bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparative Study of Traditional, Ensemble and Neural Network-Based Natural Language Processing Algorithms
Authors: Chikhi Achraf , Mohammadi Ziabari Seyed Sahand , van Essen Jan-Willem
Published: July 2023

Accurate data analysis is an important part of data-driven financial audits. Given the increased data availability and various systems from which audit files are generated, RCSFI provides a way for standardization on behalf of analysis. This research attempted to automate this hierarchical text classification task in order to save financial auditors time and avoid errors. Several studies have shown that ensemble-based models and neural-network-based natural language processing (NLP) techniques achieved encouraging results for classification problems in various domains. However, there has been limited empirical research comparing the performance of both of the aforementioned techniques in a hierarchical multi-class classification setting. Moreover, neural-network- based NLP techniques have commonly been applied to English datasets and not to Dutch financial datasets. Additionally, this research took the implementation of hierarchical approaches into account for the traditional and ensemble-based models and found that the performance did not increase when implementing the included hierarchical approaches. DistilBERT achieved the highest scores on level 1-2-3-4 and outperformed the traditional and ensemble-based models. The model obtained a F1 of 94.50% for level 1-2-3-4. DistilBERT also outperformed BERTje at level 1-2-3-4 despite BERTje being specifically pre-trained on Dutch datasets.
Field-Scale Floating Treatment Wetlands: Quantifying Ecosystem Service Provision from Monoculture vs. Polyculture Macrophyte Communities
Authors: Fletcher Jonathan , Willby Nigel , Oliver David M. , Quilliam Richard S.
Published: July 2023

Global water security is critical for human health, well-being, and economic stability. However, freshwater environments are under increasing anthropogenic pressure and now, more than ever, there is an urgent need for integrated approaches that couple issues of water security and the remediation of degraded aquatic environments. One such strategy is the use of floating treatment wetlands (FTW), which are artificial floating mats that sustain and support the growth of macrophytes capable of removing nutrients from over-enriched waterbodies. In this study, we quantify a range of indicators associated with FTWs, planted with different vegetation community types (i.e., monocultures and polycultures) over the course of a three-year field-scale study. The composition of the two different types of FTWs changed significantly with a convergence in diversity and community composition between the two types of FTWs. Phytoremediation potential of the two FTW communities, in terms of nutrient standing stocks, were also similar but did compare favourably to comparable wild-growing plant communities. There were few substantial differences in invertebrate habitat provision under the FTWs, although the high incidence of predators demonstrated that FTWs can support diverse macroinvertebrate communities. This field-scale study provides important practical insights for environmental managers and demonstrates the potential for enhanced ecosystem service provision from employing nature-based solutions, such as FTWs, in freshwater restoration projects.
Research on the Impact of Carbon Emissions and Spatial Form of Town Construction Land: A Study of Macheng, China
Authors: Xu Yao , Sun Liang , Wang Bo , Ding Shanmin , Ge Xichen , Cai Shuangrong
Published: July 2023

In the context of low-carbon construction, reducing carbon dioxide emissions from town construction land is the key to mitigating the problems caused by global warming. The influence of spatial form on carbon emissions has been generally recognized, but its influence at the level of town construction land is less explored. Therefore, in this study, in order to investigate the relationship between the spatial form of town construction land and carbon emissions, the relationship between them was analyzed, taking Macheng town of Bengbu city as the research object, selecting spatial form elements and quantifying them, and characterizing and accounting for the carbon emissions from the town construction land by each building’s energy consumption. The study demonstrates that the spatial form elements such as building area and building storeys are important factors affecting the carbon emissions of residential land. Likewise, the building area, building shape coefficient, and floor area ratio are crucial factors impacting the carbon emissions of public lands. This research offers spatial form optimization strategies from a carbon reduction perspective by delving into the inherent relationship between spatial form and carbon emissions in town construction land. Consequently, it provides valuable scientific guidance for quantifying spatial planning and formulating carbon reduction strategies within a low-carbon framework.
Exploring Switzerland’s Land Cover Change Dynamics Using a National Statistical Survey
Authors: Thomas Isabel Nicholson , Giuliani Gregory
Published: July 2023

Timely and reliable Land Use and Cover change information is crucial to efficiently mitigate the negative impact of environmental changes. Switzerland has the ambitious objective of being a sustainable country while remaining an attractive business location with a high level of well-being. However, this aspiration is hampered by increasing pressures that are significantly impacting the environment and putting serious demands on land. In the present study, we used the national Land Cover (LC) dataset, named ArealStatistik, produced by the Federal Statistical Office, to explore the spatiotemporal patterns of Land Cover in Switzerland, providing a comprehensive assessment of land cover change at the national scale. Results indicate that, in general, Switzerland has undergone small, spatially dispersed, dynamic, and gradual change trends, with high rates of transition between low growing Brush Vegetation and forest LC classes in recent years. These pixel-level trends are more important in the lower altitude plateau and Jura regions, while greater changes in the spatial configuration of LC are observed in the alpine regions. However, findings also suggest that identifying drivers and understanding the rate of change are limited by the spatial resolution and temporal update frequency of the ArealStatistik. The ability to understand these drivers would benefit from a high-resolution annual LC dataset. Such a data product can be produced using the ArealStatistik together with dense satellite data time-series and Machine/Deep Learning techniques.
Characteristics and Driving Mechanism of Urban Construction Land Expansion along with Rapid Urbanization and Carbon Neutrality in Beijing, China
Authors: Yang Huicai , Ma Jingtao , Jiao Xinying , Shang Guofei , Yan Haiming
Published: July 2023

