bluuebunny/crossref_metadata_2025 huggingface dataset:
Direct Evidence for Using Coriandrum sativum var. microcarpum Essential Oil to Ameliorate Scopolamine-Induced Memory Impairment and Brain Oxidative Stress in the Zebrafish Model
Authors: Brinza Ion , Boiangiu Razvan Stefan , Cioanca Oana , Hancianu Monica , Dumitru Gabriela , Hritcu Lucian , Birsan Gheorghe-Ciprian , Todirascu-Ciornea Elena
Published: July 2023

Essential oil from Coriandrum sativum has been demonstrated to provide various pharmacological properties, such as antioxidant, antimicrobial, antibacterial, antifungal, antidiabetic, anticonvulsive, anxiolytic-antidepressant, and anti-aging properties. This study investigated the mechanism of Coriandrum sativum var. microcarpum essential oil (CSEO, 25, 150, and 300 μL/L) and cognitive impairment and brain oxidative stress in a scopolamine (SCOP, 100 μM) zebrafish model (Danio rerio) of cognitive impairment. Spatial memory, response to novelty, and recognition memory were assessed using the Y-maze test and the novel object recognition test (NOR), while anxiety-like behavior was investigated using the novel tank diving test (NTT). The cholinergic system activity and brain oxidative stress were also evaluated. CSEO was administered to zebrafish once a day for 21 days, while SCOP and galantamine (GAL, 1 mg/L) were delivered 30 min before behavioral testing and euthanasia. Our data revealed that SCOP induced memory dysfunction and anxiety-like behavior, while CSEO improved memory performance, as evidenced by behavioral tasks. Moreover, CSEO attenuated SCOP-induced brain oxidative stress and decreased acetylcholinesterase (AChE) activity. The results demonstrated the potential use of the CSEO in providing beneficial effects by reducing memory deficits and brain oxidative stress involved in the genesis of a dementia state.
Relationship between Malondialdehyde Serum Levels and Disease Features in a Full Characterized Series of 284 Patients with Systemic Lupus Erythematosus
Authors: Merino de Paz Nayra , García-González María , Gómez-Bernal Fuensanta , Quevedo-Abeledo Juan , de Vera-González Antonia , López-Mejias Raquel , Abreu-González Pedro , Martín-González Candelaria , González-Gay Miguel , Ferraz-Amaro Iván
Published: July 2023

Malondialdehyde (MDA) is a marker of oxidative stress and antioxidant status. Oxidative stress has been observed to be increased in systemic lupus erythematosus (SLE). Some studies have shown that MDA is upregulated in SLE compared to controls. However, the literature lacks reports regarding the relationship of MDA to disease manifestations. This is relevant since SLE is a multisystemic disease which may affect virtually any organ in the body. In this study, we set out to analyze how MDA serum levels are associated with disease expression in a large series of SLE patients who were fully characterized in clinical and laboratory terms. A total of 284 patients with SLE were recruited. Serum levels of MDA, and the activity (SLEDAI), severity (Katz) and damage index (SLICC-DI) scores, full lipid profile, and carotid subclinical atherosclerosis were assessed. In addition, a full characterization of the complement system was performed in SLE patients’ samples. Multivariable linear regression analysis was executed to study the relationship between clinical and laboratory disease characteristics and MDA. A statistically significant negative relationship was found between disease duration and MDA. In contrast, the presence of anti-nucleosome antibodies was positively associated with MDA. Regarding the SLICC-DI areas, both the musculoskeletal domain and the cutaneous domain were significantly related to higher serum MDA values. Furthermore, after adjustment for confounding factors, lower levels of the classical complement pathway, which denotes activation, were associated with higher serum levels of MDA. In conclusion, cumulative musculoskeletal and skin damage in SLE patients is associated with superior serum levels of MDA. In addition, activation of the complement system is also related to higher circulating MDA levels.
Exploring the Antioxidant, Neuroprotective, and Anti-Inflammatory Potential of Olive Leaf Extracts from Spain, Portugal, Greece, and Italy
Authors: Romero-Márquez Jose M. , Navarro-Hortal María D. , Forbes-Hernández Tamara Y. , Varela-López Alfonso , Puentes Juan G. , Pino-García Raquel Del , Sánchez-González Cristina , Elio Iñaki , Battino Maurizio , García Roberto , Sánchez Sebastián , Quiles José L.
Published: July 2023

The leaves of the olive tree (Olea europaea L.) are one of the major solid wastes from the olive industry. Globally, the European Union is the largest producer of olive by-products, with Spain, Italy, Greece, and Portugal accounting for almost the entire production. Many questions remain to be solved concerning olive leaves (OL), including those related to possible differences in composition and/or biological activities depending on their geographical origin. In the present work, OL from Spain, Italy, Greece, and Portugal have been characterized according to their phytochemical profile, antioxidant capacity, neuroprotective activity, and anti-inflammatory effects. The Spanish and Italian OL samples presented the highest antioxidant and neuroprotective activities, while the Greek OL showed the lowest. These results were strongly associated with the content of oleoside methyl ester and p-hydroxybenzoic acid for the Spanish and Italian samples, respectively, whereas the content of decarboxymethyl elenolic acid dialdehyde form (hydrated) was negatively associated with the mentioned biological activities of the Greek samples. No country-related effect was observed in the anti-inflammatory activity of OL. Comprehensively, this work could provide a useful tool for manufacturers and R&D departments in making environmentally friendly decisions on how OL can be used to generate nutraceutical products based on the composition and origin of this by-product.
Multi-Indicator Weighted Robustness Analysis of Planktonic Community Systems under Different Destructive Factors
Authors: Zhao Danfeng , Zhang Tao , Chen Tianwen , He Qi , Huang Dongmei
Published: July 2023

