bluuebunny/crossref_metadata_2025_split huggingface dataset:
Weaving the Fabric of Social and Emotional Learning in the Context of Teaching: A Study in Hong Kong Kindergarten Classrooms
Authors: Chen Jennifer J. , Liang Xiaoting , Lin Jasmine C. 
Published: June 2024

Abstract This study investigated how children’s social and emotional learning (SEL) might reflect their teachers’ social and emotional teaching (SET) by means of social learning. To this end, the research team conducted 20 videotaped observation sessions of four teachers’ SET and 71 children’s SEL during whole-group instruction in four kindergarten classrooms in Hong Kong. The research team coded SET and SEL based on teacher and child utterances for evidence of the CASEL’s five key social and emotional competencies (Self-Awareness, Self-Management, Social Awareness, Relationship Skills, and Responsible Decision-Making). Additionally, we coded a one-on-one correspondence between each competency and one of the four strategies identified (Telling/Commanding/Directing, Explaining, Asking Questions, and Affirming/Confirming). Both the teachers and children evidenced Responsible Decision-Making the most. Except for Social Awareness, the teachers’ SET and children’s SEL in the other four competencies were correlated significantly and strongly. Furthermore, among the five strategies, teachers primarily utilized the Asking Questions strategy, while children predominantly corresponded with the Telling strategy. Significant correlations were observed among the strategies: between teachers’ Asking Questions and children’s Telling, between teachers’ Asking Questions and children's Explaining, between teachers’ Explaining and children's Explaining, Asking Questions, and Affirming/Confirming, and between teachers’ Affirming/Confirming and children’s Telling. These findings suggest that social learning was at work to guide children’s SEL in the context of their teachers’ SET.
Detection of a major Lynch Syndrome-causing MLH1 founder variant in a large-scale genotyped cohort
Authors: Sipilä Lauri J. , Aavikko Mervi , Ravantti Janne , Martin Samantha , Kuopio Teijo , Lahtinen Laura , FinnGen  , Peltomäki Päivi , Mecklin Jukka-Pekka , Aaltonen Lauri A. , Seppälä Toni T. 
Published: June 2024

AbstractSome 50% of Finnish Lynch Syndrome (LS) cases are caused by a founder variant in MLH1, in which the entire exon 16 has been lost due to an Alu-mediated recombination event. We piloted detecting the variant in FinnGen, a large genotyped cohort comprising approximately 10% of the current Finnish population, and validated the MLH1 founder variant status of identified individuals residing in the Central Finland Biobank catchment area. A consensus sequence flanking the deletion was identified in whole genome sequences of six LS individuals with the founder variant. Genotype data of 212,196 individuals was queried for regional matches to the consensus sequence. Enrichment of cancer and age at cancer onset was compared between matching and non-matching individuals. Variant status was validated for a subset of the identified individuals using a polymerase chain reaction assay. Allelic matches in a chosen target region was detected in 348 individuals, with 89 having a cancer diagnosis (Bonferroni-adjusted p-value = 1), 20 a familial cancer history (p-adj. < .001), with mean age of onset of cancer being 53.6 years (p-adj. = .002). Eighteen of potential variant carriers had been sampled by the Central Finland Biobank, of which four (22%) were validated as true variant carriers. The workflow we have employed identifies MLH1 exon 16 deletion variant carriers from population-wide SNP genotyping data. An alternative design will be sought to limit false positive findings. Large genotyped cohorts provide a potential resource for identification and prevention of hereditary cancer.
Beyond the Canopy: Social Play Behavior in Wild Spider Monkeys (Ateles geoffroyi)
Authors: Cardoso Rodriguez Sara , Corral Eva , Llorente Miquel , Liebal Katja , Amici Federica 
Published: June 2024

