bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlations in population dynamics in multi-component networks
Authors: Saraf Sonica , Young Lai-Sang 
Published: November 2019

AbstractThis is a theoretical study of correlations in spiking activity between neuronal populations. We focus on the spike firing of entire local populations without regard to the identities of the neurons that fire the spikes, and show that such a population-level metric is more robust than correlations between pairs of neurons. Between any source and target populations, there is an intrinsic response time characterized by the phase-shift that maximizes the correlation between their spiking. We find that the alignment of gamma-band rhythms contributes significantly to the positive correlations between populations. Hence, the correlation metric sheds light on the transference of gamma rhythms between populations; the effectiveness of such transference has been hypothesized to be connected to communication between brain regions. We investigate the dependence of correlations on connectivity and degree of synchrony, and consider multi-component network motifs with configurations known to occur in real cortex, studying the correlations between components that are directly or indirectly connected, by single or multiple pathways, with or without feedback. Mechanistic explanations are offered for many of the phenomena observed.
Cell-type specific asynchronous modulation of PKA by dopamine during reward based learning
Authors: Lee Suk Joon , Lodder Bart , Chen Yao , Patriarchi Tommaso , Tian Lin , Sabatini Bernardo L. 
Published: November 2019

SummaryCanonical reinforcement learning models postulate that dopamine neurons encode reward prediction error (RPE) and provide a teaching signal to striatal spiny projection neurons (SPNs) in the form of dopamine (DA) release. DA is thought to guide learning via dynamic modulation of protein kinase A (PKA) in SPNs. However, this fundamental assumption remains untested in behaving animals. Here we utilized multi-channel fiber photometry and fluorescence lifetime photometry (FLiP) to monitor the activity of DA neurons, extracellular DA levels, and net PKA activity in SPNs in the nucleus accumbens during learning. We found dynamic encoding of RPE in the activity of DA neurons, which is both necessary and sufficient to explain striatal DA levels and SPN PKA activity. The modulation of PKA in SPNs that express type-1 (D1R-SPNs) and type-2 (D2R-SPNs) DA receptors was dichotomous such that in each cell class it is selectively sensitive to increases and decreases in DA, respectively, and occur at and support different phases of learning. Thus, PKA-dependent pathways in D1R- and D2R-SPNs are asynchronously engaged by RPE-encoding DA signals to promote different aspects of reinforcement learning: the former responsible for the initial association between action and outcome and the latter responsible for refining the learned association.
Principles of tactile search over the body
Authors: Halfen Elizabeth J. , Magnotti John F. , Rahman Md. Shoaibur , Yau Jeffrey M. 
Published: November 2019

AbstractAlthough we experience complex patterns over our entire body, how we selectively perceive multi-site touch over our bodies remains poorly understood. Here, we characterized tactile search behavior over the body using a tactile analog of the classic visual search task. Participants judged whether a target stimulus (e.g., 10-Hz vibration) was present or absent on the upper or lower limbs. When present, the target stimulus could occur alone or with distractor stimuli (e.g., 30-Hz vibrations) on other body locations. We varied the number and spatial configurations of the distractors as well as the target and distractor frequencies and measured the impact of these factors on search response times. First, we found that response times were faster on target-present trials compared to target-absent trials. Second, response times increased with the number of stimulated sites, suggesting a serial search process. Third, search performance differed depending on stimulus frequencies. This frequency-dependent behavior may be related to perceptual grouping effects based on timing cues. We constructed models to explore how the locations of the tactile cues influenced search behavior. Our modeling results reveal that, in isolation, cues on the index fingers make relatively greater contributions to search performance compared to stimulation experienced on other body sites. Additionally, co-stimulation of sites within the same limb or simply on the same body side preferentially influence search behavior. Our collective findings identify some principles of attentional search that are common to vision and touch, but others that highlight key differences that may be unique to body-based spatial perception.New & NoteworthyLittle is known about how we selectively experience multi-site touch over the body. Using a tactile analog of the classic visual search paradigm, we show that tactile search behavior for flutter cues is generally consistent with a serial search process. Modeling results reveal the preferential contributions of index finger stimulation and two-site interactions involving ipsilateral and within-limb patterns. Our results offer initial evidence for spatial and temporal principles underlying tactile search behavior over the body.
In vivo nuclear RNA structurome reveals RNA-structure regulation of mRNA processing in plants
Authors: Liu Zhenshan , Liu Qi , Yang Xiaofei , Zhang Yueying , Norris Matthew , Chen Xiaoxi , Cheema Jitender , Ding Yiliang 
Published: November 2019

