bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Are we making a quilt, with lots of ill-fitting cloths in here?”: Teachers’ internal conversations on curriculum making
Authors: Hizli Alkan Sinem 
Published: March 2022

AbstractTeachers exercising reflexivity through their internal conversations is one of the most important factors in the process of curriculum change. Drawing from Margaret Archer’s theory, this research explores teachers’ internal conversations in their own descriptions about a range of matters related to curriculum making. Eight secondary school teachers from different subject backgrounds (6 from Scotland and 2 from Wales) participated in the research. Findings suggest that although teachers may have similar concerns to produce internal conversations, the texture of the conversations, their standpoints, and how they project future actions differed. This variation can be partially explained by teachers exercising different modes of reflexivity in their unique circumstances. Findings suggest that a complex, nuanced and dynamic understanding of reflexivity is a salient feature to explain teachers’ stances towards curriculum, reasoning, decision-making and actions, which may help to understand curriculum change processes better.
Arts and Cultural Engagement, Reportedly Antisocial or Criminalized Behaviors, and Potential Mediators in Two Longitudinal Cohorts of Adolescents
Authors: Bone Jessica K. , Bu Feifei , Fluharty Meg E. , Paul Elise , Sonke Jill K. , Fancourt Daisy 
Published: March 2022

AbstractArts and cultural engagement is a potential strategy for reducing or preventing reportedly antisocial or criminalized behaviors (those previously and problematically termed as “delinquent”) in adolescence. However, most research to date has focused on arts-based interventions and has not tested arts and cultural engagement in large population-based longitudinal studies. This study investigated whether arts and cultural engagement reduced reportedly antisocial or criminalized behaviors in two large nationally representative cohorts, the National Longitudinal Study of Adolescent to Adult Health (n = 10,610; 50% female, 72% White, age range = 11–21 mean = 15.07) and the National Education Longitudinal Study of 1988 (n = 15,214; 50% female, 73% White, age range = 13–16 mean = 14.38). Structural equation modelling also allowed exploration of two potential mechanisms that might link arts and cultural engagement to reportedly antisocial or criminalized behaviors (self-control and attitudes towards these behaviors). More arts and cultural engagement was associated with fewer reportedly antisocial or criminalized behaviors, better self-control scores, and fewer positive perceptions of reportedly antisocial or criminalized behaviors concurrently and one to two years later. Arts and cultural engagement may provide opportunities for adolescents to realize positive developmental outcomes, reducing their risk of reportedly antisocial or criminalized behaviors.
Semi-Lipschitz functions and machine learning for discrete dynamical systems on graphs
Authors: Falciani H. , Sánchez-Pérez E. A. 
Published: March 2022

AbstractConsider a directed tree$${\mathcal {U}}$$Uand the space of all finite walks on it endowed with a quasi-pseudo-metric—the space of the strategies$${\mathcal {S}}$$Son the graph,—which represent the possible changes in the evolution of a dynamical system over time. Consider a reward function acting in a subset$${\mathcal {S}}_0 \subset {\mathcal {S}}$$S0⊂Swhich measures the success. Using well-known facts of the theory of semi-Lipschitz functions in quasi-pseudo-metric spaces, we extend the reward function to the whole space$${\mathcal {S}}.$$S.We obtain in this way an oracle function, which gives a forecast of the reward function for the elements of$${\mathcal {S}}$$S, that is, an estimate of the degree of success for any given strategy. After explaining the fundamental properties of a specific quasi-pseudo-metric that we define for the (graph) trees (the bifurcation quasi-pseudo-metric), we focus our attention on analyzing how this structure can be used to represent dynamical systems on graphs. We begin the explanation of the method with a simple example, which is proposed as a reference point for which some variants and successive generalizations are consecutively shown. The main objective is to explain the role of the lack of symmetry of quasi-metrics in our proposal: the irreversibility of dynamical processes is reflected in the asymmetry of their definition.
Faster CNN-based vehicle detection and counting strategy for fixed camera scenes
Authors: Gomaa Ahmed , Minematsu Tsubasa , Abdelwahab Moataz M. , Abo-Zahhad Mohammed , Taniguchi Rin-ichiro 
Published: March 2022

