bluuebunny/crossref_metadata_2025_split huggingface dataset:
Family and parenting factors are associated with emotion regulation neural function in early adolescent girls with elevated internalizing symptoms
Authors: Lin Sylvia C. , Pozzi Elena , Kehoe Christiane E. , Havighurst Sophie , Schwartz Orli S. , Yap Marie B. H. , Zhao Junxuan , Telzer Eva H. , Whittle Sarah 
Published: June 2024

AbstractA prominent tripartite model proposes that parent role modeling of emotion regulation, emotion socialization behaviors, and the emotional climate of the family are important for young people’s emotional development. However, limited research has examined the neural mechanisms at play. Here, we examined the associations between family and parenting factors, the neural correlates of emotional reactivity and regulation, and internalizing symptoms in early adolescent girls. Sixty-four female adolescents aged 10–12 years with elevated internalizing symptoms completed emotional reactivity, implicit (affect labeling) and explicit (cognitive reappraisal) emotion regulation tasks during functional magnetic resonance imaging. Positive family emotional climate was associated with greater activation in the anterior cingulate and middle temporal cortices during emotional reactivity. Maternal emotion regulation difficulties were associated with increased frontal pole and supramarginal gyrus activation during affect labeling, whereas supportive maternal emotion socialization and positive family emotional climate were associated with activation in prefrontal regions, including inferior frontal and superior frontal gyri, respectively, during cognitive reappraisal. No mediating effects of brain function were observed in the associations between family/parenting factors and adolescent symptoms. These findings highlight the role of family and parenting behaviors in adolescent emotion regulation neurobiology, and contribute to prominent models of adolescent emotional development.
The healthy context paradox: a cross-country analysis of the association between bullying victimisation and adolescent mental health
Authors: Odigie Tracy , Elsden Esme , Hosozawa Mariko , Patalay Praveetha , Pingault Jean-Baptiste 
Published: June 2024

Abstract
Bullying victimisation is an increasing global health problem among adolescents and is associated with short- and long-term adverse mental health outcomes. Investigating whether associations with mental health vary across national contexts and why, can provide insights into mechanisms underlying those associations and inform policy. We used data from 479,685 adolescents participating in the 2018 Program for International Student Assessment (PISA) cross-sectional survey and examined whether the associations between bullying victimisation, psychological distress and life satisfaction vary across 63 countries. We further tested the modifying role of country-level factors – bullying prevalence, income inequality and national wealth, by implementing multilevel cross-country analyses. We found significant associations between bullying victimisation, increased psychological distress (β = 0.181; 95%CI: 0.178, 0.184) and decreased life satisfaction (β = -0.158; 95%CI: -0.162, -0.155). Associations between bullying victimisation, psychological distress and life satisfaction among adolescents were consistent across countries in terms of direction but effect sizes varied substantially. The effects ranged from β = 0.08 in the Philippines to β = 0.40 in South Korea for psychological distress and from β = −0.05 in the Philippines to β = −0.36 in the United Kingdom for life satisfaction. In addition, consistent with the “healthy context paradox” effect, associations between bullying and mental health were larger in countries where the prevalence of bullying was lower, as well as in higher-income countries. Interventions aiming to reduce bullying victimisation should aim to provide additional targeted support for those who still experience bullying after the intervention.
An asynchronous proximal bundle method
Authors: Fischer Frank 
Published: June 2024

Abstract
We develop a fully asynchronous proximal bundle method for solving non-smooth, convex optimization problems. The algorithm can be used as a drop-in replacement for classic bundle methods, i.e., the function must be given by a first-order oracle for computing function values and subgradients. The algorithm allows for an arbitrary number of master problem processes computing new candidate points and oracle processes evaluating functions at those candidate points. These processes share information by communication with a single supervisor process that resembles the main loop of a classic bundle method. All processes run in parallel and no explicit synchronization step is required. Instead, the asynchronous and possibly outdated results of the oracle computations can be seen as an inexact function oracle. Hence, we show the convergence of our method under weak assumptions very similar to inexact and incremental bundle methods. In particular, we show how the algorithm learns important structural properties of the functions to control the inaccuracy induced by the asynchronicity automatically such that overall convergence can be guaranteed.
A phase 1/1b, open-label, dose-escalation study of PD-1 inhibitor, cetrelimab alone and in combination with FGFR inhibitor, erdafitinib in Japanese patients with advanced solid tumors
Authors: Yamamoto Noboru , Kuboki Yasutoshi , Harano Kenichi , Koyama Takafumi , Kondo Shunsuke , Hagiwara Akiko , Suzuki Noriko , Fujikawa Ei , Toyoizumi Kiichiro , Mukai Mayumi , Doi Toshihiko 
Published: June 2024