Marine plankton communities play a vital role in global carbon and nutrient cycles. Ensuring the robustness of these intricate ecosystems is critical for sustainable environmental management. In this paper, we apply complex network analysis to assess plankton community resilience against disturbances. We construct ecological interaction networks and simulate disruptions using four attack strategies targeting vertices and edges. Our multi-indicator evaluation scheme provides a more nuanced measure of robustness compared to single metrics. Our experiments revealed varying vulnerabilities across networks. Targeted attacks caused abrupt collapse, while random failures led to gradual decline. Identifying critical species and linkages is key to guiding protection efforts. Overall, plankton networks proved fragile, especially against deliberate attacks on central hubs. In our simulations, betweenness-based attacks were the most destructive. The multi-indicator robustness coefficient achieved better performance than individual metrics, with under 3% variance. This network methodology reveals hidden topological vulnerabilities and complements traditional plankton research. The quantitative insights provided in this paper can support marine conservation and governance.
Neural-Based Detection and Segmentation of Articulated Objects for Robotic Interaction in a Household Environment
Authors: Mula Arkadiusz , Młodzikowski Kamil , Gawron Patryk , Belter Dominik
Published: July 2023

Robots operating in household environments should detect and estimate the properties of articulated objects to efficiently perform tasks given by human operators. This paper presents the design and implementation of a system for estimating a point-cloud-based model of a scene, enhanced with information about articulated objects, based on a single RGB-D image. This article describes the neural method used to detect handles, detect and extract fronts, detect rotational joints, and build a point cloud model. It compares various architectures of neural networks to detect handles, the fronts of drawers and cabinets, and estimate rotational joints. In the end, the results are merged to build a 3D model of articulated objects in the environment.
A Green Technology Approach Using Enzymatic Hydrolysis to Valorize Meat Waste as a Way to Achieve a Circular Economy
Authors: Angulo Miguel , Márquez Mª Carmen
Published: July 2023

The retail meat industry produces a significant amount of waste, containing proteins, lipids, and other elements that could serve as the basis for other products. This work presents the results of research on the enzymatic hydrolysis of meat waste as a green technology to obtain products with added value as a substitute for other raw materials. pH, temperature, the protease/proteinic substrate ratio (Eo/So), and the lipolase/lipidic substrate ratio (Eo’/So’) were studied as process variables for hydrolysis of proteins and lipids, respectively. Hydrolysis for the recovery of proteins (as protein hydrolysates or collagen) was carried out with the protease Alcalase; pH around 8.0, temperature around 50 °C, and Eo/So around 0.16 AU/g were the optimum process variables’ values for obtaining high amounts of recovered proteins and peptides that are easily digestible and have a pleasant taste. The lipase Resinase was used to hydrolyze the lipids; a clear relationship was observed between Eo’/So’ and the amounts of recovered fatty acids. The optimum process variables’ values were found to be Eo’/So’ around 0.83 kLU/g, pH around 8.0 and temperature around 50 °C. Unsaturated fatty acids prevailed in the final product. For the simultaneous recovery of protein hydrolysates, collagen, and fatty acids, a combination of Alcalase and Resinase was used; the process variables examined included the optimal range of values for Eo/So and Eo’/So’, as well as pH and temperature that were suggested in research for both Alcalase and Resinase, separately. The results showed that the simultaneous process was mainly influenced by the Eo/So and Eo’/So’ ratios, instead of being influenced by the pH and temperature values which were less influential. For Eo/So = 0.16 AU/g, Eo’/So’ = 1.11 kLU/g, pH = 7.5, T = 50 °C, the maximum amounts of products (0.8 kg by kg of dry meat waste) were obtained more economically, where the whole of the proteins and lipids in meat waste were practically recovered. Therefore, in order to preserve a circular economy for retail meat waste, enzymatic hydrolysis is appealing and environmentally friendly.
Numerical Analysis of Perforated Symmetric Fissures on Mechanical Properties of Hole-Containing Sandstone
Authors: Gou Hong , Shi Peng , Wan Zhijun , Xiong Luchang , Fan Bowen , Zhen Zheng
Published: July 2023

