bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Mindfulness Training on Teachers’ Expectations and Experiences Regarding Their Mental Health and Mindfulness/Prosocial Competencies
Authors: Janssen Math , Heerkens Yvonne , Van der Heijden Beatrice , Korzilius Hubert , Peters Pascale , Engels Josephine 
Published: December 2024

Abstract
Objectives
In this qualitative study, we explored Dutch secondary vocational schoolteachers’ prior expectations of a Mindfulness-Based Stress Reduction (MBSR) training. We report on their short- and long-term experiences regarding mental health outcomes and personal or mindfulness/prosocial competencies.

Method
Between September 2016 and June 2020, we interviewed 32 teachers participating in a cluster randomised controlled trial prior to partaking in a MBSR training (T0); 27, immediately after the training (T1); and 16, 9 months after finishing the training (T3). No interviews were held on T2, 3 months after finishing the training. Qualitative data was analysed using directed content analysis.

Results
Analysis of the data at T0 resulted in five themes regarding the participants’ prior expectations related to the MBSR training. Data analysis at T1 and T3 resulted in 10 themes regarding their experiences, four of which were the same as at T0: one mental health outcome (i.e. stress and unpleasant feelings) and three personal competencies (i.e. being in the present, taking distance, and recognising and changing dysfunctional patterns). The fifth "other" theme at T0 was knowledge of mindfulness and of mindfulness skills. Six additional themes emerged related to a new mental health outcome (i.e. inner calmness and pleasant feelings) and five personal competencies (i.e. being aware, concentration, acceptance and non-judgment, communicating, and showing compassion towards yourself and others).

Conclusion
Our results suggest that MBSR can reduce teachers’ stress, increase inner calmness, and foster mindfulness and prosocial competencies.

Preregistration
The trial was registered with the Dutch Trial Register (www.trialregister.nl): NL5581 (July 2016).
A relational turn in climate change adaptation: Evidence from urban nature-based solutions
Authors: Goodwin Sean , Olazabal Marta , Castro Antonio J. , Pascual Unai 
Published: December 2024

Abstract
The emergence of nature-based solutions (NbS) in science, policy, and practice signals a paradigmatic shift in urban climate change adaptation, yet empirical investigations into its impact on adaptation definitions and progress tracking remain scarce. Addressing this gap, we conducted thematic analysis on semi-structured interviews (n = 15) with practitioners responsible for implementing and evaluating urban NbS in different countries. We provide a nuanced understanding of urban adaptation goals within urban NbS according to the insights from these practitioners, extending beyond hazard mitigation and towards cultivating and strengthening relationships between humans and nature. Tracking adaptation progress towards such relational adaptation goals requires acknowledging knowledge pluralism and the diversity of human–nature relations. We propose an alternative definition of adaptation supported by our data that aims to foster a more holistic approach to urban climate adaptation that accounts for the potential benefits of urban NbS across interconnected climate, biodiversity, and social goals.
Rail Flaw B-Scan Image Analysis Using a Hierarchical Classification Model
Authors: Hu Guoxi , Li Jie , Jing Guoqing , Aela Peyman 
Published: December 2024

AbstractAs railway traffic volumes and train speeds increase, rail maintenance is becoming more crucial to prevent catastrophic failures. This study aimed to develop an artificial intelligence (AI)-based solution for automatic rail flaw detection using ultrasound sensors to overcome the limitations of traditional inspection methods. Ultrasound sensors are well-suited for identifying structural abnormalities in rails. However, conventional inspection techniques like rail-walking are time-consuming and rely on human expertise, risking detection errors. To address this, a hierarchical classification model was proposed integrating ultrasound B-scan images and machine learning. It involved a two-stage approach—model A for fuzzy classification followed by Model EfficientNet-B7 was identified as the most effective architecture for both models through network comparisons. Experimental results demonstrated the model's ability to accurately detect rail flaws, achieving 88.56% accuracy. It could analyze a single ultrasound image sheet within 0.45 s. An AI-based solution using ultrasound sensors and hierarchical classification shows promise for automated, rapid, and reliable rail flaw detection to support safer railway infrastructure inspection and maintenance activities.
No One Home? New Evidence for MIS 3 Occupations in the Western Cape (South Africa) from Mertenhof Rock Shelter
Authors: Will Manuel , Jacobs Zenobia , Mackay Alex 
Published: December 2024

