bluuebunny/crossref_metadata_2025_split huggingface dataset:
Finite element method study on VLF propagation in the fine Earth‐ionosphere waveguide
Authors: Liu Bing , Baraya Jamilu T. , Zhang Shitian , Wang Maoyan , Nemati Samira , Yu Mengxia , Li Guiping , Xu Jun , Zhang Xiaochuan , Liu Yu , Li Hailong 
Published: July 2023

AbstractA fast and highly efficient frequency‐domain finite element method (FEM) is developed to simulate propagation characteristics of very low frequency (VLF) waves in the fine Earth‐ionosphere waveguide structure containing the transition period between day and night. The FEM is accelerated by embedding the GPU‐based parallel LU factorization method. We present an approach for determining the waveguide structure with the VLF transmitter and receiver locations. After validating the method, effects of the time‐ and location‐varying electric density on the amplitude and phase of the VLF wave are investigated. The electric density of the International Reference Ionosphere (IRI) is revised by coupling with the solar zenith angle. Numerical results simulated using the revised IRI model show excellent agreement with the measured data for the VLF wave from Novosibirsk to Qingdao. This work provides a promising way to research VLF electromagnetic properties of the Earth‐ionosphere waveguide and improve the prediction accuracy of VLF navigation and communication.
Psychological distress and physical activity behaviors among parents and caregivers during different COVID‐19 restriction periods: Secondary analysis of the Active Kids voucher program evaluation
Authors: Foley Bridget C. , Reece Lindsey J. , Rose Catriona , Rosenbaum Simon , Owen Katherine B. 
Published: July 2023

AbstractParents and caregivers who participate in regular physical activity have improved physical and mental health and can influence the physical activity behaviors of children in their care. This study aimed to assess the association between psychological distress and physical activity levels of parents/caregivers in New South Wales, Australia during different COVID‐19 restriction periods. A repeat‐cross‐sectional design was adopted. Parents/caregivers involved in a government‐led children's sport and recreation voucher program were recruited to participate in an online survey as part of the program's evaluation. In response to COVID‐19, parents and caregivers' psychological distress and physical activity levels were assessed using validated items. Binary logistic regression models were used to examine the relationship between physical activity and probable mental illness, and differences across different COVID‐19 restriction periods in 2020 and 2021. In 2020, 10,990 parents/caregivers responded to survey questions and in 2021, 17,106 parents/caregivers responded. Parents/caregivers who were physically active on 7 days per week had lower odds of reporting high psychological distress (odds ratio [OR]: 0.40, 95% confidence interval [CIs]: 0.33, 0.49) than parents/caregivers physically active on fewer days per week. In 2020 9.8% of parents/caregivers (n = 1076) reported high psychological distress, which decreased to 8% in 2021 (n = 1366). In 2021, parents/caregivers had lower odds of reporting high psychological distress (OR: 0.79, 95% CIs: 0.72, 0.86). Socioeconomic disadvantage negatively impacted psychological distress and physical activity levels. Australian parents and caregivers who reported high psychological distress, during and after COVID‐19 restrictions, were participating in low levels of physical activity. Greater collaboration between the mental health, and sport and recreation sectors is recommended to harness the co‐benefits of physical activity throughout parenthood, particularly in low socioeconomic areas.
On the influence of soil flexibility in structural topology optimization
Authors: Cortez R. , Sivapuram R. , Barros P. L. A. , Labaki J. , Picelli R. 
Published: July 2023

AbstractThis paper investigates for the first time the effect of soil flexibility in structural topology optimization. The case of a structure resting on an underlying soil is explored. The response of the soil is modeled using the Indirect Boundary Element Method (IBEM). The structure is modeled using Finite Element Method (FEM) and the soil domain is coupled by imposing continuity and equilibrium conditions at the soil‐structure interface. Original soil stress influence functions are derived to model voids in the soil. The optimization is carried out by using the Topology Optimization of Binary Structures (TOBS), a recently developed method that employs sequential integer linear programming and the branch‐and‐cut algorithm. Structural compliance minimization subject to a volume constraint is solved. Selected optimization problems are solved for various soil‐to‐structure flexibility ratios. Results show that the soil flexibility may have a significant impact in both the optimized topology and in the achievable compliance of the structure. Results considering voids on the soil, which increases the soil flexibility, affected the final topology of the structures as well as the optimized values.
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
Authors: Diercks Philipp , Veroy Karen , Robens‐Radermacher Annika , Unger Jörg F. 
Published: July 2023

