bluuebunny/crossref_metadata_2025_split huggingface dataset:
Helical metaphase chromatid coiling is conserved
Authors: Kubalová Ivona , Câmara Amanda Souza , Cápal Petr , Beseda Tomáš , Rouillard Jean-Marie , Krause Gina Marie , Toegelová Helena , Himmelbach Axel , Stein Nils , Houben Andreas , Doležel Jaroslav , Mascher Martin , Šimková Hana , Schubert Veit 
Published: September 2021

SummaryThe higher-order organization of metaphase chromosomes has been debated for almost 140 years. Classical light and electron microscopy studies suggested that chromatids are composed of helically organized chromatin fibers (chromonemata). Non-helical models were also recently proposed. We studied chromosome organization in barley using cutting-edge approaches and obtained evidence for a helically arranged 400-nm chromatin fiber representing the chromonema within chromatid arms. The number of turns is positively correlated with arm length. Turn size and chromatin density decrease towards the telomeres. Due to their specialized functions, the helical organization of centromeres and nucleolus-organizing regions is interrupted by several thinner, straight chromatin fibers. A comparison with previously published data indicates that the helical turning of metaphase chromatid arms is a conserved feature of large eukaryotic chromosomes.
Global naturopathy research as reflected by Scopus during 2000-2019
Authors: Khan Nadim Akhtar , Ahangar Humma , Jhamb Garvita 
Published: September 2021

Purpose
The purpose of this study is to analyze research output in the naturopathy field at the global level and to examine the various trends in scientific literature available on naturopathy using bibliometric analysis.

Design/methodology/approach
The data was collected from the SciVerse Scopus database published from 2000 through 2019. The search was conducted using Medical Subject headings entry terms, i.e. “Naturopathy” OR “Naturopathic Medicine” using the “Document” search option. The search results comprised of documents that had these above search terms in their article title, abstract and keywords. The retrieved documents were then analyzed concerning different parameters like the growth of publications, authorship patterns, productive countries and institutions, highly cited papers, top prolific authors, funding agencies and document types.

Findings
The results of this study reveal that a total of 1,099 documents were published during 20-year time span. The most preferred publication type is research articles 683 (62.14%). Germany, USA, Australia, India and Canada were the most productive countries in terms of the number of scientific documents. The findings also show that the most preferred journal in the field of naturopathy is MMW Fortschritte der Medizin, with 115 documents followed by Journal of Alternative and Complementary Medicine with 58 documents. In contrast, the journal BMC Complementary and Alternative Medicine had the highest citations per paper (17.85). For the 20-year study period, the average value for the degree of collaboration was calculated as 0.57, indicating 54% of the total publications in naturopathy were multi-authored. The value of the collaboration coefficient (CC) signifies the levels of multi-authored papers. CC was highest in the year 2019 (0.55) indicating that the publications were contributed in collaboration rather than in isolation and the number of multi-authored/mega-authored papers outnumbered the single authors in the collection of all authors in the year 2019. Bastyr University, USA was the most productive Institution. Journal articles were the most preferred form of publication.

Practical implications
This study traces various trends in the research behavior and preferences of researchers in the field of naturopathy. It thus can be of immense help to identify strong areas in naturopathy research. Further, this study will help the librarians to identify the core/preferred journals in naturopathy.

Originality/value
This paper makes an endeavor to carry an extensive bibliometric study that provides an overview of emerging trends in naturopathy research.
Data-driven structure selection for the grey NGMC(1,N) model
Authors: Luo Dang , Sun Decai 
Published: September 2021

PurposeWith the prosperity of grey extension models, the form and structure of grey forecasting models tend to be complicated. How to select the appropriate model structure according to the data characteristics has become an important topic. The purpose of this paper is to design a structure selection method for the grey multivariate model.Design/methodology/approachThe linear correction term is introduced into the grey model, then the nonhomogeneous grey multivariable model with convolution integral [NGMC(1,N)] is proposed. Then, by incorporating the least absolute shrinkage and selection operator (LASSO), the model parameters are compressed and estimated based on the least angle regression (LARS) algorithm.FindingsBy adjusting the values of the parameters, the NGMC(1,N) model can derive various structures of grey models, which shows the structural adaptability of the NGMC(1,N) model. Based on the geometric interpretation of the LASSO method, the structure selection of the grey model can be transformed into sparse parameter estimation, and the structure selection can be realized by LASSO estimation.Practical implicationsThis paper not only provides an effective method to identify the key factors of the agricultural drought vulnerability, but also presents a practical model to predict the agricultural drought vulnerability.Originality/valueBased on the LASSO method, a structure selection algorithm for the NGMC(1,N) model is designed, and the structure selection method is applied to the vulnerability prediction of agricultural drought in Puyang City, Henan Province.
A hybrid predictive framework for evaluating P2P credit risks
Authors: He Liang , Xu Haiyan , Ke Ginger Y. 
Published: September 2021

