bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of the cooling time t8/5 on weld metals
Authors: Rust Brian , Schmidt Jan , Stroetmann Richard 
Published: January 2025

Abstract
The increasing use of high-strength steels in construction has raised the importance of high-strength filler materials. Therefore, precise control of the mechanical properties of these fillers is crucial, as their strength often closely matches that of the base material. Heat input during welding can weaken slightly overmatched joints, turning them undermatched and compromising the safety of the welded component. In this context, the ongoing AiF-FOSTA research project P1453 investigates the impact of cooling time t
8/5 on the mechanical properties of weld metals in gas-shielded metal arc welding. Furthermore, the introduction of the new Eurocode 3 Part 1–8 allows the consideration of the nominal tensile strength of the filler material for fillet and butt welds, directly affecting the design resistance of the welded joint and increasing the importance of the filler material’s tensile strength. Experimental characterizations of filler materials G62 and G89 on new centric drilled flat tensile specimens highlight the correlation between tensile strength and cooling time. The study reveals that the standardized tensile strength requirements for filler materials of strength classes G79 were not reliably met for cooling times of 7.5 s and beyond. Moreover, the study indicates that the filler material E89 consistently fails to meet the specified minimum tensile strength requirements by 5%. However, filler materials such as G35, G42, G62, and G69 consistently comply with normative standards. These results emphasize the critical need to consider welding parameters, particularly cooling time, to ensure weld quality and structural integrity.
SOLFA study: a multicenter, open-label, prospective, randomized study to investigate the clotting propensity of asymmetric cellulose triacetate membrane compared to synthetic membranes in on line HDF
Authors: Puerta Marta , Jaldo María Teresa , Muñoz Patricia , Martínez-Miguel Patricia , Maduell Francisco , Lancho Carolina , García-Herrera Antonio Luis , Eloot Sunny , de Sequera Patricia 
Published: January 2025

Abstract

Background
Performing hemodialysis without heparin is still challenging. The objective of the present work was to evaluate the impact on thrombogenicity of the hemodialysis circuit using synthetic membranes compared to the asymmetric cellulose triacetate (ATA) membrane.

Methods
Prospective, multicenter, randomized, crossover, open-label study. In each of the two phases of the study, six consecutive hemodialysis sessions were performed over two weeks, in which the patients were dialyzed with the dialyzer randomly assigned (synthetic vs asymmetric cellulose triacetate membrane). During the six sessions of both phases, the heparin dose was progressively reduced from the full usual heparin dose in the first session to zero heparin in the sixth session. After each session, visual inspection of the venous chamber and dialyzer was performed, and a coagulation score was assigned. A micro- computed tomography (CT) scanning of some dialyzers was also executed at Ghent University.

Results
Comparison of the last completed sessions shows that there were significant differences depending on the dialyzer used: 60% of dialysis sessions with asymmetric cellulose triacetate could be completed without heparin versus 24% with synthetic membranes (p = 0.01). We also found differences in the number of sessions completed: 46% with the asymmetric cellulose triacetate membrane and 7% with the synthetic membrane (p = 0.001). The results obtained with the micro-CT analysis were also better with the asymmetric cellulose triacetate.

Conclusions
Our findings strongly suggest that asymmetric cellulose triacetate membranes may be useful in situations in which dialysis should be performed without heparin or with low-dose heparins.

Trail registry
NCT06505616.

Graphical abstract
Mobility of Sediment and Phosphorus in a Small Stream During Artificial Flood Wave
Authors: Neumann Martin , Jáchymová Barbora , Koudelka Petr , Dostál Tomáš , Bauer Miroslav , Krása Josef , Laburda Tomáš , Rosendorf Pavel , Fiala Daniel , Bynum Karina , Schwartz John S. , Zumr David 
Published: January 2025

