bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preliminary Danish Norms for the Odense Child Trauma Screening (OCTS)
Authors: Alkærsig Mette , Elklit Ask , Løkkegaard Sille Schandorph 
Published: April 2024

AbstractThe Odense Child Trauma Screening (OCTS) is Danish story stem screening tool applicable for assessment of preschoolers and young children in risk of being traumatized. Having shown initial evidence of validation, Danish norms are needed to strengthen the clinical assessment with the OCTS by serving as a baseline comparison for assessment of potentially traumatized children. We tested 169 children from the Danish general population aged 4–8 with the OCTS and investigated sex and age differences in play-based behavior and narrative representations. Caregivers reported electronically on child demographic information, psychosocial functioning, and history of trauma exposure using The Strengths and Difficulties Questionnaire (SDQ) and The Diagnostic Infant and Preschool Assessment (DIPA) trauma list. Across the 145 scores of the OCTS coding scheme, significant sex and age differences were only found in five and sixteen scores respectively. In the five codes where significant sex differences were observed, boys’ normative scores were higher. No significant sex differences were found in the partial story scores or the OCTS total score. Three significant age differences in partial story and OCTS total scores emerged with 4-year-olds scoring higher than 6–8-year-olds. We further found 13 significant age differences in code scores with higher scores among the youngest of the two groups in question suggesting that scores tend to decrease along older age. Few significant sex and age differences were found in children’s OCTS play-based behavior and narrative representations. Indicative of few sex and age biases of the OCTS coding scheme and stories, results suggest that the OCTS can be applied across the intended target group of children aged 4 to 8 years. As higher scores were found in the younger age groups, clinicians should be attentive to age in certain codes of the OCTS coding scheme in their assessment of children in clinical practice. The preliminary normative scores must be interpreted and clinically applied with caution due to our non-representative sample and lack of analyses on factors potentially influencing children’s responses to the OCTS (e.g., developmental, contextual, cultural factors).
Stretchable, Transparent, and Ultra-Broadband Terahertz Shielding Thin Films Based on Wrinkled MXene Architectures
Authors: Yang Shaodian , Lin Zhiqiang , Wang Ximiao , Huang Junhua , Yang Rongliang , Chen Zibo , Jia Yi , Zeng Zhiping , Cao Zhaolong , Zhu Hongjia , Hu Yougen , Li Enen , Chen Huanjun , Wang Tianwu , Deng Shaozhi , Gui Xuchun 
Published: April 2024

AbstractWith the increasing demand for terahertz (THz) technology in security inspection, medical imaging, and flexible electronics, there is a significant need for stretchable and transparent THz electromagnetic interference (EMI) shielding materials. Existing EMI shielding materials, like opaque metals and carbon-based films, face challenges in achieving both high transparency and high shielding efficiency (SE). Here, a wrinkled structure strategy was proposed to construct ultra-thin, stretchable, and transparent terahertz shielding MXene films, which possesses both isotropous wrinkles (height about 50 nm) and periodic wrinkles (height about 500 nm). Compared to flat film, the wrinkled MXene film (8 nm) demonstrates a remarkable 36.5% increase in SE within the THz band. The wrinkled MXene film exhibits an EMI SE of 21.1 dB at the thickness of 100 nm, and an average EMI SE/t of 700 dB μm−1 over the 0.1–10 THz. Theoretical calculations suggest that the wrinkled structure enhances the film's conductivity and surface plasmon resonances, resulting in an improved THz wave absorption. Additionally, the wrinkled structure enhances the MXene films' stretchability and stability. After bending and stretching (at 30% strain) cycles, the average THz transmittance of the wrinkled film is only 0.5% and 2.4%, respectively. The outstanding performances of the wrinkled MXene film make it a promising THz electromagnetic shielding materials for future smart windows and wearable electronics.
Compositional and Hollow Engineering of Silicon Carbide/Carbon Microspheres as High-Performance Microwave Absorbing Materials with Good Environmental Tolerance
Authors: Gai Lixue , Wang Yahui , Wan Pan , Yu Shuping , Chen Yongzheng , Han Xijiang , Xu Ping , Du Yunchen 
Published: April 2024

