bluuebunny/crossref_metadata_2025_split huggingface dataset:
Happiness in Old Age: The Daughter Connection
Authors: Sukontamarn Pataporn , Asadullah M. Niaz , Photphisutthiphong Nopphawan , Nguyen Yen Thi Hai 
Published: April 2023

AbstractFamily and intergenerational relationships are becoming increasingly important as sources of support and care for the elderly population in rapidly ageing Asian societies. However, this has also raised concerns over reinforcement of cultural preference for sons as a source of old-age security. This paper therefore revisits the question—what determines happiness in old age—by investigating the role of adult children’s gender in the context of Thailand, an ageing Asian country with no legacy of sex-preference in fertility. We employ nationally representative data to examine the association between old-age happiness and presence of a co-residing child. Compared to living alone, living with at least one child is found to positively associate with older persons’ happiness. However, this result is specific to daughters. Moreover, compared to older men, women systematically benefit from a “daughter effect”. Co-residing daughters with university education and those who maintain a good relationship with their parents help explain the positive happiness effect on older persons. Co-residing daughters are also positively linked to reduced loneliness; improved self-rated health; and improved economic conditions of older parents. Our findings suggest that policies that increase human capital of the girl child and enhance family solidarity are likely to have long term intergenerational wellbeing benefits.
Reprocessing 2-D airgun seismic reflection data SALTFLU (salt deformation and sub-salt fluid circulation in the Algero-Balearic abyssal plain) in the Balearic promontory and the Algerian basin
Authors: Blondel Simon , Ford Jonathan , Lockwood Aaron , Del Ben Anna , Camerlenghi Angelo 
Published: April 2023

AbstractIn an ever more challenging context for the acquisition of seismic data in the Mediterranean Sea, reprocessing to improve the quality of legacy data has become increasingly important. This work presents the newly reprocessed, open access dataset SALTFLU acquired in the Algerian basin by the National Institute of Oceanography and Applied Geophysics (OGS) in 2012. We apply a ‘broadband’ reprocessing strategy adapted for offset-limited (3 km streamer for a target 4 km below the sea level) airgun reflection seismic data acquired in deep water settings. We then assess if the reprocessed images provide new geological insights on the Mediterranean sub-surface. The workflow relies on an integrated approach combining geophysics and geological interpretation to iteratively build the velocity model. In this way we aim to tackle some of the challenges linked to imaging deep complex geological structures containing high velocity contrasts with 2-D, offset-limited seismic data. We first broaden the bandwidth of the data through multi-domain de-noising, deghosting and a source designature using an operator derived from the seabed reflection. We then perform iterative migration velocity analysis, pre-stack time migration and multiple attenuation in the Radon domain to obtain time-migrated images. The initial velocity model is derived from the resulting time migration velocities, and geologically driven model updates are generated using a combination of travel-time tomography, seismic interpretation of the major salt horizons and velocity gradient flooding. The gradient flooding aims to reproduce the large scale first-order velocity variations, while the travel-time tomography aims to resolve the smaller second-order velocity variations. The results improve our deep geological knowledge of the under-explored Algerian basin down to the base salt and the pre-salt. Fluid indicators are imaged within the Plio-Quaternary of the Algerian basin, which we interpret as thermogenic or biogenic gas sourced from either the Messinian Upper Unit or from the pre-salt, migrating through a hydro-fractured salt. The reprocessed data image lateral and vertical seismic facies variation within the Messinian units that could shed new light on the tectono-stratigraphic processes acting during the Messinian Salinity Crisis. It also reveals numerous previously unresolved volcanic structures within the Formentera basin.
Enhancement of mesenchymal stem cells’ chondrogenic potential by type II collagen-based bioscaffolds
Authors: Piperigkou Zoi , Bainantzou Dimitra , Makri Nadia , Papachristou Eleni , Mantsou Aglaia , Choli-Papadopoulou Theodora , Theocharis Achilleas D. , Karamanos Nikos K. 
Published: April 2023

Abstract
Background
Osteoarthritis (OA) is a common degenerative chronic disease accounting for physical pain, tissue stiffness and mobility restriction. Current therapeutic approaches fail to prevent the progression of the disease considering the limited knowledge on OA pathobiology. During OA progression, the extracellular matrix (ECM) of the cartilage is aberrantly remodeled by chondrocytes. Chondrocytes, being the main cell population of the cartilage, participate in cartilage regeneration process. To this end, modern tissue engineering strategies involve the recruitment of mesenchymal stem cells (MSCs) due to their regenerative capacity as to promote chondrocyte self-regeneration.