AbstractAutomatic detection and counting of vehicles in a video is a challenging task and has become a key application area of traffic monitoring and management. In this paper, an efficient real-time approach for the detection and counting of moving vehicles is presented based on YOLOv2 and features point motion analysis. The work is based on synchronous vehicle features detection and tracking to achieve accurate counting results. The proposed strategy works in two phases; the first one is vehicle detection and the second is the counting of moving vehicles. Different convolutional neural networks including pixel by pixel classification networks and regression networks are investigated to improve the detection and counting decisions. For initial object detection, we have utilized state-of-the-art faster deep learning object detection algorithm YOLOv2 before refining them using K-means clustering and KLT tracker. Then an efficient approach is introduced using temporal information of the detection and tracking feature points between the framesets to assign each vehicle label with their corresponding trajectories and truly counted it. Experimental results on twelve challenging videos have shown that the proposed scheme generally outperforms state-of-the-art strategies. Moreover, the proposed approach using YOLOv2 increases the average time performance for the twelve tested sequences by 93.4% and 98.9% from 1.24 frames per second achieved using Faster Region-based Convolutional Neural Network (F R-CNN ) and 0.19 frames per second achieved using the background subtraction based CNN approach (BS-CNN ), respectively to 18.7 frames per second.
Vernacular Multilingualism. The use of French in Medieval Dutch Literature
Authors: Hugen Jelmar 
Published: March 2022

AbstractRecently new attention has been paid to the presence and use of French outside of France in multilingual regions, one of them being the Southern Low Countries. Scholarship focusing on this area has emphasized the presence of French within the Dutch literary culture as well as studied the language attitude of Dutch authors towards French. This article adds a third focus to this scholarship, namely that of the use of French found within multilingual texts from the Southern Low Countries. Through an analysis of a selection of bilingual and trilingual texts, it is determined how French is incorporated in these texts, what functionality it serves and to what extent this function reflects or contradicts findings from the other two views on French in medieval Dutch literary culture.
A computational model of TE-dominant noticing, repetition, prior knowledge and grammatical knowledge acquisition
Authors: Yang Juan , Qi X. F. , Liu R. , Wang L. , Sun B. 
Published: March 2022

AbstractComputer-assisted textual enhancement (CATE) technology has been widely used to improve English as foreign language (EFL) learners’ syntactical and grammatical learning. Visual attention, repetition, and prior knowledge are known as the vital factors in CATE-assisted knowledge-acquisition; however, there still lacks a model which can describe those factors’ intrinsic cooperating-mechanism that works in the CATE-based knowledge-acquisition. Therefore, this paper built up a computational model (PESE) of using those factors as variables, by fitting and predicting the data collected from empirical experiments with an average accuracy of 78%, PESE testified and complemented the assumptions proposed by previous studies. PESE suggested that although the efficacy of CATE is majorly decided by learners’ prior-knowledge of the targets, the interactive effects of visual-attention, repetition, and inductive activity could partly compensate for the effect from prior-knowledge, and the efficacy ceiling of repetition also could be estimated according to the ‘easy-perceiving level’ coefficient. At the end of this paper, 3 pedagogical implications were proposed for English teachers who are willing to integrate CATE into their teaching activities.
The regulating effect of growth plasticity on the dynamics of structured populations
Authors: Croll Jasper C. , de Roos Andé M. 
Published: March 2022

