bluuebunny/crossref_metadata_2025_split huggingface dataset:
Primary Preservice Teachers’ Mathematics Teaching Efficacy Beliefs: the Role Played by Mathematics Attainment, Educational Level, Preparedness to Teach, and Gender
Authors: Twohill Aisling , NicMhuirí Siún , Harbison Lorraine , Karakolidis Anastasios 
Published: March 2022

AbstractThis paper reports on research which explored the mathematics teaching efficacy beliefs of preservice primary teachers, where efficacy beliefs describe individuals’ beliefs in their potential to enact teaching to promote learning. Efficacy was conceptualised as a bi-faceted construct consisting of personal efficacy and outcome expectancy. This research sought to establish the extent to which differences in efficacy are explained by students’ mathematics attainment level prior to entry into teacher education; the educational level of the students (whether postgraduate or undergraduate); students’ sense of preparedness to teach mathematics on school placement; and students’ gender. A total of 186 students responded to a questionnaire designed to measure their efficacy beliefs after completing one taught mathematics education module in university and one teaching practice placement in primary schools. Bivariate and regression analysis pointed to complex relationships between the explanatory and outcome variables. On bivariate analysis, findings included statistically significant associations between gender, mathematics attainment, preparedness to teach, and one or both of personal efficacy and outcome expectancy. In the regression analysis, gender was statistically significantly associated with outcome expectancy, while preparedness to teach and mathematics attainment were statistically significantly correlated with personal efficacy. Personal efficacy and outcome expectancy were significantly correlated on bivariate analysis, but significance was not retained after controlling for other factors in the regression models. This research has implications for teacher educators in understanding factors explaining mathematics teaching efficacy and therefore helping to better prepare preservice teachers to teach mathematics in the primary school classroom.
An Efficient, Memory-Saving Approach for the Loewner Framework
Authors: Palitta Davide , Lefteriu Sanda 
Published: March 2022

AbstractThe Loewner framework is one of the most successful data-driven model order reduction techniques. If N is the cardinality of a given data set, the so-called Loewner and shifted Loewner matrices $${\mathbb {L}}\in {\mathbb {C}}^{N\times N}$$

L
∈

C

N
×
N

and $${\mathbb {S}}\in {\mathbb {C}}^{N\times N}$$

S
∈

C

N
×
N

can be defined by solely relying on information encoded in the considered data set and they play a crucial role in the computation of the sought rational model approximation.In particular, the singular value decomposition of a linear combination of $${\mathbb {S}}$$
S
and $${\mathbb {L}}$$
L
provides the tools needed to construct accurate models which fulfill important approximation properties with respect to the original data set. However, for highly-sampled data sets, the dense nature of $${\mathbb {L}}$$
L
and $${\mathbb {S}}$$
S
leads to numerical difficulties, namely the failure to allocate these matrices in certain memory-limited environments or excessive computational costs. Even though they do not possess any sparsity pattern, the Loewner and shifted Loewner matrices are extremely structured and, in this paper, we show how to fully exploit their Cauchy-like structure to reduce the cost of computing accurate rational models while avoiding the explicit allocation of $${\mathbb {L}}$$
L
and $${\mathbb {S}}$$
S
. In particular, the use of the hierarchically semiseparable format allows us to remarkably lower both the computational cost and the memory requirements of the Loewner framework obtaining a novel scheme whose costs scale with $$N \log N$$

N
log
N

.
Religiosity and Quality of Life in Older Christian Women in Ireland: A Mixed Methods Analysis
Authors: Orr Joanna , Kenny Rose Anne , McGarrigle Christine A. 
Published: March 2022

