bluuebunny/crossref_metadata_2025_split huggingface dataset:
The secret of VDAC isoforms is in their gene regulation? Characterization of human VDAC genes expression profile, promoter activity, and transcriptional regulators
Authors: Zinghirino Federica , Pappalardo Xena Giada , Messina Angela , Guarino Francesca , De Pinto Vito 
Published: August 2020

AbstractBackgroundVDACs (Voltage-Dependent Anion-selective Channels) are pore-forming proteins of the outer mitochondrial membrane, whose permeability is primarily due to their presence. In higher eukaryotes three isoforms raised during the evolution: they have the same exon-intron organization and the proteins show the same channel-forming activity. We provide a comprehensive analysis of the three human VDAC genes (VDAC1–3), their expression profiles, promoter activity, and potential transcriptional regulators.ResultsVDAC isoforms are broadly but also specifically expressed in various human tissues at different levels with a predominance of VDAC1 and VDAC2 over VDAC3. However, RNA-seq CAGE approach revealed a higher level of transcription activation of VDAC3 gene. We experimentally confirmed this information by reporter assay of VDACs promoter activity. Transcription Factor Binding Sites (TFBSs) distribution in the promoters was investigated. The main regulators common to the three VDAC genes were identified as E2FF, NRF1, KLFS, EBOX transcription factors family members. All of them are involved in cell cycle and growth, proliferation, differentiation, apoptosis, and metabolism. More transcription factors specific for each isoform gene were identified, supporting the results in the literature, indicating a general role of VDAC1, as actor of apoptosis for VDAC2, and the involvement in sex determination and development of VDAC3.ConclusionsFor the first time, we propose a comparative analysis of human VDAC promoters to investigate their specific biological functions. Bioinformatics and experimental results confirm the essential role of VDAC protein family in mitochondrial functionality. Moreover, insights about a specialized function and different regulation mechanisms arise for the three isoforms genes.
A Neural Habituation Account of the Negative Compatibility Effect
Authors: Jacob Len P. L. , Potter Kevin W. , Huber David E. 
Published: August 2020

AbstractThe Negative Compatibility Effect (NCE) is slower reaction times (RTs) to report the direction of a target arrow that follows a matching prime arrow. The cause has been debated, with some studies indicating perception, while others indicate a response effect. We applied the neural habituation model of Huber and O’Reilly (2003) to the NCE, explaining the varied results as reflecting changes in the timing of events. We developed a novel variant of the NCE task, specifying the perceptual dynamics of orientation priming as measured with threshold accuracy. This revealed a transition from positive to negative priming as a function of prime duration, and a second experiment ruled out response priming. The perceptual dynamics of the neural habituation model were fit to these results and the parameter values were fixed in applying the model to the NCE literature. Application of the model to RTs necessitated a response representation that accumulates response information during the trial. Our results indicate that the NCE reflects rapid perceptual priming and slower response priming. Because the accumulation of response information is slow and does not suffer from habituation, the response factor of the prime is a positive effect (lingering response information). In contrast, because perceptual activation is fast and habituates, the perceptual factor can be positive or negative priming depending on the timing of the display sequence. These factors interact with the post-prime mask, which can prime the alternative direction when the mask is a related mask created by combining arrows pointing in both directions.
Adaptive control of missile attitude based on BP–ADRC
Authors: Qiao Haiyan , Meng Hao , Ke Wei , Gao Quanxi , Wang Shaobo 
Published: August 2020

Purpose
To improve the robustness of missile control system and reduce the error, a missile attitude adaptive control method based on active disturbance rejection control technology (ADRC) and BP neural network is innovatively proposed.

Design/methodology/approach
ADRC improves the performance of the missile control system by estimating and eliminating the total disturbance of the system. BP neural network adjusts the parameters of ADRC controller according to the state of the system to realize adaptive control. Based on the control system and missile dynamics model, the convergence analysis of the extended state observer and the stability analysis of the closed-loop system after embedding BP neural network are given.

Findings
The simulation results show that the adaptive control method can adjust the coefficient of error feedback rate according to the system input, output and error change rate, which accelerates the response speed of missile attitude angle and reduces the attitude angle error.

Practical implications
BP–ADRC further improves the robustness and environmental adaptability of the missile control system. The BP–ADRC control method proposed in this paper is proved feasible.