The symmetrical fissures located within the surrounding rock of the roadway (borehole) in tunnel engineering activities can easily induce damage and instability of the surrounding rock. Therefore, studying the impact of perforated symmetrical fissures on the mechanical properties of rock with a hole has significant practical significance. Based on indoor experimental results, conventional triaxial compression simulations were performed on symmetrical fissure-hole sandstone using PFC2D. The impact of the dip angle and length of symmetric fissures on the mechanical properties of the hole-containing sandstone was analyzed. Furthermore, the relationship between crack propagation and the macroscopic mechanical properties of the specimen was discussed. The results show that: (1) The deterioration effect of symmetric fissures on hole-containing sandstone can be controlled by increasing the fissure dip angle, suppressing the stress drop phenomenon. However, increasing the fissure length exacerbates the deterioration effect. (2) The effect of symmetrical fissure dip angle on the displacement field near the hole decreases with increasing dip angle while increasing fissure length exacerbates the effect of fissures on the displacement field. (3) As the angle between the fissure and the vertical principal stress increases, the degree of tensile failure weakens while the degree of shear failure increases. (4) During the crack development phase, the extension of the stress concentration zone drives rapid crack growth. It exhibits a stress drop in the macroscopic mechanical properties, followed by the evolution of the stress field with loading, allowing rapid expansion of the microcracks and eventually leading to rock destabilization damage.
Analysis of the Temperature Field Effect on the Thermal Stress of the Main Tower of Long-Span Suspension Bridges
Authors: Duan Maojun , Zhu Juntian , Gu Zhong , Fang Zijun , Xu Jiaying
Published: July 2023

To investigate the temperature field variation of the main tower of large-span suspension bridges, the Nanjing Xinshengwei Yangtze River Bridge was selected as the objective of the present study. The finite element model of the main tower was developed, and the analysis of the effect of the temperature field on the structure of the main tower was carried out. The calculation parameters of the temperature field of the main tower were determined, and the influence of the solar radiation temperature of the main tower within 24 h was investigated. Differences in the temperatures inside and outside the wall of the tower column were analyzed, and the thermal stress of the tower wall under the most unfavorable temperature difference was calculated. Results show that under the positive temperature difference, the area of tensile stress is mainly concentrated on the inner wall, the maximum value is located at the corner of the intersection of the tower wall, and the range of tensile stress is mainly diffused along the vertical wall. Under the action of negative temperature difference, the area of tensile stress is mainly concentrated in the outer tower wall, the maximum value is located in the upper part of the western outer tower wall, and the range of tensile stress is mainly diffused along the center of the tower wall to both sides. The maximum tensile stresses in the inner and outer tower wall are 2.8 MPa and 1.3 MPa, respectively, which meets the standard value of 2.85 MPa for the tensile strength of C60 concrete specified in the Chinese national standard.
A Semantic Information-Based Optimized vSLAM in Indoor Dynamic Environments
Authors: Wei Shuangfeng , Wang Shangxing , Li Hao , Liu Guangzu , Yang Tong , Liu Changchang
Published: July 2023

In unknown environments, mobile robots can use visual-based Simultaneous Localization and Mapping (vSLAM) to complete positioning tasks while building sparse feature maps and dense maps. However, the traditional vSLAM works in the hypothetical environment of static scenes and rarely considers the dynamic objects existing in the actual scenes. In addition, it is difficult for the robot to perform high-level semantic tasks due to its inability to obtain semantic information from sparse feature maps and dense maps. In order to improve the ability of environment perception and accuracy of mapping for mobile robots in dynamic indoor environments, we propose a semantic information-based optimized vSLAM algorithm. The optimized vSLAM algorithm adds the modules of dynamic region detection and semantic segmentation to ORB-SLAM2. First, a dynamic region detection module is added to the vision odometry. The dynamic region of the image is detected by combining single response matrix and dense optical flow method to improve the accuracy of pose estimation in dynamic environment. Secondly, the semantic segmentation of images is implemented based on BiSeNet V2 network. For the over-segmentation problem in semantic segmentation, a region growth algorithm combining depth information is proposed to optimize the 3D segmentation. In the process of map building, semantic information and dynamic regions are used to remove dynamic objects and build an indoor map containing semantic information. The system not only can effectively remove the effect of dynamic objects on the pose estimation, but also use the semantic information of images to build indoor maps containing semantic information. The proposed algorithm is evaluated and analyzed in TUM RGB-D dataset and real dynamic scenes. The results show that the accuracy of our algorithm outperforms that of ORB-SLAM2 and DS-SLAM in dynamic scenarios.
Deep Multi-View Clustering Based on Reconstructed Self-Expressive Matrix
Authors: Shi Zonghan , Zhao Haitao
Published: July 2023

Deep Multi-view Subspace Clustering is a powerful unsupervised learning technique for clustering multi-view data, which has achieved significant attention during recent decades. However, most current multi-view clustering methods rely on learning self-expressive layers to obtain the ultimate clustering results, where the size of the self-expressive matrix increases quadratically with the number of input data points, making it difficult to handle large-scale datasets. Moreover, since multiple views are rich in information, both consistency and specificity of the input images need to be considered. To solve these problems, we propose a novel deep multi-view clustering approach based on the reconstructed self-expressive matrix (DCRSM). We use a reconstruction module to approximate self-expressive coefficients using only a small number of training samples, while the conventional self-expressive model must train the network with entire datasets. We also use shared layers and specific layers to integrate consistent and specific information of features to fuse information between views. The proposed DCRSM is extensively evaluated on multiple datasets, including Fashion-MNIST, COIL-20, COIL-100, and YTF. The experimental results demonstrate its superiority over several existing multi-view clustering methods, achieving an improvement between 1.94% and 4.2% in accuracy and a maximum improvement of 4.5% in NMI across different datasets. Our DCRSM also yields competitive results even when trained by 50% samples of the whole datasets.
Convergence Analysis of the Phase-Scheduled-Command FXLMS Algorithm with Phase Error
Authors: Wang Yushuai , Liu Feng , Fu Zhenrong , Yang Lianxin , Wang Pengfei
Published: July 2023