AbstractImmune checkpoint inhibitors are the leading approaches in tumor immunotherapy. The aim of the study was to establish recommended phase 2 doses (RP2Ds) of intravenous cetrelimab, a checkpoint inhibitor, alone and with oral erdafitinib in Japanese patients with advanced solid tumors. This open-label, non-randomized, dose-escalation phase 1/1b study enrolled adults with advanced solid tumors who were ineligible for standard therapy. Study was conducted in two parts: phase 1a assessed cetrelimab at three dosing levels (80 mg every 2 weeks [Q2W], 240 mg Q2W, and 480 mg Q4W); phase 1b assessed cetrelimab+erdafitinib at two dosing levels (240 mg Q2W + 6 mg once daily [QD] and 240 mg Q2W + 8 mg QD). Primary endpoint was frequency and severity of dose-limiting toxicities (DLTs) of cetrelimab ± erdafitinib. In total 22 patients (phase 1a, n = 9; phase 1b, n = 13) were enrolled. Median duration of follow-up was 8.64 months in phase 1a and 2.33 months in phase 1b. In phase 1a, DLTs weren’t reported while in phase 1b, 1 patient who received 240 mg cetrelimab + 6 mg erdafitinib reported Stevens-Johnson syndrome (grade 3, immune-related). Overall, 88.9% patients in phase 1a (grade ≥ 3: 44.4%) and 100.0% in phase 1b (grade ≥ 3: 53.8%) experienced ≥ 1 treatment-related adverse events (TEAEs); 33.3% in phase 1a and 38.5% in phase 1b reported serious TEAEs, of which 11.1% patients in phase 1a and 15.4% in phase 1b had TEAEs which led to treatment discontinuation. Cetrelimab alone and in combination with erdafitinib showed manageable safety in Japanese patients with advanced solid tumors. RP2Ds were determined as 480 mg cetrelimab Q4W for monotherapy, and cetrelimab 240 mg Q2W + erdafitinib 8 mg QD for combination therapy.
Humanoid Robots as Learning Assistants? Useability Perspectives of Grade 6 Students
Authors: Tilden Solveig , Parish Karen , Mishra Deepti , Lugo Ricardo G. , Andersen Per Normann 
Published: June 2024

AbstractDespite the increasing number of robots in educational settings, they are relatively new, with ambiguous research findings regarding a robot’s influence on students’ learning, psychosocial aspects, and gender differences. In this study, 17 Grade 6 students in a Norwegian school participated in a human–robot interaction (HRI) session with mathematics and programming tasks followed by focus group interviews to explore their experiences. Thematic analysis resulted in four main themes: (1) Technical aspects, (2) Robots as educational assistants, (3) Robot features, and (4) Attitudes regarding robots. Overall, the students found the robot entertaining, providing mastery experiences in mathematics and programming. Some technical difficulties were experienced, and the robot’s lack of facial expressions, emotions, and tailored feedback created interaction challenges. Gender differences regarding interest in people versus things were found. The implementation of robots in education shows potential, however, more research is needed, especially longitudinal exploring the impact of HRI in education.
Artificial Intelligence in Education: Implications for Policymakers, Researchers, and Practitioners
Authors: Ifenthaler Dirk , Majumdar Rwitajit , Gorissen Pierre , Judge Miriam , Mishra Shitanshu , Raffaghelli Juliana , Shimada Atsushi 
Published: June 2024