AbstractMicrowave absorbing materials (MAMs) characterized by high absorption efficiency and good environmental tolerance are highly desirable in practical applications. Both silicon carbide and carbon are considered as stable MAMs under some rigorous conditions, while their composites still fail to produce satisfactory microwave absorption performance regardless of the improvements as compared with the individuals. Herein, we have successfully implemented compositional and structural engineering to fabricate hollow SiC/C microspheres with controllable composition. The simultaneous modulation on dielectric properties and impedance matching can be easily achieved as the change in the composition of these composites. The formation of hollow structure not only favors lightweight feature, but also generates considerable contribution to microwave attenuation capacity. With the synergistic effect of composition and structure, the optimized SiC/C composite exhibits excellent performance, whose the strongest reflection loss intensity and broadest effective absorption reach − 60.8 dB and 5.1 GHz, respectively, and its microwave absorption properties are actually superior to those of most SiC/C composites in previous studies. In addition, the stability tests of microwave absorption capacity after exposure to harsh conditions and Radar Cross Section simulation data demonstrate that hollow SiC/C microspheres from compositional and structural optimization have a bright prospect in practical applications.
Imagining education beyond growth: A post-qualitative inquiry into the educational consequences of post-growth economic thought
Authors: White Ricky John 
Published: April 2024

AbstractThis paper explores the possible consequences for education of a transition to a post-growth society. Utilising a post-qualitative approach to inquiry, this study begins by analysing post-growth economic literature. It then connects this literature to existing educational scholarship to explore the consequences for education of a transition to a post-growth society. The analysis reveals key features and arrangements proposed in the literature for a post-growth society. It discusses the ways in which education can prepare young people for a future beyond economic growth and speculates as to how education can contribute towards the realisation of this type of society. The paper concludes that education can help prepare students for a post-growth future by focusing on the development of ecological literacy, embracing a place-based approach to education, helping students to comprehend the need for social and economic change, introducing them to a plurality of ideas about how the future might look, developing their capacity to think critically about their future, enhancing their sense of personal autonomy and capacity for self-determination, and supporting their capacity to form strong social relationships.
Shaping citizens: teachers enacting democratic education in the history classroom
Authors: Golledge Claire 
Published: April 2024

AbstractThe work of history teachers in schools is contentious and often heavily scrutinised, characterised by conflicts between professional and ideological perspectives on the purpose of the work they do (Macintyre & Clark, 2003). History curricula in Australia have been the subject of regular, ongoing political intervention, in particular about the role of history education in constructing and maintaining narratives of Australian democracy and citizenship. Against this landscape, this paper explores how history teachers from New South Wales, Australia conceive of the contemporary role of history curriculum in the development of students’ understanding of civics and democracy, and their navigation of the tensions between the written curriculum and the contexts in which they teach. Using both observational and interview data, this paper explores teachers’ perceptions of the gap between curriculum “as intention and as reality” (Stenhouse, 1975, p. 2) illuminating the experiences of teachers who interact with and implement the curriculum in their daily work, and highlighting the role that school context plays in determining how civics and citizenship education is enacted in practice. Contrast is offered between the teachers of history in the context of a privileged, urban school community, to that of an Aboriginal teacher working in a regional context - with an exploration of the impact of these contexts in framing the possibilities for democratic and civic engagement in the history classroom. Using the theoretical framework of practice architectures (Kemmis & Grootenboer, 2008), I explore the role of curriculum as both an enabling and constraining force in the way teachers work to develop student understandings of democracy and civic identity and the complex relationship that emerges from teachers’ interaction with curriculum documents and their decision-making in relation to their students and communities.
Microstructural investigation of tensile fractography and wear properties of scrap aluminium engine head (SAEH) reinforced with fresh and spent catalysts from petrochemical industries using stir casting method
Authors: Rajan Raj Thilak Krishnan , Boppana Satish Babu , S. Ramesh , Krishnan Pradeep Kumar 
Published: April 2024

AbstractThis research aims to investigate the microstructural properties, tensile fractography, and wear characteristics of scrap aluminum engine head (SAEH) composites reinforced with fresh alumina catalysts (FAC) and spent alumina catalysts (SAC) derived from petrochemical industries. Utilizing the stir casting method, four composite variants were fabricated: SAEH + SAC, SAEH + FAC, LM25 + SAC, and LM25 + FAC. The materials were characterized through scanning electron microscopic (SEM) analysis, and the composition of FAC and SAC was detailed. The investigation delves into the wear properties through pin-on-disk tests conducted at different conditions. Tensile strength results revealed distinctive performance: SAEH + FAC = 208 MPa, SAEH + SAC = 217 MPa, LM25 + FAC = 92 MPa, and LM25 + SAC = 184 MPa. Fractography analysis provided insights into the fracture behavior, showcasing the influence of agglomerates, non-coherent interfaces, lack of wetting, grain refinement, and the presence of oxides. The wear behavior, evaluated under varying operating conditions, demonstrated that wear rates increased with escalating conditions and were generally higher for LM25-based composites than for SAEH-based composites. This study introduces the innovative use of SAC in composites, offers a comparative analysis between different materials, and provides a comprehensive understanding of wear behavior under diverse conditions, contributing to the advancement of metal matrix composites.
Nonparametric tests for combined location-scale and Lehmann alternatives using adaptive approach and max-type metric
Authors: Funato Mika , Murakami Hidetoshi , Kössler Wolfgang , Mukherjee Amitava 
Published: April 2024