In this paper, a phase-scheduled-command filtered-x least mean square (FXLMS) algorithm with a phase error between the disturbance and command signal is analyzed in detail. The influence of the phase error on the control effort, convergence time constant and performance of convergence is explained for both stationary and nonstationary disturbance signal cases. An estimation ratio, in both stationary and nonstationary disturbance cases, of the pseudo-error MSE convergence performance is also developed and discussed. Simulation results were collected to verify the analysis. The results show that, for both stationary and nonstationary disturbance, the phase error may heavily increase the distance of the optimum vector from the initial value, leading to a large control effort, a large convergence time constant and poor convergence performance. The estimation ratio also has a satisfactory performance for estimating the influence of the phase error.
Dynamic Monitoring and Analysis of Mining Land Subsidence in Multiple Coal Seams in the Ehuobulake Coal Mine Based on FLAC3D and SBAS-InSAR Technology
Authors: Zhou Shihang , Wang Hongzhi , Shan Chengfang , Liu Honglin , Li Yafeng , Li Guodong , Yang Fajun , Kang Haitong , Xie Guoliang
Published: July 2023

Aiming at the land subsidence problem caused by multiple coal seam mining in the Ehuobulake Coal Mine, this paper, considering the geological conditions of the first and fifth layers of coal, adopts the method of combining FLAC3D numerical simulation and SBAS-InSAR technology to analyze the dynamic evolution law of land subsidence amount and range under multiple coal seam repeated mining conditions. The reliability of the technology is verified by the field GPS monitoring data. The results show that, under the mining condition of multiple coal seams in the Ehuobulake Coal Mine, the land subsidence presents obvious asymmetry, and the size and range of the land subsidence in the mining area further increase due to the mining of lower layer coal. FLAC3D simulation results show that the maximum land subsidence is −211.8 mm. The results of SBAS-InSAR monitoring show that the maximum land subsidence is −225 mm, and the land subsidence obtained by the two methods has a high degree of fitting. The method of combining FLAC3D and InSAR technology can accurately and reliably monitor and analyze the land subsidence under the repeated mining of multiple coal seams in the mining area. It can provide effective guidance for the stability analysis of mined-out areas and the prediction of the influence of repeated mining on ground deformation.
Experimental Study on Axial Stress–Strain Behaviour of Steel Fibre-Reinforced Steel Slag Micropowder UHPC
Authors: Tang Xianyuan , He Binbing , Yang Bai , Chen Junhua
Published: July 2023

To investigate the toughening effect and stress–strain relationship of steel fibre-reinforced steel slag micropowder ultra-high-performance concrete (UHPC), nine sets of specimens with coarse aggregate and steel fibre contents were prepared for axial compression and elastic modulus tests. This study examines the variations in compressive strength and peak strain of the steel slag micropowder UHPC specimens to determine the corresponding characteristics of the stress–strain relationship. The results indicate that the experimental groups mixed with 1%, 1.5%, and 2% steel fibre increased the peak strain by about 20.3%, 25.3%, and 26.2%, respectively, compared to the non-steel fibre specimens. It can be seen that the toughening effect of UHPC with steel fibre and slag micro powder is good. With a fixed steel fibre content, the compressive strength and peak strain of steel slag micropowder UHPC initially increase and then decrease as the coarse aggregate content increases. The maximum compressive strength is achieved when the steel fibre content is 1.5% and the coarse aggregate content is 20%. A constitutive equation suitable for steel fibre-reinforced steel slag micropowder UHPC was derived through curve fitting based on the experimentally obtained stress–strain curves. The calculated values from the equation show deviations within 10% of the measured values, indicating a good fit. Nonlinear analysis of the entire compression process of prismatic specimens using the finite element method confirms the rationality of the constitutive equation, as the simulated curve closely aligns with the experimental curve. This research findings provide a reference for the engineering application of steel slag micropowder UHPC.
A New Approach to Quantify Soccer Players’ Readiness through Machine Learning Techniques
Authors: Mandorino Mauro , Tessitore Antonio , Leduc Cédric , Persichetti Valerio , Morabito Manuel , Lacome Mathieu
Published: July 2023