Abstract
Southern Africa features an intensively studied Stone Age sequence, though one with geographical and temporal gaps. The archaeology of Marine Isotope Stage (MIS) 3 remains understudied, particularly between ~ 50 and 25 ka. This period encompasses important ecological, demographic and cultural changes, most notably the transition from Middle Stone Age (MSA) to Later Stone Age (LSA) technologies. In western South Africa, previous research postulated a demographic hiatus during the second half of MIS 3, potentially due to hyperarid climatic conditions. Here, we provide evidence of occupation during this period at Mertenhof Rock Shelter (MRS) in the form of new chronometric and technological data. OSL estimates suggest two pulses of low-intensity occupations at ~ 50 ka and 41–37 ka, allowing for a diachronic assessment of technological changes. These sporadic MSA occupations complement the more widespread occurrence of open-air settlements along the Doring River during ~ 50–35 ka. At MRS, knappers procured local rock types and produced small flakes and some laminar elements via platform, bipolar and Levallois reduction. The retouched elements feature splintered pieces and denticulates but mostly lack points. Differences to contemporaneous sites in eastern southern Africa underscore ongoing technological regionalisation and demographic partitioning during MIS 3. The temporal changes in the sequence show some antecedents of Early LSA technological systems, which appear in the region around 25 ka, but not in a unidirectional manner. Lithic and chronometric evidence from MRS supports scenarios of a long MSA persistence within MIS 3 in southern Africa and a late emergence of the LSA sometime after 35 ka.
Individual differences in escalation of commitment: a multi-level adaptive learning perspective
Authors: Wong Kin Fai Ellick , Kwong Jessica Y. Y. , Yik Michelle 
Published: December 2024

Abstract
Previous studies have found stable individual differences in decision-making under escalation situations. Conventionally, the differences have been attributed to dispositional factors. In this paper, we offer multi-level adaptive learning as an alternative, positing that stable individual differences can develop (a) from an equal starting point at which there are no individual differences among all simulated learners, and (b) without the presumption of influences from dispositional factors. The results of three computer simulation studies showed that after sufficient learning trials, simulated individuals developed the key characteristics of stable individual differences in escalation of commitment: (a) a stable escalation tendency, (b) stable individual differences in escalation tendency, (c) decreases in stability of individual differences as more learning occurs, and (d) decreases in test–retest correlation as the test–retest interval increases. The findings suggest that adaptive learning can explain the emergence and development of individual differences in escalation of commitment without the assumption of dispositional factors.
Incidental mood affects decision under uncertainty: findings from an experiment with Nigerian farmers
Authors: Begho Toritseju , Daubry Tare Philip 
Published: December 2024

AbstractSmall farmers in low-and-middle-income countries are disproportionately affected by uncertainties under which they have to make decisions. However, decision-making may not be purely rational as it could be influenced by affective or emotional states. Compared to integral mood, there are few studies investigating whether incidental mood influences farmers’ monetary decisions under uncertainty. This paper applies the Cumulative prospect theory (CPT) model to determine farmers’ attitudes under uncertainty and examines the association with farmers mood, measured by direct elicitation during an experimental session. Participants (farmers) were mostly uncertainty averse in the gain domain. In contrast, farmers were uncertainty-seeking for losses. A one-way ANOVA was conducted to examine the differences between groups in sad, neutral and happy mood states, followed by posthoc tests to determine which groups differed from each other. The results revealed statistically significant differences in uncertainty aversion, loss aversion, and the parameters representing how probabilities are perceived and weighted, i.e., sad, neutral and happy in the gain domain. However, there was an absence of a relationship between incidental mood and several CPT parameters in the loss domain. The paper highlights how understanding the association between mood and attitudes can be harnessed for a better quality of decision-making in various contexts. This finding has important implications for agricultural contexts where farmers often face uncertain outcomes and must make choices that involve potential gains and losses. Since the transfer of incidental moods to decision making is usually done unconsciously, it is crucial to eliminate or reduce the impact of negative moods on decision-making, especially where the outcome is likely to be suboptimal.
Moisture Sources and Atmospheric Circulation Patterns for Extreme Rainfall Event Over North China Plain From 29 July to 2 August 2023
Authors: Guo Hui , Hu Wanting , Yang Chen , Wan Fang 
Published: December 2024