AbstractThe paper deals with the classical two-sample problem for the combined location-scale and Lehmann alternatives, known as the versatile alternative. Recently, a combination of the square of the standardized Wilcoxon, the standardized Ansari–Bradley and the standardized Anti-Savage statistics based on the Euclidean distance has been proposed. The Anti-Savage test is the locally most powerful rank test for the right-skewed Gumbel distribution. Furthermore, the Savage test is the locally most powerful linear rank test for the left-skewed Gumbel distribution. Then, a test statistic combining the Wilcoxon, the Ansari–Bradley, and Savage statistics is proposed. The limiting distribution of the proposed statistic is derived under the null and the alternative hypotheses. In addition, the asymptotic power of the suggested statistic is investigated. Moreover, an adaptive test is proposed based on a selection rule. We compare the power performance against various fixed alternatives using Monte Carlo. The proposed test statistic displays outstanding performance in certain situations. An illustration of the proposed test statistic is presented to explain a biomedical experiment. Finally, we offer some concluding remarks.
The mechanisms of AI hype and its planetary and social costs
Authors: Markelius Alva , Wright Connor , Kuiper Joahna , Delille Natalie , Kuo Yu-Ting 
Published: April 2024

AbstractOur global landscape of emerging technologies is increasingly affected by artificial intelligence (AI) hype, a phenomenon with significant large-scale consequences for the global AI narratives being created today. This paper aims to dissect the phenomenon of AI hype in light of its core mechanisms, drawing comparisons between the current wave and historical episodes of AI hype, concluding that the current hype is historically unmatched in terms of magnitude, scale and planetary and social costs. We identify and discuss socio-technical mechanisms fueling AI hype, including anthropomorphism, the proliferation of self-proclaimed AI “experts”, the geopolitical and private sector “fear of missing out” trends and the overuse and misappropriation of the term “AI” in emerging technologies. The second part of the paper seeks to highlight the often-overlooked costs of the current AI hype. We examine its planetary costs as the AI hype exerts tremendous pressure on finite resources and energy consumption. Additionally, we focus on the connection between AI hype and socio-economic injustices, including perpetuation of social inequalities by the huge associated redistribution of wealth and costs to human intelligence. In the conclusion, we offer insights into the implications for how to mitigate AI hype moving forward. We give recommendations of how developers, regulators, deployers and the public can navigate the relationship between AI hype, innovation, investment and scientific exploration, while addressing critical societal and environmental challenges.
Talking existential risk into being: a Habermasian critical discourse perspective to AI hype
Authors: Westerstrand Salla , Westerstrand Rauli , Koskinen Jani 
Published: April 2024

AbstractRecent developments in Artificial Intelligence (AI) have resulted in a hype around both opportunities and risks of these technologies. In this discussion, one argument in particular has gained increasing visibility and influence in various forums and positions of power, ranging from public to private sector organisations. It suggests that Artificial General Intelligence (AGI) that surpasses human intelligence is possible, if not inevitable, and which can—if not controlled—lead to human extinction (Existential Threat Argument, ETA). Using Jürgen Habermas’s theory of communicative action and the validity claims of truth, truthfulness and rightness therein, we inspect the validity of this argument and its following ethical and societal implications. Our analysis shows that the ETA is problematic in terms of scientific validity, truthfulness, as well as normative validity. This risks directing AI development towards a strategic game driven by economic interests of the few rather than ethical AI that is good for all.
The effects of burosumab on growth, nephrocalcinosis and cardiovascular outcomes in children with X-linked hypophosphatemia: a single-center experience
Authors: Olivotto Bettyna , Akolly Eliane Djatougbé , Cabet Sara , Flammier Sacha , Bertholet-Thomas Aurélia , de Mul Aurélie , Bacchetta Justine 
Published: April 2024

Abstract
Purpose
X-linked hypophosphatemia (XLH) is the most common cause of inherited rickets. It is characterized by chronic hypophosphatemia due to increased levels of Fibroblast Growth Factor 23 hormone (FGF23), renal phosphate wasting, and decreased renal vitamin D hydroxylation. Burosumab, an anti-FGF23 antibody, was approved in 2018 for XLH children.

Methods
This retrospective single-center study assessed the progression of clinical, biological, renal, and cardiovascular outcomes of XLH patients who started burosumab before 18 years of age, between July 2018 and June 2022.

