bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of methods for automated identification of wild turkey gobbles
Authors: Wightman Patrick H. , Henrichs Darren W. , Collier Bret A. , Chamberlain Michael J. 
Published: February 2022

AbstractAutonomous recording units (ARUs) allow for collection of extensive acoustic data sets, while reducing costs and time associated with traditional surveys used to determine gobbling chronology of male wild turkeys (Meleagris gallopavo). A challenge with ARUs is efficiently locating and identifying calls of interest, so autonomous call recognition (ACR) software such as Raven Pro have traditionally been used to identify wild turkey gobbles. However, ACR software often produces high false positive detections, requiring substantive time to verify selections as gobbles. We used ARUs across 3 study sites in the southeastern United States to collect 107,580 hours of ambient sound. We developed a convolutional neural network (CNN) to autonomously identify wild turkey gobbles and compared results of our CNN to results gathered using the commercially available program Raven Pro. After processing of ambient sound, the CNN detected 15,793 more gobbles than Raven Pro, and did so with 5,716,718 fewer selections. Collectively, our CNN improved precision from 0.01 to 0.32 relative to Raven Pro, while decreasing the time required for validation from 4,452 hours to 219. We found precision of our CNN varied across ARUs primarily due to differences in occurrence of ambient sounds similar to gobbles. Thus, we recommend that additional site‐specific training data should be considered when developing CNNs. Our results suggest that researchers interested in describing gobbling activity by male wild turkeys should consider developing and applying CNNs for automated call recognition.
A robust method for clustering football players with mixed attributes
Authors: D’Urso Pierpaolo , De Giovanni Livia , Vitale Vincenzina 
Published: February 2022

AbstractA robust fuzzy clustering model for mixed data is proposed. For each variable, or attribute, a proper dissimilarity measure is computed and the clustering procedure combines the dissimilarity matrices with weights objectively computed during the optimization process. The weights reflect the relevance of each attribute type in the clustering results. A simulation study and an empirical application to football players data are presented that show the effectiveness of the proposed clustering algorithm in finding clusters that would be hidden unless a multi-attributes approach were used.
Sexual and Reproductive Health in Women with Pulmonary Hypertension: A Qualitative Study
Authors: Cipolletta Sabrina , Ravasio Giorgia , Bussotti Maurizio 
Published: February 2022

AbstractPulmonary arterial hypertension (PAH) is a devastating disease characterized by elevation in pulmonary artery pressure causing progressive symptoms: shortness of breath, fatigue, and a decline in functional ability. Research on the impact of PAH on sexual and reproductive health was sparse. The aim of this study is to explore sexual and reproductive health of women with PAH in relation to their illness experience. Twenty-five women with PAH participated in semistructured interviews. A thematic analysis was conducted on the transcripts using the ATLAS.ti software. Four main themes were identified: illness experience, intimate relationship, sexuality, and attitudes toward pregnancy. Results showed that illness changed women’s self-perception, couples’ relationship, sexuality, and the idea of an eventual pregnancy. The relationship with the partner was usually indicated as an important resource, whereas communication with health care professionals was a critical but also potential key resource for the future. Results point to the need for intervention strategies to support women with PAH and help them make aware choices. Moreover, intervention strategies may inform health care interventions and policies for tackling the challenges posed by this illness.
Harnessing Indigenous Tweets: The Reo Māori Twitter corpus
Authors: Trye David , Keegan Te Taka , Mato Paora , Apperley Mark 
Published: February 2022

