bluuebunny/crossref_metadata_2025_split huggingface dataset:
X-ray structures, thermal stabilities and kinetics of guest desolvation of complexes of three fluorenone-derived host compounds with the polar aprotic guest solvent, tetramethylurea
Authors: McFarlane Duncan W. , Barton Benita , Caira Mino R. 
Published: September 2024

AbstractThe wheel-and-axle host compounds 9,9′-(1,4-phenylene)bis(fluoren-9-ol) (H1), 9,9′-(ethyne-1,2-diyl)bis(fluoren-9-ol) (H2) and 9,9′-(biphenyl-4,4′-diyl)bis(fluoren-9-ol) (H3) each formed complexes with tetramethylurea (TMU), a polar aprotic organic solvent, with host: guest ratios of 1:2. Single crystal X-ray diffraction revealed that these complexes crystallized in the monoclinic space group P21/c, their analyses being performed in P21/c for H1⋅2(TMU) and in the alternative setting P21/n for both H2·2(TMU) and H3·2(TMU). Furthermore, these inclusion compounds are stabilized by both classical and non-classical hydrogen bonds between the host and guest molecules. Hirshfeld surface analyses demonstrated that the percentage of interatomic (host)H···O(guest) interactions ranged between 7.8 and 10.3%, while thermal analyses showed that the relative thermal stabilities of these complexes were high, with the onset temperatures for the guest release event, Ton, being 83.1 (H1·2(TMU)), 81.1 (H2·2(TMU)) and 90.3 °C (H3·2(TMU)). Moreover, the calculated mass loss percentages, after heating each complex in a controlled manner to release the guest species, correlated closely with those expected for these 1:2 host: guest inclusion complexes. Finally, determination of the activation energies for complex desolvation yielded 148.7 ± 5.4, 128.6 ± 10.8 and 149.4 ± 0.8 kJ·mol‒1 for H1·2(TMU), H2·2(TMU) and H3·2(TMU) respectively. A single guest desolvation mechanism was at work in the first and last of these complexes, while this mechanism in H2·2(TMU) changed during this process. The H1·2(TMU) inclusion complex has been reported previously, and the results obtained in that work are also compared with those from the present investigation.
Enhancing the luminescent properties of strontium phosphate glass via controlled crystallization and rare earth dopants
Authors: Marzouk M. A. , Ali I. S. 
Published: September 2024

AbstractThe study focused on investigating the photoluminescence behavior of pure strontium phosphate glasses with a composition of 62.5% P2O5 and 37.5% SrO. Then it was extended to investigate the effects of adding rare earth elements (Pr3+, Sm3+, Eu3+, Dy3+) and the crystallization process on improving luminescent properties of the parent glass. Various spectroscopic measurements, including XRD, SEM & EDAX, and FTIR, were conducted to examine the relationship between structural changes and their impact on luminescent performance. The optical measurements showed a characteristic enhancement resulting from the addition of RE3+-dopants and the crystallization process. The crystallization of glasses yielded a single phase from Sr(PO3)2 with an extended emission peak at 671 nm and heightened intensity compared to the glassy sample. The development of efficient and stable luminescent glasses via crystallization and dopant type can lead to advancements in applications such as glowing devices, optical detectors, and photonics innovations.
Physical health mindsets and information avoidance
Authors: O’Brien Abigail G. , Foust Jeremy L. , Taber Jennifer M. 
Published: September 2024

AbstractHealth mindsets refer to beliefs about the malleability (growth mindset) versus stability (fixed mindset) of physical health and have gained traction as a predictor of health beliefs and behaviors. Across two studies, we tested whether health mindsets were associated with avoiding personalized health risk information. In Study 2, we also tested whether conceptually-related constructs of internal and chance health locus of control, health self-efficacy, fatalism, and genetic determinism were associated with information avoidance. Health mindsets were manipulated in Study 1 (college students, n = 284; 79.58% female; Mage = 19.74) and measured in Study 2 (participants recruited through MTurk, n = 735; 42.04% female; Mage = 35.78). In both studies, participants viewed a prediabetes infographic and were informed they could learn their prediabetes risk by completing an online risk calculator. Behavioral obligation was also manipulated in both studies to test whether an additional behavioral requirement associated with learning one’s risk would exacerbate any negative impact of health mindsets on avoidance rates. All participants then indicated their interest in learning their prediabetes risk (avoidance intentions) and decided whether to complete the online risk calculator (avoidance behavior). In Study 1, there was no impact of health mindsets, behavioral obligation, or their interaction on avoidance intentions or behavior. Study 2 similarly did not provide consistent evidence for an association of health mindsets, behavioral obligation, or their interaction with avoidance intentions or behavior. However, in Study 2, internal health locus of control was consistently associated with both intentions and behavior. Health information avoidance may be a barrier to prevention and early detection of disease. To encourage individuals to learn potentially important health information, public health interventions might seek to increase people’s beliefs that their own actions play a role in their health outcomes. Interventions may also seek to increase people’s knowledge about and skills regarding improving their health outcomes, which may influence health locus of control beliefs.
A Review of the Applicability of Non-destructive Testing for the Determination of the Fire Performance of Reused Structural Timber
Authors: Uldry Aline , Husted Bjarne P. , Pope Ian , Ottosen Lisbeth M. 
Published: September 2024