AbstractPlay is a multifunctional behavior that may confer different advantages depending on the context, the species, sex, and age of the players. Despite numerous studies of social play in primates, we know little about this behavior in platyrrhines. This study was designed to provide a systematic description of social play in a wild group of Geoffroy’s spider monkeys (Ateles geoffroyi). We conducted behavioral observations of acrobatic social play, object social play, cuddling play, and rough-and-tumble play in a large group of spider monkeys (N = 54) in Yucatan, Mexico. Over 5 months, we recorded and analyzed 104 play sessions. The probability of engaging in social play was higher for infants and juveniles than for subadults and adults, and it did not differ between sexes. Moreover, the probability of engaging in different types of social play did not vary across individuals based on their sex and age, nor on the frequency of play faces. Play sessions lasted longer when both players were younger and with a higher number of players, but there was no significant variation in session length associated with the frequency of play faces or players’ sex. Overall, our study revealed patterns of play behavior that suggest substantial flexibility in play in this species, in line with the high levels of tolerance that characterize spider monkeys.
Early insights into Piaget’s cognitive development model through the lens of the Technologies curriculum
Authors: Cerovac Milorad , Keane Therese 
Published: June 2024

Abstract
Piaget’s theory of stage structure is synonymous with discussions involving cognitive development. As with any theoretical model, researchers inevitably and rightly seek to affirm and/or contest the elements of the model presented. In this comparative study, students’ performance across three hands-on engineering tasks for two distinct student cohort groups were investigated including young primary school students (aged 8 to 10) in Piaget’s concrete operations; and older secondary school students (aged 15 to 18) in Piaget’s formal operations stage of cognitive development. The purpose was to gain an insight into Piaget’s stage structure from the perspective of the compulsory national Technologies curriculum in Australia, of which engineering is a core subject. The senior students outperformed their younger peers on all three tasks (simple, complicated and complex), with differences in abstraction and spatial inferential reasoning abilities increasing, as the task complexity increased. Although there is very limited evidence linking practical technological subjects and Piaget’s cognitive development model, the findings were consistent with respect to students’ abstract thinking capabilities and their cognitive development.
Examining engineering design students’ perceptions of agency for sustainability in a problem- and project-based learning (PBL) context—a Q methodology study
Authors: Guerra Aida , Jiang Dan , Du Xiangyun , Abou-Hayt Imad , Valderrama Pineda Andrés Felipe 
Published: June 2024

AbstractThis study explores engineering design students’ perceptions of their agency for sustainability in a Danish problem- and project-based learning (PBL) context. A conceptual framework is proposed with three dimensions: personal, action, and contextual. Q methodology was adopted to investigate the subjective views of 24 first-year undergraduate students in a Sustainable Design program regarding the most important contributors in their development of agency for sustainability. The Q factor analysis identified three prevailing opinions, which emphasized: 1) The professional role of engineering designers to act for the United Nations’ Sustainable Development Goals (SDGs); 2) The role of the formal curriculum in building the foundations to act for the SDGs; and 3) Collaboration within and beyond the university. These results indicate the complexity of student agency and highlight PBL's effectiveness for supporting students’ learning for sustainability across all three dimensions of student agency. The results also suggest that institutions and educators should design more formal and informal sustainability-related activities with clear structures and well-defined regulations and strategies for sustainability.
Energy-efficient tool path generation and expansion optimisation for five-axis flank milling with meta-reinforcement learning
Authors: Lu Fengyi , Zhou Guanghui , Zhang Chao , Liu Yang , Chang Fengtian , Lu Qi , Xiao Zhongdong 
Published: June 2024