Previous studies have shown that variation in PlayerLoad (PL) could be used to detect fatigue in soccer players. Machine learning techniques (ML) were used to develop a new locomotor efficiency index (LEI) based on the prediction of PL. Sixty-four elite soccer players were monitored during an entire season. GPS systems were employed to collect external load data, which in turn were used to predict PL during training/matches. Random Forest Regression (RF) produced the best performance (mean absolute percentage error = 0.10 ± 0.01) and was included in further analyses. The difference between the PL value predicted by the ML model and the real one was calculated, individualized for each player using a z-score transformation (LEI), and interpreted as a sign of fatigue (negative LEI) or neuromuscular readiness (positive LEI). A linear mixed model was used to analyze how LEI changed according to the period of the season, day of the week, and weekly load. Regarding seasonal variation, the lowest and highest LEI values were recorded at the beginning of the season and in the middle of the season, respectively. On a weekly basis, our results showed lower values on match day − 2, while high weekly training loads were associated with a reduction in LEI.
A Numerical Investigation of the Thermal Performance of a Gabion Building Envelope in Cold Regions with a Mountainous Climate
Authors: Liu Fang , Li Yafei , Wang Yushi , Zhang Qunli , Gao Wei , Cao Ying
Published: July 2023

Applying rock-filled gabion to buildings in cold regions with mountainous climates has multiple potentials, such as utilizing rock resources, improving building sustainability and saving building energy. Therefore, it is necessary to analyze the thermal performance of gabion buildings. Based on the CFD method, this paper establishes a numerical model of buildings with gabion enclosure structures, analyzes the influence of the gabion structure on the external convective heat transfer coefficient (CHTC), wind pressure, air infiltration, room temperature and building load, and further uses the building energy consumption simulation method to analyze the heat load of gabion buildings. The results showed that the adverse impact of climate on the building thermal performance is significantly diminished by the gabion. Under different weather conditions, the CHTC, the maximum wind pressure difference on the exterior surface, and the air infiltration rate are reduced by different rates. Further, the room base temperature increases throughout the heating season, and the maximum heat load and the cumulative heat load of the building are, respectively, reduced by 10.6% and 24.8%. This work revealed that the gabion is an eco-friendly and adaptive measure to improve thermal performance and indoor thermal comfort.
Exploring the Role of Emotions in Arabic Rumor Detection in Social Media
Authors: Al-Saif Hissa F. , Al-Dossari Hmood Z.
Published: July 2023

With the increasing reliance on social media as a primary source of news, the proliferation of rumors has become a pressing global concern that negatively impacts various domains, including politics, economics, and societal well-being. While significant efforts have been made to identify and debunk rumors in social media, progress in detecting and addressing such issues in the Arabic language has been limited compared to other languages, particularly English. This study introduces a context-aware approach to rumor detection in Arabic social media, leveraging recent advancements in Natural Language Processing (NLP). Our proposed method evaluates Arabic news posts by analyzing the emotions evoked by news content and recipients towards the news. Moreover, this research explores the impact of incorporating user and content features into emotion-based rumor detection models. To facilitate this investigation, we present a novel Arabic rumor dataset, comprising both news posts and associated comments, which represents a first-of-its-kind resource in the Arabic language. The findings from this study offer promising insights into the role of emotions in rumor detection and may serve as a catalyst for further research in this area, ultimately contributing to improved detection and the mitigation of misinformation in the digital landscape.
Operational Performance and Energy Efficiency of MEX 3D Printing with Polyamide 6 (PA6): Multi-Objective Optimization of Seven Control Settings Supported by L27 Robust Design
Authors: David Constantine , Sagris Dimitrios , Petousis Markos , Nasikas Nektarios K. , Moutsopoulou Amalia , Sfakiotakis Evangelos , Mountakis Nikolaos , Charou Chrysa , Vidakis Nectarios
Published: July 2023

Both energy efficiency and robustness are popular demands for 3D-printed components nowadays. These opposing factors require compromises. This study examines the effects of seven general control variables on the energy demands and the compressive responses of polyamide (PA6) material extrusion (MEX) 3D printed samples. Nozzle Temperature, Layer Thickness, Orientation Angle, Raster Deposition Angle, Printing Speed, Bed Temperature, and Infill Density were studied. An L27 orthogonal array was compiled with five replicas. A total of 135 trials were conducted, following the ASTM D695-02a specifications. The stopwatch method was used to assess the construction time and energy usage. The compressive strength, toughness, and elasticity modulus were experimentally determined. The Taguchi technique ranks each control parameter’s impact on each response measure. The control parameter that had the greatest impact on both energy use and printing time was layer thickness. Additionally, the infill density had the greatest influence on the compressive strength. Quadratic regression model equations were formed for each of the response measures. The ideal compromise between mechanical strength and energy efficiency is now reported, with merit related to technological and economic benefits.
Accurate Modeling, Operation Laws and Commutation Timing Matching for Concrete Pumping Systems
Authors: Ding Haigang , Wang Chen
Published: July 2023

The pump system is the heart of the concrete pump truck, and its main function is to deliver high-pressure concrete into the pipeline through the reciprocating motion and cooperation of the main cylinder and the distribution valve driven by the swing cylinder. However, there are currently problems, such as unclear pumping operation rules and mismatched commutation timing, that result in poor pumping efficiency and short life of wear parts such as spectacle plates and cutting rings. To address above problems, based on AMEsim software and system test data, this thesis establishes an accurate simulation model of the pump system with more than 90% precision. Based on this model, the simulation reveals the operating rules of the main cylinder and the swing cylinder during the pumping process; draws the commutation timing diagram of the pumping system; clarifies that the commutation timing has four characteristics: sequential, hysteresis, coupling and cyclic; and proposes an optimization scheme for the commutation timing, i.e., reducing the relief pressure of the main cylinder and shortening the swing time of the distribution valve. The proposed optimization has been proven in the market and significantly improved the life of wearing parts by more than 90%. This study provides technical reference for the structure and parameter optimization of concrete pumping systems.
Numerical Analysis of Cyclic Impact Damage Evolution of Rock Materials under Confining Pressure
Authors: Yuan Pu , Zhang Qinghe , Li Aobo
Published: July 2023