AbstractTe reo Māori, the Indigenous language of Aotearoa New Zealand, is a distinctive feature of the nation’s cultural heritage. This paper documents our efforts to build a corpus of 79,000 Māori-language tweets using computational methods. The Reo Māori Twitter (RMT) Corpus was created by targeting Māori-language users identified by the Indigenous Tweets website, pre-processing their data and filtering out non-Māori tweets, together with other sources of noise. Our motivation for creating such a resource is three-fold: (1) it serves as a rich and unique dataset for linguistic analysis of te reo Māori on social media; (2) it can be used as training data to develop and augment Natural Language Processing (NLP) tools with robust, real-world Māori-language applications; and (3) it will potentially promote awareness of, and encourage positive interaction with, the growing community of Māori tweeters, thereby increasing the use and visibility of te reo Māori in an online environment. While the corpus captures data from 2007 to 2020, our analysis shows that the number of tweets in the RMT Corpus peaked in 2014, and the number of active tweeters peaked in 2017, although at least 600 users were still active in 2020. To the best of our knowledge, the RMT Corpus is the largest publicly-available collection of social media data containing (almost) exclusively Māori text, making it a useful resource for language experts, NLP developers and Indigenous researchers alike.
Students’ collaboration in technology-enhanced reciprocal peer tutoring as an approach towards learning mathematics
Authors: Oikarinen Riitta Maarit , Oikarinen Juho Kaleva , Havu-Nuutinen Sari , Pöntinen Susanna 
Published: February 2022

AbstractTechnology-enhanced Reciprocal Peer Tutoring (RPT) was carried out with Finnish, nine to ten year-old primary school students (N=40). The RPT as a method of paired mathematics placed specific emphasis on electrical mathematical writing and drawing. Little is known about the important area of implementing digital mathematical skills at the primary level. The contribution of this study is to address the research gap in implementing Technological Pedagogical Content Knowledge (TPACK) into primary school students’ digital mathematics learning. Data was collected from one primary school mathematics lessons by videotaping student’s peer collaboration. In this empirical educational study, the data was analysed qualitatively with content analysis and quantified based on the Contact Summary Sheet (CSS)-instrument and TPACK -framework. This work sheds a light on how students’ collaboration such as instruction, thinking aloud, feedback, support and new ideas during their peer tutoring arouse students’ mathematical attainment and technological discourse. The results indicate that all dimensions of TPACK emerged during primary school students Technology-enhanced RPT. Data reveals that there was a high degree of PK in all videotaped episodes. More research on RPT with an empirical electrical mathematical focus is needed.
Less Partnering, Less Children, or Both? Analysis of the Drivers of First Birth Decline in Finland Since 2010
Authors: Hellstrand Julia , Nisén Jessica , Myrskylä Mikko 
Published: February 2022

AbstractIn the 2010s, fertility has declined in the Nordic countries, most strikingly in Finland, and first births drive the decline. It remains unclear whether this decline results from decreased fertility within unions, changing union dynamics, or both. Thus, we investigated changes in the union–first birth dynamics from 2000 through 2018 in Finland using full-coverage population register data and an incidence-based multistate model. To do so, we calculated the yearly age-specific transition probabilities across states of single, cohabitation, marriage, and first births among 15- to 45-year-old childless men and women. We found lower fertility rates in unions after 2010, increasing dissolution rates amongst cohabiting couples, and long-term declines in the transition to marriage. Counterfactual simulations showed that, for the decline in first births since 2010, fertility within unions matters more (three-quarters) than union dynamics (one-quarter): that is, lower fertility in cohabitating and married individuals explained 42% and 13% of the decline, respectively, and decreasing fertility rates among couples entering cohabitation explained a further 17%. Decreasing marriage (19%) and cohabitation rates (2–4%) as well as higher union dissolution rates (6%) explained a smaller share of the first birth decline. The decline in first births was somewhat sharper among the lower social strata, but across strata the decreasing first birth transitions in unions explained most of the decline. To conclude, while changing union dynamics provide a partial explanation, postponing or foregoing fertility within unions represents the primary reason for the fertility decline.
Behaviour Change Techniques in Computerized Cognitive Training for Cognitively Healthy Older Adults: A Systematic Review
Authors: Peeters Geeske , Black Irene L. , Gomersall Sjaan R. , Fritschi Juliette , Sweeney Aoife , Guedes de Oliveira Yasmin , Panizzutti Rogerio , McEvoy Claire T. , Lampit Amit 
Published: February 2022