Escalating urban issues in Beijing call for comprehensive exploration of urban construction land expansion towards the goal of carbon neutrality. Firstly, urban construction land in Beijing during the period 2005–2020 was accurately detected using Landsat images and impervious surface data, and then its expansion characteristics were revealed. Finally, the driving mechanism of urban construction land expansion was explored using geographically and temporally weighted regression from the input–output perspective. The results showed that the expansion speed and intensity of urban construction land in Beijing showed an overall tendency to slow down, and the center of urban expansion shifted to the new urban development zone and ecological function conservation zone. Urban construction land expansion in the central urban area was first scattered and then compact, while that in the new urban development zone and ecological function conservation zone primarily followed an outward pattern. The permanent population, per capita GDP, and per capita retail sales of social consumer goods were the primary driving factors of urban construction land expansion in Beijing, the impacts of which varied significantly among different districts of Beijing. All these results can provide a solid foundation for improving land use policies towards the goal of carbon neutrality in highly urbanized areas.
Pathophysiology of Acute Coronary Syndromes—Diagnostic and Treatment Considerations
Authors: Theofilis Panagiotis , Oikonomou Evangelos , Chasikidis Christos , Tsioufis Konstantinos , Tousoulis Dimitris
Published: July 2023

Coronary artery disease and acute coronary syndromes are accountable for significant morbidity and mortality, despite the preventive measures and technological advancements in their management. Thus, it is mandatory to further explore the pathophysiology in order to provide tailored and more effective therapies, since acute coronary syndrome pathogenesis is more varied than previously assumed. It consists of plaque rupture, plaque erosion, and calcified nodules. The advancement of vascular imaging tools has been critical in this regard, redefining the epidemiology of each mechanism. When it comes to acute coronary syndrome management, the presence of ruptured plaques almost always necessitates emergent reperfusion, whereas the presence of plaque erosions may indicate the possibility of conservative management with potent antiplatelet and anti-atherosclerotic medications. Calcified nodules, on the other hand, are an uncommon phenomenon that has largely gone unexplored in terms of the best management plan. Future studies should further establish the importance of detecting the underlying mechanism and the role of various treatment plans in each of these distinct entities.
The Effect of Nanoparticle Additives on the Lubricity of Diesel and Biodiesel Fuels
Authors: Jokubynienė Vida , Slavinskas Stasys , Kreivaitis Raimondas
Published: July 2023

Fuel lubricity is an essential property that ensures the longevity end efficiency of diesel CI engines. Nanomaterials have been shown to have the potential to improve lubricity in many different lubricating substances, including fuels. Moreover, the combustion process has also been shown to improve with the introduction of nanomaterials. This study investigated a series of nanoparticles, including carbon nanoplates, carbon nanotubes, aluminum oxide, zinc oxide, and cerium oxide, as lubricity-enhancing additives for selected fuels. Conventional diesel fuel and rapeseed oil methyl ester, referred to as biodiesel, were chosen as base fuels for modification. The lubricity was evaluated according to the standard test method ASTM 6079 using the HFRR tribometer. The leading lubricity indicators were the wear scar diameter, wear volume, and coefficient of friction. In addition, the worn surface analysis was performed to elucidate the lubrication mechanism. The results show that the addition of nanoparticles can improve the lubricity of both investigated fuels. However, the effect differed among nanoparticles and fuels. In summary, carbon nanotubes could be a rational choice for both fuels. In addition, zinc oxide improved the lubricity of diesel fuel, while carbon nanoplatelets and aluminum oxide nanoparticles showed improvements in the lubricity of biodiesel.
Effects of Hyperelliptic Bearings Bush on Connecting Rod Big-End Lubrication and Design Optimization
Authors: Jia Dewen , Li Chengkun , Deng Wei , Ji Huiping , Hao Lina
Published: July 2023

