bluuebunny/crossref_metadata_2025_split huggingface dataset:
Independent synaptic inputs to motor neurons driving antagonist muscles
Authors: Borzelli Daniele , Vieira T.M.M. , Botter A. , Gazzoni M. , Lacquaniti F. , d’Avella A. 
Published: August 2022

AbstractThe CNS may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of co-contraction, which does not contribute to joint torque generation but allows to modulate mechanical impedance. Whether co-contraction is controlled through the same synaptic input to motor neurons involved in generating joint torque is still unclear. We hypothesized that co-contraction is controlled through a specific synaptic input, independent from that underlying the control of torque. To test this hypothesis, we asked participants to concurrently generate multi-directional isometric forces at the hand and to modulate the co-contraction of arm muscles to displace and stabilize a virtual end-effector. The firings of motor units were identified through decomposition of High-Density EMGs collected from two antagonist muscles, Biceps Brachii and Triceps Brachii. We found significant peaks in the coherence between the neural drive to the two muscles, suggesting the existence of a common input modulating co-contraction across different exerted forces. Moreover, the within-muscle coherence computed after removing the component synchronized with the drive to the antagonist muscle or with the exerted force revealed two subsets of motor neurons that were selectively recruited to generate joint torque or modulate co-contraction. This study is the first to directly investigate the extent of shared versus independent control of antagonist muscles at the motor neuron level in a task involving concurrent force generation and modulation of co-contraction.Significance StatementHow the CNS coordinates the activity of antagonist muscles to modulate limb mechanical impedance is still unclear. We hypothesized that a common synaptic input, shared by the motor neurons pools of antagonist muscles, and independent from the inputs underlying force generation, regulates co-contraction. We then analyzed the coherence between the firing trains of motor neurons to assess whether a common input drives antagonist muscles only during tasks requiring co-activation for impedance but not for force generation. Results highlighted the existence of separate neural pathways underlying the control of joint torque or impedance. Scientifically, this study addressed an important gap in understanding how neural drive is delivered to antagonist muscles, disentangling the control of muscles for joint torque or impedance modulation.
Corporate governance, CEO compensation, and corporate performance: evidence from India
Authors: Jatana Chhavi 
Published: August 2022

Purpose
The purpose of this study is to examine the impact of corporate governance (CG) on chief executive officer compensation (CEO COMP) and pay–performance relationship (PPR) in Indian listed firms.

Design/methodology/approach
A sample of 196 companies listed on the S&P BSE 500 (Standard and Poor's Bombay Stock Exchange 500) Index has been analyzed using the panel (random effects) regression technique over the period 2010–2019. In addition, the system GMM technique was used to deal with the endogeneity issue.

Findings
The study found that block ownership and ownership concentration negatively impact COMP measures and PPR. Board size also had a negative direct and moderating impact on CEO COMP; however, the linkages were generally insignificant, especially for total pay. Similarly, outsider blockholders were found to be playing an insignificant role. Further, board independence positively influences COMP levels and PPR, though the results were mixed with respect to significance. Finally, CEO duality positively and significantly influences CEO COMP and PPR. A comparison before and after the new Indian Companies Act 2013 also revealed similar results, particularly in the after period. It suggests that the new legislative initiative was not effective enough in improving the CG and, hence, the alignment of pay with performance.

Originality/value
This study investigates the direct and moderating impact of CG on CEO COMP in the context of emerging economy India. Further, it makes a comparison before and after the introduction of the new governance reform, that is, the Indian Companies Act, 2013. Moreover, providing support to the entrenchment effect, the study reveals that large shareholders expropriate minority shareholders’ wealth by not aligning CEO pay with performance, making agency problems graver in emerging economies like India.
Coupling coordination degree spatiotemporal characteristics and driving factors between new urbanization and construction industry: evidence from China
Authors: Ma Shengbin , Li Zhongfu , Li Long , Yuan Mengqi 
Published: August 2022

