bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Foundations of Critical Studies in Education in Finland
Authors: Kosunen Sonja , Kauko Jaakko , Seppänen Piia , Thrupp Martin 
Published: March 2023

AbstractThis chapter considers the historical roots of critical studies of Finnish education, particularly sociology, politics, and the history of education. It presents an interview with six emeriti professors who have participated in constructing the academic field. The chapter highlights their views about the greatest achievements of societally-oriented educational research in Finland, and what they considered the biggest disappointments or mistakes in this line of research.
Teachers’ Expectations and Expectations of Teachers: Understanding Teachers’ Societal Role
Authors: Juvonen Sara , Toom Auli 
Published: March 2023

AbstractBeing a teacher is an esteemed position in Finland. Finnish class teachers are academically educated professionals in five-year masters level programmes, where only a small percentage of applicants are accepted. However, in recent years, more teachers have reported having intentions to leave the profession, and there has been a slight decline in the number of applicants to teacher education programmes too. In this chapter, we elaborate Finnish expectations of teaching as a profession, set by society on the one hand, and teachers themselves on the other. Society sets both explicit and implicit expectations for teachers: teachers’ work is defined by a national curriculum as well as current policy aims, but is also moulded by the surrounding culture and norms. Teachers themselves are likely to have expectations of a personally fulfilling career; expectations that have begun to form already in their years as students in school, observing and learning what teachers and school are like. Schools, ideally, function to both maintain and reform society. We argue that expectations concerning teachers—normative expectations learned through observation in particular—act as part of the way schools maintain society. We ask whether Finnish teacher education today does enough to help teachers to assume their teacher role in society broadly and navigate the constantly changing field of education.
Herausforderungen der Translation von innovativen Produkten und Technologien in die klinische Praxis
Authors: Moser Lukas B. , Nehrer Stefan , Angele Peter , Aurich Matthias , Dyrna Felix , Hackl Wolfgang , Hess Silvan , Neubauer Markus , Niemeyer Philipp , Rupp Marco-Christopher , Zellner Johannes ,   das AGA-Komitee Innovation und Translation
Published: March 2023

ZusammenfassungIn Zeiten der zunehmenden Technisierung und Digitalisierung hat die Bedeutung der translationalen Medizin zugenommen. Eine erfolgreiche Translation von der Grundlagenforschung bis zur klinischen Anwendung ist ein kostspieliger und zeitaufwendiger Prozess, der von vielen Faktoren abhängt. Negative Beispiele aus der Vergangenheit (Thalidomid, Metall-Metall-Paarungen bei der Hüftendoprothetik) zeigen, dass eine Translation auch Risiken für die Patienten birgt. In den letzten Jahren wurden strengere Auflagen für die Herstellung und Zulassung von Medizinprodukten eingeführt, um die Patientensicherheit gewährleisten zu können. Die autologe Chondrozytentransplantation (ACT) ist ein Beispiel für eine gelungene Translation. Auf präklinische experimentelle Tierstudien folgten klinische Patientenstudien mit einer Marktzulassung und Implementation in den klinischen Alltag. Die Wirksamkeit allein ist nicht entscheidend, ob dieses Produkt auf dem Markt zugelassen wird. Zwischen der Grundlagenwissenschaft und der Bereitschaft des Markts, in die Weiterentwicklung und Kommerzialisierung eines Produkts zu investieren, ist eine erhebliche Hürde, die auch Tal des Todes genannt wird. Nur wenn diese Hürde überwunden wird, kommt es letztendlich zur Marktzulassung und zum klinischen Einsatz. Das Minced-cartilage-Verfahren zur Behandlung von fokalen Knorpelschäden hat kürzlich diese Hürde genommen und den Translationsprozess abgeschlossen. Aktuell liegen lediglich Kurzzeitergebnisse vor; frühzeitige Anwender verwenden diese Technik bereits, obwohl noch keine randomisierten Studien und mittelfristige Ergebnisse vorliegen. Weitere Studien werden zeigen, ob sich ein klinischer Nutzen abzeichnet und das Produkt am Markt bleibt.
Who is Exposed to HIV Prevention Interventions? An Assessment of Associated Factors Among Adolescent Girls and Young Women in South Africa
Authors: Jonas Kim , Beattie Daniel , Crutzen Rik , Mathews Catherine 
Published: March 2023

