bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reliability and Validity Analysis of Correlations on Strength and Consolidation Parameters for Ankara Clay and Proposal for a New Correlation
Authors: Tuc Ertac , Akbas Sami Oguzhan , Babagiray Gunes 
Published: June 2024

AbstractThis study aims to assess the accuracy and consistency of existing correlations between undrained shear strength (cu) and modulus of volumetric compressibility (mv) with SPT N value, and compression index (Cc) with index parameters for Turkish clays, with a specific focus on Ankara clay using laboratory testing of over 2500 high-quality undisturbed samples from 42 sites. A comparison of correlations for cu using five different statistical variables indicates that no single method stands out as superior in terms of both accuracy and conservatism and that the quality of the tests in the database has a significant impact on the correlation performance. Even the most effective correlation for cu appear insufficient for direct application in geotechnical design processes, given its low consistency characterized by coefficient of variations (COV) ranging between 50% and more than 100%. The widely used mv estimates proposed by Stroud (1974) were found to be notably unconservative when applied to Turkish clays. Consequently, a new trendline, leveraging both SPT N value and Plasticity Index (PI), was introduced to address this discrepancy. Meanwhile, an examination of 283 high-quality undisturbed samples from Ankara Clay revealed existing correlations between initial void ratio (e0) and compression index (Cc) to be conservative, yet consistently reliable. This underscores their suitability for routine or preliminary design applications. Notably, a newly derived correlation was proposed, which demonstrates equal applicability to the well-established Bowles (1979) equation.
A Hierarchical Parametric and Non-Parametric Forecasting Source Models with Uncertainties: 10 Years Ahead Prediction of Sources for Electric Energy Production
Authors: Balikçi Kemal 
Published: June 2024

AbstractLong-term accurate forecasting of the various sources for the electric energy production is challenging due to unmodelled dynamics and unexpected uncertainties. This paper develops non-parametric source models with higher-order polynomial bases to forecast the 16 sources utilized for the electric energy production. These models are optimized with the modified iterative neural networks and batch least squares, and their prediction performances are compared. In addition, for the first time in the literature, this paper quantifies the unseen uncertainties like the drought years and watery years affecting especially the hydropower and natural gas-based electric energy productions. These uncertainties are incorporated into the parametric imported-local source models whose unknown parameters are optimized with a modified constrained particle swarm optimization algorithm. These models are trained by using the real data for Türkiye, and the results are analysed extensively. Finally, 10 years ahead estimates of the 16 imported-local sources for the energy production have been obtained with the developed models.
Modelling attack and defense games in infrastructure networks with interval-valued intuitionistic fuzzy set payoffs
Authors: Dong Yibo , Liu Jin , Ren Jiaqi , Li Zhe , Li Weili 
Published: June 2024

AbstractInfrastructure networks are critical components of contemporary society, and numerous approaches have been suggested for the selection of strategies to protect these networks. However, for uncertain environments, research on attack and defense game models for infrastructure networks is limited. Therefore, after reviewing the existing approaches, a method based on interval-valued intuitionistic fuzzy set (IVIFS) theory is proposed for attack and defense games in critical infrastructure networks. First, we present the process of constructing the game model proposed in this paper, which mainly includes the formulation of the cost model, the strategies, and the method of generating IVIFS payoffs. Next, the Nash equilibria of the game are identified by a pair of nonlinear programming models based on IVIFS theory. Finally, experiments are conducted on a target scale-free network, and an investigation into the variation patterns of the Nash equilibria under different circumstances is also conducted. We provide explanations for these variation patterns by considering payoffs from the perspective of mathematical programming models. Furthermore, we find that compared to the existing attack and defense game model with crisp payoffs, the model proposed in this paper leads to superior Nash equilibria. Our work is a preliminary attempt to analyse attack and defense games for infrastructure networks based on IVIFS theory, providing a method for assessing payoffs in uncertain environments for the attacker and defender. This topic deserves further study.
Intelligent optimization of steam gasification catalysts for palm oil waste using support vector machine and adaptive transition marine predator algorithm
Authors: Guo Xin , Bouteraa Yassine , Khishe Mohammad , Li Cen , Martín Diego 
Published: June 2024