Originality/value
Different from the traditional ADRC, the BP–ADRC feedback signal proposed in this paper uses the output signal and its rate of the closed-loop system instead of the system state quantity estimated by extended state observer (ESO). This innovative method combined with BP neural network can make the system output meet the requirements when ESO has errors in the estimation of missile dynamics model.
Correlates and impact of crop insurance in India: evidence from a nationally representative survey
Authors: Cariappa A.G. Adeeth , Mahida Darshnaben P. , Lal Priyanka , Chandel B.S. 
Published: August 2020

PurposeThe purpose of this paper is to identify the correlates of crop insurance adoption and estimate the impact on debt and farm income.Design/methodology/approachThe authors used nationally representative data from National Sample Survey Office (NSSO), which consisted of 35,200 farming households. Logit and propensity score matching (PSM) (nearest neighbor, caliper and kernel matching) techniques were used.FindingsWith only around 5% of households insuring their crops and 87% of them not receiving claims, crop insurance in India has failed. Logit model estimates of correlates of adoption indicated that households with larger family size, lower social group, less education, lower standard of living and poor were more likely to be left out of the ambit of crop insurance. Further, propensity score estimates suggested that households with access to crop insurance had significantly lesser outstanding debt with positive effect on input costs and crop income. The authors’ results were in contrast to the risk balancing theory.Practical implicationsResults of our work encourage us to rethink and restructure the crop insurance policy design in India. With credit and insurance markets interlinked by design and as the risk balancing in the farm business found absent, policies to strengthen both the markets are the need of the hour. To encourage more farmers to take up crop insurance, revenue-based indemnity calculation could be tried in India.Originality/valueImpact estimates from three different algorithms of matching were compared and tested for robustness. Consistent average treatment effect on treated (ATT) was considered for interpretation and policy implications. Since the data are from a nationally representative survey, results are believed to be of extreme value to policy makers and insurance providers as it can be generalized.
Can multiple large shareholders promote corporate social responsibility?
Authors: Wang Xiao-xia , Pan Hai-ying , Xue Kun-kun 
Published: August 2020

PurposeThis study aims to examine the relationship between an ownership structure with multiple large shareholders and corporate social responsibility (CSR) with regard to Chinese-listed companies.Design/methodology/approachMultiple regression analysis was used on 4,940 samples of 884 listed companies in China for the period 2009–2017, to empirically test the influence of an ownership structure on enterprises’ fulfillment of social responsibility. Moreover, the propensity score matching–difference in differences and Heckman two-stage approaches were used for the robustness of the regression results.FindingsThe results show that ownership structures with multiple large shareholders can promote social responsibility. The check-and-balance ability of non-controlling large shareholders, corporate information transparency and corporate system environment moderate the relationship between multiple large shareholders and CSR engagement.Originality/valueThis paper complements prior studies on the ownership structure of multiple large shareholders. The findings enrich the literature on corporate governance and CSR. The results also reveal information about the situational factors, helping identify the mechanism through which the ownership structure of multiple large shareholders affects CSR.
Critical success factors for integrating artificial intelligence and robotics
Authors: Mir Umar Bashir , Sharma Swapnil , Kar Arpan Kumar , Gupta Manmohan Prasad 
Published: August 2020

Purpose
This paper aims to enlighten stakeholders about critical success factors (CSFs) in developing intelligent autonomous systems (IASs) by integrating artificial intelligence (AI) with robotics. It suggests a prioritization hierarchy model for building sustainable ecosystem for developing IASs.

Design/methodology/approach
This paper is based on the existing literature and on the opinion of 15 experts. All the experts have minimum of eight years of experience in AI and related technologies. The CSF theory is used as a theoretical lens and total interpretative structure modelling (TISM) is used for the prioritization of CSFs.

Findings
Developing countries like India could leverage IASs and associated technologies for solving different societal problems. Policymakers need to develop basic policies regarding data collection, standardized hardware, skilled manpower, funding and start-up culture that can act as building blocks in undertaking sustainable ecosystem for developing IASs and implementing national AI strategy. Clear-cut regulations need to be in place for the proper functioning of the ecosystem. Any technology that can function properly in India has better chances of working at the global level considering the size of the population.

Research limitations/implications
This paper had all its experts from India only, and that makes the limitation of this paper, as there is a possibility that some of the factors identified may not hold same significance in other countries.

Practical implications
Stakeholders will understand the critical factors that are important in developing sustainable ecosystem for IASs and what should be the possible order of activities corresponding to each CSF.

