bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using the theory of planned behaviour to understand brand love
Authors: Hegner Sabrina M. , Fenko Anna , Teravest Annemiek 
Published: April 2017

Purpose
Brand love is perceived as one of the main objectives in brand management. Nevertheless, research into the factors influencing brand love are scarce. This paper aims to apply the theory of planned behaviour to the context of brand love and investigate the influence of several factors on brand love, including attitude towards loving a brand, subjective norm and perceived control factors, namely, the propensity to anthropomorphise and the affordability of the brand. Further, the influence of brand love on brand forgiveness is proven. Additionally, this research investigates the influence of involvement with the product category on the proposed relationship.

Design/methodology/approach
A survey (N = 274) was used to test the model in the context of fashion industry with the help of a convenience sample. Exploratory factor analysis, confirmatory factor analysis and (multi-group) structural equation modelling techniques assessed the proposed model.

Findings
Results show that the proposed model gives valuable insights to brand love, where involvement serves as a moderator. While the attitude towards loving a brand has a strong influence on brand love for both high and low involved consumers, affordability only plays a minor role for experiencing brand love. Subjective norm is found to facilitate brand love for high-involved consumers, while propensity to anthropomorphise leads to higher brand love for low involved consumers.

Originality/value
This paper demonstrates the applicability of the theory of planned behaviour to a consumer–brand relationship context. This adds to a deeper theoretical understanding of the managerially relevant construct of brand love. Further, the study demonstrates that brand lovers are more forgiving in times of disappointment. Introducing involvement into the research model provides valuable insights into the processes underlying brand love.
Social network sites: early adopters’ personality and influence
Authors: Lynn Theo , Muzellec Laurent , Caemmerer Barbara , Turley Darach 
Published: April 2017

Purpose
This paper aims to provide a social network site influence (SNSI) profile of early adopters. This study explores the relationship between personality traits of early adopters of social network sites (SNS), their propensity to share information and rumors and their general SNSI.

Design/methodology/approach
An online survey was sent to the first users of Twitter (n = 200) and Google+ (n = 130) to assess their personality traits. Answers of each respondent were matched to their SNSI scores from Klout and PeerIndex, the industry standard for measuring SNSI.

Findings
Early adopters of SNS, in comparison to market mavens, are more likely to exert influence on one particular topic related to their profession: technology and the internet. Their levels of extraversion, openness and conscientiousness have a positive and significant impact on information sharing, and a negative impact on rumor sharing. Both, information sharing and rumor sharing have a positive and significant impact on the general SNSI of early adopters.

Originality/value
Firms struggle to decide whether to invest early in the life of newly created SNS as they are unsure about the characteristics of early adopters of such networks, and, more importantly, whether these sites are effective initial vectors for word-of-mouth. The findings demonstrate that early adopters’ influence (SNSI score) is on par with that of the rest of SNS users, suggesting their influence may be somewhat limited. The study also shows that the opinion leadership impact of the more influential early adopters is monomorphic in nature, being mainly confined to the related technology and internet domains.
Navigating similarities and differences in national and international accreditation standards
Authors: Wilkerson Judy R. 
Published: April 2017

Purpose
Understanding and navigating the differences in standards, and the roots and rationales underlying accreditation reviews, is necessary for all institutions that seek multiple accreditations. The purpose of this paper is to demonstrate a method to assist institutional-level leaders and assessment practitioners analyze and align these differences in various national or international agency requirements, to develop a framework for assessment and data collection. The proposed method is demonstrated by using multiple accreditors’ standards from the USA.

Design/methodology/approach
Guided by a set of process questions, a review and content analysis of national standards and 12 accreditation agency requirements from the USA was conducted using Web-based, documentary sources. An operational definition of institutional quality was derived based on the core themes that emerged. Examples of evidence matched to each core theme were outlined to suggest an assessment framework. The 12 US agency requirements were compared and contrasted with the core themes and validated.

Findings
In the USA, recognition requirements set by two national bodies, the US Department of Education and Council of Higher Education Accreditation, drive the standards applied by various agencies that accredit institutions and programs. Six themes emerged from their requirements, serving as a core framework for designing institutional assessment systems. The themes are student achievement and continuous improvement; curriculum quality; faculty; facilities, equipment and supplies; fiscal and administrative capacity; and student support services, admissions and information-gathering systems. While the 12 sampled accreditation agencies generally used these core themes, divergences were found in how they treated the themes in published requirements.