Results
In total, 12 children began burosumab treatment at a median age of 10.1(2.7–14.7) years, after 7.6 (1.1–11.3) years of conventional therapy. The last follow-up was 2.7(0.8–4.7) years after burosumab initiation, with 10 patients with at least 2 years of follow-up. Regarding the progression of anthropometric parameters, only height SDS significantly increased from baseline at the last follow-up. Regarding the biological parameters, as expected, at 12 months after starting burosumab and at the last follow-up, phosphate and alkaline phosphatase levels significantly improved. Although not significant, there was a trend towards an early increase of osteocalcin and crosslaps during the first months of therapy. Before starting burosumab, 5 patients (42%) had nephrocalcinosis (1 stage 1, 4 stage 2). One patient displayed a complete resolution of nephrocalcinosis after 1 year of treatment, and one patient showed improvement of nephrocalcinosis. No nephrocalcinosis appeared in a patient while being treated with burosumab. Cardiac ultrasounds remained normal in all.

Conclusion
Our real-life data confirm that burosumab improves outcomes in XLH children, including nephrocalcinosis and growth.
Uncertainty Quantification of Data-driven Quality Prediction Model For Realizing the Active Sampling Inspection of Mechanical Properties in Steel Production
Authors: Song Yong , Li Feifei , Wang Zheng , Zhang Baozhong , Zhang Borui 
Published: April 2024

AbstractPre-production quality defect inspection is a crucial step in industrial manufacturing, and many traditional inspection strategies suffer from inefficiency issues. This is especially true for tasks such as mechanical performance testing of steel products, which involve time-consuming processes like offline sampling, specimen preparation, and testing. The inspection volume significantly impacts the production cycle, inventory, yield, and labor costs. Constructing a data-driven model for predicting product quality and implementing proactive sampling inspection based on the prediction results is an appealing solution. However, the prediction uncertainty of data-driven models poses a challenging problem that needs to be addressed. This paper proposes an active quality inspection approach for steel products based on the uncertainty quantification in the predictive model for mechanical performance. The objective is to reduce both the sampling frequency and the omission rate on the production site. First, an ensemble model based on improved lower and upper bound estimation is established for interval prediction of mechanical performance. The uncertainty of the specific value prediction model is quantitatively estimated using interval probability distributions. Then, a predictive model for the mechanical performance failure probability is built based on the prediction interval size and probability distribution. By determining an appropriate probability threshold, the trade-off between prediction accuracy and defect detection accuracy (recall rate) is balanced, enabling the establishment of an active sampling strategy. Finally, this functionality is integrated into the manufacturing execution system of a steel factory, realizing a mechanical performance inspection approach based on proactive sampling. The proposed approach is validated using real production datasets. When the probability threshold is set to 30%, the prediction accuracy and recall rate for failure mechanical performance samples are 75% and 100%, respectively. Meanwhile, the sampling rate is only 5.33%, while controlling the risk of omission. This represents a 50% reduction in sampling rate compared to the inspection rules commonly used in actual production. The overall efficiency of product quality inspection is improved, and inspection costs are reduced.
Semiconductor Price Index Predicting Based on a Novel Improved AdaBoost Feature-Weighted Combination Model
Authors: Chen Feng , Jiang Qi , Deng Hongyu 
Published: April 2024

AbstractThe semiconductor price index serves as a vital metric for assessing technological developments and related market trends. Establishing a more accurate forecasting model for the semiconductor price index is of significant importance for analyzing the industry’s trends and market directions. In this paper, a novel framework for semiconductor price index forecasting is proposed. In addition to traditional financial data, the study introduces search engine data (Google Trends) representing investor attention, and introduces text information extracted from online news headlines reflecting major market events and government policies as independent variables. Used to predict the dependent variable: The PHLX Semiconductor Sector (SOX). First, the XGBoost model is employed to compute the importance scores of each feature. Then, a feature weight coefficient indicator is constructed based on these importance scores to calculate the weight coefficient indicator values for each feature. These indicator values are then used to weight the kernel function of Support Vector Regression (SVR), resulting in weighted Support Vector Regression (WSVR). Finally, WSVR is utilized as the base learner for Adaptive Boosting (AdaBoost), yielding the XGBoost–WSVR–AdaBoost model based on feature weighting. The proposed model outperforms AdaBoost, RNN, ERT, LSTM, and other models in terms of Mean Absolute Percentage Error (MAPE) and goodness-of-fit ($${R}^{2}$$R2). It also exhibits superior predictive performance compared to models in ablation experiments, and the introduction of text data or Google trends further improves the prediction performance of the model. In conclusion, the improved AdaBoost feature-weighted combination model proposed in this study offers a more accurate prediction for semiconductor price index.