Originality/value
The paper is the first of its kind that has used the CSF theory and TISM methodology for the identification and prioritization of CSFs in developing IASs. Further, eight significant factors, that is, emerging economy multinational enterprises (EMNEs), governance, utility, manpower, capital, software, data and hardware, have come up as the most important factors in integrating AI with robotics in India.
Prioritizing complexity using fuzzy DANP: case study of international development projects
Authors: Kim Soo Yong , Nguyen Minh V. , Dao Tuyen T.N. 
Published: August 2020

PurposeThis paper aims to propose a comprehensive framework for prioritizing complexity criteria. The framework was validated by applying in infrastructure international development (ID) project as a case study.Design/methodology/approachA literature review highlighted the limitations of existing complexity prioritization methods. Then, a combination of the fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy analytic network process (ANP) was employed as a foundation to develop a three-stage complexity prioritization framework. Focus group discussion and questionnaire surveys were used to practically test the framework in the infrastructure ID projects.FindingsThe three-stage complexity prioritization framework was validated to be reliable and feasible. The findings showed ability of consultants, scope uncertainties, site compensation and clearance, communication between stakeholders, administrative procedure and project duration were the most significant complexity criteria of ID projects in the Vietnamese context.Practical implicationsThe framework is a robust tool that enables the researchers to grasp the interaction of complexity criteria for complexity prioritization. Later studies can apply the proposed framework, with some minor revisions, to assess the interaction of criteria in other research topics in, and beyond, project complexity. Results of the case study suggest project stakeholders focusing on complex interactions among criteria to reduce project complexity.Originality/valueThis study contributes to the body of knowledge by providing a comprehensive complexity prioritization framework that grasps the interrelationship of complexity criteria. For stakeholders of ID projects, the findings provide insightful perspectives to understand complexity, which can help to enhance project performance.
Nestlé South Africa: leading multi-stakeholder partnership response in the COVID-19 context
Authors: Pillay Ravi , Scheepers Caren Brenda 
Published: August 2020

Learning outcomes
The learning outcomes are as follows: identifying and prioritising of stakeholders’ needs during crises; gaining insight into applying contextual intelligence in leaders’ decision-making on philanthropic investments; and evaluating initiatives by differentiating between creating shared value and corporate social responsibility.

Case overview/synopsis
On 15 March 2020, Bruno Olierhoek, Chairman and MD, Nestlé East and Southern Africa considers his dilemma of where to focus his community support initiatives during COVID-19, which could reflect their company’s purpose of enhancing quality of life and contributing to a healthier future in their response to the crisis? Also, creating shared value (CSV) was in their DNA as a company, and they wanted to do more than philanthropic gestures; therefore, they had to decide carefully about leveraging their strategic partnerships in the relief effort. The case highlights existing community involvement projects, pre-COVID-19, which illustrate multi-stakeholder collaboration. These existing trust relationships and partnerships are then leveraged during the COVID-19 pandemic. The case highlights unintended consequences of Nestlé’s gesture of donating food products to the 5,000 frontline health-care workers for specific stakeholder groups, such as the positive emotional responses of Nestlé’s own employees. These events in the case relate to existing theoretical frameworks, such as corporate citizenship which elicits pro-organisational behaviour in stakeholder groups.

Complexity academic level
Postgraduate programmes MBA or MPhil.

Supplementary materials
Teaching Notes are available for educators only.

Subject code
CSS: 7 Management Science
Looking at you: celebrity direct eye gaze influences social media post effectiveness
Authors: Ilicic Jasmina , Brennan Stacey M. 
Published: August 2020

PurposeThe purpose of this paper is to introduce and examine the effect of a celebrity’s eye gaze on self-celebrity connection. A celebrity’s direct (vs averted) eye gaze can be used as a tactic in social media posts to increase self-celebrity connection and behavioral intentions. Examining the effectiveness of a celebrity’s eye gaze is important, as celebrities regularly use social media to manage their brand image and to build a relationship with consumers.Design/methodology/approachStudy 1 examines the effect of a celebrity’s eye gaze (direct vs averted) on self-celebrity connection. Study 2 investigates the role of celebrity authenticity in explaining the effect of a celebrity’s eye gaze on consumer–celebrity brand relationships. Study 3 examines the moderating role of a non-Duchenne smile (fake, social smile) in diluting the effect of a celebrity’s direct eye gaze on self-celebrity connection and the downstream consequences on behavioral intentions.FindingsThe findings from Study 1 indicate that a celebrity’s direct (averted) eye gaze strengthens (weakens) self-celebrity connection. Study 2 provides evidence of celebrity authenticity as the explanation for stronger consumer–celebrity connection when a celebrity is featured with a direct eye gaze. The results of Study 3 show that a fake smile in a celebrity’s social media posts can weaken relationships with and behavioral intentions toward celebrities with a direct eye gaze.Research limitations/implicationsThis paper is limited, as it focuses only on eye gaze and smiles as non-verbal cues depicted in celebrity images on social media.Practical implicationsThis paper has important implications for celebrities, celebrity brand managers (including digital/social media marketing managers and public relations professionals) and advertisers. Celebrities, celebrity brand managers and advertisers should develop social media posts that can strengthen consumer–celebrity relationships and positively influence behaviors toward the celebrity through: 1) ensuring that photographs are taken with the celebrity looking directly into the camera at the target (audience); and 2) avoiding posting images of a celebrity’s direct eye gaze with a non-Duchenne (fake) smile.Originality/valueThis paper introduces and provides evidence of a celebrity’s direct eye gaze–self-celebrity relationship effect. Tactics, such as eye gaze, can strengthen consumer–celebrity relationships, which is crucial in building brand equity and in increasing financial value for the celebrity.
Which journal ranking list? A case study in business and economics
Authors: Jaafar Rayana , Pereira Vijay , Saab Samer S. , El-Kassar Abdul-Nasser 
Published: August 2020

