bluuebunny/crossref_metadata_2025_split huggingface dataset:
2D Tantalum Disulfide Reduction Strategy Customized Ta2O5/rGO Heterointerface Aerogel Toward Boosting Electromagnetic Wave Absorption and Flame Retardancy
Authors: Deng Fukang , Zhang Zhen , Xu Xinyun , Tian Dingkun , Duan Yingjie , Lu Xi , Xu Yadong , Wan Yanjun , Lin Zhiqiang , Hu Yougen , Sun Rong 
Published: June 2024

AbstractThe exceptional and substantial electron affinity, as well as the excellent chemical and thermal stability of transition metal oxides (TMOs), infuse infinite vitality into multifunctional applications, especially in the field of electromagnetic wave (EMW) absorption. Nonetheless, the suboptimal structural mechanical properties and absence of structural regulation continue to hinder the advancement of TMOs‐based aerogels. Herein, a novel 2D tantalum disulfide (2H‐TaS2) reduction strategy is demonstrated to synthesize Ta2O5/reduced graphene oxide (rGO) heterointerface aerogels with unique characters. As the prerequisite, the defects, interfaces, and configurations of aerogels are regulated by varying the concentration of 2H‐TaS2 to ensure the Ta2O5/rGO heterointerface aerogels with appealing EMW absorption properties such as a minimum reflection loss (RLmin) of −61.93 dB and an effective absorption bandwidth (EAB) of 8.54 GHz (7.80−16.34 GHz). This strategy provides valuable insights for designing advanced EMW absorbers. Meanwhile, the aerogel exhibits favorable thermal insulation performance with a value of 36 mW m−1 K−1, outstanding fire resistance capability, and exceptional mechanical energy dissipation performance, making it promising for applications in the aerospace industry and consumer electronics devices.
In Situ Array Microextraction and Metabolic Profiling of Small Extracellular Vesicles to Guide and Monitor Maternal Delivery
Authors: Yang Chenyu , Li Ning , Chen Haolin , Zhang Man , Chen Yijie , Zhang Xiangmin , Huang Shaoqiang , Sun Nianrong , Deng Chunhui 
Published: June 2024

AbstractThe advantages of small extracellular vesicles (sEV) in disease management have become increasingly prominent, with the main challenge lying in meeting the demands of large‐scale extraction and high‐throughput analysis, a crucial aspect in the realm of precision medicine. To overcome this challenge, an engineered on‐plate aptamer array (16×24 spots) is developed for continuous scale‐up microextraction of plasma sEV and their in situ metabolic analysis using mass spectrometry. With this integrated array strategy, metabolic profiles of sEV are acquired from the plasma of 274 antenatal or postpartum women, reducing analysis time by half (7.5 h) and sample volume by 95% (only 0.125 µL usage) compared to the traditional suspension method. Moreover, using machine learning algorithms on sEV metabolic profiles, a risk score system is constructed that accurately assesses the need for epidural analgesia during childbirth and the likelihood of post‐administration fever. The system, based on admission samples, achieves an impressive 94% accuracy. Furthermore, post‐administration fever can be identified from delivery samples, reaching an overall accuracy rate of 88%. This work offers real‐time monitoring of the childbirth process that can provide timely guidance for maternal delivery, underscoring the significance of sEV detection in large‐scale clinical samples for medicine innovation and advancement.
Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach.
Authors: Leumbe Fabrice Moudjieu , Mortier Frédéric , Takam Patrice Soh , Picard Nicolas , Félix Allah‐Barem , Fidèle Baya , Tadesse Mahlet G. , Rossi Vivien 
Published: June 2024