AbstractmRNA processing is critical for gene expression. A challenge in regulating mRNA processing is how to recognize the actual mRNA processing sites, such as splice and polyadenylation sites, when the sequence content is insufficient for this purpose. Previous studies suggested that RNA structure affects mRNA processing. However, the regulatory role of RNA structure in mRNA processing remains unclear. Here, we performed in vivo selective 2’-hydroxyl acylation analysed by primer extension (SHAPE) chemical profiling on Arabidopsis nuclear RNAs and generated the in vivo nuclear RNA structure landscape. We found that nuclear mRNAs fold differently from cytosolic mRNAs. Notably, we discovered a two-nucleotide single-stranded RNA structure feature upstream of 5’ splice sites that is strongly associated with splicing and the selection of alternative 5’ splice sites. Moreover, we found the single-strandedness of branch point is also associated with 3’ splice site recognition. We also identified an RNA structure feature comprising two close-by single-stranded regions that is specifically associated with both polyadenylation and alternative polyadenylation events. Our work demonstrates an RNA structure regulatory mechanism for mRNA processing.
Computational analysis of filament polymerization dynamics in cytoskeletal networks
Authors: Caldas Paulo , Radler Philipp , Sommer Christoph , Loose Martin 
Published: November 2019

AbstractThe polymerization–depolymerization dynamics of cytoskeletal proteins play essential roles in the self-organization of cytoskeletal structures, in eukaryotic as well as prokaryotic cells. While advances in fluorescence microscopy and in vitro reconstitution experiments have helped to study the dynamic properties of these complex systems, methods that allow to collect and analyze large quantitative datasets of the underlying polymer dynamics are still missing. Here, we present a novel image analysis workflow to study polymerization dynamics of active filaments in a non-biased, highly automated manner. Using treadmilling filaments of the bacterial tubulin FtsZ as an example, we demonstrate that our method is able to specifically detect, track and analyze growth and shrinkage of polymers, even in dense networks of filaments. We believe that this automated method can facilitate the analysis of a large variety of dynamic cytoskeletal systems, using standard time-lapse movies obtained from experiments in vitro as well as in the living cell. Moreover, we provide scripts implementing this method as supplementary material.
Utilising low cost RGB-D cameras to track the real time progress of a manual assembly sequence
Authors: Oyekan John , Fischer Axel , Hutabarat Windo , Turner Christopher , Tiwari Ashutosh 
Published: November 2019

Purpose
The purpose of this paper is to explore the role that computer vision can play within new industrial paradigms such as Industry 4.0 and in particular to support production line improvements to achieve flexible manufacturing. As Industry 4.0 requires “big data”, it is accepted that computer vision could be one of the tools for its capture and efficient analysis. RGB-D data gathered from real-time machine vision systems such as Kinect ® can be processed using computer vision techniques.

Design/methodology/approach
This research exploits RGB-D cameras such as Kinect® to investigate the feasibility of using computer vision techniques to track the progress of a manual assembly task on a production line. Several techniques to track the progress of a manual assembly task are presented. The use of CAD model files to track the manufacturing tasks is also outlined.

Findings
This research has found that RGB-D cameras can be suitable for object recognition within an industrial environment if a number of constraints are considered or different devices/techniques combined. Furthermore, through the use of a HMM inspired state-based workflow, the algorithm presented in this paper is computationally tractable.

Originality/value
Processing of data from robust and cheap real-time machine vision systems could bring increased understanding of production line features. In addition, new techniques that enable the progress tracking of manual assembly sequences may be defined through the further analysis of such visual data. The approaches explored within this paper make a contribution to the utilisation of visual information “big data” sets for more efficient and automated production.
CSR performance and annual report readability: evidence from France
Authors: Bacha Sami , Ajina Aymen 
Published: November 2019

Purpose
This study aims to examine the relationship between the corporate social responsibility (CSR) performance and the readability of annual report. The shareholder theory suggests that CSR firms will provide more transparent disclosures because this reflects a socially and environmentally responsible behavior and a firm’s commitment to high ethical standards. In the same time, the agency theory offers an opposite view. It predicts that opportunistic managers use CSR as an entrenchment strategy and hide their maneuvers through complex textual financial disclosures.