AbstractFive-axis flank milling is prevalent in complex surfaces manufacturing, and it typically consumes high electricity energy. To save energy and improve energy efficiency, this paper proposes a tool path optimisation of five-axis flank milling by meta-reinforcement learning. Firstly, considering flank milling features, a feed angle is defined that guides tool spatial motion and identifies an ideal principal path. Then, machining energy consumption and time are modelled by tool path variables, i.e., feed angle, cutting strip width and path length. Secondly, an energy-efficient tool path dynamic optimisation model is constructed, which is then described by multiple Markov Decision Processes (MDPs). Thirdly, meta-learning integrating with the Soft Actor-Critic (MSAC) framework is utilised to address the MDPs. In an MDP with one principal path randomly generated by a feed angle, cutting strip width is dynamically optimised under a maximum scallop height limit to realise energy-efficient multi-expansions. By quick traversal of MDPs with various feed angles, MSAC enables an energy-efficient path generation and expansion integrated scheme. Experiments show that, regarding machining energy consumption and time, the proposed method achieves a reduction of 69.96% and 68.44% over the end milling with an iso-scallop height, and of 41.50% and 39.80% over the flank milling with an iso-scallop height, with a minimum amount of machining carbon emission, which highlights its contribution to the arena of energy-oriented and sustainable intelligent manufacturing.
Characterizing Changes in a Salt Hydrate Bed Using Micro X-Ray Computed Tomography
Authors: Arya Aastha , Martinez-Garcia Jorge , Schuetz Philipp , Mahmoudi Amirhoushang , Brem Gerrit , Donkers Pim A. J. , Shahi Mina 
Published: June 2024

AbstractThermochemical storage using salt hydrates presents a promising energy storage method. Ensuring the long-term effectiveness of the system is critical, demanding both chemical and mechanical stability of material for repetitive cycling. Challenges arise from agglomeration and volume variations during discharging and charging, impacting the cyclability of thermochemical materials (TCM). For practical usage, the material is often used in a packed bed containing millimetre-sized grains. A micro-level analysis of changes in a packed bed system, along with a deeper understanding involving quantifying bed characteristics, is crucial. In this study, micro X-ray computed tomography (XCT) is used to compare changes in the packed bed before and after cycling the material. Findings indicate a significant decrease in pore size distribution in the bed after 10 cycles and a decrease in porosity from 41.34 to 19.91% accompanied by an increase in grain size, reducing void space. A comparison of effective thermal conductivity between the uncycled and cycled reactor indicates an increase after cycling. Additionally, the effective thermal conductivity is lower in the axial direction compared to the radial. XCT data from uncycled and cycled experiments are further used to observe percolation paths inside the bed. Furthermore, at a system scale fluid flow profile comparison is presented for uncycled and cycled packed beds. It has been observed that the permeability decreased and the pressure drop increased from 0.31 to 4.88 Pa after cycling.
Standard addition method for the rapid analysis of 226Ra, gross alpha–beta and total radium isotope activities in surface water of Maritsa River, Türkiye
Authors: Zaim Nimet , Camtakan Zeyneb , Kiremitçioğlu Şevki 
Published: June 2024

AbstractThis research aimed to determine the activity concentration of 226Ra in the natural radioactivity of the surface water of the Maritsa River, Türkiye. The gamma spectrometric analysis was conducted by using 3′′ × 3′′ NaI(Tl) and (HPGe) detector. Since the direct measurement method could not acquire reliable results, the mean activity concentration of 226Ra was calculated as 0.62 Bq L−1 with the “standard addition method”. The mean values of the gross alpha/beta activities and the total radium alpha activity concentration were measured. The results are 0.013 Bq L−1, 0.304 Bq L−1, and 0.014 Bq L−1 respectively.
The impact of data distribution on Q-learning with function approximation
Authors: Santos Pedro P. , Carvalho Diogo S. , Sardinha Alberto , Melo Francisco S. 
Published: June 2024

AbstractWe study the interplay between the data distribution and Q-learning-based algorithms with function approximation. We provide a unified theoretical and empirical analysis as to how different properties of the data distribution influence the performance of Q-learning-based algorithms. We connect different lines of research, as well as validate and extend previous results, being primarily focused on offline settings. First, we analyze the impact of the data distribution by using optimization as a tool to better understand which data distributions yield low concentrability coefficients. We motivate high-entropy distributions from a game-theoretical point of view and propose an algorithm to find the optimal data distribution from the point of view of concentrability. Second, from an empirical perspective, we introduce a novel four-state MDP specifically tailored to highlight the impact of the data distribution in the performance of Q-learning-based algorithms with function approximation. Finally, we experimentally assess the impact of the data distribution properties on the performance of two offline Q-learning-based algorithms under different environments. Our results attest to the importance of different properties of the data distribution such as entropy, coverage, and data quality (closeness to optimal policy).
A Retrospective Cohort Study of Disparities in Urine Drug Testing During the Perinatal Period in an Urban, Academic Medical Center
Authors: Ganetsky Valerie S. , Yates Brianna , Salzman Matthew , Heil Jessica , Jones Iris , Hunter Krystal , Perry Robin L. , Baston Kaitlan E. 
Published: June 2024