SummaryThe understanding of tree growth processes is crucial for promoting sustainable forest management strategies. This is a challenging task in highly biodiverse ecosystems where many tree species are observed on very few individuals and the small sample sizes hinder a good fit of species‐specific models. We propose the use of finite mixture of random coefficient regression models with multilevel nested random effects to infer guild specific fixed and random effects while evaluating the relative importance of the nested sources of variability on goodness‐of‐fit. This approach extends finite mixture of linear mixed model used for longitudinal or single group structured data contexts. A dedicated expectation–maximisation algorithm is introduced for parameter estimation. Simulations are performed for the evaluation of the misspecification of nested‐grouping structures. This work has been motivated by data collected biennially in Central African rainforests from 1986 to 2010. We show the accuracy of the proposed approach in successfully reproducing individual growth processes and classifying tree species into well‐differentiated clusters with clear ecological interpretations. Moreover, results confirm that interindividual variability appears as the most important factor to explain tropical tree species growth process variability from Central Africa forests.
Mechanical properties of steel fiber RPC, basalt fiber RPC, and hybrid fiber RPC: A review of research progress
Authors: Li Fangyuan , Guo Zhenwei , Wu Peifeng 
Published: June 2024

AbstractBased on an analysis of the literature on fiber‐reinforced concrete (FRC), especially the development and formation of various types of FRC combined with reactive powder concrete (RPC) in recent years, this paper systematically expounds the research progress, particularly the mechanical properties, of steel fiber RPC, basalt fiber RPC and hybrid fiber RPC. This paper concludes the improvement in the mechanical properties of RPC under common curing methods, elaborates on the influence of steel fiber on the compressive, tensile, and flexural strength of RPC, and outlines the principle of fiber enhancing the mechanical properties of RPC. Additionally, it discusses the research progress in basalt FRC, and further examines the impact of basalt fiber on the mechanical properties of RPC. Referring to the research on single fiber reinforced RPC, the mechanical properties of hybrid fiber RPC are analyzed and summarized; based on the characteristics of steel fiber and basalt fiber, research on steel‐basalt hybrid fiber RPC is proposed.
Properties of set-valued Young integrals and Young differential inclusions generated by sets of Hölder functions
Authors: Michta Mariusz , Motyl Jerzy 
Published: June 2024

AbstractThe present studies concern properties of set-valued Young integrals generated by families of $$\beta $$
β
-Hölder functions and differential inclusions governed by such a type of integrals. These integrals differ from classical set-valued integrals of set-valued functions constructed in an Aumann’s sense. Integrals and inclusions considered in the manuscript contain as a particular case set-valued integrals and inclusions driven by a fractional Brownian motion. Our study is focused on topological properties of solutions to Young differential inclusions. In particular, we show that the set of all solutions is compact in the space of continuous functions. We also study its dependence on initial conditions as well as properties of reachable sets of solutions. The results obtained in the paper are finally applied to some optimality problems driven by Young differential inclusions. The properties of optimal solutions and their reachable sets are discussed.
AI in situated action: a scoping review of ethnomethodological and conversation analytic studies
Authors: Mlynář Jakub , de Rijk Lynn , Liesenfeld Andreas , Stommel Wyke , Albert Saul 
Published: June 2024

AbstractDespite its elusiveness as a concept, ‘artificial intelligence’ (AI) is becoming part of everyday life, and a range of empirical and methodological approaches to social studies of AI now span many disciplines. This article reviews the scope of ethnomethodological and conversation analytic (EM/CA) approaches that treat AI as a phenomenon emerging in and through the situated organization of social interaction. Although this approach has been very influential in the field of computational technology since the 1980s, AI has only recently emerged as such a pervasive part of daily life to warrant a sustained empirical focus in EM/CA. Reviewing over 50 peer-reviewed publications, we find that the studies focus on various social and group activities such as task-oriented situations, semi-experimental setups, play, and everyday interactions. They also involve a range of participant categories including children, older participants, and people with disabilities. Most of the reviewed studies apply CA’s conceptual apparatus, its approach to data analysis, and core topics such as turn-taking and repair. We find that across this corpus, studies center on three key themes: openings and closing the interaction, miscommunication, and non-verbal aspects of interaction. In the discussion, we reflect on EM studies that differ from those in our corpus by focusing on praxeological respecifications of AI-related phenomena. Concurrently, we offer a critical reflection on the work of literature reviewing, and explore the tortuous relationship between EM and CA in the area of research on AI.
We’re only human after all: a critique of human-centred AI
Authors: Ryan Mark 
Published: June 2024