AbstractOne trending theme within research on learning and teaching is an emphasis on artificial intelligence (AI). While AI offers opportunities in the educational arena, blindly replacing human involvement is not the answer. Instead, current research suggests that the key lies in harnessing the strengths of both humans and AI to create a more effective and beneficial learning and teaching experience. Thus, the importance of ‘humans in the loop’ is becoming a central tenet of educational AI. As AI technology advances at breakneck speed, every area of society, including education, needs to engage with and explore the implications of this phenomenon. Therefore, this paper aims to assist in this process by examining the impact of AI on education from researchers’ and practitioners' perspectives. The authors conducted a Delphi study involving a survey administered to N = 33 international professionals followed by in-depth face-to-face discussions with a panel of international researchers to identify key trends and challenges for deploying AI in education. The results indicate that the three most important and impactful trends were (1) privacy and ethical use of AI; (2) the importance of trustworthy algorithms; and (3) equity and fairness. Unsurprisingly, these were also identified as the three key challenges. Based on these findings, the paper outlines policy recommendations for AI in education and suggests a research agenda for closing identified research gaps.
Investigation of different deposition methods for synthesized gold nanoparticles on a South African sugarcane leaves derived silica xerogel support
Authors: Maseko Ncamisile Nondumiso , Enke Dirk , Iwarere Samuel Ayodele , Oluwafemi Oluwatobi Samuel , Pocock Jonathan 
Published: June 2024

AbstractValue added materials made from agricultural residues are very attractive since they contribute in reducing environmental waste and enhancing economic sustainability. Two deposition methods were investigated where silica xerogel from sugarcane leaves (a waste from sugarcane industry) was used as a support for the synthesized gold nanoparticles. Biogenic silica was refluxed with sodium hydroxide at 80 °C to form sodium silicate solution. The gold nanoparticles were either synthesized in the sodium silicate solution or separately to form silica/Au nanoparticles through a sol-gel method. Ultraviolet (UV)-visible spectroscopy, x-ray powder diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), x-ray fluorescence spectroscopy (XRF), energy dispersive x-ray (EDX) and nitrogen adsorption-desorption were used to characterize the produced Si/Au nanoparticles. The two investigated methods resulted in distinctive deposition of gold nanoparticles on a silica xerogel support and also significantly different textural properties. The produced silica/gold nanoparticles had a Brunauer-Emmett-Teller (BET) surface area of up to 619 m2/g, pore diameter of 8.3 nm and pore volume of 1.28 cm3.g−1.
Enhancing thermal properties and surface quality of lappato glazed porcelain tiles through milling time optimization
Authors: Bayer Ozturk Zahide , Karaca Yusuf , Ubay Elif 
Published: June 2024

AbstractIncreasing the surface quality of porcelain tiles, preferred in public, commercial, and living centers, where human density is high, is one of the crucial goals. Surface applications can be applied on the tiles produced as glazed and unglazed tiles in different versions. In lappato glazed tiles, staining-resistance is of great importance besides glossy-surface and wear-resistance. In this study, technical properties such as staining, chemical agent-resistance, color-parameters, thermal-behavior (heat microscopy), roughness, abrasion resistance, and microstructure of glazes (SEM/EDS) depending on the optimizing grinding time were examined with compared to standard lappato-glaze under the industrial conditions. It was observed that with the increase of the glaze grinding, the whiteness value and the increasing smoothness, and higher staining chemicals resistance and the glaze which has lower characteristic temperatures than the standard. As the surface roughness decreased due to grinding, the number and size of pores in the microstructure decreased. The glassy phase exhibited homogeneous distribution due to the dissolution of anorthite crystals.
Coronary Vessel Segmentation in X-ray Angiography Images Using Edge-Based Tracking Method
Authors: Lalinia Mehrshad , Sahafi Ali 
Published: June 2024