AbstractThis study used a mixed methods approach to understand the ways in which religion and quality of life (QoL) are associated in later life in Ireland. Longitudinal quantitative data from 2112 Christian women aged 57 and over at baseline (2009–10) participating in the Irish Longitudinal Study on Ageing (TILDA), as well as qualitative data from semi-structured interviews from 11 Christian women aged 65 and over in 2018, were used. The quantitative data showed an association between lower religiosity and lower QoL. Qualitative data supported an effect of religious involvement on QoL although certain aspects of being religious in Ireland were accompanied by distress. The data suggested that the relationship between religious attendance and higher QoL could be driven by multifactorial pathways, including psychological, social, and practical benefits.
Solid wood impregnated with a bio-based phase change material for low temperature energy storage in building application
Authors: Nazari Meysam , Jebrane Mohamed , Terziev Nasko 
Published: March 2022

AbstractWood impregnated with a multicomponent mixture of fatty acids as a bio-based phase change material (BPCM) to improve its thermal characteristics was studied. The studied wood/BPCM composites can be used as internal elements in buildings for energy storage. Scots pine and beech sapwood were impregnated with a multicomponent mixture of linoleic acid and coconut oil fatty acids at a ratio of 20:80. Leakage test was conducted and revealed that the maximum leakage for pine and beech were 9 and 8%, respectively. Light microscopy was employed to demonstrate the distribution of the BPCM in the wood structure. Rays in both pine and beech wood served as pathways for impregnation of the BPCM to partly fill the tracheid lumens (pine) and vessels (beech). Thermal characterization of the studied samples employed T-history and DSC methods, concluding that the impregnated wood had significant thermal mass, ability to store excessive energy in terms of latent heat and keep the temperature constant for long time. The specific heat capacity of the impregnated samples was 4–5 J g−1 K−1 i.e., higher than that of the untreated control samples of ca. 2 J g−1 K−1. The thermal conductivity of the samples before and after the impregnation was measured using heat flow meter method and the results showed that the untreated beech wood had higher thermal conductivity compared to pine and the parameter improved when the cell lumens were filled with the BPCM. Scots pine wood with to 80% mass percentage gain (MPG) after impregnation demonstrated an increment in thermal conductivity of 33% while Scots pine and beech with 43 and 38% MPG demonstrated an increase of the conductivity with 8 and 11%, respectively.
Robustness verification of ReLU networks via quadratic programming
Authors: Kuvshinov Aleksei , Günnemann Stephan 
Published: March 2022

AbstractNeural networks are known to be sensitive to adversarial perturbations. To investigate this undesired behavior we consider the problem of computing the distance to the decision boundary (DtDB) from a given sample for a deep neural net classifier. In this work we present a procedure where we solve a convex quadratic programming (QP) task to obtain a lower bound on the DtDB. This bound is used as a robustness certificate of the classifier around a given sample. We show that our approach provides better or competitive results in comparison with a wide range of existing techniques.
Performance evaluation of salient object detection techniques
Authors: Ahmed Kareem , Gad Mai A. , Aboutabl Amal Elsayed 
Published: March 2022

AbstractRecently, the detection and segmentation of salient objects that attract the attention of human visual in images is determined by using salient object detection (SOD) techniques. As an essential computer vision problem, SOD has increasingly attracted the researchers’ interest over the years. While a lot of SOD models and applications have been proposed, there is still a lack of deep understanding of the issues and achievements. A comprehensive study on the recent techniques of SOD is provided in this paper. Precisely, this paper presents a review of SOD techniques from various perspectives. Various image segmentation techniques are presented such as segmentation based on machine learning or deep learning, the second perspective concentrates on classifying them into supervised and unsupervised learning techniques and the last one based on manual approach, semi-automatic approach, and fully automatic approach and so on. Then, the paper presents a summarization of datasets used for SOD. Finally, analyses of SOD models and comparison results are presented.
A methodology for mapping of quick clay in Sweden
Authors: With Christoffer , Löfroth Hjördis , Bastani Mehrdad , Persson Lena , Rodhe Lars , Hedfors Jim , Schoning Kristian 
Published: March 2022