AbstractThis study examined the prevalence of HIV risk factors and their association with intervention exposure among adolescent girls and young women (AGYW) living in six South African districts in which a combination HIV-prevention intervention was being implemented. A cross-sectional household survey was conducted from 2017 to 2018 among a representative sample of AGYW aged 15–24 years living in the six districts. We used an electronic questionnaire for self-reported demographic and behavioural questions and blood samples were taken to confirm HIV status in the laboratory. Chi-Squared tests and multivariate binary logistic regression were used to examine associations between demographic characteristics, HIV acquisition and transmission risk factors and the likelihood of participating in any of the key components of the combination HIV-prevention intervention. Among the 4399 participants, 45.3% reported inconsistent condom use with casual partner and 46.6% with a main partner. Almost half of participants (47.8%) had participated in one or more components of the HIV-prevention intervention, and in a multivariate logistic regression, those reporting a higher number of HIV risk behaviours were no more (or less) likely to participate. Participants who were not in high school were significantly less likely to have participated in the intervention compared to those still in high school, when adjusting for age and HIV risk factors. The barriers to access and uptake of combination HIV prevention interventions among AGYW who are out of the education system need to be explored and combination HIV prevention interventions and implementation strategies need to be tailored to reach this population.
Predicting Coral Reef Carbonate Chemistry Through Statistical Modeling: Constraining Nearshore Residence Time Around Guam
Authors: Hirsh Heidi K. , Oliver Thomas A. , Barkley Hannah C. , Wren Johanna L. K. , Monismith Stephen G. , Manzello Derek P. , Enochs Ian C. 
Published: March 2023

AbstractTo accurately predict the impacts of ocean acidification on shallow-water ecosystems, we must account for the biogeochemical impact of local benthic communities, as well as the connectivity between offshore and onshore water masses. Estimation of residence time can help quantify this connectivity and determine the degree to which the benthos can influence the chemistry of the overlying water column. We present estimates of nearshore residence time for Guam and utilize these estimates to model the effects of benthic ecosystem metabolism on the coral reef carbonate system. Control volume and particle tracking approaches were used to estimate nearshore residence time. These estimates were paired with observed patterns in the reef carbonate system around Guam using water samples collected by NOAA’s National Coral Reef Monitoring Program. Model performance results suggest that when considering the effects of benthic metabolism on the carbonate system, it is paramount to represent the contact time of the water volume with the benthos. Even coarse estimates of residence time significantly increase model skill. We observed the highest predictive skill in models including control volume derived estimates of residence time, but only when those estimates were included as an interaction with benthic composition. This work shows that not only is residence time critically important to better predict biogeochemical variability in coral reef environments, but that even coarse hydrodynamic models can provide useful residence time estimates at management relevant, whole-ecosystem scales.
Concept maps as assessment for learning in university mathematics
Authors: Evans Tanya , Jeong Inae 
Published: March 2023

AbstractA concept map is a visualisation of a group of related concepts with their relationships identified by directed arrows, which can be viewed as an externalisation of a schema encoded in a learner’s long-term memory. Concept maps have become popular learning tools in various educational settings. However, the existing research has not fully explored the effectiveness of concept mapping as a learning tool nor analysed its utility as an assessment tool in mathematics. This study reports on the implementation and evaluation of a novel assessment, concept mapping, in a university mathematics course (N = 219). We investigated relationships between concept mapping performance and two major outcome variables: academic achievement and assessment self-efficacy (a two-factor measure comprising Comprehension and Execution and Emotional Regulation). Hierarchical multiple regression showed that concept mapping performance explains a statistically significant amount of variance in both the final exam scores and the Emotional Regulation factor of assessment self-efficacy after accounting for other conventional coursework assessments. The explained variance in the final exam suggests that concept mapping used as an assessment tool can detect and evaluate learners’ distinct capabilities that are not discerned by conventional assessments. Hence, concept mapping’s potential to assess conceptual understanding warrants further investigations. Moreover, the association with the emotional regulation efficacy measure suggests that concept mapping as a learning activity involves more positivity about the ability to succeed in facing challenges than a typical assignment. This potentially indicates more perseverance and effortful learning while actively engaged in meaning-making and the type of relational reasoning elicited by concept mapping.
Trace elements in farmland soils and crops, and probabilistic health risk assessment in areas influenced by mining activity in Ecuador
Authors: Romero-Crespo Paola , Jiménez-Oyola Samantha , Salgado-Almeida Bryan , Zambrano-Anchundia Johanna , Goyburo-Chávez Cindy , González-Valoys Ana , Higueras Pablo 
Published: March 2023