Aiming at the impact of bearing bushes on the lubrication and friction and wear of diesel engine connecting rod big-end bearings, a certain type of diesel engine connecting rod big-end bearing bush was taken as the research object and a multi-body dynamics numerical calculation model of the connecting rod group was built. The connecting rod big-end bearing bushes with four profiles: exponential, hyperelliptic, barrel and trapezoid were used to study the effect on bearing lubrication. The study found that the hyperelliptic bush has the best lubrication performance for the connecting rod big-end bearing. On the basis of the hyperelliptic bush, the bearing clearance, bearing width, journal oil hole diameter and oil supply pressure are used as design variables, using the Box–Behnken experimental design and radial basis function (RBF) neural network method to construct an approximate multi-objective model, which the minimum oil film thickness (abbreviated as MOFT) and average rough contact effective pressure are the objectives. A non-dominated sorting genetic algorithm (NSGA-II) is used for multi-objective optimization. The optimization results show that the bearing clearance remains basically unchanged, the bearing width, journal oil hole diameter and oil supply pressure increase, so that MOFT of the connecting rod big-end bearing rises from 1.56 μm to 1.97 μm, and the average rough contact effective pressure increases from 3.97 MPa decreases to 0.25 MPa. The research results can provide a reference for the analysis and optimization of the lubrication performance of the connecting rod big-end bearing.
Experimental and Numerical Simulation Studies on V-Shaped Bending of Aluminum/CFRP Laminates
Authors: Cheng Hang , Zhang Zhiqiang , Ren Mingwen , Jia Hongjie
Published: July 2023

With the increasing requirements of automotive lightweighting, metal/CFRP laminates are increasingly used. In this paper, Al/CFRP laminates were prepared using an integrated hot press curing method, and the optimum curing conditions were determined using the single-lap shear test at 130 °C for 45 min. The effects of fiber lay-up, forming speed, and metal layer thickness on bending springback were investigated using the V-shaped bending test and Abaqus finite element analysis method. The results show that fiber lay-up has an important influence on springback. Among the five different fiber lay-ups (0° unidirectional, 90° unidirectional, 0° orthotropic, 90° orthotropic, and 45° orthotropic), the 45° orthotropic lay-up had the lowest springback rate of 1.11%. Increasing the thickness of the sheet metal can significantly reduce the resilience rate. As the sheet thickness increased from 2 mm to 3 mm, the springback of the 90° unidirectional lay-up decreased by 43%. Springback was not sensitive to forming speed, and the difference in springback was within 1% at different forming speeds. The damage behavior of the forming process was analyzed using the three-dimensional Hashin damage law with the Vumat subroutine and microscopic analysis. Fiber and resin damage under 45° orthotropic lay-up conditions was relatively small compared to fiber damage under 0° unidirectional lay-up and resin damage under 90° unidirectional lay-up.
Study on Mechanical Behavior of Hollow-Core Slab Bridge with Pinned Reinforcement
Authors: Chen Jihao , Li Xin , Zhu Qian
Published: July 2023

Joints connect prefabricated hollow-core slabs, the key elements of force transmission of hollow-core slab bridges. The joints are easily damaged, which affects the integrity and safety of the hollow-core slab bridge. This paper uses MIDAS FEA NX finite element analysis software to simulate the deep hinge joint segment model, comparing and analyzing the finite element simulation analysis results with the test results, and proposes the critical parameters of the hinge joint interface and concrete damage plasticity. Further, an assembled hollow slab bridge model is established to compare and analyze the force transfer performance of conventional and pinned reinforcement bridges and reveal the deep joint damage evolution process. The results showed that the hollow slab bridge damage appeared first at the hinge joint interface at the load location. Cracks in the joints can develop along the longitudinal and height directions, with the longitudinal crack length reaching 40% of the span. The vertical crack height can get the lower edge of the paving layer, increasing the distance from the load position, and the cracking height decreases symmetrically. Under an ultimate load, the hinge concrete of conventional reinforcement and pinned reinforcement hollow-core slab bridges showed significant damage in 30–70% and 40–60% of the span, respectively. Compared with the conventional reinforcement bridges, the cracking load and ultimate load of the pinned reinforcement bridges increase by 28.57% and 58.14%, respectively, and the relative deflection under 420 kN load reduces by 97.95%. The hollow slab bridges have improved the force performance and thus enhanced the integrity of the hollow-core slab bridges.
Effectiveness of Porcelain Polishing Methods on the Roughness and Color Stability of CAD–CAM Ceramics after Orthodontic Bracket Debonding
Authors: Haralur Satheesh B. , Shiban Abdullah Saeed , Alqahtani Nasser Mohammed
Published: July 2023