AbstractWe aimed to describe behaviour change techniques (BCT) used in trials evaluating computerised cognitive training (CCT) in cognitively healthy older adults, and explore whether BCTs are associated with improved adherence and efficacy. The 90 papers included in a recent meta-analysis were reviewed for information about adherence and use of BCTs in accordance with the Behaviour Change Taxonomy. Studies using a specific BCT were compared with studies not using that BCT on efficacy (difference in Hedges’ g [Δg]) using three level meta-regression models and on median adherence using the Wilcoxon test. The median number of BCTs per study was 3 (interquartile range [IQR] = 2–5). ‘Feedback on behaviour’ (if provided by a person; Δg = -0.19, 95% confidence interval [CI] = -0.31;-0.07) and ‘non-specific reward’ (Δg = -0.19, CI = -0.34;-0.05) were associated withlowerefficacy. Certain BCTs that involve personal contact may be beneficial, although none were statistically significantly associated withgreaterefficacy. The median percentage of adherence was 90% (IQR = 81–95). Adherence was higher in studies using the BCT ‘self-monitoring of behaviour’ and lower in studies using the BCT ‘graded tasks’ than studies not using these BCTs (p < 0.001). These findings provide first evidence that BCTs can influence both adherence to and efficacy of CCT programs in cognitively healthy older adults.
Improving the performance of city-scale hydrodynamic flood modelling through a GIS-based DEM correction method
Authors: Xing Yun , Chen Huili , Liang Qiuhua , Ma Xieyao 
Published: February 2022

AbstractFlood modelling can provide useful information to support flood risk assessment and management. The accuracy of flood simulation results is highly dependent on the quality of input data. In particular, digital elevation models (DEMs) may directly influence the performance of flood predictions and improper representation of complex urban features including buildings and bridges may lead to incorrect prediction of flooding paths and extents, and consequently miscalculate flood risk. In this work, a geographic information system (GIS)-based correction method is proposed to make modifications in high-resolution DEMs by adding building complexes and removing unphysical representations of bridges for a more realistic description of flood paths in considering the flow connectivity in intensely urbanized areas and with the objective of obtaining more accurate flood simulation results. The proposed DEM correction method is applied to support large-scale urban flood modelling in Fuzhou City, China, using an established hydrodynamic flood model known as High-Performance Integrated hydrodynamic Modelling System (HiPIMS). Comparisons are made to the simulation results with and without the DEM improvements using the proposed correction method. The results demonstrate that correct representation of the artificial structures in the urban DEM can significantly improve the flood simulation results.
A systematic review of vaccine-induced thrombotic thrombocytopenia in individuals who received COVID-19 adenoviral-vector-based vaccines
Authors: Elberry Mostafa H. , Abdelgawad Hussien Ahmed H. , Hamdallah Aboalmagd , Abdella Walid Shaban , Ahmed Ahmed Sayed , Ghaith Hazem S. , Negida Ahmed 
Published: February 2022