Practical implications
Where multiple US or other accreditations are sought, the approach recommended could facilitate the work of institutional accreditation leaders and practitioners in establishing assessment systems that reduce redundancy while also maximizing efficiency in assessment and data collection.

Originality/value
There is little guidance in the literature on how institutional leaders and practitioners confronting the challenges of accreditation can negotiate multiple, and sometimes conflicting, sets of requirements. This paper demonstrates a possible solution strategy. Outside the general utility of the demonstrated method, the findings and core assessment framework produced could be useful for institutions seeking accreditation through the agencies in the study sample, in both the USA and overseas.
An assessment of resource availability for problem based learning in a Ghanaian University setting
Authors: Okyere Gabriel Asare , Tawiah Richard , Lamptey Richard Bruce , Oduro William , Thompson Michael 
Published: April 2017

PurposeThe purpose of this paper is to assess the differences pertaining to the resources presently accessible for problem-based learning (PBL) among six colleges of Kwame Nkrumah University of Science and Technology (KNUST) in Ghana.Design/methodology/approachData for the study are the cross-sectional type drawn from 1,020 students. Poisson and zero-inflated Poisson (ZIP) models were implemented on the data to ascertain the variations regarding the extent of resources available for PBL across the colleges of the university.FindingsThe study outlines the specific resources accessible for PBL across college levels of KNUST. On aggregate, 25.7 per cent reported that their respective colleges have sufficient resources, while 74.3 per cent indicated otherwise. The ZIP model exhibited superiority over the Poisson model, when compared under a Vuong test. As per the ZIP model, none of the colleges appeared to differ significantly in terms of having sufficient resource for PBL.Practical implicationsFindings are applicable to informed decision-making which targets achieving quality education through the use of PBL. Access to sufficient resources that meet the needs of colleges or departments of a University is emphasized.Originality/valueThe application of Poisson and ZIP models to aggregated count data in a PBL setting is novel.
Individual heterogeneity determines sex differences in mortality in a monogamous bird with reversed sexual dimorphism
Authors: Colchero Fernando , Aliaga Alix Eva , Jones Owen R. , Conde Dalia A. 
Published: April 2017

Summary

Sex differences in mortality are pervasive in vertebrates, and usually result in shorter life spans in the larger sex, although the underlying mechanisms are still unclear. On the other hand, differences in frailty among individuals (i.e. individual heterogeneity), can play a major role in shaping demographic trajectories in wild populations. The link between these two processes has seldom been explored.

We used Bayesian survival trajectory analysis to study age‐specific mortality trajectories in the Eurasian sparrowhawk (Accipiter nisus), a monogamous raptor with reversed sexual size dimorphism. We tested the effect of individual heterogeneity on age‐specific mortality, and the extent by which this heterogeneity was determined by average reproductive output and wing length as measures of an individual's frailty.

We found that sex differences in age‐specific mortality were primarily driven by the differences in individual heterogeneity between the two sexes. Females were more heterogeneous than males in their level of frailty. Thus, a larger number of females with low frailty are able to survive to older ages than males, with life expectancy for the least frail adult females reaching up to 4·23 years, while for the least frail adult males it was of 2·68 years.

We found that 50% of this heterogeneity was determined by average reproductive output and wing length in both sexes. For both, individuals with high average reproductive output had also higher chances to survive. However, the effect of wing length was different between the two sexes. While larger females had higher survival, larger males had lower chances to survive.

Our results contribute a novel perspective to the ongoing debate about the mechanisms that drive sex differences in vital rates in vertebrates. Although we found that variables that relate to the cost of reproduction and sexual dimorphism are at least partially involved in determining these sex differences, it is through their effect on the level of frailty that they affect age patterns of mortality. Therefore, our results raise the possibility that observed differences in age‐specific demographic rates may in fact be driven by differences in individual heterogeneity.
Fine‐scale population dynamics in a marine fish species inferred from dynamic state‐space models
Authors: Rogers Lauren A. , Storvik Geir O. , Knutsen Halvor , Olsen Esben M. , Stenseth Nils C. 
Published: April 2017

Summary

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub‐structure and dynamics.

The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence).

Specifically, we developed dynamic, age‐structured, state‐space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93‐year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod.

Cross‐validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density‐dependent survival. Recent biomass was estimated to be at a near‐record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics.