AbstractIn this article, a methodology for fine scale modeling of large scale linear elastic structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse scale is modeled by the use of an additive split of the displacement field, addressing applications without a clear scale separation. Local reduced spaces are constructed by solving an oversampling problem with random boundary conditions. Herein, we inform the boundary conditions by a global reduced problem and compare our approach using physically meaningful correlated samples with existing approaches using uncorrelated samples. The local spaces are designed such that the local contribution of each subdomain can be coupled in a conforming way, which also preserves the sparsity pattern of standard finite element assembly procedures. Several numerical experiments show the accuracy and efficiency of the method, as well as its potential to reduce the size of the local spaces and the number of training samples compared to the uncorrelated sampling.
Quantifying the importance of urban trees to people and nature through tree removal experiments
Authors: Ordóñez Camilo , Threlfall Caragh G. , Kendal Dave , Baumann Jess , Sonkkila Cherese , Hochuli Dieter F. , van der Ree Rodney , Fuller Richard A. , Davern Melanie , Herzog Kelly , English Alex , Livesley Stephen J. 
Published: July 2023

AbstractExperimentally manipulating urban tree abundance and structure can help explore the complex and reciprocal interactions among people, biodiversity and the services urban forests provide to humans and wildlife.In this study we take advantage of scheduled urban tree removals to experimentally quantify the benefits that urban trees provide to humans and wildlife. Specifically, we aim to understand how trees affect: (1) bird and mammal abundance and diversity, as well as an ecological process (predation); and (2) people's perception responses, such as the importance that people assign to the trees, wildlife and the site.We designed two independent Before‐after‐control‐impact (BACI) experiments based on two sites where tree removals were occurring (impact sites): an urban park and a residential street, both located in the Greater Melbourne Area, Australia. We selected three control sites for each impact site, or four per experiment. Ecological data were collected through field surveys, and social data on people's perceptions through intercept questionnaires among park and street users. Data were analysed using a GLMMs to determine the combined effect of time (before and after) and treatment (impact and controls).At the urban park, the abundance of nectarivorous birds and possums both declined by 62% following tree removal, while invertebrate predation increased by 82.1%. The level of importance people assigned to the urban park and to the trees at the site decreased after tree removal, and people's attitudes towards tree planting became more positive, meaning more people wanted to plant more trees at the site.None of these changes were observed in the street experiment where fewer and smaller trees were removed, suggesting that effects may be highly specific to context, where factors such as tree volume, diversity and arrangement influence the magnitude of social–ecological effects observed.By demonstrating the social–ecological effect of removing urban trees, we provide evidence that urban trees provide critical habitat to urban wildlife and are perceived as an important aspect of the human experience of urban nature.Read the freePlain Language Summaryfor this article on the Journal blog.
Analysis and modeling of the mechanical behavior of the compaction process of flexible guided 3D weaving
Authors: Du Wudi , Shan Zhongde , Liu Feng , Wu Xiaochuan , Zou Guisheng 
Published: July 2023

AbstractThe preform presents viscoelastic behaviors during the compaction process of flexible guided 3D weaving. The compaction process directly affects the structure of the 3D preform and significantly impacts composite properties. Thus, a viscoelastic model to describe the 3D preform viscoelastic compaction behaviors and a compaction structure model to analyze the causes of the mechanical behavior of the compaction process are originally proposed. The 3D preform compaction experiments with different section area, different number of layers, and different guide structure ratio were conducted to verify the viscoelastic model and the compaction structure model and obtain the influence law on the mechanical behavior. The viscoelastic model can well capture the stress and strain evolution. The compaction structure model can analyze the main structural factors affecting the behavior of compaction mechanical behavior. This work provides a new approach to studying the mechanical behavior in the 3D preform manufacturing process.
Compressive performance of 3D printed fault‐tolerant polymer lattice structures
Authors: Ye Wenguang , Dou Hao , Zhang Dinghua , Cheng Yunyong , Yang Fuqiang , Rudykh Stephan 
Published: July 2023