AbstractReports of thrombotic response after receiving COVID-19 Adenoviral-Vector Based Vaccines raise concerns about vaccine-induced thrombotic thrombocytopenia (VITT); therefore, we conduct this systematic review to report susceptible demographics outcomes, commonalities, and prognosis of reporting cases. We identified published articles by searching PubMed, SCOPUS, and Web of Science from December 2020 till May 2021, with an updated search in September 2021. All case reports and case series reporting thrombotic response after receiving COVID-19 Adenoviral-Vector Based Vaccines were eligible for including. In addition, two authors independently extracted data and assessed the quality of the included studies. A total of 157 patients with thrombotic events after the ChAdOx1 nCoV-19 vaccine and 16 patients with thrombotic events after Ad26.COV2. S vaccine was included in our study. 72% of the ChAdOx1 nCoV-19 cases were females, while in Ad26.COV2.S subgroup, all reported patients were females. The commonest presentations were deep vein thrombosis 20 (12.7%) and cerebral venous sinus thrombosis 18 (11.5%) in the ChAdOx1 nCoV-19 subgroup while cerebral venous sinus thrombosis 14 (87.5%) and pulmonary embolism 2 (12.5%) in the Ad26.COV2. S subgroup. In this study, we described the certain demographics associated with VITT and the clinical presentations of those cases in the ChAdOx1 nCoV-19 and Ad26.COV2. S vaccines. Young individuals, particularly females, may be more susceptible to VITT, and future studies should seek to confirm this association. In addition, the clinical presentation of VITT commonly includes cerebral thrombi, pulmonary embolism, and deep venous thrombosis, but other presentations are also possible, highlighting the importance of clinical vigilance in recent vaccine recipients.
Bipartite graph capsule network
Authors: Zhang Xianhang , Wang Hanchen , Yu Jianke , Chen Chen , Wang Xiaoyang , Zhang Wenjie 
Published: February 2022

AbstractGraphs have been widely adopted in various fields, where many graph models are developed. Most of previous research focuses on unipartite or homogeneous graph analysis. In this graphs, the relationships between the same type of entities are preserved in the graphs. Meanwhile, the bipartite graphs that model the complex relationships among different entities with vertices partitioned into two disjoint sets, are becoming increasing popular and ubiquitous in many real life applications. Though several graph classification methods on unipartite and homogenous graphs have been proposed by using kernel method, graph neural network, etc. However, these methods are unable to effectively capture the hidden information in bipartite graphs. In this paper, we propose the first bipartite graph-based capsule network, namely Bipartite Capsule Graph Neural Network (BCGNN), for the bipartite graph classification task. BCGNN exploits the capsule network and obtains information between the same type vertices in the bipartite graphs by constructing the one-mode projection. Extensive experiments are conducted on real-world datasets to demonstrate the effectiveness of our proposed method.
Automatic detection and classification of peri-prosthetic femur fracture
Authors: Alzaid Asma , Wignall Alice , Dogramadzi Sanja , Pandit Hemant , Xie Sheng Quan 
Published: February 2022

Abstract
Purpose
Object classification and localization is a key task of computer-aided diagnosis (CAD) tool. Although there have been numerous generic deep learning (DL) models developed for CAD, there is no work in the literature to evaluate their effectiveness when utilized in diagnosing fractures in proximity of joint implants. In this work, we aim to assess the performance of existing classification systems on binary and multi-class problems (fracture types) using plain radiographs. In addition, we evaluated the performance of object detection systems using the one- and two-stage DL architectures.

Methods
A data set of 1272 X-ray images of Peri-prosthetic Femur Fracture PFF was collected. The fractures were annotated with bounding boxes and classified according to the Vancouver Classification System (type A, B, C) by two clinical specialists. Four classification models such as Densenet161, Resnet50, Inception, VGG and two object detection models such as Faster RCNN and RetinaNet were evaluated, and their performance compared. Six confusion matrix-based measures were reported to evaluate fracture classification. For localization of the fracture, Average Precision and localization accuracy were reported.

Results
The Resnet50 showed the best performance with $$95\%$$

95
%

accuracy and $$94\%$$

94
%

F1-score in the binary classification: fracture/normal. In addition, the Resnet50 showed $$90\%$$

90
%

accuracy in multi-classification (normal, Vancouver type A, B and C).