AbstractPlasticity is the extent to which life history processes such as growth and reproduction depend on the environment. Plasticity in individual growth varies widely between taxa. Nonetheless, little is known about the effect of plasticity in individual growth on the ecological dynamics of populations. In this article, we analyse a physiologically structured population model of a consumer population in which the individual growth rate can be varied between entirely plastic to entirely non-plastic. We derive this population level model from a dynamic energy budget model to ensure an accurate energetic coupling between ingestion, somatic maintenance, growth and reproduction within an individual. We show that the consumer population is either limited by adult fecundity or juvenile survival up to maturation, depending on the level of growth plasticity and the non-plastic individual growth rate. Under these two regimes, we also find two different types of population cycles which again arise due to fluctuation in, respectively, juvenile growth rate or adult fecundity. In the end, our model not only provides insight into the effects of growth plasticity on population dynamics, but also provides a link between the dynamics found in age- and size-structured models.
The gulf of cross-disciplinary research collaborations on global river basins is not narrowed
Authors: Wei Yongping , Wu Shuanglei 
Published: March 2022

AbstractUsing publications in the Web of Science database (WoS), this study investigates the research collaboration on the top 95 most researched global river basins since 1900. The links of both the disciplines involved and the management issues studied between the biophysical, economic, societal, climatic and governance sub-systems of these river basins were examined. We found that research collaborations were dominated within the biophysical sub-system (65.3%) since the knowledge predevelopment period (1900–1983), with continuous increases (by 18.5%) during the rapid development (1984–2000) and the stabilisation (12.9% increase) (2001–2017). However, research collaborations related to the societal sub-system remained marginalised (varied at about 1%), while those related to the governance sub-system expanded in issues studied (32.8%) but were not supported by the core governance disciplines (3.4%). The key findings explained why global river basins are degraded from the perspective of knowledge development and they can assist the strategic planning and management of scientific research for improving governance capacity in modifying the relationship between human and nature on river basins in the Anthropocene. Tackling challenges in the Anthropocene requires transformation of the current pattern of knowledge development, a revolution in the governance of science.
A pilot project for the long-term structural health monitoring of historic city gates
Authors: Zini Giacomo , Betti Michele , Bartoli Gianni 
Published: March 2022

AbstractThis paper reports on a pilot project for long-term structural health monitoring of historical city gates. This structural typology is what today remains of the defensive structures that characterised the medieval centres of many European cities. Even though in the last years the scientific community has paid great attention to the structural analysis and on the structural health monitoring of masonry towers, which are apparently similar to the typology of city gates, only a few studies explicitly approach such heritage buildings. In most cases, the surviving gates are immersed in the daily vehicular-traffic flows and hence continuously subjected to traffic-induced vibration. Consequently, a key point both for their conservation is the assessment of the optimal sensors position to be used for reliable structural health monitoring procedures. These issues are here discussed with reference to a specific case: the San Niccolò gate in Florence (Italy). First, an expeditious experimental campaign performed with a reduced number of accelerometers is reported. This test is aimed to identify a numerical model that is subsequently employed to design the optimal sensor position of long-term structural monitoring. This optimal sensor grid must be assessed to ensure a low-cost and sustainable dynamic monitoring system but, at the same time, to maximize the information contents.
Valorization of landscape management grass
Authors: Krenz Lina Maja Marie , Pleissner Daniel 
Published: March 2022

Abstract
The aim of this review was to investigate and develop possible material and energetic utilization strategies for grass from nature conservation areas, which is harvested late in the year and currently largely unused. Compared to freshly harvested grass, it contains less proteins and higher contents of fibers. Landscape management grass has therefore poor forage quality and is not suitable as animal feed. Due to its high calorific value, grass biomass can be used as a material for combustion. However, combustion technology must be adapted to the high contents of inorganics. Fresh grass is a widely used feedstock in biogas plants; late-harvested grass however shows lower biogas yields. The integrated generation of solid fuel and biogas represents a promising combination of combustion and digestion. Grass biomass can also be used in a green biorefinery (GBR) or a lignocellulose biorefinery (LCB). A GBR uses fresh green biomass, producing a protein concentrate (recovery of 30–60%, w/w) and a fiber fraction (recovery of up to 95%, w/w). It is supposed that late-harvested grass is less suitable due to low contents of exploitable components. An LCB operates on dry lignocellulosic feedstock and produces a wide range of carbohydrate products. To date, no LCB or GBR operating on late-harvested grass from semi-natural grasslands was described, and further research on the practical implementation is needed.
Antinormality and m-isometry of shift on weighted trees
Authors: Khan Mohammad Irshad , Chandra Harish 
Published: March 2022