Abstract
This study investigates the dynamics of sediment and phosphorus transport in small streams affected by recurrent flood waves. The experiments were carried out in two streams with contrasting conditions: one in an agricultural headwater section, which serves as a sediment source, and the other in a mid-water section influenced by fish ponds. High-frequency data on suspended sediment and phosphorus concentrations were collected during several flood waves to assess how floods affect the transport regime, including the role of small reservoirs. The results showed that even initially clear water can mobilize significant amounts of sediment from the riverbed when discharge increases. Sediment mobilization was strongest at the beginning of the flood wave, with concentrations peaking early and then decreasing. Successive floods without additional sediment input led to a decrease in sediment concentrations, as the stream had already flushed out the available sediments. Hysteresis loops showed that most of the sediment transport occurred during the rising part of the flood wave, indicating that the sediment originated from the nearby streambed areas. Phosphorus was mobilized simultaneously with the sediment, and an almost linear relationship was observed between sediment concentration and total phosphorus (r = 0.979, p < 0.0001). However, only a fraction of the phosphorus was dissolved, so most of the phosphorus was bound to the sediment particles. Soluble reactive phosphorus showed a weaker correlation with sediment concentration (r = 0.272, p = 0.047). This shows how important it is to consider both sediment dynamics and phosphorus mobilization in event-based flood models.
High-resolution characterization of complex groundwater systems using wireline logs analyzed with machine learning classifiers and isometric mapping techniques
Authors: Mohammed Musaab A. A. , Szabó Norbert P. , Szűcs Péter 
Published: January 2025

Abstract
Characterizing the lithological and hydraulic behavior of heterogeneous groundwater systems presents a significant challenge in hydrogeology. Traditional methods often rely on sparse data points that lead to inaccurate representations of the complex systems. This study presents an innovative approach to the characterization of the heterogeneous groundwater systems using wireline logs analyzed by machine learning (ML) techniques to infer the lithological variations and estimate aquifer parameters within the Quaternary aquifer system in the Debrecen area, Eastern Hungary. Initially, Manhattan distance-based k-means analysis as an outliers-resistance clustering method is employed to identify distinct lithological clusters based on the well logs responses. The results of the k-means clustering were then used to train ML classifiers including linear discriminant analysis, gradient boosting, random forest, and support vector machine for automated mapping of the lithofacies distribution. Additionally, the study introduced the first application of isometric map (IsoMap) to estimate the shale content and hydraulic conductivity within the aquifer system. The IsoMapping extracts latent components that capture essential features of the wireline logs and correlate them to the aquifer parameters. The regression between the latent component and the deterministically estimated shale volume and hydraulic conductivity showed significant exponential relationships resulting in universal equations that can be used independently to estimate these parameters. For more robust estimation, genetic algorithm global optimization was applied to refine the regression parameters governing these relationships to overcome the limitations associated with linearized estimations. The proposed approach provided a fast, automated, and effective alternative for characterizing heterogeneous groundwater, offering reliable inputs for groundwater flow and contaminant transport models.
A comparison of confidence interval methods for the intraclass correlation coefficient based on the one-way random effects model
Authors: Ohyama Tetsuji 
Published: January 2025

Abstract
Intraclass correlation coefficients are widely used not only in medicine but also in various other fields. This study focuses on the intraclass correlation coefficient based on the one-way random effects model. We review the methods for constructing confidence intervals and compare their performance through simulations. Donner and Wells (Biometrics 42:401–412, 1986) and Ukoumunne (Stat Med 21(24):3757–3774, 2002) conducted simulation studies to compare some methods. However, in this study, we also include methods developed after their studies. These include a method based on the nonparametric bootstrap by Ukoumunne et al. (Stat Med 22(24):3805–3821, 2003), a method based on the restricted maximum likelihood (REML) by Burch (Comput Stat Data Anal 55(2):1018–1028, 2011), and a method based on the beta distribution by Demetrashvili et al. (Stat Methods Med Res 25(5):2359–2376, 2016). Our simulations reveal that under the normality of random effects and errors, the REML-based method performs best overall in terms of coverage probability of confidence intervals, upper and lower error rates, and mean interval width.
Design, Fabrication and Characterization of L&T Hybrid Mode Transducers for Thermoplastic Welding
Authors: Ergun Celaletdin , Sezer Semih 
Published: January 2025

Abstract

Objectives
This study aims to present a systematic approach for designing, fabricating and characterizing ultrasonic transducers for thermoplastic sheet welding capable of operating in longitudinal–torsional (L&T) hybrid vibration modes at 20 kHz, driven by an axially poled piezoceramic stack.