AbstractThe purpose of this study was to evaluate disparities in urine drug testing (UDT) during perinatal care at a single academic medical center. This retrospective cohort study included patients who had a live birth and received prenatal care at our institution between 10/1/2015 and 9/30/2020. The primary outcomes were maternal UDT during pregnancy (UDTPN) and UDT only at delivery (UDTDEL). Secondary outcomes included the number of UDTs (UDTNUM) and the association between a positive UDT test result and race/ethnicity. Mixed model logistic regression and negative binomial regression with clustering based on prenatal care locations were used to control for confounders. Of 6,240 live births, 2,265 (36.3%) and 167 (2.7%) received UDTPN and UDTDEL, respectively. Black (OR 2.09, 95% CI 1.54–2.84) and individuals of Other races (OR 1.64, 95% CI 1.03–2.64) had greater odds of UDTPN compared to non-Hispanic White individuals. Black (beta = 1.12, p < 0.001) and Hispanic individuals (beta = 0.78, p < 0.001) also had a positive relationship with UDTNUM. Compared to individuals with non-Medicaid insurance, those insured by Medicaid had greater odds of UDTPN (OR 1.66, 95% CI 1.11–2.49) and had a positive relationship with UDTNUM (beta = 0.89, p < 0.001). No significant associations were found for UDTDEL and race/ethnicity. Despite receiving more UDT, Black individuals were not more likely to have a positive test result compared to non-Hispanic White individuals (OR 0.95, 95% CI 0.72–1.25). Our findings demonstrate persistent disparities in substance use testing during the perinatal period.
Ambient Air Pollution, Housing Context, and Birth Outcomes Among Wisconsin Mothers
Authors: Fottrell Amy K. , Curtis Marah A. , Weeks Fiona H. 
Published: June 2024

Abstract
Objectives
To assess the association between air pollution exposure and housing context during pregnancy and adverse birth outcomes.

Methods
We linked air pollution data from the Environmental Protection Agency and housing data from the American Community Survey with birth records from Wisconsin counties over a 9-year period. We calculated average daily pregnancy exposure to fine particulate matter and ozone and modeled its relationship to preterm birth, low birthweight and NICU admission, adjusting for individual characteristics and housing context.

Results
Ozone exposure and housing cost-burden had substantive and statistically significant negative associations with birthweight and gestational age, and positive associations with NICU admission, while a poor-quality housing environment had a significant negative effect on weeks of gestation. Fine particulate matter exposure had a negligible correlation with these outcomes.

Conclusions for practice
An additional tenth of one part-per-million daily average exposure to ozone is associated with a 33 g decrease in birthweight. This decrease in birthweight is about the same size as the association of gestational diabetes (32 g), larger than the association of chronic hypertension (22 g), and about 40% the size of the effect of smoking during pregnancy on birthweight (84 g). Given the magnitudes of the associations with atmospheric ozone and adverse birth outcomes, reducing atmospheric ozone should be a public health priority. Inclusion of controls for housing cost-burden and poor-quality housing reduces the magnitude of the association with mothers who identify as Black, suggesting the importance of these structural factors in understanding adverse birth outcomes by race.
Protein vicinal thiols as intrinsic probes of brain redox states in health, aging, and ischemia
Authors: Foley Timothy D. , Huang Wen C. , Petsche Emily A. , Fleming Emily R. , Hornickle James C. 
Published: June 2024