PurposeDespite better accessibility and flexibility, peer-to-peer (P2P) lending has suffered from excessive credit risks, which may cause significant losses to the lenders and even lead to the collapse of P2P platforms. The purpose of this research is to construct a hybrid predictive framework that integrates classification, feature selection, and data balance algorithms to cope with the high-dimensional and imbalanced nature of P2P credit data.Design/methodology/approachAn improved synthetic minority over-sampling technique (IMSMOTE) is developed to incorporate the randomness and probability into the traditional synthetic minority over-sampling technique (SMOTE) to enhance the quality of synthetic samples and the controllability of synthetic processes. IMSMOTE is then implemented along with the grey relational clustering (GRC) and the support vector machine (SVM) to facilitate a comprehensive assessment of the P2P credit risks. To enhance the associativity and functionality of the algorithm, a dynamic selection approach is integrated with GRC and then fed in the SVM's process of parameter adaptive adjustment to select the optimal critical value. A quantitative model is constructed to recognize key criteria via multidimensional representativeness.FindingsA series of experiments based on real-world P2P data from Prosper Funding LLC demonstrates that our proposed model outperforms other existing approaches. It is also confirmed that the grey-based GRC approach with dynamic selection succeeds in reducing data dimensions, selecting a critical value, identifying key criteria, and IMSMOTE can efficiently handle the imbalanced data.Originality/valueThe grey-based machine-learning framework proposed in this work can be practically implemented by P2P platforms in predicting the borrowers' credit risks. The dynamic selection approach makes the first attempt in the literature to select a critical value and indicate key criteria in a dynamic, visual and quantitative manner.
Improving emergency response operations in maritime accidents using social media with big data analytics: a case study of the MV Wakashio disaster
Authors: Dominguez-Péry Carine , Tassabehji Rana , Vuddaraju Lakshmi Narasimha Raju , Duffour Vikhram Kofi 
Published: September 2021

PurposeThis paper aims to explore how big data analytics (BDA) emerging technologies crossed with social media (SM). Twitter can be used to improve decision-making before and during maritime accidents. We propose a conceptual early warning system called community alert and communications system (ComACom) to prevent future accidents.Design/methodology/approachBased on secondary data, the authors developed a narrative case study of the MV Wakashio maritime disaster. The authors adopted a post-constructionist approach through the use of media richness and synchronicity theory, highlighting wider community voices drawn from social media (SM), particularly Twitter. The authors applied BDA techniques to a dataset of real-time tweets to evaluate the unfolding operational response to the maritime emergency.FindingsThe authors reconstituted a narrative of four escalating sub-events and illustrated how critical decisions taken in an organisational and institutional vacuum led to catastrophic consequences. We highlighted the specific roles of three main stakeholders (the ship's organisation, official institutions and the wider community). Our study shows that SM enhanced with BDA, embedded within our ComACom model, can better achieve collective sense-making of emergency accidents.Research limitations/implicationsThis study is limited to Twitter data and one case. Our conceptual model needs to be operationalised.Practical implicationsComACom will improve decision-making to minimise human errors in maritime accidents.Social implicationsEmergency response will be improved by including the voices of the wider community.Originality/valueComACom conceptualises an early warning system using emerging BDA/AI technologies to improve safety in maritime transportation.
Artificial intelligence adoption in business-to-business marketing: toward a conceptual framework
Authors: Chen Lujie , Jiang Mengqi , Jia Fu , Liu Guoquan 
Published: September 2021

Purpose
The purpose of this study is to develop a synthesized conceptual framework for artificial intelligence (AI) adoption in the field of business-to-business (B2B) marketing.

Design/methodology/approach
A conceptual development approach has been adopted, based on a content analysis of 59 papers in peer-reviewed academic journals, to identify drivers, barriers, practices and consequences of AI adoption in B2B marketing. Based on these analyses and findings, a conceptual model is developed.

Findings
This paper identifies the following two key drivers of AI adoption: the shortcomings of current marketing activities and the external pressure imposed by informatization. Seven outcomes are identified, namely, efficiency improvements, accuracy improvements, better decision-making, customer relationship improvements, sales increases, cost reductions and risk reductions. Based on information processing theory and organizational learning theory (OLT), an integrated conceptual framework is developed to explain the relationship between each construct of AI adoption in B2B marketing.