AbstractTwo years following the extreme rainfall event in Henan Province in July 2021, North China was struck by another significant rainfall episode in late July and early August 2023 (the “23.7” event). This recent event, surpassed only by the August 1963 deluge in Henan province, precipitated extensive disasters across the Beijing‐Tianjin‐Hebei region (BTH) over the North China Plain. Understanding the mechanisms underlying such extreme precipitation events, including moisture sources and atmospheric circulation patterns, in the context of synoptic‐scale systems is crucial for accurate predictions and effective disaster mitigation in the future. To achieve this, this study utilized a vertically integrated water vapor transport method and a Water Accounting model to investigate the moisture sources and pathways of the “23.7” event. A systematic analysis of circulation patterns was also conducted based on the ERA5 reanalysis. The results showed that the western North Pacific and Indian Ocean contributed 38.1% and 18.6%, respectively, to the extreme rainfall over the BTH region. Additionally, terrestrial moisture sources contributed 16.59%, playing a significant role in the event. The stable and moisture‐laden air was transported to the BTH due to the influence of binary tropical cyclones “Doksuri” and “Khanun,” as well as the western Pacific subtropical high‐pressure system. Convergence and updraft dynamics trigger convective processes modulated by vortices and topography. The findings of this study help to build a deeper understanding of the formation processes and mechanisms behind such heavy rainfall, which provides insights for model predictions of similar high‐impact low‐frequency extreme rainfall events.
Extreme Responses of the Ionospheric Radial Currents to the Main Phase of the Super Geomagnetic Storm on 10 May 2024
Authors: Xia Hao , Wang Hui , Zhang Kedeng 
Published: December 2024

AbstractOn 10 May 2024, a super geomagnetic storm occurred with a minimum Dst index of −412 nT. This study investigates the behavior of the ionospheric radial current (IRC) during the main phase of this storm using data from Swarm A and simulations from the Thermosphere‐Ionosphere Electrodynamics General Circulation Model (TIEGCM). At dawn, the IRC exhibits distinct temporal variations: a strong outward flow of 14 nA/m2 between 18:00 and 20:00 UT and an inward flow of −15 nA/m2 by 24:00 UT. At dusk, the IRC starts with an inward value of −6 nA/m2 and rapidly reverses to an outward flow peaking at 15 nA/m2 between 22:00 and 24:00 UT. The dawn‐dusk asymmetry of the IRC is primarily influenced by the merging electric field (Em). Increasing Em penetrates to low latitudes, establishing an eastward (dusk) or westward (dawn) electric field and enhancing the outward (dusk) or inward (dawn) IRC through meridional Hall currents. Model results indicate that the strong polarity changes in dawn IRC are linked to local disturbed zonal winds (). Which are eastward at dawn and westward at other magnetic local times (MLT). The eastward/westward generate outward/inward F‐layer dynamo currents, driving the disturbed vertical electric field () in opposite direction. The significant outward reversal of dusk ∆IRC could be attribute to the rapid enhancement of disturbed Pedersen conductivity (). Due to nonzero geomagnetic declination, eastward/westward corresponds to an increase/decrease in .
Evaluation of Sub‐Hourly MRMS Quantitative Precipitation Estimates in Mountainous Terrain Using Machine Learning
Authors: White Phoebe , Nelson Peter A. 
Published: December 2024

