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Constraining the primary growth channel of supermassive black holes (SMBHs) remains one the most actively debated questions in the context of cosmological structure formation. Owing to the expected connection between SMBH spin parameter evolution and the accretion and merger history of individual black holes, population spin measurements offer a rare observational window into the cosmic growth of SMBHs. As of today, the most common method for estimating SMBH spin relies on modeling the relativistically broaden atomic profiles in the reflection spectrum observed in X-rays. In this paper, we study the observational requirements needed to confidently distinguish between the primary SMBH growth channels based on their distinct spin-mass distributions predicted by the Horizon-AGN cosmological simulation. Indoing so, we characterize outstanding limitations associated with the existing measurements and discuss the landscape of future observational campaigns which could be planned and executed with future X-ray observatories. We focus our attention on the High-Energy X-ray Probe (HEX-P), a proposed probe-class mission designed to serve the high-energy community in the 2030s.

Background: Computational thinking (CT) has emerged as a critical component of 21st-century skills, and increasing effort was seen in exploring the development of CT skills in K-12 students. Despite cumulative research on exploring students' CT acquisition and its influencing factors, learners' development of the skill over time and the underlying mechanism that contributes to individual differences remain unclear. Objective: To bridge this gap, the present study aimed to explore the individual differences in CT acquisition among primary school students and how these differences were shaped over time. Specifically, variations in the development of CT across demographics, including gender and learning experience, were explored. Method: Three waves of data were collected from a sample of 322 primary school students (aged 7-12) across 18 months, with a 9-month interval between adjacent waves. A time-lagged model was leveraged for data analysis, and control variables were included in the model to strengthen statistical robustness. Results and Conclusion: The results indicate that male students and those who were more experienced in coding tended to have more positive attitudes toward coding. Additionally, coding interest was found to mediate the relationship between demographics and CT, demonstrating that male students and more experienced learners tended to be more interested in coding, which, in turn, contributed to the development of CT skills in later stages. Conclusion: The study provides valuable insights into the mechanisms underlying individual differences in CT development over time. The findings highlight the importance of nurturing coding interest among female students and promoting coding exposure for novice learners.

This study examined the developmental process of children's computational thinking using block-based programming tools, specifically algorithmic thinking and debugging skills. With this aim, a group of children (N = 191) from two primary schools were studied for two years beginning from the fourth grade, as they engaged in our block-based programming curriculum in their primary schools. A mixed-methods multiple case study was designed with pre- and posttests, classroom observations and postintervention interviews. The statistical results showed that students' algorithmic thinking and debugging skills significantly increased through our intervention, with girls gaining more on algorithmic thinking. During the students' learning process, we found that they demonstrated behavioral, affective, and cognitive engagement while acquiring these skills in schools. This study presents the key to student engagement contributing to the process of computational thinking development, with implications for the design of future computational learning in primary school.

Abstract This article details the development of a next-word prediction model utilizing federated learning and introduces a mechanism for detecting backdoor attacks. Federated learning enables multiple devices to collaboratively train a shared model while retaining data locally. However, this decentralized approach is susceptible to manipulation by malicious actors who control a subset of participating devices, thereby biasing the model’s outputs on specific topics, such as a presidential election. The proposed detection mechanism aims to identify and exclude devices with anomalous datasets from the training process, thereby mitigating the influence of such attacks. By using the example of a presidential election, the study demonstrates a positive correlation between the proportion of compromised devices and the degree of bias in the model’s outputs. The findings indicate that the detection mechanism effectively reduces the impact of backdoor attacks, particularly when the number of compromised devices is relatively low. This research contributes to enhancing the robustness of federated learning systems against malicious manipulation, ensuring more reliable and unbiased model performance.

As the impact of digital technologies pervades on our lives at all levels, it is important for students to develop their digital literacy. Computational thinking (CT) education is one pathway helping young students to thrive in the digital world. CT is a critical reasoning process whereby people formulate and solve problems using computers. CT education relies not only on schools and teachers, but also on parents. We reviewed 34 studies of the influence of parents on their children's CT education. We explore the following four aspects in CT education: (1) the contexts, (2) the effects regarding participation (affective, behavioral, and cognitive) outcomes in CT education, (3) the research designs, and (4) the mechanisms through which parents' participation influences children's CT education. Two theoretical frameworks, the tripartite model and parental involvement theory, were used to synthesize the 34 articles to analyze parents' affective, behavioral, and cognitive participation outcomes as well as the mechanisms of parental influence on CT education. We propose a conceptual framework of parental involvement in CT education. We further provide recommendations for supporting parents' involvement in children's CT education by suggesting appropriate parental mindsets and strategies to maximize the effectiveness of children's CT education.