AbstractConsumption of food grown in contaminated soils may be a significant human exposure pathway to pollutants, including toxic elements. This study aimed to investigate the pollution level of trace elements in farmland soil and crops collected in orchards from Ponce Enriquez, one of the Ecuador’s most important gold mining areas. The concentration of arsenic (As), cadmium (Cd), chrome (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) was analyzed in soil and crop samples (celery, chives, corn, herbs, lettuce, turnips, green beans, cassava, and carrots). In addition, a probabilistic human health risk assessment, in terms of hazard quotients (HQ) and cancer risk (CR), was conducted to assess the potential risk related to local crop ingestion. The contents of As, Cr, Cu, and Ni in soils exceeded the Ecuadorian quality guidelines for agricultural soils. The trace elements concentration in local crops was higher than the maximum permissible levels set by the Food and Agriculture Organization of the United Nations (FAO). The HQ and CR of local crop ingestion were several orders higher than the safe exposure threshold, mainly for lettuce, chives, and turnips. Our results revealed that inhabitants of the study area are exposed to developing carcinogenic and non-carcinogenic effects due to long-term food consumption with high trace elements. This study sheds light on the need to assess further the quality of agricultural soils and crops grown in mining areas with signs of contamination to guarantee consumer food safety.
Characterization of a DRC1 null variant associated with primary ciliary dyskinesia and female infertility
Authors: Pereira R. , Carvalho V. , Dias C. , Barbosa T. , Oliveira J. , Alves Â. , Oliveira E. , Sá R. , Sousa M. 
Published: March 2023

Abstract
Propose
We here present a female case with primary ciliary dyskinesia (PCD) and infertility. In this report, we also present the evaluation of the patient family, including her twin sister, also with PCD and infertility.

Methods
Confirmation of the PCD clinical diagnosis was performed through assessment of cilia motility, by high-speed video microscopy (HSVM), axoneme ultrastructure, by transmission electron microscopy (TEM), and genetic characterization, by whole-exome sequence (WES). Gene expression studies used qPCR for mRNA expression and immunofluorescence to determine cell protein localization.

Results
We identified a homozygous nonsense variant in the DRC1 gene (NM 145038.5:c.352C>T (p.Gln118Ter)) in the female patient with PCD and infertility that fit the model of autosomal recessive genetic transmission. This variant eventually results in a dyskinetic ciliary beat with a lower frequency and a partial lack of both dynein arms as revealed by TEM analysis. Moreover, this variant implies a decrease in the expression of DRC1 mRNA and protein. Additionally, expression analysis suggested that DRC1 may interact with other DRC elements.

Conclusions
Our findings suggest that the DRC1 null variant leads to PCD associated with infertility, likely caused by defects in axoneme from Fallopian tube cilia. Overall, our outcomes contribute to a better understanding of the genetic factors involved in the pathophysiology of PCD and infertility, and they highlight the interaction of different genes in the patient phenotype, which should be investigated further because it may explain the high heterogeneity observed in PCD patients.
Magnetocaloric Effect in R6Fe23: R = Dy, Ho, Er, and Tm
Authors: Abu Elnasr Raghda , H. Aly Samy , Yehia Sherif , Mohammad Fatema Z. 
Published: March 2023