Increased utilization of all ceramic restorations for aesthetic consideration in combination with routine adult orthodontic practice has led to numerous clinical challenges. Obtaining adequate bond strength between the orthodontic bracket and all-ceramic restoration and damage to the ceramic surface during the bracket debonding procedure needs to be better understood. This study analyzed the surface texture and color change of glazed and bracket-debonded ceramic CAD–CAM materials and the efficiency of porcelain polishing systems in restoring surface morphology and color. A total of 30 rectangular test specimens from each lithium disilicate CAD (LD-CAD), polymer-infiltrated ceramic (PICN), zirconia-reinforced lithium silicate glass ceramic (ZLS), and 5YTZP zirconia (5YZP) were prepared. The ceramic samples were embedded within acrylic resin, and baseline surface roughness and color were recorded using an optical profilometer and a reflected color spectrophotometer. The porcelain samples were bonded with lower incisor ceramic brackets. The samples were thermocycled 2000 times between 5 and 55 °C. Afterward, the brackets were peeled with bracket-removing pliers. The resin adhesive from the debonded surface was eliminated with tungsten carbide bur, and samples were randomly divided into three subgroups of (n = 10) to be polished with Diapol-twist (DT), a Keramik-Politur 4313B Komet polishing kit (KK), and a Horico diamond polisher (HDP). The polished surface roughness and color were recorded. The data were statistically analyzed using a two-way analysis of variance at p < 0.05. The debonded porcelain surfaces across the groups displayed significantly higher mean surface roughness (Ra) compared to glazed surfaces. The debonded 5YZP showed the least Ra at 0.661 (0.09), while the highest Ra was recorded by PICN at 4.057 (0.82). All of the polishing systems evaluated in the study significantly reduced the surface roughness. However, they were unsuccessful in regaining the surface topography of the glazed surface. The flexible discs (DT) produced the smoothest surface, followed by the diamond-impregnated rubber points (KK). Unpolished porcelain surfaces had a discernable mean color difference from glazed surfaces. Polished surfaces from the different polishing systems among the all-ceramic groups achieved a clinically acceptable mean color difference. Polishing debonded rough porcelain surfaces is imperative, and flexible discs performed better in all of the tested CAD–CAM ceramic materials.
Unveiling Sustainable Potential: A Life Cycle Assessment of Plant–Fiber Composite Microcellular Foam Molded Automotive Components
Authors: Feng Tao , Guo Wei , Li Wei , Meng Zhenghua , Zhu Yao , Zhao Feng , Liang Weicheng
Published: July 2023

The development and utilization of new plant–fiber composite materials and microcellular foam molding processes for the manufacturing of automotive components are effective approaches when achieving the lightweight, low-carbon, and sustainable development of automobiles. However, current research in this field has mainly focused on component performance development and functional exploration, with a limited assessment of environmental performance, which fails to meet the requirements of the current green and sustainable development agenda. In this study, based on a life cycle assessment, the resource, and environmental impacts of plant–fiber composite material automotive components and microcellular foam molding processes were investigated. Furthermore, a combined approach to digital twinning and life cycle evaluation was proposed to conduct resource and environmental assessments and analysis. The research results indicate that under current technological conditions, resource and environmental issues associated with plant–fiber composite material automotive components are significantly higher than those of traditional material components, mainly due to differences in their early-stage processes and the consumption of electrical energy and chemical raw materials. It is noteworthy that electricity consumption is the largest influencing factor that causes environmental issues throughout the life cycle, especially accounting for more than 42% of indicators such as ozone depletion, fossil resource consumption, and carbon dioxide emissions. Additionally, the microcellular foam molding process can effectively reduce the environmental impact of products by approximately 15% and exhibits better overall environmental performance compared to chemical foaming. In future development, optimizing the forming process of plant–fiber composite materials, increasing the proportion of clean energy use, and promoting the adoption of microcellular foam injection molding processes could be crucial for the green and sustainable development of automotive components.
Graphene/Heterojunction Composite Prepared by Carbon Thermal Reduction as a Sulfur Host for Lithium-Sulfur Batteries
Authors: Li Jiahao , Gao Bo , Shi Zeyuan , Chen Jiayang , Fu Haiyang , Liu Zhuang
Published: July 2023

An interlayer nanocomposite (CC@rGO) consisting of a graphene heterojunction with CoO and Co9S8 was prepared using a simple and low-cost hydrothermal calcination method, which was tested as a cathode sulfur carrier for lithium-sulfur batteries. The CC@rGO composite comprises a spherical heterostructure uniformly distributed between graphene sheet layers, preventing stacking the graphene sheet layer. After the introduction of cobalt heterojunction on a graphene substrate, the Co element content increases the reactive sites of the composite and improves its electrochemical properties to some extent. The composite exhibited good cycling performance with an initial discharge capacity of 847.51 mAh/g at 0.5 C and a capacity decay rate of 0.0448% after 500 cycles, which also kept 452.91 mAh/g at 1 C and in the rate test from 3 C back to 0.1 C maintained 993.27 mAh/g. This article provides insight into the design of cathode materials for lithium-sulfur batteries.
Research on the Influence of Charging Oil Conditions on the Axial Force of Hydraulic Torque Converter
Authors: Liu Cheng , Jin Chen , Guo Meng , Yan Qingdong , Wei Wei
Published: July 2023

The hydraulic torque converter is a critical component in high-power tracked vehicles such as bulldozers or bridge machines. Its axial force has a significant impact on the reliability and load-carrying capacity of the transmission system, which is greatly influenced by the charging oil conditions. To investigate the axial force characteristic of the torque converter and its charging oil effects, a computational fluid dynamics (CFD) method is established by considering inner and outer leakage regions, as well as inlet and outlet channels. Additionally, a novel axial force-testing method is proposed, and the axial force testing and validation experiments on the torque converter prototype have been completed. The research findings reveal that changes in oil viscosity resulting from variations in charging oil temperature have a considerable impact on the axial force of the torque converter. The axial force of the pump and turbine decreases as the temperature increases due to varying pressure sensitivity among different components. The influence of charging oil pressure on axial force follows a linear relationship, with its magnitude determined by the axial unbalanced area of the hydraulic torque converter during its design and development. In addition, a formula for the axial force of the hydraulic torque converter is proposed under different charging oil pressures. Furthermore, a novel suppression of axial force has been proposed without altering the structure, which has been validated as an effective method. The results lay a theoretical foundation for the research and suppression of axial forces in hydraulic torque converters, and they also have an engineering application value in the design of high-reliability and long-life converters.
Improving Agent Decision Payoffs via a New Framework of Opponent Modeling
Authors: Liu Chanjuan , Cong Jinmiao , Zhao Tianhao , Zhu Enqiang
Published: July 2023