AbstractThe sudden macroscopic damage to the structure is one of the main factors affecting its safe service. This paper investigates the compressive performance of a fault‐tolerant polymer lattice structure prepared by stereolithography apparatus. The lattice structure comprises hexagonal and rhombohedral lattices with varying thicknesses. The quasi‐static compression experiment results show that bi‐lattice has better fault tolerance than single rhombohedral lattice or pure triangular lattice. Compared with the low stiffness of the rhombohedral lattice and the abrupt fracture of the triangular lattice, the bi‐lattice possesses excellent stiffness and substantial deformation capability. When a thinner beam breaks, the thicker beam impedes the transmission of damage, resulting in even dispersion of damage throughout the structure. Consequently, the overall structure remains intact, and its carrying capacity is maintained. This advantage of damage tolerance before macro fracture is significant for the design and safe operation of structures.
Antidiabetic, hypolipidemic, and antioxidant activities of Pistacia atlantica: A systematic review and meta‐analysis of preclinical studies
Authors: Choghakhori Razieh , Abbasnezhad Amir , Yazdi Mohammad , Ahmadvand Hassan 
Published: July 2023

AbstractTo determine the pharmaceutical applications, we assessed the evidence from preclinical studies about the hypoglycemic, hypolipidemic, and antioxidant potential of Pistacia atlantica (PA) as a natural source for prevention and treatment of diabetes. A comprehensive literature search of the articles published until March 12, 2022 was conducted on PubMed, Embase, Web of Sciences, and Scopus databases, using relevant keywords. This meta‐analysis included 12 articles that examined the blood glucose (BG), insulin, homeostatic model assessment for insulin resistance (HOMA‐IR), triglyceride (TG), total cholesterol (TC), high‐density lipoprotein cholesterol (HDL‐C), malondialdehyde (MDA) and superoxide dismutase (SOD). A random‐effects model was used to estimate the pooled effect size. Findings indicated that PA supplementation significantly decreased BG, HOMA‐IR, TC, TG, and MDA, and increased insulin and SOD in diabetic animals compared with control group (p < .05). However, PA supplementation had no significant effects on HDL‐C (p > .05). The subgroup analysis also confirmed the beneficial effect of PA supplementation with longer duration (>4 weeks) and higher doses (≥100 mg/kg/day) as well as in the extract type. The studies have heterogeneity associated with methodological diversity and there were some concerns about the risk of bias, especially about randomization and blind outcome assessment. This meta‐analysis provided convincing evidence for antidiabetic, hypolipidemic, and antioxidant activity of PA in animals. Further high‐quality studies are needed to firmly establish the clinical efficacy of the plant.
Cryptotanshinone alleviates radiation‐induced lung fibrosis via modulation of gut microbiota and bile acid metabolism
Authors: Li Zhanhong , Shen Yunheng , Xin Jiayun , Xu Xike , Ding Qianqian , Chen Wei , Wang Jie , Lv Yanhui , Wei Xintong , Wei Yanping , Zhang Weidong , Zu Xianpeng , Wang Shumei 
Published: July 2023

AbstractCryptotanshinone (CPT), a major biological active ingredient extracted from root of Salvia miltiorrhiza (Danshen), has shown several pharmacological activities. However, the effect of CPT on radiation‐induced lung fibrosis (RILF) is unknown. In this study, we explored the protective effects of CPT on RILF from gut‐lung axis angle, specifically focusing on the bile acid (BA)‐gut microbiota axis. We found that CPT could inhibit the process of epithelial mesenchymal transformation (EMT) and suppress inflammation to reduce the deposition of extracellular matrix in lung fibrosis in mice induced by radiation. In addition, 16S rDNA gene sequencing and BAs‐targeted metabolomics analysis demonstrated that CPT could improve the dysbiosis of gut microbiota and BA metabolites in RILF mice. CPT significantly enriched the proportion of the beneficial genera Enterorhabdus and Akkermansia, and depleted that of Erysipelatoclostridium, which were correlated with increased intestinal levels of several farnesoid X receptor (FXR) natural agonists, such as deoxycholic acid and lithocholic acid, activating the FXR pathway. Taken together, these results suggested that CPT can regulate radiation‐induced disruption of gut microbiota and BAs metabolism of mice, and reduce the radiation‐induced lung inflammation and fibrosis. Thus, CPT may be a promising drug candidate for treating RILF.
A discussion on the relativistic corrections of the electronic structures of multi‐electron atoms
Authors: Nanni Luca 
Published: July 2023