AbstractThe present study investigates the optimization of the steam gasification process for the conversion of palm oil waste into environmentally friendly energy, utilizing the catalytic properties of calcium oxide and coal bottom ash. The objective of our research is to investigate the enhancement of the conversion process by employing a machine-learning approach. Specifically, we utilize a support vector machine (SVM) to model and evaluate the impact of different operational parameters on the resulting gas mixture. One notable feature of this study involves the incorporation of an adaptive marine predator algorithm (AMPA) into the SVM framework, aiming to enhance the predicted precision and efficiency of the model. The primary focus of this study revolves around the development of an intelligent optimization framework that surpasses conventional machine learning techniques, hence providing a more dynamic and efficient strategy for process improvement. The SVM model’s performance, as assessed against experimental benchmarks, exhibits a notable degree of predictive accuracy and substantial concurrence with observed data. This increase in performance indicates that our methodology has the potential to make a significant contribution to the enhancement of renewable catalysts in gasification processes. The findings of this study could potentially have significant ramifications for the advancement of renewable energy production and the creation of intelligent systems in complicated industrial applications.
Approaching Ultimate Synthesis Reaction Rate of Ni-Rich Layered Cathodes for Lithium-Ion Batteries
Authors: Liu Zhedong , Zhang Jingchao , Luo Jiawei , Guo Zhaoxin , Jiang Haoran , Li Zekun , Liu Yuhang , Song Zijing , Liu Rui , Liu Wei-Di , Hu Wenbin , Chen Yanan 
Published: June 2024

AbstractNickel-rich layered oxide LiNixCoyMnzO2 (NCM, x + y + z = 1) is the most promising cathode material for high-energy lithium-ion batteries. However, conventional synthesis methods are limited by the slow heating rate, sluggish reaction dynamics, high energy consumption, and long reaction time. To overcome these challenges, we first employed a high-temperature shock (HTS) strategy for fast synthesis of the NCM, and the approaching ultimate reaction rate of solid phase transition is deeply investigated for the first time. In the HTS process, ultrafast average reaction rate of phase transition from Ni0.6Co0.2Mn0.2(OH)2 to Li- containing oxides is 66.7 (% s−1), that is, taking only 1.5 s. An ultrahigh heating rate leads to fast reaction kinetics, which induces the rapid phase transition of NCM cathodes. The HTS-synthesized nickel-rich layered oxides perform good cycling performances (94% for NCM523, 94% for NCM622, and 80% for NCM811 after 200 cycles at 4.3 V). These findings might also assist to pave the way for preparing effectively Ni-rich layered oxides for lithium-ion batteries.
Soil type and temperature determine soil respiration seasonal dynamics in dairy grassland
Authors: Liu Yulin , Zhang Jingjing , Bader Martin Karl-Friedrich , Leuzinger Sebastian 
Published: June 2024

Abstract

Soil respiration rates (Rs) were measured in New Zealand dairy grassland.

Both season and soil type significantly affected Rs.

Soil temperature and soil type dominated overall Rs.

Soil respiration (Rs), the CO2 release from root respiration and microbial metabolism, affects global soil carbon storage and cycling. Only few studies have looked at Rs in the southern hemisphere, especially regarding the interaction between soil type and environmental factors on Rs in dairy grassland. We investigated the relationship between Rs and soil temperature (Ts), soil water content (SWC), soil type, and other environmental factors based on summer and winter measurements at four sites in New Zealand. Across sites, soil respiration rates ranged from 0.29 to 14.58 with a mean of 5.38 ± 0.13 (mean ± standard error) µmol CO2 m−2 s−1. Mean summer Rs was 86.5% higher than mean winter Rs, largely driven by organic/gley and pumice soils while ultic soils showed very little seasonal temperature sensitivity. Overall mean Rs in organic/gley soils was 108.0% higher than that in ultic soils. The high Rs rate observed in organic/gley was likely due to high soil organic matter content, while low Rs in ultic and pallic soils resulted from high clay content and low hydraulic conductance. Soil temperature drove overall Rs. Our findings indicate that soil type and soil temperature together best explain Rs. This implies that a mere classification of land use type may be insufficient for global C models and should be supplemented with soil type information, at least locally.
Examination of wnt signaling mediated melanin transport and shell color formation in Pacific oyster (Crassostrea gigas)
Authors: Min Yue , Li Qi , Yu Hong , Du Shaojun 
Published: June 2024

