bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reforming Education in Times of Pandemic: The Case of Spain
Authors: Tiana-Ferrer Alejandro 
Published: September 2023

AbstractThis chapter examines how the impact of the pandemic interacted with the process of development and implementation of an education reform. The suspension of in person instruction was minimal, compared to other countries, and several programs supported the distribution of devices and connectivity. The pandemic heightened attention to wellbeing and mental health, and to pedagogical and organizational challenges, such as the overcrowded curriculum and the lack of teacher collaboration, as well as the conditions of vulnerability of socially marginalized students, the poor, immigrants, and students with disability. The recognition of these issues fed back into the process of development of the reform and incorporated them into the post-pandemic policy agenda.
Brazil. How Two Municipalities Achieved Above-Average Results in Reading in the Early Years of Elementary School During the COVID-19 Pandemic
Authors: Palacios Carlos , Bonamino Alicia 
Published: September 2023

AbstractThis chapter discusses the impacts of distance learning during the COVID-19 pandemic on students’ reading development in the early years of elementary school in Brazil and analyzes educational policies that may have mitigated part of these effects. The research focuses on reading assessments carried out in 2021 by CAEd/UFJF and Associação Bem Comum in ten Brazilian states. Although the assessments revealed major challenges for students’ literacy in many states, some municipalities managed to mitigate part of the effects of the pandemic, achieving above-average results. Two municipalities that reached rates of fluent students in reading higher than the average were selected for survey and analysis: Machados-PE and Coruripe-AL. This paper examines the public policies of these networks to identify and understand the actions that contributed to their unique performance in the assessment.
Post-Pandemic Crisis in Chilean Education. The Challenge of Re-institutionalizing School Education
Authors: Bellei Cristián , Contreras Mariana 
Published: September 2023

AbstractIn this chapter, we describe and analyze the available evidence (including our own research) about Chilean education during the COVID-19 pandemic and its efforts to recover once the health crisis was controlled. We show that the implementation of distance education produced markedly unequal experiences between schools and students, which essentially reinforced pre-existing inequalities and created new ones. This crisis was aggravated by the enormous difficulties encountered by the educational system to resume in-person activities, resulting in a massive and prolonged closure of Chilean schools. Additionally, the capacity to go back to school was very unevenly distributed, further harming the most disadvantaged students, both socioeconomically and socio-emotionally, as shown by the extreme difficulties of school reopening, teacher absenteeism and mental health problems, and student irregular attendance, learning losses and behavioral problems. Thus, the pandemic affected the very foundations of the regular operating of the Chilean education system triggering a multifaceted process of deinstitutionalization.
The Switch to Distance Teaching and Learning in Finland During the COVID-19 Pandemic (2020–2022) Went Technically Well but Was Emotionally Challenging
Authors: Salmela-Aro Katariina , Lavonen Jari 
Published: September 2023

AbstractIn this chapter, we analyze and discuss teaching, learning and well-being in Finnish education during the COVID-19 pandemic between Spring 2020 and Fall 2022. First, we analyze the preconditions, such as teachers’ and students’ digital competences and the digital infrastructure necessary to switch to distance teaching and learning. Second, we present the results of a survey concerning the organization and experience of teaching and learning during the COVID-19 pandemic. Third, we discuss the engagement and well-being of teachers, principals and students during the pandemic based on survey data. During the pandemic, teachers developed digital pedagogy and students enhanced their digital competence, and several digital pedagogy and co-teaching innovations were created. However, we identified decreased engagement among students, teachers, and principals during the pandemic and an increase in stress and burnout among teachers and principals. Principals felt the impact of the stress their teachers faced, and teachers struggled to make up for the differing efforts among families to cope with distance learning. Overall, the switch to distance teaching and learning was organized effectively, but the distance-learning period weakened the equality of teaching and the conditions that encourage learning and well-being.
Understanding Potential Causes of Learning Loss: Teachers’ Perceptions Regarding Educational Challenges During the COVID-19 Pandemic in Mexico
Authors: Cárdenas Sergio , Ruelas Ignacio , Sánchez Edson 
Published: September 2023