To study the effect of cyclic impacts and confining pressure on the damage evolution of rock materials, numerical simulations of cyclic impact tests on rock materials under confining pressure were carried out by LS-DYNA using dynamic relaxation and full restart analysis. The static confining pressure was applied by dynamic relaxation, and cyclic impacts were realized by full restart analysis. As the crack generation and propagation result in the failure of elements in the finite element model, the damage variable defined by the crack density method was characterized by volume reduction. Numerical simulation indicates that both the confining pressure and amplitude of incident stress waves significantly affect the damage evolution of rock materials. High incident stress waves lead to severe damage, while large confining pressure results in minor damage. Under confining pressure, the damage to rock materials is alleviated due to the constraint effect on crack propagation. The number of cyclic impacts before macroscopic fracture increases as the confining pressure increases and decreases when the amplitude of the incident stress waves increases. The cumulative damage of rock materials under confining pressure progressively increases with the number of cyclic impacts, and the damage evolution exhibits three distinct stages: rapid rising, steady development, and sharp rising.
Achieving an Optimal Decision for the Joint Planning of Renewable Power Supply and Energy Storage for Offshore Oil–Gas Platforms
Authors: Hu Changbin , Deng Jufu , Liu Chao , Luo Shanna , Li Xuecheng , Lu Heng
Published: July 2023

To address the complexity of siting and sizing for the renewable energy and energy storage (ES) of offshore oil–gas platforms, as well as to enhance the utilization of renewable energy and to ensure the power-flow stability of offshore oil–gas platforms, this paper proposes a hierarchical clustering-and-planning method for wind turbine (WT)/photovoltaic (PV) ES. The proposed strategy consists of three stages. First, the WT/PV power generation is forecast by a LightGBM model. The WT/PV siting and sizing at each node of the distribution network is optimized with a particle swarm optimization (PSO) algorithm, with the objectives of economy and stability. In the second stage, the distribution network is partitioned into sub-clusters, based on a voltage and loss-sensitivity index. Finally, the ES siting and sizing is optimized with PSO to minimize the line loss and the voltage fluctuation for each sub-cluster. The relationship between the economic and stability indicators is conducted quantitatively in the joint-planning approach. Considering the 10 kV distribution network of an oil–gas platform in the Bohai Sea of China as an example, our experiments demonstrated that by adjusting the WT/PV ES capacity for different gas-turbine power outputs, line losses can be reduced by 55–66% and voltage fluctuations can be reduced by 30.4–47.5%.
Improving the Measurement of Characteristic Parameters for the Determination of GHG Emissions in the Semiconductor and Display Industries in Korea
Authors: Lee Bong-Jae , Yun Soo-Young , Jeong In-Kwon , Hwang Yujin , Park Jun-Hyeok , Kim Jonghoon
Published: July 2023

Semiconductor and display industries in the Republic of Korea make up the global electronics market with some of the greatest potential for growth due to accelerated digital transformation. Greenhouse gases (GHGs) present in the Earth’s atmosphere could trap heat and contribute to the greenhouse effect, leading to global warming and climate change, and it is important to note that while GHGs are naturally present in the atmosphere and play a crucial role in regulating the Earth’s temperature, human activities have significantly increased their concentration, leading to accelerated global warming and climate change. Volatile fluorinated compounds (FCs), including perfluorocompounds (PFCs), hydrofluorocompounds (HFCs), NF3, and SF6, are potent long-standing greenhouse gases that are used and emitted by electronics during the manufacturing and display stages of semiconductors. In accordance with global climate change, GHG reduction has developed as a demand of the times, and the electronics industry has also made efforts to reduce GHG emissions in response. Until now, process emissions from the use of fluorinated greenhouse gases (F-GHGs) in various industries have been calculated according to the ’06 IPCC G/L, and emission factors of ’06 IPCC G/L have also been applied. However, the reduction and emission factors proposed in the IPCC G/L are values that do not reflect the latest and advanced reduction technologies in South Korean electronics, and national GHG emissions are overestimated. In this paper, by preparing accurate measurement methods for destruction removal efficiency (DRE), the use rate of gas (Ui), and b-product emission factors (Bby-product, i), which are characteristic parameters for estimating GHG Tier 3a emissions, we aim to increase the accuracy of GHG emissions by advancing emission factors that are unique to the semiconductor and display industries within the Republic of Korea.
Simulation Study on Axial Location Identification of Damage in Layered Pipeline Structures Based on Damage Index
Authors: Li Ying , Qu Lingzhi , Qi Baoxin
Published: July 2023

