bluuebunny/crossref_metadata_2025_split huggingface dataset:
An aphrodisiac produced byVibrio fischeristimulates mating in the closest living relatives of animals
Authors: Woznica Arielle , Gerdt Joseph P , Hulett Ryan E. , Clardy Jon , King Nicole 
Published: May 2017

AbstractWe serendipitously discovered that the marine bacteriumVibrio fischeriinduces sexual reproduction in one of the closest living relatives of animals, the choanoflagellateSalpingoeca rosetta. Although bacteria influence everything from nutrition and metabolism to cell biology and development in eukaryotes, bacterial regulation of eukaryotic mating was unexpected. Here we show that a singleV. fischeriprotein, the previously uncharacterized EroS, fully recapitulates the aphrodisiac activity of liveV. fischeri. EroS is a chondroitin lyase; although its substrate, chondroitin sulfate, was previously thought to be an animal synapomorphy, we demonstrate thatS. rosettaproduces chondroitin sulfate and thus extend the ancestry of this important glycosaminoglycan to the premetazoan era. Finally, we show thatV. fischeri, purified EroS, and other bacterial chondroitin lyases induceS. rosettamating at environmentally-relevant concentrations suggesting that bacterially-produced aphrodisiacs likely regulate choanoflagellate mating in nature.
Untargeted metabolomic analysis in naturally occurring canine diabetes mellitus identifies similarities to human Type 1 Diabetes
Authors: O’Kell Allison L. , Garrett Timothy J. , Wasserfall Clive , Atkinson Mark A. 
Published: May 2017

AbstractWhile predominant as a disease entity, knowledge voids exist regarding the pathogenesis of canine diabetes. To test the hypothesis that diabetic dogs have similar metabolomic perturbations to humans with type 1 diabetes (T1D), we analyzed serum metabolomic profiles of breed- and body weight-matched, diabetic (n=6) and healthy (n=6) dogs by liquid chromatography-mass spectrometry (LC-MS) profiling. We report distinct clustering of diabetic and control groups based on heat map analysis of known and unknown metabolites. Random forest classification identified 5/6 dogs per group correctly with overall out of bag error rate=16.7%. Diabetic dogs demonstrated significant upregulation of glycolysis/gluconeogenesis intermediates (e.g., glucose/fructose, C6H12O6, keto-hexose, deoxy-hexose, (P<0.01)), with significant downregulation of tryptophan metabolism metabolites (e.g., picolinic acid, indoxyl sulfate, anthranilate, (P<0.01)). Multiple amino acids (AA), AA metabolites, and bile acids were also significantly lower in diabetic versus healthy dogs (P<0.05) with the exception of the branched chain AA valine, which was elevated in diabetic animals (P<0.05). Metabolomic profiles in diabetic versus healthy dogs shared similarities with those reported in human T1D (e.g., alterations in glycolysis/gluconeogensis metabolites, bile acids, and elevated branched chain AA). Further studies are warranted to evaluate the utility of canine diabetes to provide novel mechanistic insights to the human disorder.AbbreviationsAA(amino acid)AAb(autoantibody)FA(fatty acid)HILIC(hydrophilic interaction liquid interaction chromatography)LC-MS(liquid chromatography mass spectrometry)OOB(out of bag)T1D(type 1 diabetes)T2D(type 2 diabetes)UF(University of Florida)
The cerebellum does more than sensory-prediction-error-based learning in sensorimotor adaptation tasks
Authors: Butcher Peter A. , Ivry Richard B. , Kuo Sheng-Han , Rydz David , Krakauer John W. , Taylor Jordan A. 
Published: May 2017

AbstractIndividuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory-prediction-error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why don’t individuals with cerebellar damage come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, prior to executing a movement on each trial, the participants verbally reported their intended aiming location. Compared to healthy controls, participants with spinocerebellar ataxia (SCA) displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly (Exp. 1) or gradually (Exp. 2). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability (Exp. 3). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory-prediction-error-based learning, but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials.New and noteworthyIndividuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here, we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.
The mu-opioid receptor gene OPRM1 as a genetic marker for placebo analgesia
Authors: Aslaksen Per , Forsberg June Thorvaldsen , Gjerstad Johannes 
Published: May 2017