More generally, we demonstrated how state‐space models can be used to test evidence for population spatial structure based on survey time‐series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations.
Multi‐scale drivers of community diversity and composition across tidal heights: an example on temperate seaweed communities
Authors: Robuchon Marine , Valero Myriam , Thiébaut Eric , Le Gall Line 
Published: April 2017

Summary

Despite recent advances in understanding community assembly processes, appreciating how these processes vary across multiple spatial scales and environmental gradients remains a crucial issue in ecology.

This study aimed to disentangle the drivers of diversity and composition of seaweed communities through a gradient of spatial scales based on a hierarchical sampling design consisting of 19 sites distributed in four sectors along the Brittany coastline. Using randomised community matrices and Moran's eigenvector maps (MEMs), we compared (i) the relative importance of deterministic and stochastic processes, (ii) the environmental correlates of community composition, and (iii) the scale of variation in community composition for seaweed communities located at two different tidal heights.

Processes shaping community patterns are expected to vary along a gradient of tidal heights. Therefore, we specifically examined the following hypotheses: the contribution of deterministic over stochastic processes as well as the relative importance of environmental filtering over biotic interactions should be enhanced for seaweed communities of the infralittoral fringe compared to subtidal ones, whereas dispersal of propagules in the water column should be more restricted resulting in finer scale variation in community composition for seaweed communities of the infralittoral fringe compared to subtidal communities.

Seaweed communities were largely shaped by deterministic processes, although the relative importance of deterministic processes was greater for communities of the infralittoral fringe than for subtidal communities. Sea surface temperature and geophysical variables were correlates of community composition at the two tidal heights; additionally, waves and current were correlated with the composition of the communities of the infralittoral fringe while kelp density was correlated with the composition of subtidal communities. Variation in community composition was observed at a finer scale for infralittoral fringe than for subtidal communities.

Synthesis. Our results suggest that the relative importance of deterministic and stochastic processes in structuring seaweed communities varies across tidal heights. Furthermore, the Moran's eigenvector maps framework highlights that the nature of environmental correlates and the spatial scale at which they were good correlates of community composition also vary across tidal heights and may therefore be useful to broaden our understanding of community assembly across vertical gradients.
Tiron ameliorates high glucose‐induced cardiac myocyte apoptosis by PKCδ‐dependent inhibition of osteopontin
Authors: Jiang Ping , Zhang Deling , Qiu Hong , Yi Xianqi , Zhang Yemin , Cao Yingkang , Zhao Bo , Xia Zhongyuan , Wang Changhua 
Published: April 2017

SummaryTiron functions as an effective antioxidant alleviating the intracellular reactive oxygen species (ROS) or the acute toxic metal overload. Previous studies have shown that cardiac myocyte apoptosis can be effectively inhibited by tiron administration in streptozotocin (STZ)‐induced diabetic rats, primary neonatal rat cardiomyocytes (NRVMs), and H9c2 embryonic rat cardiomyocytes. However, the underlying signalling mechanism is ill‐defined. In the present study, we found that tiron supplementation significantly inhibited apoptosis of high glucose (HG)‐treated NRVMs and the left ventricular cardiomyocytes from STZ‐diabetic rat, accompanied with a reduction of osteopontin (OPN) levels as well as an inhibition of PKCδ phosphorylation. OPN knockdown protected NRVMs against HG‐induced cell apoptosis. In addition, genetic inhibition of PKCδ mitigated HG‐stimulated enhancement of intracellular OPN levels in NRVMs. These findings indicate that ROS‐mediated activation of PKCδ upregulated OPN expression, leading to cardiac myocyte apoptosis. Interfering with ROS/PKCδ pathway by antioxidants such as tiron provides an optional therapeutic strategy for treatment and prevention of apoptosis‐related cardiovascular diseases including diabetic cardiomyopathy.
Quantifying uncertainty of taxonomic placement in DNA barcoding and metabarcoding
Authors: Somervuo Panu , Yu Douglas W. , Xu Charles C.Y. , Ji Yinqiu , Hultman Jenni , Wirta Helena , Ovaskainen Otso 
Published: April 2017

Summary

A crucial step in the use of DNA markers for biodiversity surveys is the assignment of Linnaean taxonomies (species, genus, etc.) to sequence reads. This allows the use of all the information known based on the taxonomic names. Taxonomic placement of DNA barcoding sequences is inherently probabilistic because DNA sequences contain errors, because there is natural variation among sequences within a species, and because reference data bases are incomplete and can have false annotations. However, most existing bioinformatics methods for taxonomic placement either exclude uncertainty, or quantify it using metrics other than probability.