AbstractSchool lockdowns due to the COVID-19 pandemic resulted in a rapid transition from face-to-face to distance learning without considering teachers’ capacities and experience. Deep educational inequalities observed in Mexico before the pandemic made this change complex, disproportionately affecting the poorest students and their families. Estimations about the magnitude of the adverse effects of the transition on student learning are now available for different countries and regions. However, research on the factors explaining these adverse effects is limited, including how teachers reacted to the lockdown policies and adapted their instructional practices during the pandemic to adequately support all students. This chapter describes and analyzes teachers’ perceptions regarding the main barriers that affected their instructional activities during the pandemic to identify policy lessons that may inform the design of educational interventions for a post-pandemic stage.
The Fragility of the Norwegian Policy Response: How Relying on Digital Infrastructure and Local Autonomy Led to an Increase in Inequality in Education
Authors: Blikstad-Balas Marte 
Published: September 2023

AbstractNorway is in a privileged position globally in the sense that the country is wealthy, the population is well educated, and the digital infrastructure is robust and accessible to the entire population. However, Norway has some painful lessons to learn when evaluating its response to the global pandemic. Key aspects addressed in this chapter are the lack of a national response other than keeping schools open as much as possible, and the results of requiring individual principals and teachers to define the content and form of remote teaching. The lack of a national response targeting remote learning resulted in increased variation—and inequality—in the education available to students in Norway during the school years 2020 and 2021. Students spent a significant amount of time alone and unaided as they worked on individual written tasks. Furthermore, the system’s heavy reliance on pre-pandemic solutions to new problems may have resulted in a failure to recognize that the label, “vulnerable student” may mean something different during a pandemic than it traditionally would. For example, high-achieving students with two high-earning parents who worked long hours as physicians may have also suffered from a lack of support when school relied so heavily on parental involvement and self-regulation. Toward the end of the chapter, I will highlight some silver linings.
Pandemic Lessons: Story of Cooperation and Competition in Russian Education
Authors: Andreeva Anastasia A. , Koroleva Diana O. , Kosaretsky Sergei G. , Frumin Isaak D. 
Published: September 2023

AbstractThis chapter examines how main actors such as policymakers, school teams, and Edtech companies faced the pandemic challenges and whether they cooperated with each other. The analysis demonstrates that while before COVID-19, Russian schools and Edtechs rarely cooperated with each other, the partnership developed in response to the necessity of an emergency transition to distance learning. The government attempted to establish a nationwide infrastructure for distance learning and the vetting of educational content during the initial stages of the pandemic, however, this strategy was not implemented. Since the government did not immediately react to the situation, schools were forced to cope with the transition themselves. EdTech helped students, teachers, and regions deal with the crisis. After the pandemic, EdTech companies found themselves in a situation of increased government regulation, to which they reacted differently: some companies preferred to focus on B2C formats, while others responded with investments in the B2G sector. The school-Edtech partnership might be one of the most far-reaching positive changes of the pandemic for education, but our analysis shows this lesson has rather not been learned.
Pretty Good Strategies for Benaloh Challenge
Authors: Jamroga Wojciech 
Published: September 2023

AbstractBenaloh challenge allows the voter to audit the encryption of her vote, and in particular to check whether the vote has been represented correctly. An interesting analysis of the mechanism has been presented by Culnane and Teague. The authors propose a natural game-theoretic model of the interaction between the voter and a corrupt, malicious encryption device. Then, they claim that there is no “natural” rational strategy for the voter to play the game. In consequence, the authorities cannot provide the voter with a sensible auditing strategy, which undermines the whole idea.Here, we claim the contrary, i.e., that there exist simple rational strategies that justify the usefulness of Benaloh challenge.
Sustainable Fashion Product Development: The Importance of Skills in New Materials and Processes in the Academy and Industry Context
Authors: Bicho Marta , Pereira Madalena , Barata Teresa Raquel , Belino Nuno , Miguel Rui 
Published: September 2023