AbstractThe use of a ‘human-centred’ artificial intelligence approach (HCAI) has substantially increased over the past few years in academic texts (1600 +); institutions (27 Universities have HCAI labs, such as Stanford, Sydney, Berkeley, and Chicago); in tech companies (e.g., Microsoft, IBM, and Google); in politics (e.g., G7, G20, UN, EU, and EC); and major institutional bodies (e.g., World Bank, World Economic Forum, UNESCO, and OECD). Intuitively, it sounds very appealing: placing human concerns at the centre of AI development and use. However, this paper will use insights from the works of Michel Foucault (mostly The Order of Things) to argue that the HCAI approach is deeply problematic in its assumptions. In particular, this paper will criticise four main assumptions commonly found within HCAI: human–AI hybridisation is desirable and unproblematic; humans are not currently at the centre of the AI universe; we should use humans as a way to guide AI development; AI is the next step in a continuous path of human progress; and increasing human control over AI will reduce harmful bias. This paper will contribute to the field of philosophy of technology by using Foucault's analysis to examine assumptions found in HCAI [it provides a Foucauldian conceptual analysis of a current approach (human-centredness) that aims to influence the design and development of a transformative technology (AI)], it will contribute to AI ethics debates by offering a critique of human-centredness in AI (by choosing Foucault, it provides a bridge between older ideas with contemporary issues), and it will also contribute to Foucault studies (by using his work to engage in contemporary debates, such as AI).
Assessing the eco-environmental aspects of fossil fuels-based units substitution of Point Aconi thermal power plant by green-based energies: a case study of Canada
Authors: Amiri Nima , Shaterabadi Mohammad , Ben-Brahim Lazhar , Ahmadi Jirdehi Mehdi 
Published: June 2024

Abstract
Canada possesses significant potential in harnessing renewable energy from its vast and diverse geography, which can generate clean electricity. This paper presents a model that replaces fossil fuels used in a proposed thermal power plant in Point Aconi, Nova Scotia, with photovoltaic and wind turbine units based on the region’s climate conditions. The research results are based on evaluating multiple thermal power plants worldwide and examining various wind turbines and PV panels from different companies to ensure accuracy. The chosen units that best suit the location’s geographical and biological conditions, transmission, and operation costs demonstrate that the power plant currently consumes approximately 47 tons of coal and petroleum coke per hour. Replacing these materials with the proposed green units makes it possible to reduce environmental pollution by eliminating almost 165 tons of CO2 and other pollutants per hour while increasing the plant’s efficiency and independence from fossil fuel price variations. The presented structure’s ROI is approximately 20 years, which is reasonable compared to the economic and environmental benefits of utilizing such a structure and converting the thermal power plant to green units.
Newton strata in Levi subgroups
Authors: Schremmer Felix 
Published: June 2024

AbstractCertain Iwahori double cosets in the loop group of a reductive group, known under the names of P-alcoves or $$(J,w,\delta )$$

(
J
,
w
,
δ
)

-alcoves, play an important role in the study of affine Deligne–Lusztig varieties. For such an Iwahori double coset, its Newton stratification is related to the Newton stratification of an Iwahori double coset in a Levi subgroup. We study this relationship further, providing in particular a bijection between the occurring Newton strata. As an application, we prove a conjecture of Dong-Gyu Lim, giving a non-emptiness criterion for basic affine Deligne–Lusztig varieties.
The research on the effect of dynamic tilt variation on the phase of cold atomic gravimeter
Authors: Chen Peijun , Zhou Yin , Zhu Dong , Wang Kainan , Zhang Chan , Peng Shuping , Cheng Bing , Wu Bin , Lin Qiang 
Published: June 2024