This study investigates the feasibility of identifying the axial position of circumferential defects in laminated pipeline structures based on damage indices. Wavelet packet decomposition is combined with damage indices, and the effects of dual defects with the same circumferential position but different axial positions, as well as dual defects with different circumferential and axial positions, on damage indices are separately studied. Our aim was to determine the potential to use damage indices to identify the axial position of circumferential defects in laminated pipeline structures. ABAQUS finite element analysis software was used to establish models of laminated pipeline structures with single defects and dual defects (with the same circumferential position but different axial positions, and with different circumferential and axial positions). The laminated pipeline structure was composed of a steel pipe (structural layer), a rigid polyurethane foam (insulation layer), and a high-density polyethylene (anticorrosion layer). The received sensing signals were averaged, and subjected to 5-level wavelet packet decomposition, to calculate the damage index values, which were then organized into a damage index matrix. Based on the trend of changes in the damage index matrix, the effects of variations in the number and circumferential position of the defects on the identification of the axial position of the damage were analyzed. The results indicate that the trend in damage index changes is influenced by the number of defects, and the increase in the circumferential distance between the second and the piezoelectric element sensor. This study found that when 1.7λ≤PD≤3.4λ, Idouble defect 90°<Isingle defect<Idouble defect 0°; when 3.7λ≤PD≤4λ, Idouble defect 90°<0.3<Idouble defect 0°<Isingle defect. This article demonstrates that the identification of the axial position of damage in laminated pipeline structures can be achieved using the damage index values in the damage index matrix. Additionally, this damage identification method overcomes the limitation of the wavelet packet’s inability to identify dual defects with relatively small relative axial distances. This provides new ideas and methods for finite element analysis in identifying the axial position of damage in laminated pipeline structures.
Assessment of Multifractal Fingerprints of Reference Evapotranspiration Based on Multivariate Empirical Mode Decomposition
Authors: Sankaran Adarsh , Plocoste Thomas , Nourani Vahid , Vahab Shamseena , Salim Aayisha
Published: July 2023

This study analyzed the multifractal characteristics of daily reference evapotranspiration (ETo) time series of the Tabriz and Urmia stations of northwestern Iran and its cross-correlation with five other meteorological variables. The results of multifractal detrended fluctuation analysis (MFDFA) of ETo, temperature, pressure, relative humidity solar radiation, and wind velocity showed that all the time series of both stations exhibited multifractality and long memory persistence with higher persistence and complexity in the datasets of Urmia station. Then, a multivariate empirical mode decomposition (MEMD)-(MFDFA) coupled framework was proposed to identify the dominant modes suitable for the forecasting of the different variables. The examination of reconstructed time series consistently displayed an increase in persistence and multifractality. The cross-correlation between different candidate variables and ETo was examined using a recently proposed multifractal cross-correlation analysis (MFCCA) method. The results showed that in each pair-wise cross-correlation analysis, the joint persistence is approximately half of the persistence of an individual time series, reinforcing the universality in the fractal cross-correlation analysis. The cross-correlation properties displayed diverse patterns in different pair-wise combinations of cross-correlation analysis despite the similarity of patterns among the data of the two stations.
Diffuse and Direct UV Index Experimental Values
Authors: Marín María J. , Estellés Víctor , Gómez-Amo José L. , Utrillas María P.
Published: July 2023

In this work, we study the different components of the UV Index, direct, diffuse, and global, for seven years of UV erythemal measurements in a Mediterranean locality at Burjassot AtmoSpheric Station (BASS). The measurements have been taken with three YES-UVB-1 radiometers: one provided with a shadow disk on a Sun tracker; a radiometer to measure the global horizontal radiation; and a Sun-tracking radiometer to measure the direct radiation with an especially designed radiance collimator. It is known that diffuse UV irradiance represents at least 50% of total UV irradiance on a horizontal plane, which means being able to obtain a high UV Index even under shade. Our study aims to establish the relationship between the UV Index at noon and the maximum daily UV erythemal irradiance in the mid-latitude area, as well as the potential erythemal effects of exposure to solar UV radiation on different skin phototypes (skin phototypes I–IV) for both direct and diffuse components.
Temporal Evolution of PM2.5 Levels and COVID-19 Mortality in Europe for the 2020–2022 Period
Authors: Renard Jean-Baptiste , Surcin Jérémy , Annesi-Maesano Isabella , Poincelet Eric
Published: July 2023