Originality/value
This study is the first conceptual paper that synthesizes drivers, barriers and outcomes of AI adoption in B2B marketing. The conceptual model derived from the combination of information processing theory and OLT provides a comprehensive framework for future work and opens avenues of research on this topic. This paper contributes to both AI literature and B2B literature.
Effects of brand feedback to negative eWOM on brand love/hate: an expectancy violation approach
Authors: Yang Jing , Mundel Juan 
Published: September 2021

PurposeThis study aims to explore the role of consumers’ expectation violation in brands’ negative eWOM management on social media. The effects of brand feedback strategies (i.e. compensation and causal attribution) and brand type (i.e. full-service vs low-cost) in consumers’ expectation violations and the impact of such violations on consumers’ satisfaction and responses to a brand (i.e. brand love and brand hate) were examined.Design/methodology/approachThis study used a 2 (causal attribution: external/brand) × 2 (compensation: present/absent) × 2 (brand type: low cost vs full service) × 2 (industry: airline and hotel) between-subjects experimental design.FindingsResults indicated that the presence (vs absence) of compensation can result in positive consumer expectation violations, which can lead to consumer satisfaction and brand love. Alternately, the absence of compensation can result in negative consumer expectation violations, which can lead to consumers dissatisfaction and brand hate. Moreover, brand type (i.e. full-service vs low-cost) significantly interacted with the presence of compensation in influencing consumers’ responses. The attribution of the cause did not significantly influence consumers’ responses.Practical implicationsThis study highlights the importance of knowing consumers’ expectations when responding to negative eWOM on social media. Offering compensation is an effective strategy for restoring consumer satisfaction. Specifically, for low-cost brands, offering compensation can lead to even more favorable responses.Originality/valueThis study pioneers in exploring the roles of different brand feedback strategies and brand type in influencing consumers’ responses to brands’ handling of negative eWOM. This study revealed the underlying mechanism through the theoretical lens of expectancy violation and examined the impact of expectation violations on consumer satisfaction and brand love and brand hate.
Professional community and student engagement in higher education: rethinking the contributions of professional staff
Authors: Owusu-Agyeman Yaw , Moroeroe Enna 
Published: September 2021

PurposeScholarly studies on student engagement are mostly focused on the perceptions of students and academic staff of higher education institutions (HEIs) with a few studies concentrating on the perspectives of professional staff. To address this knowledge gap, this paper aims to examine how professional staff who are members of a professional community perceive their contributions to enhancing student engagement in a university.Design/methodology/approachData for the current study were gathered using semi-structured face-to-face interviews among 41 professional staff who were purposively sampled from a public university in South Africa. The data gathered were analysed using thematic analysis that involved a process of identifying, analysing, organising, describing and reporting the themes that emerged from the data set.FindingsAn analysis of the narrative data revealed that when professional staff provide students with prompt feedback, support the development of their social and cultural capital and provide professional services in the area of teaching and learning, they foster student engagement in the university. However, the results showed that poor communication flow and delays in addressing students’ concerns could lead to student disengagement. The study further argues that through continuous interaction and shared norms and values among members of a professional community, a service culture can be developed to address possible professional knowledge and skills gaps that constrain quality service delivery.Originality/valueThe current paper contributes to the scholarly discourse on student engagement and professional community by showing that a service culture of engagement is developed among professional staff when they share ideas, collaborate and build competencies to enhance student engagement. Furthermore, the collaboration between professional staff and academics is important to addressing the academic issues that confront students in the university.
Quality assurance systems: enemies or allies of innovation in higher education institutions?
Authors: Mello Silva Mariana Ferreira de , Vargas Eduardo Raupp de 
Published: September 2021

Purpose
This study aims to examine the extant literature to analyze the relationship between quality assurance (QA) and innovation in the higher education context.

Design/methodology/approach
This study selected 63 articles through a systematic literature review in Scopus and Web of Science databases and performed a descriptive and thematic synthesis-analysis on the sample.

Findings
The research identifies several perspectives discussed on QA systems covering experiences, criticisms and practice implications. The literature review shows there is no clear consensus on whether innovation in higher education institutions (HEIs) is fostered or hindered by QA processes. However, it seems that the likelihood of innovativeness and positive QA outcomes are directly linked to how these processes are managed in universities.

Research limitations/implications
This review highlights the university management concerns that emerge with QA issues as it is not yet clear to what extent innovation is actually promoted in scenarios where QA is applied. Hence, this literature review could be considered comprehensive but not exhaustive. Further studies are recommended to improve the understanding of how HEIs can both innovate and ensure quality at the same time.

Originality/value
The paper contributes to the existing body of knowledge by advancing the opportunities and challenges that HEIs face due to QA system features.
Effect of post-processing on microstructure and mechanical properties of Alloy 718 fabricated using powder bed fusion additive manufacturing processes
Authors: Götelid Sareh , Ma Taoran , Lyphout Christophe , Vang Jesper , Stålnacke Emil , Holmberg Jonas , Hosseini Seyed , Strondl Annika 
Published: September 2021

Purpose
This study aims to investigate additive manufacturing of nickel-based superalloy IN718 made by powder bed fusion processes: powder bed fusion laser beam (PBF-LB) and powder bed fusion electron beam (PBF-EB).