AbstractIn recent years, absolute gravity comparison experiments between cold atomic gravimeter and traditional gravimeter have been carried out by combining cold atomic gravimeter with stable platform. Due to the working characteristics of the stable platform, the tilt angle of the cold atomic gravimeter will change slightly in the process of dynamic measurement, and the measurement noise will be introduced. In order to improve the accuracy of dynamic measurement, this paper first analyzes the trajectory of the mirror and atom in the atomic gravimeter combined with carrier motion information, obtains the phase expression of the atomic interferometer using the translation and rotation matrix, evaluates the main terms of the gravity deviation using the 20-min navigation data on the ship in the South China Sea, and simplifies the higher-order small-terms in the main terms to deduce the simplified form of the gravity deviation. Then, the Fourier transform is used to transform the simplified expression into the power spectrum expression of phase noise, the corresponding noise sensitivity function is used in the form of trigonometric. The 20-min data is divided into 10 intervals, the root-mean-square (RMS) value of the overall gravity deviation is 1.5–3 mGal using the power spectrum of the platform angle, angular velocity and carrier acceleration in each interval. The variation fluctuation of the RMS value is consistent with the fluctuation of solving the gravity deviation through the trajectory. The conclusion provides the calculation method of gravity noise caused by dynamic tilt change and horizontal acceleration, and also provides the basis for platform design.
Exploring GZMK as a prognostic marker and predictor of immunotherapy response in breast cancer: unveiling novel insights into treatment outcomes
Authors: Li Zitao , Xie Qiqi , Zhao Fuxing , Huo Xinfa , Ren Dengfeng , Liu Zhilin , Zhou Xiaofeng , Shen Guoshuang , Zhao Jiuda 
Published: June 2024

Abstract
Background
Granzyme K (GZMK) is a crucial mediator released by immune cells to eliminate tumor cells, playing significant roles in inflammation and tumorigenesis. Despite its importance, the specific role of GZMK in breast cancer and its mechanisms are not well understood.

Methods
We utilized data from the TCGA and GEO databases and employed a range of analytical methods including GO, KEGG, GSEA, ssGSEA, and PPI to investigate the impact of GZMK on breast cancer. In vitro studies, including RT-qPCR, CCK-8 assay, cell cycle experiments, apoptosis assays, Celigo scratch assays, Transwell assays, and immunohistochemical methods, were conducted to validate the effects of GZMK on breast cancer cells. Additionally, Cox regression analysis integrating TCGA and our clinical data was used to develop an overall survival (OS) prediction model.

Results
Analysis of clinical pathological features revealed significant correlations between GZMK expression and lymph node staging, differentiation grade, and molecular breast cancer subtypes. High GZMK expression was associated with improved OS, progression-free survival (PFS), and recurrence-free survival (RFS), as confirmed by multifactorial Cox regression analysis. Functional and pathway enrichment analyses of genes positively correlated with GZMK highlighted involvement in lymphocyte differentiation, T cell differentiation, and T cell receptor signaling pathways. A robust association between GZMK expression and T cell presence was noted in the breast cancer tumor microenvironment (TME), with strong correlations with ESTIMATEScore (Cor = 0.743, P < 0.001), ImmuneScore (Cor = 0.802, P < 0.001), and StromalScore (Cor = 0.516, P < 0.001). GZMK also showed significant correlations with immune checkpoint molecules, including CTLA4 (Cor = 0.856, P < 0.001), PD-1 (Cor = 0.82, P < 0.001), PD-L1 (Cor = 0.56, P < 0.001), CD48 (Cor = 0.75, P < 0.001), and CCR7 (Cor = 0.856, P < 0.001). Studies indicated that high GZMK expression enhances patient responsiveness to immunotherapy, with higher levels observed in responsive patients compared to non-responsive ones. In vitro experiments confirmed that GZMK promotes cell proliferation, cell division, apoptosis, cell migration, and invasiveness (P < 0.05).

Conclusion
Our study provides insights into the differential expression of GZMK in breast cancer and its potential mechanisms in breast cancer pathogenesis. Elevated GZMK expression is associated with improved OS and RFS, suggesting its potential as a prognostic marker for breast cancer survival and as a predictor of the efficacy of immunotherapy.
Early periodontal wound healing after chlorhexidine rinsing: a randomized clinical trial
Authors: Graziani Filippo , Izzetti Rossana , Perić Marina , Marhl Urška , Nisi Marco , Gennai Stefano 
Published: June 2024

Abstract
Objectives
This single-center randomized, parallel design, clinical trial with a 2-week follow-up involved patients affected by periodontitis undergoing periodontal surgery. The aim was to evaluate periodontal surgical wound healing with the use of chlorhexidine-based mouth rinses versus an untreated control group.