AbstractThis paper presents a review of the possible methods for testing the fire performance properties of reused timber through non-destructive techniques, focusing on structural elements. Evaluating the fire performance of old wooden specimen is necessary to facilitate reuse, in the support of the transition to a circular economy. The use of non-destructive methods minimizes damages to the pieces during the evaluation process. Three angles are reviewed: (1) The properties of wood influencing fire performance, (2) the change of wood properties over time, and (3) the known non-destructive tests. Some properties of wood are known to influence the fire performance, e.g., the density. Of these, there is no evidence of irreversible changes due to the passage of time only. The many different non- and semi- destructive techniques that can be applied to wood seldom relate to these properties, but rather to mechanical properties or geometry. Additionally, accurate measurements are often difficult, while some are only done in laboratories. This review concludes that currently there is no known non-destructive method that permits to estimate the fire performance of a reused timber element compared to a new one. There is a gap of knowledge on the evolution of the fire properties of timber during the use phase of the building, and there are no established methods to test for these properties without destroying a significant portion of the element. Development of non-destructive test methodologies to assess fire properties of timber will expand the market for reused timber to include load carrying timber.
People do not always want more: Effects of gains and satisfaction on goal orientation in different age groups
Authors: Gong Xianmin , Freund Alexandra M. 
Published: September 2024

AbstractPast research suggests age-related differences in goal orientation: Whereas younger adults are more likely to orient their goals towards gains and growth, older adults have a stronger orientation towards maintenance and loss avoidance. Three online studies with US participants on MTurk examined the role of gains, losses, and satisfaction for these age-related differences in goal orientation. Studies 1 (N = 179, 20–82 years, 49.2% female) and 2 (N = 241, 18–73 years, 53.1% female) showed that goal orientation was mainly associated with perceived gains and satisfaction with the current state but not with losses: the subjectively experienced accumulation of gains was positively associated with gain, maintenance, and loss-avoidance orientation; higher satisfaction with the status quo was associated with a stronger maintenance orientation and a weaker gain orientation. Subjectively experienced and expected losses were unrelated to goal orientation. Study 3 (N = 611, 18–83 years, 46.7% female) confirmed the causal effect of satisfaction with the current state on gain orientation (but not on maintenance or loss-avoidance orientation) by experimentally manipulating satisfaction with a given status quo. When higher (versus lower) satisfaction was induced, participants were less oriented towards striving for gains. The results suggest that, across age groups, perceived accumulation of gains and satisfaction with the current state impact goal orientation more strongly than losses. This research promotes our understanding of the antecedents of age-related differences in goal orientation and motivational development across adulthood.
Combined parameter and shape optimization of electric machines with isogeometric analysis
Authors: Wiesheu Michael , Komann Theodor , Merkel Melina , Schöps Sebastian , Ulbrich Stefan , Cortes Garcia Idoia 
Published: September 2024

AbstractIn structural optimization, both parameters and shape are relevant for the model performance. Yet, conventional optimization techniques usually consider either parameters or the shape separately. This work addresses this problem by proposing a simple yet powerful approach to combine parameter and shape optimization in a framework using Isogeometric Analysis (IGA).The optimization employs sensitivity analysis by determining the gradients of an objective function with respect to parameters and control points that represent the geometry. The gradients with respect to the control points are calculated in an analytical way using the adjoint method, which enables straightforward shape optimization by altering these control points. Given that a change in a single geometry parameter corresponds to modifications in multiple control points, the chain rule is employed to obtain the gradient with respect to the parameters in an efficient semi-analytical way.The presented method is exemplarily applied to nonlinear 2D magnetostatic simulations featuring a permanent magnet synchronous motor and compared to designs, which were optimized using parameter and shape optimization separately. It is numerically shown that the permanent magnet mass can be reduced and the torque ripple can be eliminated almost completely by simultaneously adjusting rotor parameters and shape. The approach allows for novel designs to be created with the potential to reduce the optimization time substantially.
The proposal and application of a 2-Dimensional Fuzzy Monte Carlo Frontier analysis for estimating Islamic bank efficiency
Authors: Tan Yong , Azad Md Abul Kalam , Araújo de Medeiros Antônio Mamede , Wanke Peter Fernandes 
Published: September 2024