Methods and results
In the present study, we evaluated the role of type II collagen, as the main matrix macromolecule in the cartilage matrix, to promote chondrogenic differentiation in two MSC in vitro culture systems. The chondrogenic differentiation of human Wharton’s jelly- and dental pulp-derived MSCs was investigated over a 24-day culture period on type II collagen coating to improve the binding affinity of MSCs. Functional assays, demonstrated that type II collagen promoted chondrogenic differentiation in both MSCs tested, which was confirmed through gene and protein analysis of major chondrogenic markers.

Conclusions
Our data support that type II collagen contributes as a natural bioscaffold enhancing chondrogenesis in both MSC models, thus enhancing the commitment of MSC-based therapeutic approaches in regenerative medicine to target OA and bring therapy closer to the clinical use.
Parameter estimation for ergodic linear SDEs from partial and discrete observations
Authors: Kurisaki Masahiro 
Published: April 2023

AbstractWe consider a problem of parameter estimation for the state space model described by linear stochastic differential equations. We assume that an unobservable Ornstein–Uhlenbeck process drives another observable process by the linear stochastic differential equation, and these two processes depend on some unknown parameters. We construct the quasi-maximum likelihood estimator of the unknown parameters and show asymptotic properties of the estimator.
Shared goals and values in the teaching profession, job satisfaction and motivation to leave the teaching profession: The mediating role of psychological need satisfaction
Authors: Skaalvik Einar M. , Skaalvik Sidsel 
Published: April 2023

Abstract This study explored relations between teachers’ perceptions of sharing educational goals and values with their colleagues (shared values), job satisfaction, and motivation to leave the teaching profession. The extent to which these associations were mediated through indicators of psychological need satisfaction (belonging, autonomy, and competence) was also examined. Participants were 1145 Norwegian teachers. SEM analyses showed that shared values were positively associated with all indicators of psychological need satisfaction. Shared values were also indirectly associated with general job satisfaction, mediated through perceived belonging and competence. In turn, job satisfaction was strongly and negatively associated with motivation to leave.
BARC: Breed-Augmented Regression Using Classification for 3D Dog Reconstruction from Images
Authors: Rueegg Nadine , Zuffi Silvia , Schindler Konrad , Black Michael J. 
Published: April 2023

AbstractThe goal of this work is to reconstruct 3D dogs from monocular images. We take a model-based approach, where we estimate the shape and pose parameters of a 3D articulated shape model for dogs. We consider dogs as they constitute a challenging problem, given they are highly articulated and come in a variety of shapes and appearances. Recent work has considered a similar task using the multi-animal SMAL model, with additional limb scale parameters, obtaining reconstructions that are limited in terms of realism. Like previous work, we observe that the original SMAL model is not expressive enough to represent dogs of many different breeds. Moreover, we make the hypothesis that the supervision signal used to train the network, that is 2D keypoints and silhouettes, is not sufficient to learn a regressor that can distinguish between the large variety of dog breeds. We therefore go beyond previous work in two important ways. First, we modify the SMAL shape space to be more appropriate for representing dog shape. Second, we formulate novel losses that exploit information about dog breeds. In particular, we exploit the fact that dogs of the same breed have similar body shapes. We formulate a novel breed similarity loss, consisting of two parts: One term is a triplet loss, that encourages the shape of dogs from the same breed to be more similar than dogs of different breeds. The second one is a breed classification loss. With our approach we obtain 3D dogs that, compared to previous work, are quantitatively better in terms of 2D reconstruction, and significantly better according to subjective and quantitative 3D evaluations. Our work shows that a-priori side information about similarity of shape and appearance, as provided by breed labels, can help to compensate for the lack of 3D training data. This concept may be applicable to other animal species or groups of species. We call our method BARC (Breed-Augmented Regression using Classification). Our code is publicly available for research purposes at https://barc.is.tue.mpg.de/.
Sleep-related metacognitions and cognitive behavioral therapy for insomnia
Authors: Jenewein Anna-Lea , Schredl Michael , Schilling Claudia 
Published: April 2023