PurposeWith over 3,000 academic journals in the fields of Business and Economics, most academics face a hard time selecting an adequate journal to submit their work to. In today's demanding academic environment and with the presence of different journal ranking lists (JRLs), the selection becomes more difficult when considering employment, promotion and funding. The purpose of this paper is to explore key differences among multiple JRLs pertinent to the latter common objectives. An extensive analysis is conducted to compare the content of journals in the Australian Business Deans Council (ABDC) Journal Quality list, Scopus and Web of Science (WoS) in the fields of Business and Economics. Then, a case of a university with medium research output is considered where scholarly performance evaluation is based on the ABDC Journal Quality List.Design/methodology/approachAfter ranking journals in the fields of Business and Economics based on SCImago Journal Rank (SJR) indicator, JCR's Journal Impact Factor (JIF) and JCR's Eigenfactor (EF), a methodology is proposed to categorize journals in the three JRLs into the same categorization adopted by ABDC. The latter establishes a way to compare the four JRLs under consideration and serves as a basis to compare and analyze the content of journals in the ABDC Journal Quality list, Scopus and WoS. As a proxy impact metric, a normalized citation count is associated with each article based on Google Scholar. The publications of the considered university are then evaluated from the perspective of the four JRLs in terms of citation-based impact and quality while considering the exposure to popular world university ranking tables.FindingsFor journals classified under fourth tier by ABDC, over 53 and 59% are not indexed by Scopus and WoS, respectively. In this case study, over 42% of the publications appear in journals that are not listed in JCR despite the fact that over 94% of them are listed by the SJR list. Generally, publications that appear in journals listed by JCR achieve, on a yearly average, significantly higher citation rates when compared to those that appear in journals listed in ABDC and SJR Lists.Originality/valueA four-tier mapping is proposed for consistent comparison among JRLs. Normalized citation count associated with each article based on Google Scholar is employed for evaluation. The findings provide recommendations for scholars, administrators and global universities, including Euro-Med Universities, on which JRL can be more influential for both faculty development and positioning of the university.
The impact of infrastructure investment and development on economic growth on BRICS
Authors: Apurv Rohit , Uzma Shigufta Hena 
Published: August 2020

Purpose
The purpose of the paper is to examine the impact of infrastructure investment and development on economic growth in Brazil, Russia, India, China and South Africa (BRICS) countries. The effect is examined for each country separately and also collectively by combining each country.

Design/methodology/approach
Ordinary least square regression method is applied to examine the effects of infrastructure investment and development on economic growth for each country. Panel data techniques such as panel least square method, panel least square fixed-effect model and panel least square random effect model are used to examine the collective impact by combining all countries in BRICS. The dynamic panel model is also incorporated for analysis in the study.

Findings
The results of the study are mixed. The association between infrastructure investment and development and economic growth for countries within BRICS is not robust. There is an insignificant relationship between infrastructure investment and development and economic growth in Brazil and South Africa. Energy and transportation infrastructure investment and development lead to economic growth in Russia. Telecommunication infrastructure investment and development and economic growth have a negative relationship in India, whereas there is a negative association between transport infrastructure investment and development and economic growth in China. Panel data results conclude that energy infrastructure investment and development lead to economic growth, whereas telecommunication infrastructure investment and development are significant and negatively linked with economic growth.

Originality/value
The study is novel as time series analysis and panel data analysis are used, taking the time span for 38 years (1980–2017) to investigate the influence of infrastructure investment and development on economic growth in BRICS Countries. Time-series regression analysis is used to test the impact for individual countries separately, whereas panel data regression analysis is used to examine the impact collectively for all countries in BRICS.