In this paper we evaluate the performance of the recently proposed probabilistic taxonomic placement method PROTAX by applying it to both annotated reference sequence data as well as to unknown environmental data. Our four case studies include contrasting taxonomic groups (fungi, bacteria, mammals and insects), variation in the length and quality of the barcoding sequences (from individually Sanger‐sequenced sequences to short Illumina reads), variation in the structures and sizes of the taxonomies (800–130 000 species) and variation in the completeness of the reference data bases (representing 15–100% of known species).

Our results demonstrate that PROTAX yields essentially unbiased probabilities of taxonomic placement, which means its quantification of species identification uncertainty is reliable. As expected, the accuracy of taxonomic placement increases with increasing coverage of taxonomic and reference sequence data bases, and with increasing ratio of genetic variation among taxonomic levels over within taxonomic levels.

We conclude that reliable species‐level identification from environmental samples is still challenging and that neglecting identification uncertainty can lead to spurious inference. A key aim for future research is the completion of taxonomic and reference sequence data bases and making these two types of data compatible.
Using joint species distribution models for evaluating how species‐to‐species associations depend on the environmental context
Authors: Tikhonov Gleb , Abrego Nerea , Dunson David , Ovaskainen Otso 
Published: April 2017

Summary

Joint species distribution models (JSDM) are increasingly used to analyse community ecology data. Recent progress with JSDMs has provided ecologists with new tools for estimating species associations (residual co‐occurrence patterns after accounting for environmental niches) from large data sets, as well as for increasing the predictive power of species distribution models (SDMs) by accounting for such associations. Yet, one critical limitation of JSDMs developed thus far is that they assume constant species associations. However, in real ecological communities, the direction and strength of interspecific interactions are likely to be different under different environmental conditions.

In this paper, we overcome the shortcoming of present JSDMs by allowing species associations covary with measured environmental covariates. To estimate environmental‐dependent species associations, we utilize a latent variable structure, where the factor loadings are modelled as a linear regression to environmental covariates.

We illustrate the performance of the statistical framework with both simulated and real data. Our results show that JSDMs perform substantially better in inferring environmental‐dependent species associations than single SDMs, especially with sparse data. Furthermore, JSDMs consistently overperform SDMs in terms of predictive power for generating predictions that account for environment‐dependent biotic associations.

We implemented the statistical framework as a MATLAB package, which includes tools both for model parameterization as well as for post‐processing of results, particularly for addressing whether and how species associations depend on the environmental conditions.

Our statistical framework provides a new tool for ecologists who wish to investigate from non‐manipulative observational community data the dependency of interspecific interactions on environmental context. Our method can be applied to answer the fundamental questions in community ecology about how species’ interactions shift in changing environmental conditions, as well as to predict future changes of species’ interactions in response to global change.
Comparing immediate‐type food allergy in humans and companion animals—revealing unmet needs
Authors: Pali‐Schöll I. , De Lucia M. , Jackson H. , Janda J. , Mueller R. S. , Jensen‐Jarolim E. 
Published: April 2017

AbstractAdverse food reactions occur in human as well as veterinary patients. Systematic comparison may lead to improved recommendations for prevention and treatment in both. In this position paper, we summarize the current knowledge on immediate‐type food allergy vs other food adverse reactions in companion animals, and compare this to the human situation. While the prevalence of food allergy in humans has been well studied for some allergens, this remains to be investigated for animal patients, where owner‐reported as well as veterinarian‐diagnosed food adverse reactions are on the increase. The characteristics of the disease in humans vs dogs, cats, and horses are most often caused by similar, but sometimes species‐dependent different pathophysiological mechanisms, prompting the specific clinical symptoms, diagnoses, and treatments. Furthermore, little is known about the allergen molecules causative for type I food allergy in animals, which, like in human patients, could represent predictive biomarkers for risk evaluation. The definite diagnosis of food allergy relies—as in humans—on elimination diet and provocation tests. Besides allergen avoidance in daily practice, novel treatment options and tolerization strategies are underway. Taken together, numerous knowledge gaps were identified in veterinary food allergy, which need to be filled by systematic comparative studies.