Abstract
Background
Cognitive behavioral therapy for insomnia (CBT-I) is the treatment of choice for chronic insomnia. In the metacognitive model of Ong et al., a current model of the pathogenesis of chronic insomnia, sleep-related metacognitions are considered to be an insomnia-promoting factor.

Objective
The objective of this study is to investigate the role of metacognitions in insomnia and CBT‑I. Are metacognitions reduced by CBT-I? Can the pretreatment scores of sleep-related metacognitions predict the effectiveness of the therapy? Does treatment response improve when sleep-related metacognitions are directly addressed?

Materials and methods
A total of 92 persons with chronic insomnia participated in CBT‑I with seven 90-min group sessions. Of these patients, 52 received CBT‑I and 40 received CBT‑I with integrated metacognitive elements (CBT-I + MCE). Sleep-related metacognitions and insomniac complaints were quantified using the Metacognitions Questionnaire—Insomnia (MCQ‑I 20) and the Insomnia Severity Index (ISI).

Results
CBT‑I improved subjective sleep quality (effect sizes d > 2.0) and decreased sleep-related metacognitions (effect sizes d > 0.8). Neither the presence of comorbidities nor the extent of sleep-related metacognitions affected treatment response. Treatment response did not differ between the CBT‑I and CBT-I + MCE groups.

Conclusion
Sleep-related metacognitions seem to play an important role in insomnia etiology but did not predict treatment response. The introduction of elements from metacognitive therapy (MCT) is as effective as the classical CBT‑I and might therefore be considered as an addition to the standard cognitive strategies of CBT‑I.
Kraniofaziale Mikrosomie
Authors: Brands Roman C. , Böhm Hartmut , Kübler Alexander C. , Hartmann Stefan , Schweitzer Tilmann , Kunz Felix , Linz Christian 
Published: April 2023

ZusammenfassungDie kraniofaziale Mikrosomie hat eine Inzidenz von 1:3000–1:5000, ist aber dennoch eine der häufigsten angeborenen kraniofazialen Erkrankungen. Ihre Ausprägung ist variabel und geht mit Anomalien der Kiefer, Ohren, Gesichtsweichteile, Augenhöhlen und Gesichtsnerven sowie weiteren extrakraniellen Malformationen einher. Die exakte Genese ist unklar, diskutiert werden pränatale Expositionen und genetische Anomalien. Die Komplexität dieser Erkrankung erschwert die Diagnostik und erfordert ein inter- und multidisziplinäres Therapiekonzept. In dieses sind u. a. die Fachrichtungen Mund‑, Kiefer- und Gesichtschirurgie, Neurochirurgie, Kieferorthopädie, Pädiatrie, Ophthalmologie, Otorhinolaryngologie sowie Logopädie und Ernährungsberatung eingebunden.
Metaverse platform ecosystems
Authors: Schöbel Sofia Marlena , Leimeister Jan Marco 
Published: April 2023

Abstract
Traditionally, the metaverse has been defined as a virtual reality space in which users can interact with a computer-generated environment and other users. Nowadays, it is much more than that—the metaverse can be described as a variety of digital platforms and ecosystems, with each ecosystem as an independent universe with its own material, complementors, and functionalities. Creating metaverse ecosystems and integrated platforms results in different roles and responsibilities for complementors, consumers, platform owners, and orchestrators. The term metaverse platforms is further structured and clarified by four perspectives: innovation, production, transaction, and social interaction. Consequently, this fundamental paper defines it as: “A Metaverse is a massively scaled and interoperable meta-ecosystem of other digital ecosystems of real-time rendered 3D virtual worlds which can be experienced synchronously and persistently by an unlimited number of complementors and consumers with an increased user experience caused by a creativity-guided co-creation of goods managed by orchestrators and supported by platform owners.” Consequently, the metaverse offers vast opportunities for digital innovations beyond traditional social media or computer games and creates new infrastructures for add-on innovations in all areas of the digital economy.
Developing trauma-informed university supports for refugee background students in Australia: Refocusing through an ethics of care lens
Authors: Baker Sally , Naidoo Loshini 
Published: April 2023