AbstractThe aim of the present study was to examine if genetic factors associated with pain perception could predict the placebo analgesic response in healthy volunteers. 296 participants (182 women) were randomized to either a placebo group receiving placebo cream with information that the cream was an effective painkiller, or to a natural history group receiving no treatment. Pain was induced by contact heat stimuli. Genotyping for the mu-opioid receptor gene OPRM1, the serotonin transporter gene 5-HTT, and the dopamine-metabolizing gene COMT was performed. Individuals with the OPRM1 A/A genotype reported significantly higher placebo responses compared to individuals with the */G variant. No clear effect of the 5-HTT or COMT was observed. The OPRM1 A/A had a predictive accuracy of 92.5% in identification of placebo responders. Our data indicate that the OPRM1 rsl799971 A/A genotype can be used as a reliable identification marker for placebo analgesia.
Insight into growth of Au–Pt bimetallic nanoparticles: an in situ XAS study
Authors: Nayak Chandrani , Bhattacharyya D. , Bhattacharyya K. , Tripathi A. K. , Bapat R. D. , Jha S. N. , Sahoo N. K. 
Published: May 2017

Au–Pt bimetallic nanoparticles have been synthesized through a one-pot synthesis route from their respective chloride precursors using block copolymer as a stabilizer. Growth of the nanoparticles has been studied by simultaneous in situ measurement of X-ray absorption spectroscopy (XAS) and UV–Vis spectroscopy at the energy-dispersive EXAFS beamline (BL-08) at Indus-2 SRS at RRCAT, Indore, India. In situ XAS spectra, comprising both X-ray near-edge structure (XANES) and extended X-ray absorption fine-structure (EXAFS) parts, have been measured simultaneously at the Au and Pt L
3-edges. While the XANES spectra of the precursors provide real-time information on the reduction process, the EXAFS spectra reveal the structure of the clusters formed in the intermediate stages of growth. This insight into the formation process throws light on how the difference in the reduction potential of the two precursors could be used to obtain the core–shell-type configuration of a bimetallic alloy in a one-pot synthesis method. The core–shell-type structure of the nanoparticles has also been confirmed by ex situ energy-dispersive spectroscopy line-scan and X-ray photoelectron spectroscopy measurements with in situ ion etching on fully formed nanoparticles.
Identification and analysis of employee branding typology using fuzzy c-means clustering
Authors: Natarajan Thamaraiselvan , Periaiya Sridevi , Balasubramaniam Senthil Arasu , Srinivasan Thushara 
Published: May 2017

PurposeThe purpose of this paper is to identify and analyse the typology of employee branding in an airline company using fuzzy c-means (FCM) clustering to improve the quality of employee brand (EB).Design/methodology/approachData were collected from employees of Air India, Chennai division, using a questionnaire and analysed using FCM to find the optimum cluster number. The nature of each cluster was analysed to know its type.FindingsThe results prove the presence of four types of EB, namely, all-stars, injured reserves, rookies and strike-out kings in the aviation company. It is proven that employees in all-star have high level of knowledge of the desired brand (KDB) and psychological contract (PC), those in injured reserves have high KDB and low PC, rookies have low KDB and high PC and strike-out kings have low KDB and PC.Research limitations/implicationsThe results of this study are limited to the Air India employees. This study contributes to employee branding by empirically substantiating the proposed typology using FCM. It proposes the need to analyse organisations individually before comparisons.Practical implicationsThe management must focus on the quality of training and development programmes to enhance the position of rookies and strike-out kings. It must also receive regular feedback from injured reserves and strike-out kings to evaluate their perception of PC.Originality/valueThis is the first paper to empirically prove the typology of employee branding and to implement FCM in clustering employees for enhancing the EB’s quality.
Design chain visibility
Authors: Caridi Maria , Pero Margherita , Sianesi Andrea 
Published: May 2017

PurposeResearchers ascertain that the more the activities of new product development (NPD) process are outsourced to partners, the higher the need for integration. The purpose of this paper is to study: the extent to which the amount of information shared with the partners during NPD projects (DC visibility) depends on the degree of outsourcing (DC virtuality), and what are the context variables (product features and business relationship features) that influence this relationship.Design/methodology/approachThis paper provides two sets of quantitative indexes to measure: the relevance of the activities outsourced during the NPD project (i.e. virtuality), in terms of the spread of the outsourced technological knowledge, and in terms of outsourced workload; and the amount of information that a focal company shares with product development partners (i.e. visibility). Seven NPD projects in different companies have been analyzed to investigate visibility, virtuality, and the implications of contingencies.FindingsThe cross-case analysis shows that the amount of information shared with the partners during the NPD project varies with the relevance of outsourced activities. In particular, the higher the relevance, the higher the amount of information shared with the partner. Partner location and integration, trust, and ICT support have a role in determining the amount of information shared with each single partner.Originality/valueThis study adopts an original network perspective in that the whole set of partners involved in the NPD process is analyzed. New quantitative indexes of visibility and virtuality of NPD projects are proposed, along with original insights about the impact of context variables. The quantitative indexes also provide a useful managerial tool to evaluate whether a focal company has the possibility to build competitive advantages that exploit unique resources beyond the boundaries of the company.
Road map for the implementation of green manufacturing practices in Indian manufacturing industries
Authors: Digalwar Abhijeet K. , Mundra Nidhi , Tagalpallewar Ashok R. , Sunnapwar Vivek K. 
Published: May 2017