AbstractMollusca exhibit remarkable diversity in shell coloration, attributed to the presence of melanin, a widely distributed pigment with various essential roles, such as mechanical strengthening, antioxidation and thermoregulation. However, the regulatory network governing melanogenesis and melanin transport in molluscs remains poorly understood. In this study, we conducted a systematic analysis of melanin distribution and transport in the Pacific oyster, utilizing light microscopy and high-resolution transmission electron microscopy. In addition, we characterized CgWnt1 and CgWnt2b-a in Crassostrea gigas, and analyzed Wnt signaling in melanocyte formation. Expression analysis revealed that these genes were predominantly expressed in the mantle of black-shelled individuals, particularly in the outer fold of the mantle. Furthermore, we employed RNA interference and inhibitors to specifically inhibit Wnt signaling in both in vivo and in vitro. The results revealed impaired melanogenesis and diminished tyrosinase activity upon Wnt signaling inhibition. These findings suggest the crucial role of Wnt ligands and downstream factors in melanogenesis. In summary, our study provides valuable insights into the regulatory mechanism of shell pigmentation in C. gigas. By demonstrating the promotion of melanogenesis through Wnt signaling modulation, we contribute to a better understanding of the complex processes underlying molluscan melanin production and shell coloration.
Star Generative Adversarial VGG Network-Based Sample Augmentation for Insulator Defect Detection
Authors: Zhang Linghao , Wang Luqing , Yan Zhijie , Jia Zhentang , Wang Hongjun , Tang Xinyu 
Published: June 2024

AbstractDeep learning-based automated detection of insulator defects in electric power systems is a critical technological challenge, pivotal for ensuring reliability and efficiency in the global energy infrastructure. However, the effectiveness of the deep learning model is severely compromised by the scarcity of defective insulator samples. To tackle this problem, the present study proposes a style transfer approach utilizing an improved Star Generative Adversarial Network 2 (StarGAN2) model to generate artificial samples of faulty insulators, which adeptly synthesizes artificial faulty insulator samples on a one-to-many basis, markedly diminishing the necessity for extensive empirical data collection. Through the integration of identity loss, the proposed model ensures the fidelity of content and the preservation of critical defect semantics. Additionally, the proposed model incorporates a pre-trained Visual Geometry Group (VGG) network and perceptual loss, thus improving the quality of generated samples without additional artificial labeling. Finally, various experiments are conducted to assess the quality and authenticity of the generated samples and their impact on the detection model. The results demonstrate that StarGAN2 could generate realistic insulator defect samples and improve the performance of defect detection models.
Workplace culture of health and employee physical activity: the moderating effects of gender and depression
Authors: Marenus Michele W. , Marzec Mary , Kilbourne Amy , Colabianchi Natalie , Chen Weiyun 
Published: June 2024

Abstract
Introduction
Promoting physical activity (PA) at work effectively decreases the risk of chronic disease and increases productivity. Despite the well-established benefits of PA, only 24% of adults meet the PA Guidelines for Americans. Advancing a culture of health (COH) may improve employees’ physical activity levels. The purpose of this study was to determine the effects of workplace culture of health, gender, and depression on employee physical activity.

Methods
Employees (n = 12,907) across 14 companies voluntarily completed the Workplace Culture of Health (COH) Scale, the Patient Health Questionnaire (PHQ-2), and questions on PA engagement. A logistic regression was performed to determine the effects of workplace COH, gender, and depression risk on the likelihood of engaging in 150 min of moderate to vigorous PA and in strength training 2 × per week.

Results
Workplace COH scores were associated with increased odds of PA engagement (OR = 1.058, p < 0.001). Further, gender and depression risk moderated the relationship between workplace COH and PA engagement (OR = 0.80, p = 0.026). For employees at risk for depression, an increase in COH scores was associated with higher PA for men, but not women. For employees not at risk for depression, an increase in COH scores was associated with higher PA for males and females.