Conclusions
A large data set of PFF images and the annotations of fracture features by two independent assessments were created to implement a DL-based approach for detecting, classifying and localizing PFFs. It was shown that this approach could be a promising diagnostic tool of fractures in proximity of joint implants.
Lens-Free Optical Scanners for Metal Additive Manufacturing
Authors: Bibas Charles 
Published: February 2022

AbstractGalvanometer scanners (GSs) driving selective laser sintering (SLS)/selective laser melting (SLM) printers for additive manufacturing (AM) have mechanical limits. They provide inconsistent energy density across the print surface because of changes in optical path length, surface beam speed, and angle of incidence. The resulting thermal gradients may be particularly problematic for metal, whose high heat conductivity makes temperature prediction during printing critical. In this paper, we mathematically analyze and compare GSs with a new lens-free optical scanner. The results show that the latter can facilitate metal printing by providing consistent energy deposition across the print surface.
Recognition and Capability – Prerequisites for Empowerment for Children with Disabilities?
Authors: Andersen Christina Strandholdt 
Published: February 2022

AbstractThis theoretical study explores the empowerment perspective regarding children with disabilities. Article 12 of the UNCRC states children’s right to express their views and be listened to. Meanwhile, studies show that children with disabilities are at risk of overprotection, which may restrict their participation and influence. Honneth’s theory of recognition and Sen’s Capability Approach are discussed together with the empowerment perspective when it comes to fulfilling article 12 regarding children with disabilities alongside empirical studies. Finally, a new model of dynamic empowerment is suggested to illuminate the interrelational complexity in this matter, as well as a way of identifying and understanding the possible mechanisms that may affect children with disabilities and their participation and influence.
Genetic resistance to Campylobacter coli and Campylobacter jejuni in wild boar (Sus scrofa L.)
Authors: Cecchi Francesca , Fabbri Maria Chiara , Tinacci Lara , Nuvoloni Roberta , Marotta Francesca , Di Marcantonio Lisa , Cilia Giovanni , Macchioni Fabio , Armani Andrea , Fratini Filippo , Pedonese Francesca 
Published: February 2022

AbstractWe studied the genetic resistance to Campylobacter coli and Campylobacter jejuni in wild boar using both STR analysis and genome-wide association studies (GWAS). A total of 60 wild boars hunted in Tuscany (Italy) during the 2018/2019 hunting season were analyzed and genotyped. During postmortem operations, fecal swabs, liver samples and kidneys were collected. Two groups of animals were considered for the statistical analysis: 28 Campylobacter positive (22 for C. coli and 6 for C. jejuni) and 32 Campylobacter negative. Regarding STR analysis, 15 markers belonging to a marker panel validated by the International Society of Animal Genetics (ISAG) for swine were used: for each marker, alleles and genotype frequencies between the two groups of animals were compared using the Chi-square test and Fisher’s exact tests. To analyze the genetic variability within groups, the following parameters were computed: molecular coancestry coefficients (fij), kinship distance (Dk), inbreeding coefficient (Fi), and genetic similarities (GS). The internal relatedness (IR) was also calculated, and ANOVA was used to verify the relationships between IR and Campylobacter groups. For GWAS, the Geneseek Genomic Profiler Porcine HD (70 k), containing 62,330 SNPs, was used. No differences in the internal relatedness (IR) were observed between the two groups (F = 5.64, P = 0.065) and no significant association between STRs and SNPs and Campylobacter positivity was observed. Although genetic resistance to bacterial diseases is often regulated by multiple genes controlling different processes of the host–pathogen interaction, in our studies no candidate genes that could be directly or indirectly involved in the development of the disease were identified.
Indian Ocean Ridge System and Seafloor Hydrothermal Activity
Authors: John Kurian, P. , Rajan S. , Agarwal Deepak Kumar , Linsy P. 
Published: February 2022

ABSTRACT
This paper presents a short review of some of the notable contributions by scientists from several parts of the world in furthering our understanding of the seafloor hydrothermal activity on the Indian Ocean ridges (IOR). Studies to date on the hydrothermal plumes and vents on the IOR and the marine sediments around the vents highlight the complex nature of hydrothermal activity on the Indian Ocean ridge system which is characterised by varying spreading rates, differences in the host rock system and perceptible variations in the chemical composition of the hydrothermal fluids.