Purpose
Green manufacturing (GM) has received growing attention in the last few years. As today’s business environment is highly competitive, dynamic and volatile in nature, GM is seen as the winning strategy to be adopted by manufacturers. In this scenario, successful implementation of GM by manufacturers can give them an edge over their competitors. The purpose of this paper is to identify and develop the structural relationship among different factors for the successful implementation of GM.

Design/methodology/approach
A questionnaire-based survey and interpretive structural modeling (ISM) approach has been applied in this study. In this research, 12 factors have been identified, such as top management commitment, supplier and materials management, green product and process design, employee training and empowerment, etc. On the basis of survey results and opinions of experts from industry and academia, a structural relationship model has been developed through an ISM approach.

Findings
Top management commitment has the highest driving power for the implementation of GM. Effective implementation of GM will improve organization performance in terms of product cost and quality. For effective implementation of GM, management should not ignore development of people, product and processes.

Practical implications
The developed model will be useful to managers, decision makers and practitioners of GM in prioritizing their resources more effectively.

Originality/value
Critical success factor play a pivotal role for the assessment and implementation of GM practices. Identification of key success factors and their mutual relationship can help in implementation of GM practices in various organizations. It is probably one of the leading attempts to provide road map to the implementation of GM practices in Indian manufacturing industries.
A fuzzy goal programming approach for selecting sustainable suppliers
Authors: Pandey Peeyush , Shah Bhavin J. , Gajjar Hasmukh 
Published: May 2017

Purpose
Due to the ever increasing concern toward sustainability, suppliers nowadays are evaluated on the basis of environmental performances. The data on supplier’s performance are not always available in quantitative form and evaluating supplier on the basis of qualitative data is a challenging task. The purpose of this paper is to develop a framework for the selection of suppliers by evaluating them on the basis of both quantitative and qualitative data.

Design/methodology/approach
Literature on sustainability, green supply chain and lean practices related to supplier selection is critically reviewed. Based on this, a two phase fuzzy goal programming approach integrating hyperbolic membership function is proposed to solve the complex supplier selection problem.

Findings
Results obtained through the proposed approach are compared to the traditional models (Jadidi et al., 2014; Ozkok and Tiryaki, 2011; Zimmermann, 1978) of supplier selection and were found to be optimal as it achieves higher aspiration level.

Practical implications
The proposed model is adaptive to solve real world problems of supplier selection as all criteria do not possess the same weights, so the managers can change the criteria and their weights according to their requirement.

Originality/value
This paper provides the decision makers a robust framework to evaluate and select sustainable supplier based on both quantitative and qualitative data. The results obtained through the proposed model achieve greater satisfaction level as compared to those achieved by traditional methods.
DEA and Monte Carlo simulation approach towards green car selection
Authors: Prakash Anand , Mohanty Rajendra P. 
Published: May 2017

PurposeAutomakers are engaged in manufacturing both efficient and inefficient green cars. The purpose of this paper is to categorize efficient green cars and inefficient green cars followed by improving efficiencies of identified inefficient green cars for distribution fitting.Design/methodology/approachThe authors have used 2014 edition of secondary data published by the Automotive Research Centre of the Automobile Club of Southern California. The paper provides the methodology of applying data envelopment analysis (DEA) consisting of 50 decision-making units (DMUs) of green cars with six input indices (emission, braking, ride quality, acceleration, turning circle, and luggage capacity) and two output indices (miles per gallon and torque) integrated with Monte Carlo simulation for drawing significant statistical inferences graphically.FindingsThe findings of this study showed that there are 27 efficient and 23 inefficient DMUs along with improvement matrix. Additionally, the study highlighted the best distribution fitting of improved efficient green cars for respective indices.Research limitations/implicationsThis study suffers from limitations associated with 2014 edition of secondary data used in this research.Practical implicationsThis study may be useful for motorists with efficient listing of green cars, whereas automakers can be benefitted with distribution fitting of improved efficient green cars using Monte Carlo simulation for calibration.Originality/valueThe paper uses DEA to empirically examine classification of green cars and applies Monte Carlo simulation for distribution fitting to improved efficient green cars to decide appropriate range of their attributes for calibration.
Linking intangible resources and export performance
Authors: Monteiro Albertina Paula , Soares Ana Maria , Rua Orlando Lima 
Published: May 2017