The payoff of an agent depends on both the environment and the actions of other agents. Thus, the ability to model and predict the strategies and behaviors of other agents in an interactive decision-making scenario is one of the core functionalities in intelligent systems. State-of-the-art methods for opponent modeling mainly use an explicit model of opponents’ actions, preferences, targets, etc., that the primary agent uses to make decisions. It is more important for an agent to increase its payoff than to accurately predict opponents’ behavior. Therefore, we propose a framework synchronizing the opponent modeling and decision making of the primary agent by incorporating opponent modeling into reinforcement learning. For interactive decisions, the payoff depends not only on the behavioral characteristics of the opponent but also the current state. However, confounding the two obscures the effects of state and action, which then cannot be accurately encoded. To this end, state evaluation is separated from action evaluation in our model. The experimental results from two game environments, a simulated soccer game and a real game called quiz bowl, show that the introduction of opponent modeling can effectively improve decision payoffs. In addition, the proposed framework for opponent modeling outperforms benchmark models.
Modelling Soil Compaction Parameters Using an Enhanced Hybrid Intelligence Paradigm of ANFIS and Improved Grey Wolf Optimiser
Authors: Bardhan Abidhan , Singh Raushan Kumar , Ghani Sufyan , Konstantakatos Gerasimos , Asteris Panagiotis G.
Published: July 2023

The criteria for measuring soil compaction parameters, such as optimum moisture content and maximum dry density, play an important role in construction projects. On construction sites, base/sub-base soils are compacted at the optimal moisture content to achieve the desirable level of compaction, generally between 95% and 98% of the maximum dry density. The present technique of determining compaction parameters in the laboratory is a time-consuming task. This study proposes an improved hybrid intelligence paradigm as an alternative tool to the laboratory method for estimating the optimum moisture content and maximum dry density of soils. For this purpose, an advanced version of the grey wolf optimiser (GWO) called improved GWO (IGWO) was integrated with an adaptive neuro-fuzzy inference system (ANFIS), which resulted in a high-performance hybrid model named ANFIS-IGWO. Overall, the results indicate that the proposed ANFIS-IGWO model achieved the most precise prediction of the optimum moisture content (degree of correlation = 0.9203 and root mean square error = 0.0635) and maximum dry density (degree of correlation = 0.9050 and root mean square error = 0.0709) of soils. The outcomes of the suggested model are noticeably superior to those attained by other hybrid ANFIS models, which are built with standard GWO, Moth-flame optimisation, slime mould algorithm, and marine predators algorithm. The results indicate that geotechnical engineers can benefit from the newly developed ANFIS-IGWO model during the design stage of civil engineering projects. The developed MATLAB models are also included for determining soil compaction parameters.
Effects of Exploration Weight and Overtuned Kernel Parameters on Gaussian Process-Based Bayesian Optimization Search Performance
Authors: Omae Yuto
Published: July 2023

Gaussian process-based Bayesian optimization (GPBO) is used to search parameters in machine learning, material design, etc. It is a method for finding optimal solutions in a search space through the following four procedures. (1) Develop a Gaussian process regression (GPR) model using observed data. (2) The GPR model is used to obtain the estimated mean and estimated variance for the search space. (3) The point where the sum of the estimated mean and the weighted estimated variance (upper confidence bound, UCB) is largest is the next search point (in the case of a maximum search). (4) Repeat the above procedures. Thus, the generalization performance of the GPR is directly related to the search performance of the GPBO. In procedure (1), the kernel parameters (KPs) of the GPR are tuned via gradient descent (GD) using the log-likelihood as the objective function. However, if the number of iterations of the GD is too high, there is a risk that the KPs will overfit the observed data. In this case, because the estimated mean and variance output by the GPR model are inappropriate, the next search point cannot be properly determined. Therefore, overtuned KPs degrade the GPBO search performance. However, this negative effect can be mitigated by changing the parameters of the GPBO. We focus on the weight of the estimated variances (exploration weight) of the UCB as one of these parameters. In a GPBO with a large exploration weight, the observed data appear in various regions in the search space. If the KP is tuned using such data, the GPR model can estimate the diverse regions somewhat correctly, even if the KP overfits the observed data, i.e., the negative effect of overtuned KPs on the GPR is mitigated by setting a larger exploration weight for the UCB. This suggests that the negative effect of overtuned KPs on the GPBO search performance may be related to the UCB exploration weight. In the present study, this hypothesis was tested using simple numerical simulations. Specifically, GPBO was applied to a simple black-box function with two optimal solutions. As parameters of GPBO, we set the number of KP iterations of GD in the range of 0–500 and the exploration weight as {1,5}. The number of KP iterations expresses the degree of overtuning, and the exploration weight expresses the strength of the GPBO search. The results indicate that, in the overtuned KP situation, GPBO with a larger exploration weight has better search performance. This suggests that, when searching for solutions with a small GPBO exploration weight, one must be careful about overtuning KPs. The findings of this study are useful for successful exploration with GPBO in all situations where it is used, e.g., machine learning hyperparameter tuning.
Exploring the Barriers to the Advancement of 3D Printing Technology
Authors: Liu Peace Y. L. , Liou James J. H. , Huang Sun-Weng
Published: July 2023