AbstractThe shift operator and its various generalizations are amongst the most widely studied operators on a Hilbert space. In this paper, we characterize antinormal and m-isometric shift operator S on the Hilbert space $$L^2({\mathcal {T}},\lambda ) $$

L
2

(
T
,
λ
)

associated with a locally finite directed weighted tree $${\mathcal {T}}$$
T
. We also discuss interesting connections between antinormality and m-isometry of S.
MRI Evaluation of the Lactating Breast
Authors: Chung Maggie , Ruiz-Cordero Roberto , Lee Amie Y. , Joe Bonnie N. , Kelil Tatiana 
Published: March 2022

Abstract
Purpose of Review
To review the MRI appearance of physiologic lactational changes, common benign pathologies, and malignancies in the lactating breast.

Recent Findings
The prevalence of pregnancy-associated breast cancer has increased as more women delay childbirth and lactation. There is a transient increase in breast cancer risk after delivery when women may be lactating. MRI is more sensitive than mammography and ultrasound for the evaluation of the extent of disease in lactating women.

Summary
Understanding the key MRI findings of benign and malignant pathologies in the lactating breast is critical for accurate diagnosis and prompt evaluation of pregnancy-associated breast cancer.
A Linguistic Group Best–Worst Method for Measuring Good Governance in the Third Sector: A Spanish Case Study
Authors: Licerán-Gutiérrez Ana , Ortega-Rodríguez Cristina , Moreno-Albarracín Antonio Luis , Labella Álvaro , Rodríguez Rosa M. , Martínez Luis 
Published: March 2022

AbstractThe need of Non-profit Organizations (NPOs) of generating trust and credibility, to their stakeholders by an efficient management of their resources, lead them to openly show that they develop adequate good governance practices. But this is not a simple task and few research has been done on measuring methods of good governance in this field; without achieving an agreement about the best procedure. This paper aims at facilitating the measurement of good governance practices in NPOs by a fuzzy linguistic consensus-based group multi-criteria decision-making (MCGDM) model that will provide agreed and easy-understanding weights for a list of indicators proposed by the stakeholders and entities in such good governance practices. To do that, a linguistic 2-tuple BWM method with a consensus reaching process (CRP) will be developed and then applied to a real-world case in Spain, in which a group of experts from significant Spanish NPOs will assess the list of indicators proposed by the most representative entities (the alliance between the non-governmental organizations (NGO) Platform for Social Action, and the NGO Coordinator for Development (CONGDE) to obtain a prioritization of such indicators for measuring the good governance practices in Spanish NPOs.
MSMT-CNN for Solar Active Region Detection with Multi-Spectral Analysis
Authors: Almahasneh Majedaldein , Paiement Adeline , Xie Xianghua , Aboudarham Jean 
Published: March 2022