Methods
Multiple horn models featuring circumferential deep helical grooves were designed to generate longitudinal and torsional vibratory displacements. Modal analyses were conducted to determine the appropriate dimensions for the desired mode shape and resonance frequency. The selected horn geometries were integrated with transducer bodies in a CAD environment to build 3D models of ultrasonic transducers. Modal and harmonic analyses were performed to evaluate their mode shapes, resonance frequencies, and displacement amplitudes under various excitation conditions. Prototypes of the optimized designs were fabricated using predetermined materials and geometries and characterized experimentally for resonance frequencies and tip displacements. The experimental results were compared with numerical analyses to validate the approach.

Results
The developed transducers demonstrated successful operation in L&T hybrid vibration modes at the targeted frequency, with displacement amplitudes and resonance frequencies aligning well with the numerical predictions. Combining exponential area reduction and helical grooves in the horn appears to be a highly effective method for achieving longitudinal-torsional vibration from a longitudinally vibrating transducer. Finite element analysis proved to be a valuable design tool, facilitating accurate dimensional optimization of the horns to achieve the desired L & T hybrid vibrational mode shapes. The apparent longitudinal and torsional (spring) stiffness of the horn significantly influences the longitudinal displacement amplitude and angular displacement at the horn tip. The resonance frequency of the transducers shifted to higher frequencies with increasing excitation voltage.

Conclusion
This research provides a comprehensive and validated framework for designing ultrasonic transducers capable of operating in hybrid vibration modes. The methodology reliably achieved the desired vibratory performance, with prototype results aligning closely with design objectives.
A Two-way Crossed Effects Fuzzy Panel Linear Regression Model
Authors: Hesamian Gholamreza , Johannssen Arne 
Published: January 2025

Abstract
Over the last two decades, the panel data model has become a focus of applied research. While there are numerous proposals for soft regression models in the literature, only a few linear regression models have been proposed based on fuzzy panel data. However, these models have serious limitations. This study is an attempt to propose a kind of two-way fuzzy panel regression model with crossed effects, fuzzy responses and crisp predictors to overcome the shortcomings of these models in real applications. The corresponding parameter estimation is provided based on a three-step procedure. For this purpose, the conventional least absolute error technique is employed. Two real data sets are analyzed to investigate the fitting and predictive capabilities of the proposed fuzzy panel regression model. These real data applications demonstrate that our proposed model has good fitting accuracy and predictive performance.
Machine learning and uncertainty quantification to track and monitor natural frequencies in vibration-based SHM applied to offshore wind turbines
Authors: Weil Maximillian , Sastre Jurado Carlos , Weijtjens Wout , Devriendt Christof 
Published: January 2025

Abstract
Vibration-based structural health monitoring (SHM) of (large) infrastructure through operational modal analysis (OMA) is a commonly adopted strategy. This is typically a four-step process, comprising estimation, tracking, data normalization, and decision-making. These steps are essential to ensure structural modes are correctly identified, and results are normalized for environmental and operational variability (EOV). Other challenges, such as nonstructural modes in the OMA, for example, rotor harmonics in (offshore) wind turbines (OWTs), further complicate the process. Typically, these four steps are considered independently, making the method simple and robust, but rather limited in challenging applications, such as OWTs. Therefore, this study aims to combine tracking, data normalization, and decision-making through a single machine learning (ML) model. The presented SHM framework starts by identifying a “healthy” training dataset, representative of all relevant EOV, for all structural modes. Subsequently, operational and weather data are used for feature selection and a comparative analysis of ML models, leading to the selection of tree-based learners for natural frequency prediction. Uncertainty quantification (UQ) is introduced to identify out-of-distribution instances, crucial to guarantee low modeling error and ensure only high-fidelity structural modes are tracked. This study uses virtual ensembles for UQ through the variance between multiple truncated submodel predictions. Practical application to monopile-supported OWT data demonstrates the tracking abilities, separating structural modes from rotor dynamics. Control charts show improved decision-making compared to traditional reference-based methods. A synthetic dataset further confirms the approach’s robustness in identifying relevant natural frequency shifts. This study presents a comprehensive data-driven approach for vibration-based SHM.
Free torus actions and twisted suspensions
Authors: Galaz-García Fernando , Reiser Philipp 
Published: January 2025