Design/methodology/approach
Based on a sample of 100 listed firms on the French CACAll-shares index over the period from 2013 to 2016, the authors use a panel regression analysis and run other estimation methods (IV-2SLS) and simultaneous equation model to address the endogeneity issues. They assess the readability of annual reports using the Gunning-Fog Index and the Flesch Index derived from the computational linguistics literature.

Findings
The results show a significant positive relationship between CSR performance and the readability of annual report. Firms engaging in CSR practices are more likely to provide transparent disclosures with higher readability because this reflects a socially responsible behavior and a firm’s commitment to high ethical standards. This result supports the stakeholder theory and the corporate reputational view. The finding is also robust to alternative readability measurements and to endogeneity bias.

Practical implications
This study helps all market participants to more comprehensively evaluate the CSR performance disclosed on annual report. It encourages managers to consider CSR as a means to prevent the opacity risk through improved information quality. It also drives French authorities to better regulate the narrative disclosure of CSR firms and change the way companies design their reporting practices. Moreover, it encourages CSR rating agencies to become the dominant definition of CSR evaluation by granting more importance to the quality of disclosed information.

Originality/value
This study extends previous research on the potential impact of CSR on information quality measured by annual report readability in the French context. Unlike prior studies on the impact of CSR on information quality, that focus exclusively on earnings management and adopt qualitative approaches to assess the SCR score, the authors use simultaneously the Gunning–Fog Index and the Flesch Index to assess the information quality and extract the CSR score from the CSRHub database of companies’ social, environmental and governance performance.
Predictors of knowledge transfer between expatriates and host country nationals
Authors: Zulkifly Nurul Afiqah , Ismail Maimunah , Hamzah Siti Raba’ah 
Published: November 2019

PurposeThe purpose of this paper is to investigate the influences of cultural intelligence, feedback-seeking behavior and shared vision as a mediator on bi-directional knowledge transfer involving expatriates and host country nationals (HCNs).Design/methodology/approachThis paper integrates the signaling theory, the social capital theory and the anxiety and uncertainty theory in investigating the relationships between predictors and knowledge transfer in a bi-directional manner. The participants of the study were 125 expatriate-HCN pairs of MNCs and local organizations in the areas of Klang Valley, Malaysia.FindingsShared vision was found to significantly mediate the influences of cultural intelligence and feedback-seeking behavior on knowledge transfer as perceived by the respective respondents.Originality/valueCo-existence between expatriates and HCNs leads to many organizational outcomes including knowledge transfer. This paper additionally provides theoretical and practical implications to human resource practices.
Understanding emotional customer experience and co-creation behaviours in luxury hotels
Authors: Wu Szu-Hsin , Gao Yuhui 
Published: November 2019

Purpose
A holistic understanding of sources that evoke customer emotions is essential for creating a positive emotional customer experience (ECX). Despite a significant focus on the cognitive aspect of customer experience and traditional customer behaviours (e.g. loyalty and satisfaction), limited attention has been paid to ECX and co-creation behaviours. The purpose of this paper is to address this important knowledge gap by identifying different emotions and prominent sources of ECX (i.e. emotion triggers and constructors) during service interactions. By doing so, key customer co-creation behaviours are also identified, which help enhance positive customer experience.

Design/methodology/approach
A combined application of the appraisal theory and thematic analysis was used to explore ECX, its sources and co-creation behaviours as observed from 1,063 TripAdvisor customer reviews of luxury hotels in Ireland.

Findings
The results show that a single service interaction can evoke multiple emotions during the interaction process. The findings capture prominent emotions that customers experience and various important emotion triggers (physical environment, service management and offerings and human interaction) and constructors (customer expectation, accumulated service experience and culture fusion and authenticity). Three main customer co-creation behaviours (reinforcing intention, active and resourceful behaviours), which help facilitate the co-creation of positive customer emotions, are also identified.

Originality/value
The study proposes a new framework that provides unique insights into ECX to guide service improvement and innovation. A novel approach of applying the appraisal theory to a netnographic study is used to develop an ECX framework, which integrates various emotion triggers and constructors, and subsequent customer co-creation behaviours in the hotel industry.
A comparative study of online consumer behavior: a tale of two research methods
Authors: Huarng Kun-Huang , Yu Tiffany Hui-Kuang 
Published: November 2019