AbstractThe Multi‐Radar Multi‐Sensor (MRMS) product incorporates radar, quantitative precipitation forecasts, and gage data at a high spatiotemporal resolution for the United States and southern Canada. MRMS is subject to various sources of measurement error, especially in complex terrain. The goal of this study is to provide a framework for understanding the uncertainty of MRMS in mountainous areas with limited observations. We evaluate 8‐hr time series samples of MRMS 15‐min intensity through a comparison to 204 gages located in the mountains of Colorado. This analysis shows that the MRMS surface precipitation rate product tends to overestimate rainfall with a median normalized root mean squared error (RMSE) of 42% of the maximum MRMS 15‐min intensity. For each time series sample, various features related to the physical characteristics influencing MRMS performance are calculated from the topography, surrounding storms, and rainfall observed at the gage location. A gradient‐boosting regressor is trained on these features and is optimized with quantile loss, using the RMSE as a target, to model nonlinear patterns in the features that relate to a range of error. This model was used to predict a range of error throughout the mountains of Colorado during warm months, spanning 6 years, resulting in a spatiotemporally varying error model of MRMS for sub‐hourly precipitation rates. Mapping of this data set by aggregating normalized RMSE over time reveals that areas further from radar sites in higher elevation terrain show consistently greater error. However, the model predicts larger performance variability in these regions compared to alternative error assessments.
Genome-wide methylome-based molecular pathologies associated with depression and suicide
Authors: Dwivedi Yogesh , Roy Bhaskar , Korla Praveen Kumar 
Published: December 2024

Abstract
Major depressive disorder (MDD) is a debilitating disorder. Suicide attempts are 5-times higher in MDD patients than in the general population. Interestingly, not all MDD patients develop suicidal thoughts or complete suicide. Thus, it is important to study the risk factors that can distinguish suicidality among MDD patients. The present study examined if DNA methylation changes can distinguish suicidal behavior among depressed subjects. Genome-wide DNA methylation was examined in the dorsolateral prefrontal cortex of depressed suicide (MDD+S; n = 15), depressed non-suicide (MDD−S; n = 17), and nonpsychiatric control (C; n = 16) subjects using 850 K Infinium Methylation EPIC BeadChip. The significantly differentially methylated genes were used to determine the functional enrichment of genes for ontological clustering and pathway analysis. Based on the number of CpG content and their relative distribution from specific landmark regions of genes, 32,958 methylation sites were identified across 12,574 genes in C vs. MDD+/−S subjects, 30,852 methylation sites across 12,019 genes in C vs. MDD−S, 41,648 methylation sites across 13,941 genes in C vs. MDD+S, and 49,848 methylation sites across 15,015 genes in MDD−S vs. MDD+S groups. A comparison of methylation sites showed 33,129 unique methylation sites and 5451 genes in the MDD−S group compared to the MDD+S group. Functional analysis suggested oxytocin, GABA, VGFA, TNFA, and mTOR pathways associated with suicide in the MDD group. Altogether, our data show a distinct pattern of DNA methylation, the genomic distribution of differentially methylated sites, gene enrichment, and pathways in MDD suicide compared to non-suicide MDD subjects.
StraightTrack: Towards mixed reality navigation system for percutaneous K‐wire insertion
Authors: Zhang Han , Killeen Benjamin D. , Ku Yu‐Chun , Seenivasan Lalithkumar , Zhao Yuxuan , Liu Mingxu , Yang Yue , Gu Suxi , Martin‐Gomez Alejandro , Taylor  , Osgood Greg , Unberath Mathias 
Published: December 2024