AbstractWe present a mean field study on the R6Fe23 system, where R = Dy, Ho, Er, and Tm, to calculate the magnetization, magnetic heat capacity, and the magnetocaloric effect (MCE) (isothermal entropy change (ΔSm) and the adiabatic temperature change (ΔTad)) for different field changes up to 5 T and at temperatures ranging from 0 to 600 K. The maximum ΔSm, using the trapezoidal method, for the R6Fe23 system is in the range 4.9–9.8 J/K mol, and the maximum ΔTad is in the range 9.56–15.17 K for a field change ΔH = 5 T. The largest ΔSm and largest ΔTad are found for Tm6Fe23 to be 9.8 J/K mol and 15.17 K at Curie temperature Tc = 489 K, for ΔH = 5 T. The relative cooling power RCP(S) is in the range 148–560 J/mol for ΔH = 5 T, which is comparable to that of bench-mark materials, e.g., Gd. Also, the RCP based on the adiabatic temperature change, RCP(T) is in the range 449–1092 K2 for ΔH = 5 T, which is comparable also to that of bench-mark materials, e.g., Gd. We investigated the type of phase transition in the light of universal curves, Arrott plots, and the behavior of the magnetic moment, magnetic heat capacity, and MCE (ΔSm, ΔTad), which confirm that the type of phase transition at Tc of this system is second-order phase transition (SOPT). A calculation of some critical exponents adds more evidence that the MFT is fairly suitable to handle the aforementioned properties in the studied systems.
UnbiasedNets: a dataset diversification framework for robustness bias alleviation in neural networks
Authors: Naseer Mahum , Prabakaran Bharath Srinivas , Hasan Osman , Shafique Muhammad 
Published: March 2023

AbstractPerformance of trained neural network (NN) models, in terms of testing accuracy, has improved remarkably over the past several years, especially with the advent of deep learning. However, even the most accurate NNs can be biased toward a specific output classification due to the inherent bias in the available training datasets, which may propagate to the real-world implementations. This paper deals with the robustness bias, i.e., the bias exhibited by the trained NN by having a significantly large robustness to noise for a certain output class, as compared to the remaining output classes. The bias is shown to result from imbalanced datasets, i.e., the datasets where all output classes are not equally represented. Towards this, we propose the UnbiasedNets framework, which leverages K-means clustering and the NN’s noise tolerance to diversify the given training dataset, even from relatively smaller datasets. This generates balanced datasets and reduces the bias within the datasets themselves. To the best of our knowledge, this is the first framework catering to the robustness bias problem in NNs. We use real-world datasets to demonstrate the efficacy of the UnbiasedNets for data diversification, in case of both binary and multi-label classifiers. The results are compared to well-known tools aimed at generating balanced datasets, and illustrate how existing works have limited success while addressing the robustness bias. In contrast, UnbiasedNets provides a notable improvement over existing works, while even reducing the robustness bias significantly in some cases, as observed by comparing the NNs trained on the diversified and original datasets.
Vessels Arrival Process and its Application to the SHIP/M/$$\infty$$ Queue
Authors: Di Crescenzo Antonio , Martinucci Barbara , Paraggio Paola 
Published: March 2023

AbstractIn modeling of port dynamics it seems reasonable to assume that the ships arrive on a somewhat scheduled basis and that there is a constant lay period during which, in a uniform way, each vessel can arrive at the port. In the present paper, we study the counting process N(t) which represents the number of scheduled vessels arriving during the time interval (0, t], $$t>0$$

t
>
0

. Specifically, we provide the explicit expressions of the probability generating function, the probability distribution and the expected value of N(t). In some cases of interest, we also obtain the probability law of the stationary counting process representing the number of arrivals in a time interval of length t when the initial time is an arbitrarily chosen instant. This leads to various results concerning the autocorrelations of the random variables $$X_i$$

X
i

, $$i\in \mathbb {Z}$$

i
∈
Z

, which give the actual interarrival time between the $$(i-1)$$

(
i
-
1
)

-th and the i-th vessel arrival. Finally, we provide an application to a stochastic model for the queueing behavior at the port, given by a queueing system characterized by stationary interarrival times $$X_i$$

X
i

, exponential service times and an infinite number of servers. In this case, some results on the average number of customers and on the probability of an empty queue are disclosed.
Sign language recognition from digital videos using feature pyramid network with detection transformer
Authors: Liu Yu , Nand Parma , Hossain Md Akbar , Nguyen Minh , Yan Wei Qi 
Published: March 2023