3D printing technology is suitable for application in advancing digitization in dentistry. However, the use of this technology in the dental field is not as widespread as expected. The study discusses the barriers to advancing 3D printing technology in dentistry. First, Fuzzy Delphi was used to conduct in-depth interviews with experts to explore what barriers prevent the advancement of 3D printing technology in dentistry. Second, the decision-making and trial assessment laboratory (DEMATEL) was used to identify the cause-and-effect relationship among barriers. Because DEMATEL relies on the expert decision-making system, experts often have different experiences and backgrounds, so judgment results are often uncertain and inconsistent. Therefore, this study proposes using a rough-Z-number to integrate opinions among experts, which can effectively overcome the problems of inconsistency and uncertainty. After analyzing the results, we found that “lack of standard infrastructure” is the most important barrier to the advancement of 3D printing in dentistry, and this study provides improvement strategies based on the results. The results put forward countermeasures for the barriers to the promotion of 3D printing technology in dentistry, which will make the development of dental digitization more effective.
An Overview of Forecast Analysis with ARIMA Models during the COVID-19 Pandemic: Methodology and Case Study in Brazil
Authors: Ospina Raydonal , Gondim João A. M. , Leiva Víctor , Castro Cecilia
Published: July 2023

This comprehensive overview focuses on the issues presented by the pandemic due to COVID-19, understanding its spread and the wide-ranging effects of government-imposed restrictions. The overview examines the utility of autoregressive integrated moving average (ARIMA) models, which are often overlooked in pandemic forecasting due to perceived limitations in handling complex and dynamic scenarios. Our work applies ARIMA models to a case study using data from Recife, the capital of Pernambuco, Brazil, collected between March and September 2020. The research provides insights into the implications and adaptability of predictive methods in the context of a global pandemic. The findings highlight the ARIMA models’ strength in generating accurate short-term forecasts, crucial for an immediate response to slow down the disease’s rapid spread. Accurate and timely predictions serve as the basis for evidence-based public health strategies and interventions, greatly assisting in pandemic management. Our model selection involves an automated process optimizing parameters by using autocorrelation and partial autocorrelation plots, as well as various precise measures. The performance of the chosen ARIMA model is confirmed when comparing its forecasts with real data reported after the forecast period. The study successfully forecasts both confirmed and recovered COVID-19 cases across the preventive plan phases in Recife. However, limitations in the model’s performance are observed as forecasts extend into the future. By the end of the study period, the model’s error substantially increased, and it failed to detect the stabilization and deceleration of cases. The research highlights challenges associated with COVID-19 data in Brazil, such as under-reporting and data recording delays. Despite these limitations, the study emphasizes the potential of ARIMA models for short-term pandemic forecasting while emphasizing the need for further research to enhance long-term predictions.
Numerical Simulation of Hole Cleaning of a Horizontal Wellbore Model with Breakout Enlargement Section
Authors: Sun Xiaofeng , Tao Liang , Zhao Yuanzhe , Qu Jingyu , Yao Di , Li Zijian
Published: July 2023

Horizontal wells are more likely than vertical wells to have enlarged wellbore sections due to borehole instability. However, there is scarce research on borehole cleaning of horizontal wells with enlarged wellbore sections. In this paper, we establish a horizontal wellbore model with a breakout enlargement section using field borehole diameter data. We used the three-dimensional computational fluid dynamics (CFD) method and the Realizable k-ε turbulence model with the Euler–Euler approach to simulate the effects of the drilling fluid circulation return speed and the spinning speed of the drill pipe on the cutting movement of conventional horizontal wells and horizontal wells with a breakout enlargement section. The simulation results demonstrate that increasing the drilling fluid circulation return speed and the spinning speed of the drill pipe does not significantly improve the hole cleaning impact for horizontal wells with a breakout enlargement section. We analyzed the effects of the enlargement ratio, ellipticity, and principal axis orientation on the borehole cleaning effect of horizontal wells with a breakout enlargement section. The results show that the cleaning impact is better when the enlargement ratio is lower; moreover, the ellipticity is larger and the principal axis orientation is perpendicular to the gravity direction. This paper fills a gap in the existing theory of hole cleaning in horizontal wells and provides a theoretical basis for improving the hole cleaning effect in actual drilling processes.
Identification of Genes Associated with Prognosis and Immunotherapy Prediction in Triple-Negative Breast Cancer via M1/M2 Macrophage Ratio
Authors: Liu Jianyu , Deng Yuhan , Liu Zhuolin , Li Xue , Zhang Mingxuan , Yu Xin , Liu Tong , Chen Kexin , Li Zhigao
Published: July 2023