Conclusion
Establishing a health-supportive workplace culture may increase PA, which is essential to improving population health. The differential findings by gender and depression risk illustrate the complexity of PA engagement.
Perspective: revisiting surface roughness in electrochemical machining and the paradoxes
Authors: Pan Shuaihang , Zhao Bo , Balaji A. K. , Qu Yongzhi , Yin Yingyue 
Published: June 2024

AbstractElectrochemical machining (ECM) represents a prominent electrochemistry-driven technique for surface flattening, post-processing, and (ultra-)precision machining, attracting considerable research interests recently. The method exhibits advantages in the machining of hard-to-machine nickel (Ni) superalloys, particularly those created via additive manufacturing approaches such as laser powder bed fusion (LPBF), in which enhanced microstructural features and mechanical properties are achieved with compromised surface quality. This study explores the intricate relationship between Ni alloy-specific microstructures, such as carbide precipitates, and the principles of electrochemistry integral to ECM. It further emphasizes the emerging requirement to re-examine the surface quality outcomes of ECM. We present a concise overview of the inherent paradoxes in ECM, encompassing the prediction of surface roughness range, the quantification of charge transfer coefficients, the efficiency of material removal, and the temporal dependence of the ECM process. These paradoxes necessitate systematic experimental and theoretical research to advance our understanding, and we wish to welcome, stimulate, and urge more raised awareness and attention to this matter about ECM surface quality control and prediction.
Relative Roles of Plume and Coastal Forcing on Exchange Flow Variability of a Glacial Fjord
Authors: Sanchez Robert , Straneo Fiammetta , Hughes Kenneth , Barbour Philip , Shroyer Emily 
Published: June 2024

AbstractGlacial fjord circulation determines the import of oceanic heat to the Greenland Ice Sheet and the export of ice sheet meltwater to the ocean. However, limited observations and the presence of both glacial and coastal forcing—such as coastal‐trapped waves—make uncovering the physical mechanisms controlling fjord‐shelf exchange difficult. Here we use multi‐year, high‐resolution, realistically forced numerical simulations of Sermilik Fjord in southeast Greenland to evaluate the exchange flow. We compare models, with and without a plume, to differentiate between the exchange flow driven by shelf variability and that driven by subglacial discharge. We use the Total Exchange Flow framework to quantify the exchange volume transports. We find that a decline in offshore wind stress from January through July drives a seasonal reversal in the exchange flow increasing the presence of warm Atlantic Water at depth. We also find that including glacial plumes doubles the exchange flow in the summer. Our results show that the plume‐driven circulation is more effective at renewal with a flushing time 1/3 that of the shelf‐driven circulation near the fjord head.
Phytoplankton Responses to Mesoscale and Submesoscale Processes in a Tropical Meander
Authors: Pereira Filipe , da Silveira Ilson C. A. , Tandon Amit , Franks Peter J. S. , Luko Caique D. , Santos Daniel M. C. , Pompeu Mayza , Michelazzo Luan S. , Chuqui Mateus G. , Brandini Frederico P. 
Published: June 2024

AbstractThe mesoscale activity of western boundary currents can induce changes in the oligotrophic conditions of the oceanic subtropical gyres. Off SE Brazil, recurrent meanders in the Brazil Current can modulate the pelagic ecosystem through eddy‐induced upwelling, as well as drive coastal upwelling and cross‐shelf exchanges. Despite their relevance, direct measurements of such meanders are scarce. At the end of the Spring of 2019, we acquired measurements of both physical and biogeochemical properties along a transect through one of these features, with 5–10 km spacing between stations. Displacements of the isopycnals at the meander edges arose from submesoscale filaments along the meander's rim, associated with the signature of shelf water masses. Chlorophyll distributions along the transect indicated phytoplankton responses to the different dynamic regimes in the meander: eddy stirring in the surface mixed layers versus eddy pumping in the subsurface waters, and mesoscale dynamics in the meander center versus submesoscale dynamics in its periphery. Subsurface phytoplankton biomass was enhanced in the meander center, likely due to eddy pumping raising the nutricline into the euphotic zone. Eddy pumping also appears to have contributed to a shift in the phytoplankton community composition to larger organisms. Our results indicate that the physical dynamics create different habitats across the meander, leading to spatial patchiness in the chlorophyll distributions, with different types of organisms in distinct parts of the meander.
Quantitative Assessment of Factors Contributing to Variations in Sea Surface pCO2 in the Pacific Sector of the Arctic Ocean
Authors: Tozawa Manami , Nomura Daiki , Matsuura Mirai , Hatta Mariko , Fujiwara Amane , Yasunaka Sayaka , Murata Akihiko 
Published: June 2024