AbstractWe express the total space of a principal circle bundle over a connected sum of two manifolds in terms of the total spaces of circle bundles over each summand, provided certain conditions hold. We then apply this result to provide sufficient conditions for the existence of free circle and torus actions on connected sums of products of spheres and obtain a topological classification of closed, simply connected manifolds with a free cohomogeneity-four torus action. As a corollary, we obtain infinitely many manifolds with Riemannian metrics of positive Ricci curvature and isometric torus actions.
A single source theorem for primitive points on curves
Authors: Khawaja Maleeha , Siksek Samir 
Published: January 2025

AbstractLet C be a curve defined over a number field K and write g for the genus of C and J for the Jacobian of C. Let
$n \ge 2$
. We say that an algebraic point
$P \in C(\overline {K})$
has degree n if the extension
$K(P)/K$
has degree n. By the Galois group of P we mean the Galois group of the Galois closure of
$K(P)/K$
which we identify as a transitive subgroup of
$S_n$
. We say that P is primitive if its Galois group is primitive as a subgroup of
$S_n$
. We prove the following ‘single source’ theorem for primitive points. Suppose
$g>(n-1)^2$
if
$n \ge 3$
and
$g \ge 3$
if
$n=2$
. Suppose that either J is simple or that
$J(K)$
is finite. Suppose C has infinitely many primitive degree n points. Then there is a degree n morphism
$\varphi : C \rightarrow \mathbb {P}^1$
such that all but finitely many primitive degree n points correspond to fibres
$\varphi ^{-1}(\alpha )$
with
$\alpha \in \mathbb {P}^1(K)$
.We prove, moreover, under the same hypotheses, that if C has infinitely many degree n points with Galois group
$S_n$
or
$A_n$
, then C has only finitely many degree n points of any other primitive Galois group.
Closed approximate subgroups: compactness, amenability and approximate lattices
Authors: Machado Simon 
Published: January 2025

AbstractWe investigate properties of closed approximate subgroups of locally compact groups, with a particular interest for approximate lattices (i.e., those approximate subgroups that are discrete and have finite co-volume).We prove an approximate subgroup version of Cartan’s closed-subgroup theorem and study some applications. We give a structure theorem for closed approximate subgroups of amenable groups in the spirit of the Breuillard–Green–Tao theorem. We then prove two results concerning approximate lattices: we extend to amenable groups a structure theorem for mathematical quasi-crystals due to Meyer; we prove results concerning intersections of radicals of Lie groups and discrete approximate subgroups generalising theorems due to Auslander, Bieberbach and Mostow. As an underlying theme, we exploit the notion of good models of approximate subgroups that stems from the work of Hrushovski, and Breuillard, Green and Tao. We show how one can draw information about a given approximate subgroup from a good model, when it exists.
Capsaicin supplementation on ruminal fermentation, immune responses, intake and digestibility nutrients in grazing bulls
Authors: Lopes Igor M. S. , Pereira Juliana R. , Teixeira Luísa G. , Silva Fabiano F. , de Carvalho Gleidson G. P. , Rodrigues Carlindo S. , Santiago Murilo R. , de Araújo Maria Leonor G. M. L. , Pires Aureliano J. V. , e Silva Ricardo D. G. , Pina Douglas S. , Rennó Francisco P. , Brant Lara M. S. , de Freitas Júnior José E. 
Published: January 2025