AbstractThe theory of special relativity is a topic not addressed in theoretical chemistry courses. Einstein's theory of relativity is mainly applied to high‐energy phenomena governed by physical laws not used to describe the chemical bond. Nevertheless, the electrons of heavy elements orbit around the nucleus with relativistic velocities. Here it is, then, the laws that appeared so unusual for chemistry became fundamental tools for investigating the properties of these atoms. Studying the electronic structure of heavy elements is the best place for chemists to learn to tame the pitfalls of a little‐known subject, such as Einstein's theory, and become familiar with its elegant formalism. In this paper, the main relativistic approaches to quantum chemistry are revisited. The problem of the finite nuclear size, the approximation methods used to solve the relativistic equations for k‐shell electrons, and the problem of the negative energy continuum are investigated. Some ansatzes to solve divergence's problem of relativistic corrections near the nucleus are proposed. Finally, a possible connection between the self‐consistent field method and bondonic chemistry is also investigated.
Highly efficient H2S capture using pentagonal B2C monolayer: A periodic DFT study
Authors: Rahimi Rezvan , Solimannejad Mohammad 
Published: July 2023

AbstractThe adsorption and storage properties of the chalcogenide H2S gas by pentagonal B2C nanosheet (penta‐B2C) have been explored utilizing periodic density functional theory. The present results disclose that pristine penta‐B2C nanosheet can take up eight H2S molecules with an H2S capture capacity of 50.28 wt%. Average adsorption energy values for the 1H2S/penta‐B2C, 2H2S/penta‐B2C, 3H2S/penta‐B2C, 4H2S/penta‐B2C, and 8H2S/penta‐B2C complexes are −0.876, −0.808, −0.725, −0.721, and −0.535 eV, respectively. The band structure and the total and partial density of states analyses displayed the reduction in the band gap of the penta‐B2C nanosheet after H2S adsorption of about 13%–25%. Hirshfeld charge analysis reports the charge transfer from the H2S molecules toward the penta‐B2C sheet. As the number of the adsorbed H2S molecules increases, the amount of charge transferred increases. The molecular dynamics (MD) calculations results for the pristine penta‐B2C nanosheet and ultimate 8H2S/penta‐B2C complex confirm their thermal stability at 300 K. Based on the reported analysis, penta‐B2C nanosheet can be introduced as an investible substrate for efficient H2S capture and storage.
Impacts of shelterbelt systems on pasture production and soil bacterial and fungal communities in agricultural fields
Authors: Nguyen Thi Bao‐Anh , Henao Lina A. , Li Zelin , Cheng Long , Hu Hang‐Wei 
Published: July 2023