Background and Objectives: Triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous subtype of breast cancer, accounts for approximately 10–15% of all breast cancer cases. Currently, there is no effective therapeutic target for TNBC. Tumor-associated macrophages (TAMs), which can be phenotypically classified into M1 and M2 subtypes, have been shown to influence the prognosis of various cancers, including ovarian cancer. This study aimed to investigate the role of M1/M2 macrophages in the TNBC tumor microenvironment (TME), with a focus on identifying prognostic genes and predicting immunotherapy response. Materials and Methods: The study employed the CIBERSORT algorithm to analyze immune cell expression in the TME. Genes associated with the M1/M2 macrophage ratio were identified using Pearson correlation analysis and used to classify patients into distinct clusters. Dimensionality reduction techniques, including univariate Cox regression and Lasso, were applied to these genes. The expression of prognostic genes was validated through immunohistochemistry. Results: The study found a high prevalence of TAMs in the TME. Among the patient clusters, 109 differentially expressed genes (DEGs) were identified. Three significant DEGs (LAMP3, GZMB, and CXCL13) were used to construct the riskScores. The riskScore model effectively stratified patients based on mortality risk. Gene Set Enrichment Analysis (GSEA) associated the riskScore with several significant pathways, including mismatch repair, JAK/STAT3 signaling, VEGF signaling, antigen processing presentation, ERBB signaling, and P53 signaling. The study also predicted patient sensitivity to immunotherapy using the riskScores. The expression of the three significant DEGs was validated through immunohistochemistry. Conclusions: The study concluded that the riskScore model, based on the M1/M2 macrophage ratio, is a valid prognostic tool for TNBC. The findings underscore the importance of the TME in TNBC progression and prognosis and highlight the potential of the riskScore model in predicting immunotherapy response in TNBC patients.
e-Beam and γ-rays Induced Synthesis and Catalytic Properties of Copper Nanoclusters-Deposited Composite Track-Etched Membranes
Authors: Parmanbek Nursanat , Aimanova Nurgulim A. , Mashentseva Anastassiya A. , Barsbay Murat , Abuova Fatima U. , Nurpeisova Dinara T. , Jakupova Zhanar Ye. , Zdorovets Maxim V.
Published: July 2023

Effective removal of toxic inorganic and organic pollutants is one of the current leading challenges of wastewater treatment. In this study, the decomposition of methylene blue (MB) under UV light irradiation was investigated in the presence of copper nanoclusters (NCs)-deposited polyethylene terephthalate (PET) track-etched hybrid membranes. PET track-etched membranes (TeMs) with an average pore size of ~400 nm were grafted by functional acrylic acid (AA) monomer under electron beam irradiation after oxidation with H2O2/UV system. The radiation dose varied between 46 and 200 kGy. For the deposition of copper NCs, poly(acrylic acid) (PAA)-grafted membranes saturated with Cu(II) ions were irradiated either by electron beam or γ-rays to obtain copper-based NCs for the catalytic degradation of MB. Irradiation to 100 kGy with accelerated electrons resulted in the formation of small and uniform copper hydroxide (Cu(OH)2) nanoparticles homogeneously distributed over the entire volume of the template. On the other hand, irradiation under γ-rays yielded composites with copper NCs with a high degree of crystallinity. However, the size of the deposited NCs obtained by γ-irradiation was not uniform. Nanoparticles with the highest uniformity were obtained at 150 kGy dose. Detailed analysis by X-ray diffraction (XRD) and scanning electron microscopy (SEM) confirmed the loading of copper nanoparticles with an average size of 100 nm on the inner walls of nanochannels and on the surface of PET TeMs. Under UV light irradiation, composite membranes loaded with NCs exhibited high photocatalytic activity. It was determined that the highest catalytic activity was observed in the presence of Cu(OH)2@PET-g-PAA membrane obtained at 250 kGy. More than 91.9% of the initial dye was degraded when this hybrid membrane was employed for 180 min, while only 83.9% of MB was degraded under UV light using Cu@PET-g-PAA membrane. Cu(OH)2@PET-g-PAA membranes obtained under electron beam irradiation demonstrated a higher photocatalytic activity compared to Cu@PET-g-PAA membranes attained by γ-rays.
Study on Laser Overlap Welding of Titanium/Aluminum Dissimilar Metals Based on Niobium Microalloying
Authors: Pan Hao , Wang Yue , Geng Shaoning , Yin Annan , Han Chu , Zhao Jintian
Published: July 2023