Abstract
This study evaluated the effects of capsaicin (CAP) supplementation on the intake, nutrient digestibility, ruminal fermentation, nitrogen balance, microbial protein synthesis and health traits of bulls managed on pasture. Eight crossbred (Holstein x Zebu) cattle averaging 313 ± 31 kg of body weight (BW) were arranged in a replicated 4 × 4 Latin square design (one square of four bulls, rumen fistulated with 4-inch silicone cannulas and one square of four non-fistulated bulls), which were kept on Pangola grass pasture (Digitaria decumbens). Each experimental period consisted of 21 days, with 7 days for data collection (no washout between periods). Bulls were randomly assigned to the following treatments: CON (control): concentrate supplementation at 0.5% live weight (BW) and no additive (CAPCIN®), or concentrate supplementation at 0.5% BW in association with CAPCIN® (NutriQuest, Campinas, Brazil) fed at the inclusion rates of 150 (CAP150), 300 (CAP300) and 450 (CAP450) mg/animal/day. Digestibilities of dry matter, organic matter and neutral detergent fibre showed quadratic responses to CAP supplementation. Rumen pH linearly increased with CAP supplementation. The numbers of lymphocytes and eosinophils were linearly increased with CAP supplementation. The use of encapsulated pepper in supplements of crossbred (Holstein x Zebu) bulls managed on D. decumbens pasture up to 450 mg/animal/day improves nutrients digestibility and ruminal fermentation and can positively influence the health status of beef cattle managed under tropical conditions.
Optimizing geophysics, biotechnology and other emerging tools for livestock production and management: a review
Authors: Folarin Gbolahan M. , Folarin Itunuola A. , Olanloye Silifat A. 
Published: January 2025

Abstract
In working towards meeting the rapidly rising demand for livestock products in the face of challenges such as climate change, limited forage land availability and inadequacies in water availability and quality, it is imperative to consider sustainability in farm or grazing land management and water resources conservation as well as biodiversity management and conservation, etc. Geophysics, GIS, remote sensing, etc., have been useful tools. Emerging technologies such as biotechnology, advanced sensor technologies, machine learning algorithms, internet of things, artificial intelligence, unmanned aerial vehicles, robotics, etc., are also being employed in agriculture and other aspects of human concerns. There are potentials for better utilization of these emerging technologies and more in livestock production and management. However, a limitation is that relevant knowledge and skills are still relatively inadequate, especially in developing countries; hence the need for this review, which is an enhancement of knowledge for research and improved productivity. Efforts should be made to advance in knowledge and skills acquisition so as to optimize this development for improved livestock production and management.
Benchmarking of topsoil moisture estimation methods based on a field study
Authors: Thaler Sabina , Eitzinger Josef , Fischer Milan , Kubu Gerhard , Marin David , Orság Matěj , Trnka Miroslav , Vecchiotti Filippo , Vreugdenhil Mariette , Wagner Wolfgang 
Published: January 2025

Abstract
Extreme weather events caused by climate change, such as drought and heavy rainfall, will further increase in Central Europe in the near future. Resilient crop production requires in-depth knowledge of soil moisture (SM), its spatial and temporal variability and the dynamics of agriculturally used land. In the current study, different SM estimation methods, including measurement and simulation-based methods, were evaluated over a 17-ha experimental arable crop field with respect to their abilities to capture the spatial and temporal SM dynamics of within-field areas and their related uncertainty and spatial representativeness. The high-spatial resolution in-situ topsoil moisture measurements (50 m grid) were compared with the estimated SM from satellite-based remote sensing (S1ASCAT) and the simulated SM from three different crop water balance models (Agricultural Risk Information System [ARIS], AquaCrop and DSSAT). The evaluation revealed that the spatial variability in the experimental field obtained from the reference could not be captured by the alternative methods investigated because of the limitations of the grid size-related soil map information. Nevertheless, the analysis revealed a very good temporal correlation of SM dynamics with the field area average across all approaches, with AquaCrop and ARIS at a soil depth of 0–10 cm and S1ASCAT soil–water index 05 achieving a R2 and a Kling–Gupta efficiency >0.80. These results indicate the added value of complementary methods for estimating SM to reduce spatial and temporal uncertainties in the estimated topsoil water content.