AbstractSign language recognition is one of the fundamental ways to assist deaf people to communicate with others. An accurate vision-based sign language recognition system using deep learning is a fundamental goal for many researchers. Deep convolutional neural networks have been extensively considered in the last few years, and a slew of architectures have been proposed. Recently, Vision Transformer and other Transformers have shown apparent advantages in object recognition compared to traditional computer vision models such as Faster R-CNN, YOLO, SSD, and other deep learning models. In this paper, we propose a Vision Transformer-based sign language recognition method called DETR (Detection Transformer), aiming to improve the current state-of-the-art sign language recognition accuracy. The DETR method proposed in this paper is able to recognize sign language from digital videos with a high accuracy using a new deep learning model ResNet152 + FPN (i.e., Feature Pyramid Network), which is based on Detection Transformer. Our experiments show that the method has excellent potential for improving sign language recognition accuracy. For instance, our newly proposed net ResNet152 + FPN is able to enhance the detection accuracy up to 1.70% on the test dataset of sign language compared to the standard Detection Transformer models. Besides, an overall accuracy 96.45% was attained by using the proposed method.
Performance analysis of coherent DPSK SIMO laser-based satellite-to-ground communication link over weak-to-strong turbulence channels considering Kolmogorov and non-Kolmogorov spectrum models
Authors: Abouelez Ahmed Elsayed 
Published: March 2023

AbstractThe performance of satellite-to-ground laser-based communication links is highly affected by atmospheric turbulence. Coherent detection with spatial diversity at the ground station receiver can mitigate the scintillation effects caused by atmospheric turbulence. Traditionally, the scintillation effects are modeled based on the Kolmogorov spectrum model. However, the experiments have indicated that scintillation effects on the laser beam propagation have non-Kolmogorov properties. Our goal in the present work is to analyze the average bit error rate (BER), outage probability (OP), and ergodic capacity of the satellite-to-ground heterodyne optical communication system with receiver spatial diversity. A differential phase-shift keying modulation technique is considered in this work. The propagated laser signal from the satellite to the ground station is assumed to be subjected to Málaga-distributed atmospheric turbulence. The atmospheric turbulence statistics are carried out based on the conventional Kolmogorov spectrum model and the three-layer altitude (TLA) non-Kolmogorov spectrum model. The performance of popular diversity combining techniques, namely, maximum ratio combining (MRC) and equal gain combining (EGC) techniques are analyzed. The statistical models of the MRC technique under the Málaga-distributed atmospheric channel model are obtained in analytical form expressions. The statistical models of the EGC technique under the Málaga-distributed atmospheric channel model are obtained via the fast Fourier transform representation of the characteristic function method. Based on these statistical models, average BER, OP, and ergodic capacity expressions for each type of diversity combining technique are derived. For the communication system under investigation, the performance of MRC and EGC multiple aperture receiver systems are compared to a single aperture receiver with the same total aperture area. These comparisons are carried out under the same conditions in terms of zenith angle and signal-to-noise ratio. The obtained results show that the performance of the optical communication system under investigation with MRC and EGC receivers can be improved by increasing the order of diversity. In addition, it is found that the difference in the performance between Kolmogorov and TLA non-Kolmogorov spectrum models is not significant at low zenith angles, while this difference increases as the zenith angle increases. All numerical results are verified by Monte-Carlo simulations.
Question sense, inquiry, and inventiveness
Authors: Freestone Melvin , Khan Khalid , Mason Jon 
Published: March 2023

AbstractThis article is a synthesis of possibility. A view of how question sense might generate inquiry and inventiveness across the gamut of human experience is presented. Dialogue between curiosity and questions spawns sense-making processes through which we can perceive and construct connections that have value. The application of a layered set of question frames energizes the construction of curious-concatenates that are precarious and continually networked across the template of human consciousness. They are created through intention and perceived value, and thereby, reflect underlying motivations in the life world, as distinct from psychological maturation. Ways in which curious-concatenates change and transform to make order out of disorder are discussed. The whole is synthesised into a two-phase iterative model for the generation and enactment of inventiveness, with a question-led process at the center. The implications for curriculum design and development and pedagogy are profound.