PurposeThis research draws upon the resource-based view and the dynamic capabilities view’s premise that a firm’s resources and capabilities determine competitive advantage. Specifically, the purpose of this paper is to develop and test a model entailing simultaneously the impact of intangible resources; and dynamic capabilities and entrepreneurial orientation on export performance.Design/methodology/approachTherefore, the authors developed a study based on a survey of 265 Portuguese exporting companies. Data were submitted to a multivariate statistical analysis and a linear regression model was applied in order to predict the influence of the intangible resources on export performance. The structural equations model was used for this purpose.FindingsThe results show that export performance is directly impacted by dynamic capabilities and entrepreneurial orientation. However, intangible resources do not have a significant direct impact on entrepreneurial orientation; they do have an indirect effect through the mediation of dynamic capabilities. These findings highlight the catalyst role of dynamic capabilities and entrepreneurial orientation, leveraging the role of intangible resources as antecedents of export performance. These findings are valuable inputs for exporting managers and public entities.Originality/valueWhile previous authors have attempted to analyse certain aspects of this process (linkage between intangible resources and export performance), this research developed a framework that combines these ones with entrepreneurial orientation and dynamic capabilities.
Do you feel younger enough to choose nostalgic products? Exploring the role of age identity in nostalgic purchasing behavior
Authors: Kazlauske Dovile , Gineikiene Justina 
Published: May 2017

Purpose
The purpose of this paper is to empirically examine the links between consumer age identity, nostalgia and preferences for nostalgic products.

Design/methodology/approach
A theoretical framework is proposed based on integrating nostalgia and age identity as parts of an individual’s self-concept. Research results are obtained from the empirical study of a sample of 313 consumers in Lithuania and five interviews with experts in marketing industry.

Findings
Employing structural equation modeling analysis, the current study provides initial evidence that the bigger the discrepancy between one’s chronological and cognitive age, the more nostalgic products one buys. Furthermore, age identity acts as a better predictor for purchasing nostalgic products than nostalgia.

Originality/value
The current paper explores the impact of nostalgia and age identity on consumer purchasing behavior which is not addressed in literature before. By evaluating the role of nostalgia and age identity, the study offers a deeper understanding of consumer behavior in nostalgia contexts. Moreover, unlike in most previous studies on nostalgia and age identity, it is focused on actual rather than intended behavior. The present study is also relevant for current marketers as the findings provide additional information and recommendations for choosing appropriate marketing and communication strategies.
Relation between start-ups’ online social media presence and fundraising
Authors: Yang Song , Berger Ron 
Published: May 2017

Purpose
The purpose of this study is to examine the emergences of social media such as Facebook, Twitter and Instagram have changed the way human beings communicate and interact. In the past few years, this has become crucial in the context of business, especially in start-up fund raising. Access to venture capital financing is a crucial issue in the entrepreneurial finance literature. To further explore the use of social media for entrepreneurs, the authors have explored how entrepreneurs use social media for fund-raising purposes. The authors have used Application Programming Interfaces (APIs) to collect entrepreneurs’ funding data from Crunchbase and entrepreneurs’ social media data from Facebook and Twitter. The results show that social media is significant for start-ups in their success or failure in fund raising. Investing energy into utilizing online social media and exhausting these platforms consciously contributes to the financial success of start-ups. Therefore, start-ups which are popular among online fans and followers can manage to raise larger amounts of funding in the early stages.

Design/methodology/approach
This research relies on a wide range of quantitative data, which was obtained from three different online sources which includes Facebook, Twitter and CrunchBase. The use of a variety of internet technologies have been linked to increases in individuals’ social network diversity, which likely increases access to social capital at the individual level (Hampton and Wellman, 2003). The dataset was retrieved by using APIs, which enables the collection of novel metrics, from various sources that provide a well-structured dataset (Priem and Hemminger, 2010). Hypotheses were tested on a longitudinal dataset from 2000 to 2013, comprising general and investment data and social media metrics of start-ups. First, a sample from the database was selected to ensure data availability and reliability. After sampling, all the selected companies’ Twitter and Facebook activities were observed and metrics were analysed. SPSS was used to conduct correlation and regression analyses.

Findings
This study analysed whether start-ups’ social media convention is able to influence investors’ choices, especially the amount of total funding given. The paper showed that innovative start-up companies were able to benefit from communicating on social media platforms. Start-ups, which were using Facebook and Twitter effectively, focusing on valuable social media metrics, received larger amount of funding in total. Furthermore, it was observed that as their business grew, they intended to put more effort into online social networking. It confirmed the idea that businesses are using social media consciously.

Originality/value
This is the only paper that the authors could find that examines the relationship between fundraising and activity on social networks.