AbstractIntroductionShelterbelts, which provide protection for livestock and crops against severe weather conditions, have been recognised as important contributors to increased crop yields. Soil microorganisms play important roles in nutrient cycling, soil health and plant performance, thereby exerting significant influence on ecological services in terrestrial ecosystems. However, impacts of shelterbelts on soil microbial communities in pasture ecosystems remain poorly studied.Materials and MethodsHere, we assessed the effect of shelterbelts (composed of Eucalyptus and native shrubs) on the pasture and nutrient productivity as well as soil bacterial and fungal communities at four distances from the shelterbelts with two different heights in two fields during spring and summer by applying amplicon sequencing, physicochemical and nutritional value analyses.ResultsThe results showed that the shelterbelt height, distances from shelterbelts, seasons and their interactive effects substantially affected pasture yield, neutral detergent fibre, metabolisable energy and crude protein yields, but did not increase the pasture productivity in the rows adjacent to the shelterbelts. We also identified that the alpha diversity of bacteria and fungi did not significantly change across distances from the shelterbelts in both fields, but the community structure of soil bacteria and fungi was significantly influenced by distances from the shelterbelts. Interestingly, soil calcium (Ca) and shelterbelts were identified as top predictors of fungal community while soil pH and Ca was key drivers of bacterial community.ConclusionOur study provides novel knowledge in the impact of shelterbelts on pasture and nutritional production and soil microbial communities, which contributes to appropriate application and strategic management of the windbreak systems in agriculture production.
Machine Learning as an Enabler for Automated Assistance Systems for the Classification of Tool Wear on Milling Tools
Authors: Papenberg Björn , Hogreve Sebastian , Tracht Kirsten 
Published: July 2023

AbstractTool wear and the decision when to replace tools is a universal challenge in the metal cutting industry. While the tool wear state can be accurately determined using optical measuring methods, the tool wear of milling tools is often examined by the CNC-machine operators, especially in small and medium enterprises. In order to increase the accuracy with which tool wear can be correctly classified, it is advisable to use an assistance system that automatically removes the tools from a buffer, examines the tool wear state based on visual sensor data and sorts them into separate boxes according to the classification result. In this context, the accurate classification of tool wear is a key capability that can be enabled using methods of machine learning, based on image data that was labeled by human experts. In this paper different machine learning models are examined based on their ability to classify images of milling tools into the categories worn and not worn. The EfficientNet_b0 model achieves an accuracy of 91.47% and outperforms human experts that classified similar images by 22.87%.
Input and Tracking System for Augmented Reality-Assisted Robot Programming
Authors: Brand Michael , Gravert Marvin , Wulff Lukas Antonio , Schüppstuhl Thorsten 
Published: July 2023

AbstractAugmented Reality-assisted robot programming systems (ARRPS) aim to make the programming of industrial robots more efficient by providing an AR-based human machine interface that allows operators to program robots intuitively and quickly. This work aims to contribute to the field by presenting an input and tracking system based on the VIVE Lighthouse technology that can act as a basis for ARRPS systems, improving maturity, costs and accessibility. To evaluate the system, ARRPS core functionality has been implemented so as to demonstrate its basic feasibility. An extensive evaluation of the system accuracy has been conducted, as this is one of the key criteria for potential adoption of the technology. The feasibility could be successfully demonstrated and it could be shown that the end-to-end mean absolute error of the robot path point placement amounts to 11 mm in a workspace of 0.6 × 0.6 × 0.25 m3 volume. Finally, the robustness and setup time of the system still need to be improved.
A Methodology for Developing a Model for Energy Prediction in Additive Manufacturing Exemplified by High-Speed Laser Directed Energy Deposition
Authors: Ehmsen S. , Glatt M. , Linke B. S. , Aurich J. C. 
Published: July 2023

AbstractThe need for energy-efficient manufacturing technologies is growing due to the increasing pressure from climate change, consumers, and regulations. Additive manufacturing is claimed to be a sustainable manufacturing technology, especially for individualized products and small batches. To include the energy demand in the decision-making process on whether a part should be manufactured by additive or rather by subtractive or formative manufacturing, the energy demand which arises during manufacturing of a part must be predicted before the manufacturing process. For this, individual energy prognosis models are needed for each individual AM system. This paper, therefore, presents a methodology that enables users to develop a customized model to predict the energy demand of their AM System.Four steps are necessary to create a model for energy prediction. First, the structure of the investigated system has to be captured. Here the subsystems and their corresponding process parameters are identified. Then the build cycle is analyzed and divided into several process steps in which the power consumption of the subsystems repeatedly follows the same pattern. Afterwards, those process parameters, that have a significant influence on the energy demand of each subsystem are identified within full factorial design of experiments and subsequently analyzed in detail. In the final step, individual models are developed for the energy demand of each subsystem for each process step. These individual models are then aggregated to create an overall model. The application of the methodology is also demonstrated and validated by the example of high-speed laser directed energy deposition.