AbstractThe growing literature on access, participation, and success of refugees entering higher education has illustrated the myriad challenges that this cohort faces. Much of this research has rightly focused on the student perspective, exploring the barriers and challenges that impede entry, engagement, and achievement. Relatedly, there is growing attention to the need for trauma-informed support, particularly following the impacts of COVID on learning. This article takes these challenges as a departure point to adjust the gaze on universities and ask what needs to be considered and implemented in order to develop better student supports. We use Tronto’s (2013) notion of ethics of care—examining issues of attentiveness (caring about), responsibility (caring for), competence (caregiving), responsiveness (care receiving), and trust (caring with)—to carefully probe how universities can develop trauma-informed supports that are more caring and nuanced, not only for students from refugee backgrounds but for all students.
A t-structure on the $$\infty $$-category of mixed graded modules
Authors: Pavia Emanuele 
Published: April 2023

AbstractIn this work, we shall study in a purely model-independent fashion the $$\infty $$
∞
-category of mixed graded modules over a ring of characteristic 0, as defined by D. Calaque, T. Pantev, M. Vaquié, B. Toën and G. Vezzosi. First, we collect some basic results about its main formal properties, clarifying foundational questions in a systematic manner, to serve as a reference for future work. Finally, we shall endow such $$\infty $$
∞
-category with a both left and right complete accessible t-structure, showing how this identifies the $$\infty $$
∞
-category of mixed graded modules with the left completion of the Beilinson t-structure on the $$\infty $$
∞
-category of filtered modules.
Analysis of Second-Order Thrust Bearing Coefficients Considering Misalignment Effect
Authors: Elsayed Elsayed K. , Sayed Hussein , El-Sayed T. A. 
Published: April 2023

Abstract
Purpose
Thrust bearings play a critical role in high-speed rotating machinery, such as turbines, pumps, compressors, and turbogenerators, by transferring axial loads between the collar and the bearing pads. The lubricating fluid prevents contact, friction, and wear between solid parts and acts as a cooling medium. The purpose of this study is to evaluate the first- and second-order bearing coefficients of an inclined pad hydrodynamic thrust bearing, which have not been previously investigated, to improve the accuracy of modeling thrust bearings.

Methods
In the analysis of thrust bearing systems, the lubricating fluid film is modeled as a massless spring-damper system. The finite perturbation method for the governing Reynolds equation is used to calculate the dynamic coefficients of the thrust bearing. This is done using the finite difference method (FDM) in polar coordinates.

Results
This study investigates the influence of misalignment, rotating speed, and mesh size on the bearing coefficients of the thrust bearing. The results show that misalignment angle and film thickness have a clear effect on the dynamic coefficients, while changing the rotational speed has no effect on the damping coefficients. The study also investigates the axial force and moments and dynamic coefficients of an inclined pad thrust bearing.

Conclusion
This study concludes that evaluating the first- and second-order bearing coefficients of the thrust bearing using the finite perturbation method can improve the accuracy of modeling thrust bearings. The study also highlights the significant influence of misalignment and film thickness on the dynamic coefficients of the thrust bearing. The results presented in this study provide valuable data that can be used as input for rotor dynamics analyses in high-speed rotating machinery.
Simulation of reservoir outflows using regression tree and support vector machine
Authors: Kaushik Vijay , Awasthi Noopur 
Published: April 2023