AbstractMaterials and processes play an increasingly significant role in the development of new fashion products and can significantly affect product sustainability and longevity. These aspects, like many others, are part of the numerous issues associated with sustainability [1, 2]. The Fashion ecosystem has a high impact on society and the environment. Sustainability is an important issue for the textile and clothing industry associated with the different stages of the product life cycle and their impacts. The skills of specialists in fashion product development (FPD) and respective training will have to evolve towards increased knowledge of materials and processes; however, the academy is not keeping up with these changes that go along with the rapid transformation of the industry. There is a need for new competence acquisition models that are tailored to the present-day requirements. The objective of this investigation concerns the use and validation of a set of methodologies for the acquisition of skills by students, which allows for the development of sustainable fashion products for the market. Active methodologies that are being used, include workshops, competitions, industry partnerships, and PD in the context of companies and academy, and using trainers with experience in the industry. It concludes a progress in the knowledge of sustainable materials and processes combined with motivation.
Missing Health Data Pattern Matching Technique for Continuous Remote Patient Monitoring
Authors: Arora Teena , Balasubramanian Venki , Stranieri Andrew 
Published: September 2023

AbstractRemote patient monitoring (RPM) has been gaining popularity recently. However, health data acquisition is a significant challenge associated with patient monitoring. In continuous RPM, health data acquisition may miss health data during transmission. Missing data compromises the quality and reliability of patient risk assessment. Several studies suggested techniques for analyzing missing data; however, many are unsuitable for RPM. These techniques neglect the variability of missing data and provide biased results with imputation. Therefore, a holistic approach must consider the correlation and variability of the various vitals and avoid biased imputation. This paper proposes a coherent computation pattern-matching technique to identify and predict missing data patterns. The performance of the proposed approach is evaluated using data collected from a field trial. Results show that the technique can effectively identify and predict missing patterns.
An Approach for Modeling Annotation in the e-Health Domain
Authors: Mannai Zayneb , Kalboussi Anis , Kacem Ahmed Hadj 
Published: September 2023

AbstractIn our research, we established a medical annotation model in the form of an ontology in an effort to ensure data interchange amongst medical annotation systems. We employ the “patient partner” approach to involve the patient in the medical annotative activity. In fact, the patient will be able to register, annotate, and comprehend the comments made in his medical file utilizing this new paradigm.
Comparative Usability Testing Between Lightweight Power Wheelchairs: Focused on People with Physical Disabilities in the Community
Authors: Kwon Yeong-hun , Kim Dong-wan , Kim Jongbae 
Published: September 2023

AbstractThere have been studies on Lightweight Power Wheelchairs (LPW) that compensate for the disadvantages of large and heavy powered wheelchairs for the activities of the people with physical disabilities in the community, but there is a lack of research to understand usability. Accordingly, we compared the usability of LPWs developed in Korea for 5 wheelchair participants and caregivers to find out their effectiveness, efficiency, and satisfaction. As a result of the usability testing, there was a difference between the two LPWs in effectiveness and satisfaction. LPW1 was analyzed as grade B/’Good’ usability LPW2 was analyzed as grade A/’Best Imaginable’ usability. The usability of the heavier LPW2 was highly appreciated. This can be interpreted that users feel a sense of stability in the LPW with a certain amount of weight. In future studies, it is considered necessary to study the appropriate weight of LPW that users can feel stable.
Deriving Physiological Information from PET Images Using Machine Learning
Authors: Gassara Olfa , Chikhaoui Belkacem , Mabrouk Rostom , Wang Shengrui 
Published: September 2023

AbstractMachine learning (ML) algorithms have become popular in recent years and have found increasing utility in the field of medical imaging, specifically in positron emission tomography (PET) imaging. The interest in ML in PET imaging for the study of neurodegenerative diseases stems from the potential of these techniques to analyze and predict the physiological parameters of biomarkers such as the total volume of distribution (V$$_{\text {t}}$$

t

) in the organ or a structure of the organ to be explored. In this paper, we investigated whether the V$$_{\text {t}}$$

t

of [$$^{18}$$

18

F]-FEPPA radiotracer, an indicator of neuroinflammation, could be estimated directly in a non-invasive way, given the activity of the radiotracer in brain tissue. The study used several regression models to predict the [$$^{18}$$