AbstractLandslides may cause severe destruction that affects both the individuals and functions vital for society. Minor landslides in an area with quick clay may trigger secondary slides, influencing a much greater area compared to slides in areas with no quick clay. Today’s expanding societies demand new areas for exploitation. To effectively meet this demand, there is an increased need to identify areas where quick clay may occur. Direct or indirect methods for assessing the presence of quick clay have previously been presented as well as a strategy for site investigations in quick clay areas. In this article, a methodology for mapping quick clays for the Swedish conditions with methods commonly available in this area is presented. The methodology presented in the article is structured in steps with different levels of detail and visualized with two conceptual flowcharts. Depending on the stage of planning, different types of surveys are recommended. The methodology has been applied at four sites where integrated interpretation of airborne and ground geophysical measurements as well as geotechnical investigations have been carried out. The results from two of these sites are presented here. The study reveals that all the methods used have their advantages and limitations. However, a combined use of the information provides much more accurate interpretation that can be used for a more cost-effective future planning and decision-making.
Recent technological advancements in membrane distillation and solar stills: preheating techniques, heat storage materials, and nanomaterials — a detailed review
Authors: Abdelgaied Mohamed , Seleem Mohamed Fathi , Bassuoni Mohamed Mahgoub 
Published: March 2022

AbstractFreshwater and energy are critical components for the growth and progress of societies. The scarcity of freshwater and rapid population growth, especially in remote countries, has led to an urgent need to develop desalination technologies in order to raise its productivity and reduce its energy consumption rates. Membrane distillation is one of the effective methods characterized by its high productivity, but its disadvantage by higher electricity consumption. Also, solar stills are one of the sustainable and economical technologies, but the disadvantage by lower productivity. Accordingly, this manuscript dealt with a comprehensive review and detailed comparison of the most important modifications and innovations that were made to the design of the membrane distillation units, which aim to reduce electricity consumption rates, as well as the design of solar stills, which aims to maximize the productivity and efficiency. This was done by providing a detailed comparison of the most important three axes of modifications and innovations that were addressed by recent previous studies on the design of membrane distillation units and solar stills, and their statement as follows: preheating technology, use of the thermal storage materials, and nanomaterials technology. Finally, based on this review, the authors make some recommendations for future work in the field of solar and membrane desalination.
Auto-splitting D* lite path planning for large disaster area
Authors: Heo Shin-nyeong , Chen Jiaheng , Liao Yu-chi , Lee Hee-hyol 
Published: March 2022

AbstractThis research introduces a new path planning method for rescue robots in a dynamic and partially known area when the robots are performing tasks in a large area. The path planning of the rescue robots that move in the dynamic area is introduced to solve the issue of unnecessary areas, which are the disadvantages of the existing D*-based algorithms. This paper proposes a method to eliminate unnecessary expanded nodes of the dynamic and partially known environment by segmenting a map with an auto-clustering algorithm, which is able to achieve a faster execution time than conventional algorithms. Furthermore, to show the effectiveness of the proposed algorithms, an expected value of re-planned nodes in the dynamic and partially known area is introduced using a probability-based approach.
The blood-to-plasma ratio and predicted GABAA-binding affinity of designer benzodiazepines
Authors: Manchester Kieran R. , Waters Laura , Haider Shozeb , Maskell Peter D. 
Published: March 2022

Abstract
Purpose
The number of benzodiazepines appearing as new psychoactive substances (NPS) is continually increasing. Information about the pharmacological parameters of these compounds is required to fully understand their potential effects and harms. One parameter that has yet to be described is the blood-to-plasma ratio. Knowledge of the pharmacodynamics of designer benzodiazepines is also important, and the use of quantitative structure–activity relationship (QSAR) modelling provides a fast and inexpensive method of predicting binding affinity to the GABAA receptor.

Methods
In this work, the blood-to-plasma ratios for six designer benzodiazepines (deschloroetizolam, diclazepam, etizolam, meclonazepam, phenazepam, and pyrazolam) were determined. A previously developed QSAR model was used to predict the binding affinity of nine designer benzodiazepines that have recently appeared.