AbstractWater stored in reservoirs has a lot of crucial function, including generating hydropower, supporting water supply, and relieving lasting droughts. During floods, water deliveries from reservoirs must be acceptable, so as to guarantee that the gross volume of water is at a safe level and any release from reservoirs will not trigger flooding downstream. This study aims to develop a well-versed assessment method for managing reservoirs and pre-releasing water outflows by using the machine learning technology. As a new and exciting AI area, this technology is regarded as the most valuable, time-saving, supervised and cost-effective approach. In this study, two data-driven forecasting models, i.e., Regression Tree (RT) and Support Vector Machine (SVM), were employed for approximately 30 years’ hydrological records, so as to simulate reservoir outflows. The SVM and RT models were applied to the data, accurately predicting the fluctuations in the water outflows of a Bhakra reservoir. Different input combinations were used to determine the most effective release. For cross-validation, the number of folds varied. It is found that quadratic SVM for 10 folds with seven different parameters would give the minimum RMSE, maximum R2, and minimum MAE; therefore, it can be considered as the best model for the dataset used in this study.
Time to consider the timing of conservation measures: Designing cost-effective agri-environment schemes under climate change
Authors: Gerling Charlotte , Drechsler Martin , Keuler Klaus , Sturm Astrid , Wätzold Frank 
Published: April 2023

AbstractClimate change is one of the largest threats for biodiversity as changing climatic conditions often make existing habitat sites less suitable. This poses new challenges for species conservation, in particular in agricultural landscapes, where climate change may also induce modifications in agricultural land use. To conserve species in agricultural landscapes, agri-environment schemes (AES) which compensate farmers for implementing conservation measures are commonly used. However, current research on the cost-effective design of AES largely ignores necessary adaptations of conservation measures given climate change. We develop a climate-ecological-economic (CEE) model to examine how the cost-effective design of AES has to be modified under climate change. We apply the model to the conservation of eight meadow bird species in Northern Germany and determine the cost-effective conservation measures under recent and future climatic conditions. We find that the timing of conservation measures in the AES needs to be changed in the RCP8.5 scenario given the species’ phenological adaptations and the impact of extreme events (inundations) on costs. The novelty of the research lies in the development of a CEE model which considers both spatial and temporal changes in costs and benefits to develop recommendations for the cost-effective design of AES under climate change.
Financial education: From better personal finance to improved citizenship
Authors: Fornero Elsa , Lo Prete Anna 
Published: April 2023

AbstractFinancial education is a crucial determinant of informed decisions, in both the private and social spheres. From a life cycle perspective, it improves personal finance. From youth to retirement, basic economic and financial competences, including specific pension literacy, help to plan for the future and to make better choices, thus reducing the probability of financial fragility, particularly in old age, and increasing economic independence, particularly for women. In the social sphere, a growing literature is demonstrating that basic financial education also affects public choices, influencing voting behavior, economic reforms, policy outcomes, and, more generally, the workings of our democracies.
Youngest Toba Tuff deposits in the Gundlakamma River basin, Andhra Pradesh, India and their role in evaluating Late Pleistocene behavioral change in South Asia
Authors: Anil Devara , Devi Monika , Blinkhorn James , Smith Victoria , Sanghode Satish , Mahesh Vrushab , Khan Zakir , Ajithprasad P. , Chauhan Naveen 
Published: April 2023

AbstractThe eruption of Toba ca. 75 ka was the largest volcanic eruptive event during the Quaternary, and evidence for this eruption is widespread in terrestrial sediment sequences in South Asia as primary and reworked distal ash deposits. Youngest Toba Tuff horizons (YTT) have been widely employed as isochrons to understand and link regional sediment sequences and the evidence for environmental and cultural change in the archaeological records preserved within them. We identify the YTT deposits at Retlapalle, Andhra Pradesh, India, and present the optical ages of the K-feldspar grains recovered from sediments immediately underlying and overlying the tephra horizon. We combine these results with particle size and magnetic susceptibility analyses to establish the depositional conditions of YTT, which indicate that accumulation and reworking ceased by ca. 64 ka. We explore the role of YTT deposits as an isochron for examining the effect of the 75 ka Toba super-eruption, highlighting the need for an independent chronological assessment of YTT before using it as a Late Pleistocene chronological marker in reconstructing South Asian paleo-landscapes and hominin adaptations. Further, our findings support the regional continuity of human occupations within South Asia, spanning the eruption of Toba and the enduring utility of Middle Paleolithic tools.