AbstractAutomated extraction of coronary arteries is an essential process in the diagnosis of treatment for coronary artery disease (CAD) with computer assistance. Accurately outlining the coronary artery is difficult when using X-ray coronary angiography (XCA) because of the low signal-to-noise ratio and the presence of interfering background structures. In this paper, a new approach for segmenting vessels in angiograms is presented, specifically designed to tackle the difficulties arising from non-uniform illumination, artifacts, and noise present in angiographic images. The proposed method employs an edge-based tracking tool to generate an initial probability map for segmentation. A segmentation method based on coronary vessel tracking is presented for finding the border and centerline of the vessel. The proposed method is designed based on two main components: preprocessing and tracking. In the preprocessing stage, a guided filter and edge-sharpening algorithms are used to enhance the features of the original image. In the tracking stage, an initial point is selected, and using the Gaussian property, a semi-circle operator is applied to track the line perpendicular to the vessel. The proposed method demonstrated remarkable performance in terms of sensitivity and specificity, achieving values of 86.93 and 99.61, respectively. Additionally, the method achieved an accuracy rate of 97.81. Notably, the proposed method outperformed existing state-of-the-art segmentation methods, as indicated by its higher dice score. These impressive results signify a significant advancement in the field of vessel segmentation, highlighting the effectiveness and superiority of the proposed approach.
The effects of self-leadership and mindfulness training on leadership development: a systematic review
Authors: Tenschert Julia , Furtner Marco , Peters Mike 
Published: June 2024

AbstractInvestment in leadership development programs (LDPs) does not reliably increase leaders’ competence in core socioemotional skills related to self-management, self-awareness, and relationship-building with employees. Training programs focused on self-leadership, in combination with mindfulness practices, have the potential to address this gap. However, robust research that assesses the suitability and efficacy of such programs is lacking. In this article, the results of a systematic review of the literature on self-leadership and mindfulness in the context of LDPs are reported. A total of 52 articles were selected from an initial pool of 284 articles, subjected to textual analysis, and coded in terms of the reported impact levels for all of the examined training programs. This study revealed that training in self-leadership competencies and skills improved stress resilience, job performance and satisfaction, and positive attitudes and increased leaders’ abilities to organize and motivate their teams. Mindfulness training was strongly linked to stress reduction and self-regulation as well as to enhanced sleep and reduced burnout. Mindfulness also appeared to improve job performance and emotional regulation and to increase the ability to establish positive relationships with employees.
An integrated groundwater vulnerability and artificial recharge site suitability assessment using GIS multi-criteria decision making approach in Kayseri region, Turkey
Authors: Mouhoumed Rachid Mohamed , Ekmekcioğlu Ömer , Özger Mehmet 
Published: June 2024

AbstractGroundwater resources worldwide face significant challenges that require urgent implementation of sustainable measures for effective long-term management. Managed aquifer recharge (MAR) is regarded as one of the most promising management technologies to address the degradation of groundwater resources. However, in urban aquifers, locating suitable areas that are least vulnerable to contamination for MAR implementation is complex and challenging. Hence, the present study proposes a framework encapsulating the combined assessment of groundwater vulnerability and MAR site suitability analysis to pinpoint the most featured areas for installing drywells in Kayseri, Turkey. To extrapolate the vulnerable zones, not only the original DRASTIC but also its multi-criteria decision-making (MCDA)–based modified variants were evaluated with regard to different hydrochemical parameters using the area under the receiver operating characteristic (ROC) curve (AUC). Besides, the fuzzy analytical hierarchy process (FAHP) rationale was adopted to signify the importance level of criteria and the robustness of the framework was highlighted with sensitivity analysis. In addition, the decision layers and the attained vulnerability layer were combined using the weighted overlay (WOA). The findings indicate that the DRASTIC-SWARA correlates well with the arsenic (AUC = 0.856) and chloride (AUC = 0.648) and was adopted as the vulnerability model. Groundwater quality parameters such as chloride and sodium adsorption ratio, as well as the vadose zone thickness, were found to be the most significant decision parameters with importance levels of 16.75%, 14.51%, and 15.73%, respectively. Overall, 28.24% of the study area was unsuitable for recharge activities with high to very high vulnerability, while the remaining part was further prioritized into low to high suitability classes for MAR application. The proposed framework offers valuable tool to decision-makers for the delineation of favorable MAR sites with minimized susceptibility to contamination.
The Gap in the Knowledge Argument
Authors: Montero Barbara 
Published: June 2024

