of research. quasi-experimental, that is, with a one-group pretest-posttest design. With a population of students at the Islamic boarding school kediri as many as 86 students. The sampling was carried out by purposive sampling, so a sample of 31 respondents was obtained. Meanwhile, data analysis uses the Wilcoxon Signed Rank Test formula. The results showed that the intensity of dysmenorrhea on day 1 before being given ginger tea had most of the respondents on a pain scale of 7-9 with an average pain scale of 6.9, and after being given ginger tea on day 2, the pain intensity scale of most respondents decreased between 1- 3 with an average of 1.9. The results of the Wilcoxon Signed Rank Test obtained a significance value of 0.003. Giving wedang jahe during menstrual pain is believed to reduce the intensity of dysmenorrhea pain