Design/methodology/approach
This work has focused on the influence of building methods and post-fabrication processes on the final part properties, including microstructure, surface quality, residual stresses and mechanical properties.

Findings
PBF-LB produced a much smoother surface. Blasting and shot peening (SP) reduced the roughness even more but did not affect the PBF-EB surface finish as much. As-printed PBF-EB parts have low residual stresses in all directions, whereas it was much higher for PBF-LB. However, heat treatment removed the stresses and SP created compressive stresses for samples from both PBF processes. The standard Arcam process parameter for PBF-EB for IN718 is not fully optimized, which leads to porosity and inferior mechanical properties. However, impact toughness after hot isostatic pressing was surprisingly high.

Originality/value
The two processes gave different results and also responses to post-treatments, which could be of advantage or disadvantage for different applications. Suggestions for improving the properties of parts produced by each method are presented.
Microstructure and mechanical testing of Al/graphite/Fly-ash metal matrix composite material
Authors: Yadav Rajat , Dwivedi Shashi Prakash , Dwivedi Vijay Kumar , Islam Anas 
Published: September 2021

PurposeThis study aims to attempt to make an aluminum-based composite using reinforcement such as graphite and fly ash. Pollution is an enhanced serious issue of concern for global. Industries play a major role in disturbing the balance of the environment system. Composite is made by using the stir casting technique. The waste that is generated by the industries if left untreated or left to be rotten at some place may prove fatal to invite various types of diseases. Proper treatment of these wastes is the need of the hour, the best way to get rid of such kinds of hazardous wastes is to use them by recycling.Design/methodology/approachStir casting technique was used to make a composite. Graphite and fly ash were mixed with equal amounts of 2.5% to 15% in aluminum. The microstructure of composite formed after composite was noticed. After seeing the microstructure it was understood that reinforcement particles are very well-mixed in aluminum.FindingsWhen graphite was mixed with 3.75% and 3.75% fly ash in aluminum, the strength of the composite came to about 171.12 MPa. As a result, the strength of the composite increased by about 16.10% with respect to the base material. In the same way, when 3.75% graphite and 3.75% fly ash were added to aluminum, the hardness of the composite increased by about 26.60%.Originality/valueIn this work, graphite and fly ash have been used to develop green metal matrix composite to support the green revolution as promoted/suggested by United Nations, thus reducing the environmental pollution. The addition of graphite and fly ash to aluminum reduced toughness. The thermal expansion of the composite has also been observed to know whether the composite made is worth using in higher temperatures.
The Project Appropriate Birth and a reduction in caesarean section rates: an analysis using the Robson classification system
Authors: D'Agostini Marin DF , da Rosa Wernke A , Dannehl D , de Araujo D , Koch GF , Marçal Zanoni K , Baschirotto Dorigon Coral K , Valeriano Guimarães N , Feuerschuette O , Pinto Moehlecke Iser B 
Published: September 2021

ObjectiveThe objective of this study was to assess caesarean section (CS) rates before and after the implementation of the Project Appropriate Birth (PPA), based on the Robson ten group classification system.DesignA before‐and‐after study.SettingMaternity hospital in South Brazil.PopulationAll pregnant women attending from April 2016 to April 2017 (period 1, pre‐implementation of PPA) and from June 2017 to June 2018 (period 2, post‐implementation of PPA).MethodsMaternal and obstetric characteristics were evaluated, including Robson’s classification, based on the characteristics of pregnancy and childbirth. A chi‐square test and crude and adjusted relative rates were used to analyse the study variables. The significance level was set at 5%.Main outcome measuresThe CS rate for each group, their contribution to the overall CS rate and the differences in these contributions before and after PPA implementation.ResultsThe CS rates decreased from 62.4 to 55.6%, which represented a 10.9% reduction after the implementation of the PPA. Pregnant women in Robson classification groups 1–4 had a 21.4% reduction in CS rates, ranging from 49.1 to 38.6%. The greatest contributors to the overall CS rates were group 5 and group 2, accounting for more than 60% of the CS deliveries.ConclusionThe study results suggest that Project Appropriate Birth had an impact on the reduction of CS rates, especially in Robson classification groups 1 through 4, which indicates that providing mothers with evidence‐based interventions for labour and childbirth assistance contributed to reduce CS rates.Tweetable abstractThe Project Appropriate Birth is an innovative project that has demonstrated promising results, suggesting that interventions based on scientific evidence can lead to real changes in childbirth care, contributing to reduce CS rates. The aim of the PPA is to promote activities to improve childbirth care and encourage vaginal delivery. In this study, 6238 pregnant women admitted to the hospital for delivery were included and classified into one of the Robson 10‐group classification. Findings revealed a 10.9% reduction in the overall CS rate and a 21.4% reduction for pregnant women in Robson classification groups 1 through 4, after the implementation of the PPA.