AbstractAlter (The Matter of Consciousness: From the Knowledge Argument to Russellian Monism, GB: Oxford University Pres, 2023) argues for something surprising: despite being widely rejected by philosophers, including Frank Jackson himself, Jackson’s knowledge argument succeeds. Alter’s defense of Jackson’s argument is not only surprising; it’s also exciting: the knowledge argument, if it’s sound, underscores the power of armchair philosophy, the power of pure thought to arrive at substantial conclusions about the world. In contrast, I aim to make a case for something unsurprising and unexciting: that the knowledge argument does not succeed, or, even less far-reaching, that Alter’s defense of it is not persuasive. Mine is a classic file-drawer thesis, but what it has going for it is that it’s true, or so I think, and hope to illustrate why you should too.
Stereo reconstruction from microscopic images for computer-assisted ophthalmic surgery
Authors: Peter Rebekka , Moreira Sofia , Tagliabue Eleonora , Hillenbrand Matthias , Nunes Rita G. , Mathis-Ullrich Franziska 
Published: June 2024

Abstract

Purpose

This work presents a novel platform for stereo reconstruction in anterior segment ophthalmic surgery to enable enhanced scene understanding, especially depth perception, for advanced computer-assisted eye surgery by effectively addressing the lack of texture and corneal distortions artifacts in the surgical scene.

Methods

The proposed platform for stereo reconstruction uses a two-step approach: generating a sparse 3D point cloud from microscopic images, deriving a dense 3D representation by fitting surfaces onto the point cloud, and considering geometrical priors of the eye anatomy. We incorporate a pre-processing step to rectify distortion artifacts induced by the cornea’s high refractive power, achieved by aligning a 3D phenotypical cornea geometry model to the images and computing a distortion map using ray tracing.

Results

The accuracy of 3D reconstruction is evaluated on stereo microscopic images of ex vivo porcine eyes, rigid phantom eyes, and synthetic photo-realistic images. The results demonstrate the potential of the proposed platform to enhance scene understanding via an accurate 3D representation of the eye and enable the estimation of instrument to layer distances in porcine eyes with a mean average error of 190 $$\upmu {\hbox {m}}$$

μ
m

, comparable to the scale of surgeons’ hand tremor.

Conclusion

This work marks a significant advancement in stereo reconstruction for ophthalmic surgery by addressing corneal distortions, a previously often overlooked aspect in such surgical scenarios. This could improve surgical outcomes by allowing for intra-operative computer assistance, e.g., in the form of virtual distance sensors.
On the U-Fe-C Isothermal Section at 1100 °C
Authors: Henriques Margarida I. Sousa , Silva André , Havela Ladislav , Gonçalves António Pereira 
Published: June 2024

AbstractThe energy crisis and climate change have promoted a growing interest in non-fossil sources, such as nuclear, with uranium carbides being seen as potential fuel candidates for Generation IV nuclear reactors. However, the need of accurate thermophysical data for the fuel and its compatibility with core materials during the extreme fission conditions is still an issue. Here a study of the ternary uranium-iron-carbon system performed at 1100 °C using powder x-ray diffraction and Scanning Electron Microscopy coupled with Energy Dispersive Spectrometry is presented. The U-Fe-C isothermal section is characterized by two ternary compounds, thirteen 3-phase regions and five 2-phase regions. UFeC2 and ~ U11Fe12C18 were confirmed to be present at 1100 °C and crystallize in structures related to the binary uranium carbides. UFeC2 crystallizes in an original structure type, a distorted variant of the UCoC2 structure, with space group P4/n and a = 3.503(5) Å and c = 7.405(5) Å lattice parameters. ~ U11Fe12C18, has a crystal structure related to the Th11Ru12C18 structure-type (space group I$$\overline{4 }$$

4
¯

3m) with the lattice parameter a ≈ 10 Å. Furthermore, an island of a α-UC2-based phase with 32U:4Fe:64C composition was found in the 1100 °C isothermal section, indicating the inclusion of Fe in the α-UC2 binary compound.