AbstractTo quantitatively assess seasonal variations in the partial pressure of carbon dioxide (pCO2) in the Pacific sector of the Arctic Ocean (Canada Basin and Chukchi Sea) in 2021, water temperature, salinity, chlorophyll‐a, pCO2, dissolved inorganic carbon (DIC), total alkalinity (TA), and nutrients were measured. During summer 2021, surface water pCO2 in our study area (315 ± 41 μatm) was undersaturated with respect to the atmosphere (404 ± 4 μatm), and the ocean was a sink for atmospheric CO2 (−10.5 ± 11.0 mmol C m−2 day−1). Using DIC, TA, and nutrients in the temperature minimum layer, we estimated the under‐ice pCO2 in the water during the previous winter and calculated changes in pCO2 (δpCO2) due to temperature changes, freshwater inflow, biological activity, and other factors (gas exchange and advection) from winter to summer. In the Chukchi Sea, biological activity and temperature changes had significant impacts on pCO2, whereas in the Canada Basin, the influx of freshwater caused a significant decrease in pCO2. Our results suggested that different types of freshwaters had different effects on pCO2, with sea ice meltwater having a greater effect on reducing pCO2 than river water or snowmelt water. We therefore emphasize the importance of freshwater type and proportion, as well as freshwater supply, for prediction of future pCO2 changes.
Unusually high thermal conductivity in suspended monolayer MoSi2N4
Authors: He Chengjian , Xu Chuan , Chen Chen , Tong Jinmeng , Zhou Tianya , Sun Su , Liu Zhibo , Cheng Hui-Ming , Ren Wencai 
Published: June 2024

AbstractTwo-dimensional semiconductors with high thermal conductivity and charge carrier mobility are of great importance for next-generation electronic and optoelectronic devices. However, constrained by the long-held Slack’s criteria, the reported two-dimensional semiconductors such as monolayers of MoS2, WS2, MoSe2, WSe2 and black phosphorus suffer from much lower thermal conductivity than silicon (~142 W·m–1·K–1) because of the complex crystal structure, large average atomic mass and relatively weak chemical bonds. Despite the more complex crystal structure, the recently emerging monolayer MoSi2N4 semiconductor has been predicted to have high thermal conductivity and charge carrier mobility simultaneously. In this work, using a noncontact optothermal Raman technique, we experimentally measure a high thermal conductivity of ~173 W·m–1·K–1 at room temperature for suspended monolayer MoSi2N4 grown by chemical vapor deposition. First-principles calculations reveal that such unusually high thermal conductivity benefits from the high Debye temperature and small Grüneisen parameter of MoSi2N4, both of which are strongly dependent on the high Young’s modulus induced by the outmost Si-N bilayers. Our study not only establishes monolayer MoSi2N4 as a benchmark 2D semiconductor for next-generation electronic and optoelectronic devices, but also provides an insight into the design of 2D materials for efficient heat conduction.
Single-cell analysis reveals a subpopulation of adipose progenitor cells that impairs glucose homeostasis
Authors: Wang Hongdong , Du Yanhua , Huang Shanshan , Sun Xitai , Ye Youqiong , Sun Haixiang , Chu Xuehui , Shan Xiaodong , Yuan Yue , Shen Lei , Bi Yan 
Published: June 2024

AbstractAdipose progenitor cells (APCs) are heterogeneous stromal cells and help to maintain metabolic homeostasis. However, the influence of obesity on human APC heterogeneity and the role of APC subpopulations on regulating glucose homeostasis remain unknown. Here, we find that APCs in human visceral adipose tissue contain four subsets. The composition and functionality of APCs are altered in patients with type 2 diabetes (T2D). CD9+CD55low APCs are the subset which is significantly increased in T2D patients. Transplantation of these cells from T2D patients into adipose tissue causes glycemic disturbance. Mechanistically, CD9+CD55low APCs promote T2D development through producing bioactive proteins to form a detrimental niche, leading to upregulation of adipocyte lipolysis. Depletion of pathogenic APCs by inducing intracellular diphtheria toxin A expression or using a hunter-killer peptide improves obesity-related glycemic disturbance. Collectively, our data provide deeper insights in human APC functionality and highlights APCs as a potential therapeutic target to combat T2D. All mice utilized in this study are male.