AbstractThe nature of brain redox metabolism in health, aging, and disease remains to be fully established. Reversible oxidations, to disulfide bonds, of closely spaced (vicinal) protein thiols underlie the catalytic maintenance of redox homeostasis by redoxin enzymes, including thioredoxin peroxidases (peroxiredoxins), and have been implicated in redox buffering and regulation. We propose that non-peroxidase proteins containing vicinal thiols that are responsive to physiological redox perturbations may serve as intrinsic probes of brain redox metabolism. Using redox phenylarsine oxide (PAO)-affinity chromatography, we report that PAO-binding vicinal thiols on creatine kinase B and alpha-enolase from healthy rat brains were preferentially oxidized compared to other selected proteins, including neuron-specific (gamma) enolase, under conditions designed to trap in vivo protein thiol redox states. Moreover, measures of the extents of oxidations of vicinal thiols on total protein, and on creatine kinase B and alpha-enolase, showed that vicinal thiol-linked redox states were stable over the lifespan of rats and revealed a transient reductive shift in these redox couples following decapitation-induced global ischemia. Finally, formation of disulfide-linked complexes between peroxiredoxin-2 and brain proteins was demonstrated on redox blots, supporting a link between protein vicinal thiol redox states and the peroxidase activities of peroxiredoxins. The implications of these findings with respect to underappreciated aspects of brain redox metabolism in health, aging, and ischemia are discussed.
Add-Vit: CNN-Transformer Hybrid Architecture for Small Data Paradigm Processing
Authors: Chen Jinhui , Wu Peng , Zhang Xiaoming , Xu Renjie , Liang Jia 
Published: June 2024

AbstractThe vision transformer(ViT), pre-trained on large datasets, outperforms convolutional neural networks (CNN) in computer vision(CV). However, if not pre-trained, the transformer architecture doesn’t work well on small datasets and is surpassed by CNN. Through analysis, we found that:(1) the division and processing of tokens in the ViT discard the marginalized information between token. (2) the isolated multi-head self-attention (MSA) lacks prior knowledge. (3) the local inductive bias capability of stacked transformer block is much inferior to that of CNN. We propose a novel architecture for small data paradigms without pre-training, named Add-Vit, which uses progressive tokenization with feature supplementation in patch embedding. The model’s representational ability is enhanced by using a convolutional prediction module shortcut to connect MSA and capture local features as additional representations of the token. Without the need for pre-training on large datasets, our best model achieved 81.25$$\%$$
%
accuracy when trained from scratch on the CIFAR-100.
SpanEffiDet: Span-Scale and Span-Path Feature Fusion for Object Detection
Authors: Liu Qunpo , Zhao Yi , Gao Ruxin , Bu Xuhui , Hanajima Naohiko 
Published: June 2024

AbstractLower versions of EfficientDet (such as D0, D1) have smaller network structures and parameter sizes, but lower detection accuracy. Higher versions exhibit higher accuracy, but the increase in network complexity poses challenges for real-time processing and hardware requirements. To meet the higher accuracy requirements under limited computational resources, this paper introduces SpanEffiDet based on the channel adaptive frequency filter (CAFF) and the Span-Path Bidirectional Feature Pyramid structure. Firstly, the CAFF module proposed in this paper realizes the frequency domain transformation of channel information through Fourier transform and effectively extracts the key features through semantic adaptive frequency filtering, thus, eliminating channel redundant information of EfficientNet. Simultaneously, the module has the ability to compute the weights across the channels and at fine granularity, and capture the detailed information of element features. Secondly, a two-way characteristic pyramid network multi-level cross-BIFPN, which can achieve multi-layer and multi-nodes, is proposed to build cross-level information transmission to incorporate both semantic and positional information of the target. This design enables the network to more effectively detect objects with significant size differences in complex environments. Finally, by introducing generalized focal Loss V2, reliable localization quality estimation scores are predicted from the distribution statistics of bounding boxes, thereby improving localization accuracy. The experimental results indicate that on the MS COCO dataset, SpanEffiDet-D0 achieved an AP improvement of 3.3% compared to the original EfficientDet series algorithms. Similarly, on the PASCAL VOC2007 and 2012 datasets, the mAP of SpanEffiDet-D0 is respectively 1.66 and 2.65% higher than that of EfficientDet-D0.