As block-based visual programming platform such as Scratch become more accessible and supportive to children's programming learning, the demand on understanding a trajectory of children's computational thinking development through programming from their early ages increases rapidly in recent years. To explore the developmental process of children's computational thinking in twenty-first century, an experimental study was proposed to study the children's acquisition of computational thinking (CT) concepts and skills through compulsory lessons in schools starting in the fourth grade. A computational thinking framework along with six units of programming lessons were developed as a part of the research, aiming to develop primary (or elementary) school students' computational problem-solving skills through a hybrid-based design of programming activities: combining "unplugged" (i.e., embodied cognitive activities without computing devices) and "plugged" (i.e., programming activities with computing devices) approach. Five primary schools participated in our main study, and a mixed method research was conducted with 400 fourth grade students (Male = 259; Female = 141) and 18 teachers involved in delivering our designed lessons. The findings in our study show that students achieved learning gains in basic computational thinking skills in solving programming problems under this hybrid-based learning approach. These findings can give insight for educators and researchers interested in incorporating computational thinking in primary education, which sets forth a research direction on the developmental aspects of computational thinking for children in the neo-Piagetian perspective.

Background: Computational thinking (CT) has been broadly considered one of the 21st-century competencies, and an emerging trend has been seen in integrating CT into primary education. Cumulative research was conducted to investigate the influencing factors of CT learning performance, and an ample range of factors has been identified, involving both cognitive and non-cognitive facets. However, limited has been done in exploring the non-cognitive factors, and even less at the primary education level. Objective: To address this gap, this study bridged CT with personality in the primary school context, and more importantly, it proposed a mediator in the personality-CT relationship that is, attitudinal beliefs, which are amenable to change, thereby allowing further support for nurturing the traits. Method: Based on the Big Five model of personality, standard tests were administered to a sample of 434 primary school students (ages 8-11), and data were analysed using structural equation modelling via Mplus. To improve the robustness of the results, control variables (i.e., demographic features, coding experience) were added to the research model, and a bootstrap approach with 5000 resamples was used to examine the mediating effect. Result and Conclusion: Findings demonstrated that "Conscientiousness" had a positive effect on CT, and attitudinal beliefs mediated the effect of "Open-mindedness" (positive) and "Negative Emotionality" (negative) on CT. The study contributes to the literature by enriching the CT network with non-intellectual components and unravelling the mechanism of CT regarding how disposition traits turn into learning performance. The results implicate practitioners on the importance of encouraging conscientious behaviours and nurturing positive attitudinal beliefs in CT primary education.

Environmental aspects are becoming increasingly important for construction projects and thus holistic analysis spanning different scopes such as the building and city context. With graph-based data integration we propose a general method to support cross-domain analysis tasks. In this paper, we present a testbed consisting of a data set with three university buildings in IFC and CityGML format and two use cases for sustainability analysis spanning the building and city scope. We discuss the details of the data set and the two use cases - solar irradiation and material impact analysis - and show how graph-based data integration will be carried out in the testbed.

The immune response to an allograft activates lymphocytes with the capacity to cause rejection. Activation of CD4+CD25+Foxp3+T regulatory cells (Treg) can down-regulate allograft rejection and can induce immune tolerance to the allograft. Treg represent

Abstract Despite advances in ophthalmic diagnostics, the direct ophthalmoscope remains a key clinical skill taught to medical students and is the tool of choice for retina examination among non-ophthalmic physicians. However, in recent years viable alternatives have become available. The coronavirus disease 2019 (COVID-19) pandemic has forced a major re-thinking in medical education worldwide. In this commentary, we examined the current merits and limitations of the direct ophthalmoscope in both the clinical sense and in the context of infection control. Furthermore, we compared the direct ophthalmoscope with alternatives, including commercially available portable non-mydriatic fundus cameras, that would allow a change in focus during ophthalmic teaching. We concluded that the latter will better prepare our medical students for the age of telemedicine and deep-learning systems. While the COVID-19 pandemic will not be the sole reason for the ‘death’ of the direct ophthalmoscope, the global situation will inevitably serve to expedite long overdue changes in our teaching of ophthalmic skills to non-ophthalmic physicians.