Results
Blood-to-plasma values ranged from 0.57 for phenazepam to 1.18 to pyrazolam. Four designer benzodiazepines appearing since 2017 (fluclotizolam, difludiazepam, flualprazolam, and clobromazolam) had predicted binding affinities to the GABAA receptor that were greater than previously predicted binding affinities for other designer benzodiazepines.

Conclusions
This work highlights the diverse nature of the designer benzodiazepines and adds to our understanding of their pharmacology. The greater predicted binding affinities are a potential indication of the increasing potency of designer benzodiazepines appearing on the illicit drugs market.
Field and numerical study of the lateral response of rigid piles in sand
Authors: Wang H. , Lehane B. M. , Bransby M. F. , Wang L. Z. , Hong Y. 
Published: March 2022

AbstractLarge diameter, short monopiles are the preferred foundation type for offshore wind turbines. These piles demonstrate a rigid response with significant rotation of the pile base under ultimate lateral load. As traditional empirical p-y curves used in lateral loaded pile analysis have been derived from tests on small diameter onshore piles, there is some doubt about their applicability to rigid monopiles, particularly in view of the significant difference in the response of the pile base compared with a typical onshore pile. To address this issue, this paper reports on a unique series of field tests using instrumented driven pipe piles, complimented by numerical analysis, which was performed to examine explicitly the contribution of the pile base to the response under lateral load. The field tests, which included tests on pipe piles that had the sand plug removed to below pile tip level prior to testing, confirmed that the influence of the base on the lateral response for the tested 273- and 457-mm-diameter piles was negligible. Numerical analyses that were calibrated using the field test data showed that the contribution of the base to the lateral capacity of a monopile with a diameter as large as 10 m is negligible. Results also indicated that p-y curves are not affected by the length to diameter ratio and can be used to predict the response of monopiles in sand.
Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images
Authors: Van Houtte Jeroen , Audenaert Emmanuel , Zheng Guoyan , Sijbers Jan 
Published: March 2022

Abstract
Purpose
The registration of a 3D atlas image to 2D radiographs enables 3D pre-operative planning without the need to acquire costly and high-dose CT-scans. Recently, many deep-learning-based 2D/3D registration methods have been proposed which tackle the problem as a reconstruction by regressing the 3D image immediately from the radiographs, rather than registering an atlas image. Consequently, they are less constrained against unfeasible reconstructions and have no possibility to warp auxiliary data. Finally, they are, by construction, limited to orthogonal projections.

Methods
We propose a novel end-to-end trainable 2D/3D registration network that regresses a dense deformation field that warps an atlas image such that the forward projection of the warped atlas matches the input 2D radiographs. We effectively take the projection matrix into account in the regression problem by integrating a projective and inverse projective spatial transform layer into the network.

Results
Comprehensive experiments conducted on simulated DRRs from patient CT images demonstrate the efficacy of the network. Our network yields an average Dice score of 0.94 and an average symmetric surface distance of 0.84 mm on our test dataset. It has experimentally been determined that projection geometries with 80$$^{\circ }$$

∘

to 100$$^{\circ }$$

∘

projection angle difference result in the highest accuracy.

Conclusion
Our network is able to accurately reconstruct patient-specific CT-images from a pair of near-orthogonal calibrated radiographs by regressing a deformation field that warps an atlas image or any other auxiliary data. Our method is not constrained to orthogonal projections, increasing its applicability in medical practices. It remains a future task to extend the network for uncalibrated radiographs.
Präventionsbedarfe und -interessen bei Berufslernenden
Authors: Paz Castro Raquel , Meyer Christian , Rumpf Hans-Jürgen , Schaub Michael P. , Wenger Andreas , Haug Severin 
Published: March 2022

Zusammenfassung
Hintergrund
Bislang ist zum Sucht- und Gesundheitsverhalten von Jugendlichen, die berufliche Schulen besuchen, nur wenig bekannt.