PurposeThe use of linear regression analysis is common in the social sciences. The purpose of this paper is to show the advantage of a qualitative research method, namely, structured qualitative analysis (SQA), over the linear regression method by using different characteristics of data.Design/methodology/approachData were gathered from a study of online consumer behavior in Taiwan. The authors changed the content of the data to have different sets of data. These data sets were used to demonstrate how SQA and linear regression works individually, and to contrast the empirical analyses and empirical results from linear regression and SQA.FindingsThe linear regression method uses one equation to model different characteristics of data. When facing a data set containing a big and a small size of different characteristics, linear regression tends to provide an equation by modeling the characteristics of the big size data and subsuming those of the small size. When facing a data set containing similar sizes of data with different characteristics, linear regression tends to provide an equation by averaging these data. The major concern is that the one equation may not be able to reflect the data of various characteristics (different values of independent variables) that result in the same outcome (the same value of dependent variable). In contrast, SQA can identify various variable combinations (multiple relationships) leading to the same outcome. SQA provided multiple relationships to represent different sizes of data with different characteristics so it created consistent empirical results.Research limitations/implicationsTwo research methods work differently. The popular linear regression tends to use one equation to model different sizes and characteristics of data. The single equation may not be able to cover different behaviors but may lead to the same outcome. Instead, SQA provides multiple relationships for different sizes of data with different characteristics. The analyses are more consistent and the results are more appropriate. The academics may re-think the existing literature using linear regression. It would be interesting to see if there are new findings for similar problems by using SQA. The practitioners have a new method to model real world problems and to understand different possible combinations of variables leading to the same outcome. Even the relationship obtained from a small data set may be very valuable to practitioners.Originality/valueThis paper compared online consumer behavior by using two research methods to analyze different data sets. The paper offered the manipulation of real data sets to create different data sizes of different characteristics. The variations in empirical results from both methods due to the various data sets facilitate the comparison of both methods. Hence, this paper can serve as a complement to the existing literature, focusing on the justification of research methods and on limitations of linear regression.
Marketing intensity and persistence of firm performance: empirical evidence from Indonesia
Authors: Jaisinghani Dinesh , Kaur Harwinder , Goyal Jatin , Joshi Mahesh 
Published: November 2019

PurposeThe purpose of this paper is to examine the degree of persistence of firm performance for publicly listed firms in Indonesia. The study also explores the impact of marketing expenditure on firm’s performance.Design/methodology/approachThe data comprise 165 listed firms operating in Indonesia over the period 2007–2016. Dynamic panel regression estimations using Arellano and Bond (1991) and Blundell and Bond (1998) techniques have been deployed to generate the results.FindingsThe findings show the existence of positive persistence and sub-optimal level of competition in the performance of Indonesian firms. The results highlight that marketing intensity has a positive and significant impact on firm performance. The positive persistence hints at creation of substantial entry and exit barriers by the Indonesian firms and also indicate that Indonesian firms are able to create behavioral inertia among their consumers by properly directing their marketing efforts.Practical implicationsThere is a need on the part of management to strengthen the short-term profit capabilities to nurture long-term benefits of profit maximization. On the regulators part, the authorities should frame the policies to foster long-run competition.Originality/valueThe current study contributes to the sparse literature on persistence of firm performance in the context of emerging economies like Indonesia. This is the first study on persistence of firm performance for publicly listed firms in Indonesia.
Predicting crack through a well generalized and optimal tree-based regressor
Authors: Choudhury Sasanka , Thatoi Dhirendra Nath , Hota Jhalak , Rao Mohan D. 
Published: November 2019

Purpose
To avoid the structural defect, early crack detection is oneof the important aspects in the recent area of research. The purpose of this paper is to detect the crack before its failure by means of its position and severity.

Design/methodology/approach
This paper uses two trees based regressors, namely, decision tree (DT) regressor and random forest (RF) regressor for their capabilities to adopt different types of parameter and generate simple rules by which the method can predict the crack parameters with better accuracy, making it possible to effectively predict the crack parameters such as its location and depth before failure of the beam.

Findings
The predicted parameters can be achieved, if the relationship between vibration and crack parameters can be attained. The relationship yields the results of beam natural frequencies, which is used as the input value for the regression techniques. It is observed that the RF regressor predicts the parameters with better accuracy as compared to DT regressor.

Originality/value
The idea is used the developed regression techniques to identify the crack parameters which are more effective as compared to other developed methods because the alternate name of prediction is called regression. The authors have used DT regressor and RF regressor to achieve the target. In this paper care has been given to the generalization of the model, so that the adaptability of the model can be ensured. The robustness of proposed methods has been verified in support of numerical and experimental analysis.