18

F]-FEPPA V$$_{\text {t}}$$

t

in different brain regions where 31 regions of interest were defined for each of 24 patients with Parkinson disease and 20 healthy subjects, and were used to train four tree-based regression models. The predicted and reference values were compared by Bland-Altman analysis and regression model’s performance was evaluated by the mean absolute error (MAE). The best result was obtained by the XGBoost model with a MAE of 2.6. Bland-Altman analysis results indicate that predicted V$$_{\text {t}}$$

t

are in average very close to the reference with a bias of 0.23 "Image missing" 2.82. Significant main effect of genotype on [$$^{18}$$

18

F]-FEPPA in both caudate and putamen have been preserved by predicted Vt values (p < 0.05). The results of paired t-test indicate that the difference between predicted and reference V$$_{\text {t}}$$

t

is not statistically significant in 6 out of 8 groups. The proposed algorithms provide a non-invasive and efficient tool to predict [$$^{18}$$

18

F]-FEPPA V$$_{\text {t}}$$

t

values, a hallmark of neuroinflammation that is believed to be a potential trigger for Parkinson’s disease development.
Ontology Alignment for Accurate Ontology Matching: A Survey
Authors: Khan Hasham , Saqib Muhammad , Khattak Hasan Ali , Ali Syed Imran , Lee Sungyoung 
Published: September 2023

AbstractEdge computing, a distributed computing architecture within the knowledge-defined network (KDN), faces challenges due to the significant disparities and data heterogeneity among its nodes, hindering their interaction. Ontology, a solution within the Semantic Web, is well-suited for addressing data heterogeneity and matching ontologies effectively. However, ontology matching presents difficulties due to non-linear mathematical issues. To overcome these challenges, the generative adversarial network (GAN), an unsupervised learning method, has emerged as a promising tool. GAN consists of two models with distinct objectives trained against eachother to achieve optimal outcomes. This paper introduces SA-GAN, an algorithm that combines GAN with simulation-based annealing to enhance its effectiveness. SA-GAN utilizes a stagnation counter to expedite the convergence speed of GAN. Through experiments conducted on a renowned ontology benchmark, the paper demonstrates that SA-GAN, along with other ontology matching algorithms, can identify the best alignments. Consequently, SA-GAN facilitates the construction of bridges in edge computing, improving its overall effectiveness.
Towards a Medical Test Results Management System Based on Blockchain, Smart Contracts, and NFT: A Case Study in Vietnam
Authors: Anh N. T. , Khanh V. H. , Phuc N. T. , Khoa T. D. , Khiem H. G. , Trong N. D. P. , Loc V. C. P. , Duy N. T. Q. , Bao T. Q. , Hieu D. M. , Nghia H. T. , Ngan N. T. K. , Huong L. H. 
Published: September 2023

AbstractThe role of medical test results in the diagnosis and treatment of a patient’s disease cannot be denied. Doctors and medical staff rely on these results to develop a treatment plan that meets the requirements of the patient’s health status (i.e., physical condition) and disease type. In developing countries (i.e., Vietnam), we note that test results are recorded in paper versions and stored by patients. Thus, several solutions have been introduced for electronic medical records to compensate for medical test results management. However, in Vietnam, these approaches face many obstacles such as centralized processing (e.g., storage, analysis); non-transparency issues; scalability; availability; and so on. In this paper, we exploit the benefits of blockchain, smart contracts, and NFT technologies to solve the above disadvantages. Therefore, our work contributes to five aspects. (a) Collecting procedures for handling and storing test results of patients at hospitals in Ho Chi Minh City and Mekong Delta (i.e., Can Tho city) (b) Proposing a mechanism for sharing test results based on blockchain technology, smart contract, and NFT applied; (c) Presenting an NFT tool-based certification generation model; (d) implementing the proposed model based on smart contracts (i.e., proof-of-concept); and (e) deploying proof-of-concept on four EVM- and NFT-supported platforms to find the most suitable one.
Open-closed string field theory in the large N limit
Authors: Maccaferri Carlo , Ruffino Alberto , Vošmera Jakub 
Published: September 2023