Ziel der Arbeit
Auf Grundlage der Daten einer Stichprobe Berufslernender in der Schweiz wird untersucht, (1) in welchen demographischen Subgruppen Suchtverhaltensweisen, Belastungs- und Schutzfaktoren besonders prävalent sind und (2) welche Themen innerhalb eines multibehavioralen Suchtpräventionsprogramms für Berufslernende auf besonderes Interesse stoßen.

Material und Methoden
Insgesamt nahmen im Schuljahr 2020/2021 58 % der Berufslernenden aus 60 Schulen und 493 Schulklassen an einer Gesundheitsbefragung im Rahmen des Präventionsprogramms ready4life teil. Die Daten von 5622 (von 7495, 75 %) Lernenden, die ihr Einverständnis zur Teilnahme am Programm gaben, liegen vor. Anhand von Mehrebenenmodellen und Regressionen wurden Zusammenhänge zwischen demographischen Merkmalen und Suchtverhaltensweisen, Belastungs- und Schutzfaktoren untersucht.

Ergebnisse
Die Mehrheit der Berufslernenden (77,1 %) zeigte ein risikoreiches Suchtverhalten in einem bis drei der vier untersuchten Bereiche (1) Alkoholkonsum, (2) Tabak‑/Nikotinkonsum, (3) Cannabiskonsum und (4) Internetgebrauch. Weibliche Lernende berichteten häufiger, sich gestresst, wenig sozialkompetent und selbstwirksam zu erleben und zeigen häufiger einen risikoreichen Alkoholkonsum und Internetgebrauch. Unter männlichen Lernenden war dagegen risikoreicher Konsum von Tabak/Nikotin und Cannabis prävalenter. Unter den am Programm ready4life Teilnehmenden bestand das größte Interesse an den Themen Stress und Internetgebrauch.

Schlussfolgerung
Die Arbeit gibt Aufschluss über Subgruppen von Lernenden mit besonders hohen Suchtrisiken und Hinweise auf Präventionsbedarfe und -interessen dieser Zielgruppe.
Comparative Study of the Effects of La-Substituted Ca in (Bi, Pb):2212 and (Bi, Pb):2223 Superconductors
Authors: Sedky A. , Salah Amna 
Published: March 2022

AbstractWe report here a comparative study of the effects of La-substituted Ca on (Bi, Pb):2212 and (Bi, Pb):2223 superconductors with various La content (0.00 ≤ x ≤ 0.30). Regardless of the effects of La, it is evident that the superconducting volume fraction, excess of oxygen, critical concentration for quenching superconductivity, Vickers hardness, anisotropy, interlayer coupling, critical magnetic fields, and critical current were higher for the 2212 series than the 2223 series. In contrast, orthorhombic distortion, c-parameter, crystallite diameter, doping distance, distance between two Cu atoms, hole carrier/Cu ion ratio, melting temperature Tm, critical temperature Tc, onset of diamagnetic TcM, surface energy, elastic component, resistance pressure, and c-axis coherence length were higher for the 2223 series than the 2212 series. An inverse linear relationship between Tm and Tc was estimated for both series, and for room-temperature (RT) bismuth–strontium–calcium–copper–oxide (BSCCO) superconductors, the required Tm values should be 1048.03°C for the 2223 series and 784.48°C for the 2212 series. Surprisingly, the difference in temperature between zero resistivity and diamagnetic onset |TcM − TcR| for La = 0.30 samples is 30 K. In the critical field region (CFR), the exponents of order parameters (OPD) are two-dimensional (2D), but their values were higher for the 2212 series than the 2223 series. Further, they became three-dimensional (3D) as La increased to 0.30 due to the reduced effective length in highly substituted samples. Our results were discussed with the help of the differences in the physical parameters between the considered series. These findings revealed that the 2212 series is more suitable for applications that need higher hardness and critical fields and currents. In contrast, the 2223 series is more suitable for research for higher Tc and altering plastic deformation. To our knowledge, the present systematic investigation has not been reported elsewhere, which highlights the present work.