Air pollution has a strong impact on human health, from respiratory and severe pulmonary diseases to heart attack and cancer. During the 3 years of the COVID-19 pandemic, several peaks of mortality occurred, which could be related to particulate matter (PM) pollution events. The possible effects of PM (PM10 and PM2.5, with diameters less than 10 and 2.5 µm, respectively) on COVID-19 mortality have now been established. To better understand this relationship at the European level for the period 2020–2022, data from 16 representative locations in Europe (81 million people) with PM2.5 levels (µg·m−3) ranging from low to high values were analyzed using statistical methods. The analysis confirms a temporal relation between the peaks of PM2.5 exposure and COVID-19 mortality. The best correlation was obtained considering the history of exposure to PM2.5 pollution during a 2-month integration time coupled with a one-week delay for the COVID-19 mortality. Although the trend of COVID-19 mortality vs. PM2.5 levels varies among locations, the global trend was similar, giving an estimated mean value of a 40 ± 20% mortality increase per µg·m−3 PM2.5 increase. The stronger the positive (negative) gradient of the PM peak, the stronger the positive (negative) gradient of the COVID-19 mortality. These results indicate that a succession of PM pollution peaks could be more dangerous than permanent exposure to moderate pollution levels. Finally, PM number concentrations should be used in the future rather than the PM2.5 mass concentrations (µg·m−3), with the consideration of PM composition to better evaluate the effect of submicron particles on human health, particularly for other respiratory diseases. These results must be considered in the management of future pandemics.
The Development of a Low-Cost Particulate Matter 2.5 Sensor Calibration Model in Daycare Centers Using Long Short-Term Memory Algorithms
Authors: Jeon Hyungjin , Ryu Jewan , Kim Kyoung Min , An Junyeong
Published: July 2023

Particulate matter (PM) pollution is a crucial environmental issue. Considering its adverse health impacts, especially on children’s immune systems, Korean regulations require annual PM2.5 measurements in daycare centers. Therefore, we developed a low-cost PM2.5 sensor calibration model for measuring the indoor PM concentrations in daycare centers using long short-term memory (LSTM) algorithms. Moreover, we trained the model to predict the PM2.5 based on temperature and humidity, and optimized its hyperparameters. The model achieved a high accuracy and outperformed traditional calibration methods. The optimal lookback period was 76, which led to a high calibration performance with root mean and mean squared errors, a coefficient of determination, and mean absolute errors of 3.57 and 12.745, 0.962, and 2.7, respectively. The LSTM model demonstrated a better calibration performance than those of the linear (r2 = 0.57) and multiple (r2 = 0.75) linear regression models. The developed calibration model provided precise short-term measurement values for the optimal management of indoor PM concentrations. This methodology can be applied to similar environments to obtain new learning and hyper-parameters. Our results will aid in improving the accuracy of low-cost sensors for measuring indoor PM concentrations, thereby providing cost-effective solutions for enhancing children’s health and well-being in daycare centers and other multiuse facilities.
Causes of the Interannual Variation of Summer Precipitation in Eastern Southwest China
Authors: Lu Chuhan , Huang Dingan , Chen Bo , Bai Yingying
Published: July 2023

Using ERA5 reanalysis data, we conducted an EOF analysis of summer precipitation in the eastern part of southwestern China (ESWC) over the past 60 years. Our study aimed to investigate the spatial distribution characteristics and interannual variability of summer precipitation in the ESWC, as well as to reveal the possible physical mechanisms influencing its interannual variability. The results indicate that, at the interannual scale, the first two modes of summer precipitation in the ESWC exhibit a uniform pattern and a north–south dipole pattern, respectively. The maximum and minimum time coefficients of the first mode correspond to the severe flood and drought events in 1998 and 2006, respectively, indicating that their time coefficients reflect the typical events well. The tri-pole sea surface temperature anomaly in the North Atlantic, along with the sea ice anomaly near the Barents Sea, induces a quasi-zonal wave train in the upper troposphere. This wave train propagates from the tropical and mid-latitude Atlantic, traverses the mid-high latitudes of Eurasia, and reaches the eastern part of China. The wave train induces cyclonic (anticyclonic) anomalies in the north (south) of the ESWC, facilitating the convergence of high-latitude dry and cold air with warm and moist southwesterly winds from the tropical ocean. This convergence promotes increased summer precipitation in the ESWC. We provided valuable insights into the interannual variability of summer precipitation in the ESWC, shedding light on the physical mechanisms responsible for these variations.
Extreme Droughts and Their Relationship with the Interdecadal Pacific Oscillation in the Peruvian Altiplano Region over the Last 100 Years
Authors: Angulo Eleazar Chuchón , Pereira Filho Augusto Jose
Published: July 2023

The Peruvian Altiplano Region (RAP) is a high plateau area surrounded by the Western and Eastern Andes mountain ranges. This study examines the relationship between extreme droughts in the region and the interdecadal Pacific Oscillation (IPO) over the past century. Previous research has shown that precipitation patterns in the region follow a decreasing trend, with systematic increases in precipitation on the western slope and decreases in the eastern, southern, and central parts. The temporal and spatial variability of precipitation in the Altiplano region is influenced by the easterly moisture flux and the interaction between the El Niño Southern Oscillation (ENSO) and below-average values. The study utilizes water level data for Lake Titicaca and IPO data from 1914 to 2015. The analysis employs wavelet transform and empirical orthogonal function (EOF) techniques to identify the relationship between water levels and IPO. The results indicate multidecadal variability in water levels associated with El Niño/La Niña events and the IPO. The negative phase of the IPO aligns with extreme drought periods, suggesting a connection between the IPO climate index and drought events. The EOF analysis shows a moderate positive correlation between water levels and IPO. The findings highlight the importance of considering IPO and its interaction with ENSO in understanding drought patterns in the Altiplano region. However, other atmospheric conditions also influence precipitation in the region. The study contributes to a better understanding of the factors affecting water levels and droughts in the Peruvian Altiplano, with implications for water resource management in the region.