Abstract
We use the new nilpotent formulation of open-closed string field theory to explore the limit where the number N of identical D-branes of the starting background is large. By reformulating the theory in terms of the ’t Hooft coupling λ := κN, where κ is the string coupling constant, we explicitly see that at large N only genus zero vertices with arbitrary number of boundaries survive. After discussing the homotopy structure of the obtained large N open-closed theory we discuss the possibility of integrating out the open string sector with a quantum but planar homotopy transfer. As a result we end up with a classical closed string field theory, described by a weak L∞-algebra containing a tree-level tadpole which, to first order in λ, is given by the initial boundary state. We discuss the possibility of removing the tadpole with a closed string vacuum shift solution, to end up with a new classical closed string background, where the initial D-branes have been turned into pure closed-string backreaction.
Critical functions of extracellular matrix in brain metastasis seeding
Authors: Yuzhalin Arseniy E. , Yu Dihua 
Published: September 2023

AbstractHuman brain is characterized by extremely sparse extracellular matrix (ECM). Despite its low abundance, the significance of brain ECM in both physiological and pathological conditions should not be underestimated. Brain metastasis is a serious complication of cancer, and recent findings highlighted the contribution of ECM in brain metastasis development. In this review, we provide a comprehensive outlook on how ECM proteins promote brain metastasis seeding. In particular, we discuss (1) disruption of the blood–brain barrier in brain metastasis; (2) role of ECM in modulating brain metastasis dormancy; (3) regulation of brain metastasis seeding by ECM-activated integrin signaling; (4) functions of brain-specific ECM protein reelin in brain metastasis. Lastly, we consider the possibility of targeting ECM for brain metastasis management.
Flammenfiguren – Eosinophile, die die Haut in Brand setzen
Authors: Stahl Lea-Sophie , Wolters Ann-Christin , Kautz Ocko , Patsinakidis Nikolaos , Raap Ulrike 
Published: September 2023

ZusammenfassungEine 50-jährige Landwirtin mit der initialen Verdachtsdiagnose eines Granuloma anulare disseminatum wurde über 10 Jahre lokal mittels topischen Glukokortikoiden sowie wiederholten Phototherapien ohne suffizienten Erfolg behandelt. Im Rahmen der Vorstellung in unserer Klinik erfolgte eine histopathologische Untersuchung mit dem Ergebnis einer eosinophilen Zellulitis mit typischen „flame figures“ in der Histologie. Durch eine Systemtherapie mit Steroidstoßtherapie zeigte sich eine Abheilung der Hautveränderungen sowie des ausgeprägten Pruritus. Dieser Kasus stellt einen Bericht über eine erfolgreiche Therapie einer Patientin mit eosinophiler Zellulitis dar.
Geriatrischer Patient mit neurologischer Symptomatik und verlängerter aPTT
Authors: Atakanova Aisuluu , Heiligers Anne , Kirschner Martin , Bollheimer Cornelius , Fleig Susanne 
Published: September 2023

ZusammenfassungEin 73-jähriger Mann mit vorbekannter demenzieller Entwicklung wurde mit Hypernatriämie bei Volumendepletion aufgenommen. Ursächlich dafür zeigte sich eine neue neurogene Schluckstörung, bei Z. n. mehreren Schlaganfällen bestand eine Halbseitensymptomatik. Bei der Sichtung der Unterlagen vorangegangener Krankenhausaufenthalte fiel wiederholt eine verlängerte aPTT (aktivierte partielle Thromboplastinzeit) auf; bereits fünf Jahre zuvor bestand ambulant der Verdacht auf ein Antiphospholipidantikörpersyndrom (APS), ohne dass die Diagnostik komplettiert worden wäre. Wir haben die Diagnose eines primären APS gestellt und eine Antikoagulation mit Vitamin-K-Antagonisten und ASS (Acetylsalicylsäure) begonnen.