AbstractThe current study proposes a novel 2-Dimensional Fuzzy Monte-Carlo Frontier Analysis to estimate and compare the level of efficiency for a sample of 49 Islamic Banks across 25 countries worldwide over the period 2013–2021. Additionally, in the second stage, we propose a bootstrapped robust regression approach to comprehensively examine the determinants of efficiency. Our results show that there is heterogeneity in the level of efficiency within the Islamic banking sector. Furthermore, we find that the Islamic banks in the sample experienced an improvement in efficiency over the examined period. Finally, we find that bank size, bank liquidity (measured by the ratio between net loans and gross loans), and bank risk (proxied by the ratio between loan loss reserves and gross loans) have a significant and positive impact on Islamic bank efficiency. Policy implications based on our findings are provided.
Quasi-likelihood analysis for Student-Lévy regression
Authors: Masuda Hiroki , Mercuri Lorenzo , Uehara Yuma 
Published: September 2024

AbstractWe consider the quasi-likelihood analysis for a linear regression model driven by a Student-t Lévy process with constant scale and arbitrary degrees of freedom. The model is observed at high frequency over an extending period, under which we can quantify how the sampling frequency affects estimation accuracy. In that setting, joint estimation of trend, scale, and degrees of freedom is a non-trivial problem. The bottleneck is that the Student-t distribution is not closed under convolution, making it difficult to estimate all the parameters fully based on the high-frequency time scale. To efficiently deal with the intricate nature from both theoretical and computational points of view, we propose a two-step quasi-likelihood analysis: first, we make use of the Cauchy quasi-likelihood for estimating the regression-coefficient vector and the scale parameter; then, we construct the sequence of the unit-period cumulative residuals to estimate the remaining degrees of freedom. In particular, using full data in the first step causes a problem stemming from the small-time Cauchy approximation, showing the need for data thinning.
Natural gradient hybrid variational inference with application to deep mixed models
Authors: Zhang Weiben , Smith Michael , Maneesoonthorn Worapree , Loaiza-Maya Rubén 
Published: September 2024

AbstractStochastic models with global parameters and latent variables are common, and for which variational inference (VI) is popular. However, existing methods are often either slow or inaccurate in high dimensions. We suggest a fast and accurate VI method for this case that employs a well-defined natural gradient variational optimization that targets the joint posterior of the global parameters and latent variables. It is a hybrid method, where at each step the global parameters are updated using the natural gradient and the latent variables are generated from their conditional posterior. A fast to compute expression for the Tikhonov damped Fisher information matrix is used, along with the re-parameterization trick, to provide a stable natural gradient. We apply the approach to deep mixed models, which are an emerging class of Bayesian neural networks with random output layer coefficients to allow for heterogeneity. A range of simulations show that using the natural gradient is substantially more efficient than using the ordinary gradient, and that the approach is faster and more accurate than two cutting-edge natural gradient VI methods. In a financial application we show that accounting for industry level heterogeneity using the deep mixed model improves the accuracy of asset pricing models. MATLAB code to implement the method and replicate the results can be found at https://github.com/WeibenZhang07/NG-HVI
Away from Home: The Ethics of Hostile Affective Scaffolding
Authors: Archer Alfred , Robb Catherine 
Published: September 2024

AbstractDuring live sporting events, fans often create intense atmospheres in stadiums, expressing support for their own local players and discouragement for the opposition. Crowd hostility directed at opposition players surprisingly elicits contrasting reactions across different sports. Tennis players, for example, have reported that hostile crowds are hurtful and disrespectful, whereas footballers often praise and encourage such hostility. What explains this tension? Why are hostile atmospheres considered wrong for some athletes, and not for others? We argue that creating hostile atmospheres for opposition players functions as a form of hostile affective scaffolding, as it scaffolds affective states in such a way that harms the interests of the opposition athletes, while promoting the interests of fans. These hostile atmospheres wrong the scaffolded insofar they constitute a form of recognition disrespect, and to the extent that they violate the formal rules and conventional norms internal to the sporting practices. Although the focus is on the sporting context, our analysis reveals significant implications for a more nuanced understanding of what hostile scaffolding is, and how we should understand its normativity. The existing literature views hostile scaffolding as constituted by a setback to the overall interests of the scaffolded, and that the wrong-making feature of this scaffolding is necessarily explained by harm. Instead, we argue that hostile scaffolding should be understood as hostile relative to a set of interests that an agent has, not just their overall interests, and that the wrong-making features of hostile scaffolding are not limited to harms.
Stool and blood metabolomics in the metabolic syndrome: a cross-sectional study
Authors: Ponce-de-Leon Mariana , Wang-Sattler Rui , Peters Annette , Rathmann Wolfgang , Grallert Harald , Artati Anna , Prehn Cornelia , Adamski Jerzy , Meisinger Christa , Linseisen Jakob 
Published: September 2024

Abstract
Introduction/objectives
Changes in the stool metabolome have been poorly studied in the metabolic syndrome (MetS). Moreover, few studies have explored the relationship of stool metabolites with circulating metabolites. Here, we investigated the associations between stool and blood metabolites, the MetS and systemic inflammation.