AbstractPrecisely detecting solar active regions (AR) from multi-spectral images is a challenging task yet important in understanding solar activity and its influence on space weather. A main challenge comes from each modality capturing a different location of these 3D objects, as opposed to more traditional multi-spectral imaging scenarios where all image bands observe the same scene. We present a multi-task deep learning framework that exploits the dependencies between image bands to produce 3D AR detection where different image bands (and physical locations) each have their own set of results. Different feature fusion strategies are investigated in this work, where information from different image modalities is aggregated at different semantic levels throughout the network. This allows the network to benefit from the joint analysis while preserving the band-specific information. We compare our detection method against baseline approaches for solar image analysis (multi-channel coronal hole detection, SPOCA for ARs (Verbeeck et al. Astron Astrophys 561:16, 2013)) and a state-of-the-art deep learning method (Faster RCNN) and show enhanced performances in detecting ARs jointly from multiple bands. We also evaluate our proposed approach on synthetic data of similar spatial configurations obtained from annotated multi-modal magnetic resonance images.
Spinal mobility and muscle function in middle-aged patients treated for early onset idiopathic scoliosis: compared with untreated and treated adolescent onset patients
Authors: Romberg Karin , Danielsson Aina , Olsén Monika Fagevik , Kjellby-Wendt Gunilla 
Published: March 2022

AbstractPurposeTo determine long-term outcome in terms of spinal range of motion (ROM) and trunk muscle endurance (TME) patients treated for idiopathic scoliosis, diagnosed before the age of ten, were evaluated and compared with untreated or treated patients with idiopathic scoliosis with adolescent onset (AIS).MethodsSixty-three braced and 53 operated patients underwent examination of spinal ROM and TME. Validated questionnaires were used for evaluation of back function.ResultsA total of 116 patients were examined 26.5 years after treatment. Braced EOS patients had longer bracing time and operated EOS patients had longer fusions compared to the respective AIS groups. Braced EOS patients had similar total ROM (thoracic ROM 40°, lumbar ROM 78°) and TME (trunk flexors 140 s, trunk extensors 255 s) as untreated AIS patients (thoracic ROM 34°, lumbar ROM 88°, trunk flexor endurance 158 s, trunk extensor endurance 234 s). Braced patients also had significantly better results than braced AIS patients. Operated EOS patients were slightly but significantly stronger and more mobile compared to AIS peers. The lumbar ROM was found to affect the back function in the operated EOS group (Oswestry Questionnaire, rs = 0.49,p < 0.001).ConclusionsThe braced EOS patients had mostly similar muscle strength and mobility as the untreated but younger AIS group, while the braced AIS group showed reductions of both strength and mobility. Similar significant, but small, differences were also found between operated EOS and AIS patients. Especially for muscle strength were findings at a level that would be of significant clinical importance.Levels of evidenceIII.
SINR percolation for Cox point processes with random powers
Authors: Jahnel Benedikt , Tóbiás András 
Published: March 2022

AbstractSignal-to-interference-plus-noise ratio (SINR) percolation is an infinite-range dependent variant of continuum percolation modeling connections in a telecommunication network. Unlike in earlier works, in the present paper the transmitted signal powers of the devices of the network are assumed random, independent and identically distributed, and possibly unbounded. Additionally, we assume that the devices form a stationary Cox point process, i.e., a Poisson point process with stationary random intensity measure, in two or more dimensions. We present the following main results. First, under suitable moment conditions on the signal powers and the intensity measure, there is percolation in the SINR graph given that the device density is high and interferences are sufficiently reduced, but not vanishing. Second, if the interference cancellation factor
$\gamma$
and the SINR threshold
$\tau$
satisfy
$\gamma \geq 1/(2\tau)$
, then there is no percolation for any intensity parameter. Third, in the case of a Poisson point process with constant powers, for any intensity parameter that is supercritical for the underlying Gilbert graph, the SINR graph also percolates with some small but positive interference cancellation factor.
Seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) among healthcare providers prior to the vaccine era in an integrated midwestern healthcare system
Authors: Saade Elie A. , Zhang Xiaochun , Noguez Jaime H , Stempak Lisa M. , Tisch Daniel , Schmotzer Christine , Salata Robert A. 
Published: March 2022

Abstract
We performed severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antinucleocapsid IgG testing on 5,557 healthcare providers and found a seroprevalence of 3.9%. African Americans were more likely to test positive than Whites, and HCWs with household exposure and those working on COVID-19 cohorting units were more likely to test positive than their peers.