AbstractIn percutaneous pelvic trauma surgery, accurate placement of Kirschner wires (K‐wires) is crucial to ensure effective fracture fixation and avoid complications due to breaching the cortical bone along an unsuitable trajectory. Surgical navigation via mixed reality (MR) can help achieve precise wire placement in a low‐profile form factor. Current approaches in this domain are as yet unsuitable for real‐world deployment because they fall short of guaranteeing accurate visual feedback due to uncontrolled bending of the wire. To ensure accurate feedback, StraightTrack, an MR navigation system designed for percutaneous wire placement in complex anatomy, is introduced. StraightTrack features a marker body equipped with a rigid access cannula that mitigates wire bending due to interactions with soft tissue and a covered bony surface. Integrated with an optical see‐through head‐mounted display capable of tracking the cannula body, StraightTrack offers real‐time 3D visualization and guidance without external trackers, which are prone to losing line‐of‐sight. In phantom experiments with two experienced orthopedic surgeons, StraightTrack improves wire placement accuracy, achieving the ideal trajectory within mm and , compared to over 12.08 mm and 4.07 for comparable methods. As MR navigation systems continue to mature, StraightTrack realizes their potential for internal fracture fixation and other percutaneous orthopedic procedures.
FBG‐driven simulation for virtual augmentation of fluoroscopic images during endovascular interventions
Authors: Scarponi Valentina , Verde Juan , Haouchine Nazim , Duprez Michel , Nageotte Florent , Cotin Stéphane 
Published: December 2024

AbstractEndovascular interventions are procedures designed to diagnose and treat vascular diseases, using catheters to navigate inside arteries and veins. Thanks to their minimal invasiveness, they offer many benefits, such as reduced pain and hospital stays, but also present many challenges for clinicians, as they require specialized training and heavy use of X‐rays. This is particularly relevant when accessing (i.e. cannulating) small arteries with steep angles, such as most aortic branches. To address this difficulty, a novel solution that enhances fluoroscopic 2D images in real‐time by displaying virtual configurations of the catheter and guidewire is proposed. In contrast to existing works, proposing either simulators or simple augmented reality frameworks, this approach involves a predictive simulation showing the resulting shape of the catheter after guidewire withdrawal without requiring the clinician to perform this task. This system demonstrated accurate prediction with a mean 3D error of 2.4 1.3 mm and a mean error of 1.1 0.7 mm on the fluoroscopic image plane between the real catheter shape after guidewire withdrawal and the predicted shape. A user study reported an average intervention time reduction of 56 when adopting this system, resulting in a lower X‐ray exposure.
From seagull to hummingbird: New diagnostic methods for resolving galaxy activity
Authors: Daoutis C. , Zezas A. , Kyritsis E. , Kouroumpatzakis K. , Bonfini P. 
Published: December 2024

Context. One of the principal challenges in astrophysics involves the classification of galaxies based on their activity. Currently, the characterization of galactic activity usually requires multiple diagnostics to fully cover the diverse spectrum of galaxy activity types. Additionally, the presence of multiple sources of excitation with similar observational signatures hinders the exploration of the activity of a galaxy.
Aims. In this study our objective is to develop an activity diagnostic tool that addresses the degeneracy inherent in the existing emission line diagnostics by identifying the underlying excitation mechanisms of the principal components of a mixed-activity galaxy (star formation, active nucleus, or old stellar populations) and identifying the dominant ones.
Methods. We utilized the random forest machine-learning algorithm, trained on three primary activity classes: star-forming, active galactic nucleus (AGN), and passive; these classes represent the three key gas excitation mechanisms. This diagnostic relies on four discriminating features: the equivalent widths of three spectral lines, [O III] λ5007, [N II] λ6584, and Hα, along with the D4000 continuum break index.
Results. We find that this classifier achieves almost perfect performance scores in the principal activity classes. In particular, the achieved overall accuracy is ∼99%, while the recall scores are ∼100% for star-forming, ∼98% for AGN, and ∼99% for passive. The nearly perfect scores achieved enable the decomposition of mixed-activity classes into the three primary gas excitation mechanisms with high confidence, thereby resolving the degeneracy inherent in current activity classification methods. Furthermore, we find that our classifier scheme can be simplified to a two-dimensional diagnostic diagram of D4000 index versus the log10(EW([O III])2) line without significant loss of its diagnostic power.
Conclusions. We introduce a diagnostic capable of classifying galaxies based on their primary gas excitation mechanisms. Simultaneously, it can deconstruct the activity of mixed-activity galaxies into these principal components. This diagnostic encompasses the entire range of galaxy activity. Additionally, the D4000 index serves as a valuable indicator for resolving the degeneracy among various activity components by estimating the age of the stellar populations within a galaxy.