Methods
We analyzed data from 1,370 participants of the KORA FF4 study (Germany). Metabolites were measured by Metabolon, Inc. (untargeted) in stool, and using the AbsoluteIDQ® p180 kit (targeted) in blood. Multiple linear regression models, adjusted for dietary pattern, age, sex, physical activity, smoking status and alcohol intake, were used to estimate the associations of metabolites with the MetS, its components and high-sensitivity C-reactive protein (hsCRP) levels. Partial correlation and Multi-Omics Factor Analysis (MOFA) were used to investigate the relationship between stool and blood metabolites.

Results
The MetS was significantly associated with 170 stool and 82 blood metabolites. The MetS components with the highest number of associations were triglyceride levels (stool) and HDL levels (blood). Additionally, 107 and 27 MetS-associated metabolites (in stool and blood, respectively) showed significant associations with hsCRP levels. We found low partial correlation coefficients between stool and blood metabolites. MOFA did not detect shared variation across the two datasets.

Conclusions
The MetS, particularly dyslipidemia, is associated with multiple stool and blood metabolites that are also associated with systemic inflammation. Further studies are necessary to validate our findings and to characterize metabolic alterations in the MetS. Although our analyses point to weak correlations between stool and blood metabolites, additional studies using integrative approaches are warranted.
Navigating common pitfalls in metabolite identification and metabolomics bioinformatics
Authors: Novoa-del-Toro Elva María , Witting Michael 
Published: September 2024

Abstract
Background
Metabolomics, the systematic analysis of small molecules in a given biological system, emerged as a powerful tool for different research questions. Newer, better, and faster methods have increased the coverage of metabolites that can be detected and identified in a shorter amount of time, generating highly dense datasets. While technology for metabolomics is still advancing, another rapidly growing field is metabolomics data analysis including metabolite identification. Within the next years, there will be a high demand for bioinformaticians and data scientists capable of analyzing metabolomics data as well as chemists capable of using in-silico tools for metabolite identification. However, metabolomics is often not included in bioinformatics curricula, nor does analytical chemistry address the challenges associated with advanced in-silico tools.

Aim of review
In this educational review, we briefly summarize some key concepts and pitfalls we have encountered in a collaboration between a bioinformatician (originally not trained for metabolomics) and an analytical chemist. We identified that many misunderstandings arise from differences in knowledge about metabolite annotation and identification, and the proper use of bioinformatics approaches for these tasks. We hope that this article helps other bioinformaticians (as well as other scientists) entering the field of metabolomics bioinformatics, especially for metabolite identification, to quickly learn the necessary concepts for a successful collaboration with analytical chemists.

Key scientific concepts of review
We summarize important concepts related to LC-MS/MS based non-targeted metabolomics and compare them with other data types bioinformaticians are potentially familiar with. Drawing these parallels will help foster the learning of key aspects of metabolomics.
GC–MS metabolomics of French lettuce (Lactuca Sativa L. var capitata) leaves exposed to bisphenol A via the hydroponic media
Authors: Cabrera-Peralta Jerónimo , Peña-Alvarez Araceli 
Published: September 2024

Abstract
Introduction
Bisphenol A (BPA), an organic compound used to produce polycarbonate plastics and epoxy resins, has become a ubiquitous contaminant due to its high-volume production and constant release to the environment. Plant metabolomics can trace the stress effects induced by environmental contaminants to the variation of specific metabolites, making it an alternative way to study pollutants toxicity to plants. Nevertheless, there is an important knowledge gap in metabolomics applications in this area.

Objective
Evaluate the influence of BPA in French lettuce (Lactuca Sativa L. var capitata) leaves metabolic profile by gas chromatography coupled to mass spectrometry (GC–MS) using a hydroponic system.

Methods
Lettuces were cultivated in the laboratory to minimize biological variation and were analyzed 55 days after sowing (considered the plant’s adult stage). Hexanoic and methanolic extracts with and without derivatization were prepared for each sample and analyzed by GC–MS.

Results
The highest number of metabolites was obtained from the hexanoic extract, followed by the derivatized methanolic extract. Although no physical differences were observed between control and contaminated lettuce leaves, the multivariate analysis determined a statistically significant difference between their metabolic profiles. Pathway analysis of the most affected metabolites showed that galactose metabolism, starch and fructose metabolism and steroid biosynthesis were significantly affected by BPA exposure.

Conclusions
The preparation of different extracts from the same sample permitted the determination of metabolites with different physicochemical properties. BPA alters the leaves energy and membrane metabolism, plant growth could be affected at higher concentrations and exposition times.