Materials and methods
Periodontal surgery was performed following a standardized protocol. Patients were randomly prescribed i) chlorhexidine (CHX) + anti-discoloration system (ADS) + hyaluronic acid (HA), ii) CHX + ADS or iii) no treatment (control group). Plaque score, gingival inflammation, and Early Healing Index (EHI), assessing the degree of wound closure and the presence of fibrin and necrosis, were evaluated at 3, 7 and 14 days after surgery.

Results
In total, 33 patients were enrolled. Patients were comparable at baseline for all measured clinical parameters. At 3-days wound healing was significantly improved in all patients treated with CHX + ADS-based mouth rinses with a lower EHI score at the interdental papillae compared with control group (p < 0.01). CHX + ADS + HA group presented improved healing across all time points in terms of EHI, plaque containment, and gingival inflammation when compared to control group (p < 0.01).

Conclusions
The usage of CHX-ADS following periodontal surgery improved early wound healing, reduced plaque accumulation and gingival inflammation. During the early post-operative period the adjunct of HA further improved soft tissue closure.

Clinical relevance
This study aims at evaluating the response of gingival tissues to mouth rinsing with chlorhexidine and anti-discoloration system (CHX + ADS) or CHX + ADS + hyaluronic acid (CHX + ADS + HA) versus no rinse in terms of healing of the periodontal surgical wound. CHX + ADS mouth rinses enhanced early soft tissue closure after periodontal surgery and contributed to the reduction in plaque accumulation and gingival inflammation. The adjunct of HA may be beneficial especially in the early post-operative period. CHX + ADS administration following periodontal surgery may improve soft tissue healing in the first two post-operative weeks.
Prediction of residual stress depth profiles in case-carburized gears
Authors: Müller Daniel , Tobie Thomas , Stahl Karsten 
Published: June 2024

AbstractResidual stresses have a significant influence on the load carrying capacity of gears. High near-surface compressive residual stresses can increase pitting strength and tooth root bending strength up to 50%. Tooth flank fracture (TFF) is a gear fatigue failure mode, which is in contrast to pitting or tooth root breakage not initiated at the surface or close to the surface but in larger material depths beneath the active gear flank. Therefore, the residual stresses in larger material depths are decisive for TFF. In these larger material depths, the residual stress conditions are almost unknown up to now. It is assumed that tensile residual stresses are present in these areas, which can negatively influence the TFF load carrying capacity. So far, no validated methods are known to estimate or predict these tensile residual stresses. As a result, the tensile residual stresses could not be considered in the calculation methods for the risk of TFF at all until recently.This paper presents a method to predict the residual stresses in case-carburized gears based on comprehensive numerical simulations of case-carburizing processes of different-sized gears. The calculated residual stress profiles also consider the tensile residual stresses in larger material depths.
Guiding real-world reinforcement learning for in-contact manipulation tasks with Shared Control Templates
Authors: Padalkar Abhishek , Quere Gabriel , Raffin Antonin , Silvério João , Stulp Freek 
Published: June 2024

AbstractThe requirement for a high number of training episodes has been a major limiting factor for the application ofReinforcement Learning(RL) in robotics. Learning skills directly on real robots requires time, causes wear and tear and can lead to damage to the robot and environment due to unsafe exploratory actions. The success of learning skills in simulation and transferring them to real robots has also been limited by the gap between reality and simulation. This is particularly problematic for tasks involving contact with the environment as contact dynamics are hard to model and simulate. In this paper we propose a framework which leverages a shared control framework for modeling known constraints defined by object interactions and task geometry to reduce the state and action spaces and hence the overall dimensionality of the reinforcement learning problem. The unknown task knowledge and actions are learned by a reinforcement learning agent by conducting exploration in the constrained environment. Using a pouring task and grid-clamp placement task (similar to peg-in-hole) as use cases and a 7-DoF arm, we show that our approach can be used to learn directly on the real robot. The pouring task is learned in only 65 episodes (16 min) and the grid-clamp placement task is learned in 75 episodes (17 min) with strong safety guarantees and simple reward functions, greatly alleviating the need for simulation.