Brittle intermetallic compounds, formed during the welding process of titanium/aluminum (Ti/Al), lead to a significant reduction in joint mechanical properties. The purpose of this study is to mitigate the formation of brittle phases during the laser welding of dissimilar Ti/Al metals, thereby enhancing the mechanical properties of the joints. In this investigation, an innovative approach is adopted, utilizing Nb foil as an interlayer to effectively minimize the formation of brittle intermetallic phases during dissimilar welding. A comprehensive analysis of the microstructure of the transition layer was conducted using material characterization methods, including scanning electron microscope equipped with an energy dispersive X-ray spectrometer. The mechanical performance of the welded joints was assessed using tensile testing. The results indicate that the effective welding width and joint penetration depth at the joint interface were reduced in Ti/Al dissimilar metals when Nb was added as an intermediate layer, under the same welding process parameters, when compared to unalloyed weld seams. Furthermore, the utilization of a 0.05 mm Nb foil as the intermediate layer results in a significant 25% increase in the average shear strength compared to the other condition, with the average shear strength of the joint reaching its peak value at 192 N/mm. The unalloyed Ti/Al weld joint usually fractured along the melting zone, displaying complete brittle fracture characteristics. After Nb microalloying, the joint typically fractures along the transition zone and interface, exhibiting both cleavage and ductile fracture characteristics, indicating the combination of a brittle and toughness fracture. This study provides experimental evidence and new insights for welding Ti/Al composite structures, with significant theoretical and practical applications.
The Effect of MSTN Mutation on Bile Acid Metabolism and Lipid Metabolism in Cattle
Authors: Wu Di , Wang Song , Hai Chao , Wang Linfeng , Pei Dongchao , Bai Chunling , Su Guanghua , Liu Xuefei , Zhao Yuefang , Liu Zhonghua , Yang Lei , Li Guangpeng
Published: July 2023

Myostatin (MSTN) is a negative regulator of skeletal muscle genesis during development. MSTN mutation leads to increased lean meat production and reduced fat deposition in livestock. However, the mechanism by which MSTN promotes myogenesis by regulating metabolism is not clear. In this study, we compared the metabolomics of the livers of wild-type (WT) and MSTN mutation cattle (MT), and found changes in the content and proportion of fatty acids and bile acids in MT cattle. The differential metabolites were enriched in sterol synthesis and primary bile acid synthesis. We further analyzed the expression of genes involved in the regulation of lipid and bile acid metabolism, and found that the loss of MSTN may alter lipid synthesis and bile acid metabolism. This study provides new basic data for MSTN mutations in beef cattle breeding.
The Implications in Meat Quality and Nutrition by Comparing the Metabolites of Pectoral Muscle between Adult Indigenous Chickens and Commercial Laying Hens
Authors: Yin Lingqian , Liu Li , Tang Yuan , Chen Qian , Zhang Donghao , Lin Zhongzhen , Wang Yan , Liu Yiping
Published: July 2023

Aged chickens are often a secondary dietary choice, owing to the poor organoleptic qualities of their meat. With regard to the meat quality of chickens, the metabolic profiles of pectoral muscle in Guangyuan grey chickens (group G) and Hy-Line grey hens (group H) aged 55 weeks were compared via ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). A total of 74 metabolites were identified with differential changes in the ion model. Lipids and lipid-like molecules comprised the largest proportion among the different metabolites. The content of myristic acid and palmitic acid were found to be higher in the pectoral muscle of group G, while group H showed significantly higher levels of glycerophospholipid molecules, such as LPC(18:2/0:0), Pi(38:5), Pc(16:0/16:0), and Pe(16:1e/14-hdohe). KEGG pathway analysis indicated that the abundant metabolites in group G were mainly involved in energy metabolism and fatty acid biosynthesis and metabolism, whereas those of group H were mainly attributed to the metabolism of unsaturated fatty acids and amino acids. Overall, the differences in lipid and amino acid metabolism in pectoral muscle appear to be responsible for the difference in meat quality between indigenous chickens and commercial laying hens.
Investigation of Parallel and Orthogonal MIMO Antennas with Two-Notched Structures for Ultra-Wideband Application
Authors: Wang Liang , Li Ziwei , Zheng Hongxing
Published: July 2023

Ultra-wideband (UWB) technology is widely used in many communication scenarios. However, narrowband systems can easily interfere with the UWB system, which generates multipath fading. In order to solve these interferences and meet the design requirements of high isolation of multiple-input multiple-output (MIMO) antennas, two MIMO antennas with double-notch structures are designed. Firstly, two U-shaped slots are etched on the radiating patch and feeder to achieve notch characteristics in WiMAX and ITU bands. Using this antenna element, a two-element antenna is put symmetrically in parallel, and two rectangular branches are loaded to improve the isolation. The size is 0.57λ × 0.32λ × 0.013λ (at 2.5 GHz). Then, a four-element antenna is designed to meet the requirements for another application; here, each element is placed orthogonally to each other, and the isolation is improved through loading a cross-shaped branch in the middle of these elements. The size is 0.57λ × 0.57λ × 0.013λ. Both antenna samples are tested to verify the design. Measurement results show that the working bandwidth is 2.45–14.88 GHz and 2.14–14.95 GHz, the isolation is greater than 17 and 20 dB, and the peak gain is 5.7 and 5.9 dBi for the two- and four-element MIMO antenna, respectively. Compared to the references, the designed antennas have a wider bandwidth and a higher gain and radiation efficiency. They are well-suited for diverse wireless applications.