PurposeThe coordinated development of the urbanization and construction industry is crucial for the sustainable development of cities. However, the coupling relationship and coordination mechanism between them remain unclear. To bridge this gap, this study attempts to explore the level of coupling coordination between new urbanization and construction industry development and investigate the critical driving factors influencing their coupling coordination degree.Design/methodology/approachBy referring to the existing literature, two index systems were established to evaluate the development level of the new urbanization and construction industry. The spatiotemporal characteristics of the coupled coordinated development of the new urbanization and construction industry in China from 2014 to 2020 were investigated using the coupling coordination model. The Markov chain and geographic detector were adopted to understand the transition probability and driving factors of the coupling coordination degree.FindingsThe results indicate that the coupling degree of China's new urbanization and construction industry is high, and the two systems exhibit obvious interaction phenomena. However, the construction industry in most provinces lags behind the new urbanization. A positive interactive relationship and coordination mechanism has not been established between the two systems. Furthermore, the coupling contribution degree of the driving factors from high to low is as follows: market size > labor resource concentration > government investment ability > economic development level > industrial structure > production efficiency > technology level. Accordingly, a driving mechanism including market, policy, economic, and production technology drivers was developed.Originality/valueThis study contributes to the existing body of knowledge by providing a set of scientific analysis methods to address the deficiency of coordination mechanism research on new urbanization and the construction industry. The results also provide a theoretical basis for decision makers to develop differentiated sustainable development policies.
Finnish university students' satisfaction with e-learning outcomes during the COVID-19 pandemic
Authors: Nikou Shahrokh , Maslov Ilia 
Published: August 2022

PurposeStudents' satisfaction with e-learning outcomes is a vital component in determining the adoption of e-learning systems. Understanding the antecedent factors impacting students' satisfaction with e-learning outcomes helps decision-makers at the higher education to take the necessary actions to enhance the quality of students' performance, especially during the exceptional times, such as the COVID-19 pandemic.Design/methodology/approachThis paper aims to determine and analyse the antecedent factors influencing students' satisfaction with e-learning outcomes during the pandemic. Structural equation modelling (SEM) is used to analysis a proposed research model.FindingsThe SEM results show that digital communities in e-learning, information technology (quality and accessibility) and the online course design quality directly influence students' satisfaction with e-learning outcomes. More interestingly, results show that the COVID-19-related factors (1) awareness of the COVID-19, (2) perceived challenges (negatively) and (3) the educational institutions' preparedness also influence e-learning outcomes.Research limitations/implicationsThe results suggest that the decision-makers at the educational institutions should consider adopting a blended learning system approach to deliver e-learning during the emergency, such as the COVID-19 outbreak situation.Originality/valueThis is one of the first studies in higher education context, which seek to identify the antecedent factors that influence students' satisfaction with e-learning outcomes during the COVID-19 pandemic.
Fairness perceptions regarding in-work benefits: a survey experiment
Authors: Senghaas Monika , Osiander Christopher , Stephan Gesine , Struck Olaf 
Published: August 2022

PurposeIn many countries, individuals can receive welfare support whilst simultaneously being employed. The level of earned income that welfare recipients are allowed to keep has long been a subject of debate. Core issues include whether in-work benefit regulations provide incentives for individuals to expand labour market participation and are thus also socially effective and whether the population perceives welfare benefits for individuals who earn own income as fair. This article contributes to the debate about the social legitimacy of in-work benefit regulations by shedding light on the principles guiding judgements about an adequate amount of in-work benefit receipt.Design/methodology/approachThe authors use a factorial survey experiment to investigate which factors guide judgements about an adequate level of in-work benefit receipt. In the authors' factorial survey, the household composition, health status, and monthly earnings of a hypothetical in-work benefit recipient were varied experimentally. The study investigates Germany's basic income support programme, a means-tested social policy programme that targets both unemployed and employed individuals.FindingsThe results show that respondents consider higher earnings retention rates for lower-income earners to be fair. This preference mirrors the German legislation, which is based on the principle of need. Furthermore, the presence of children and of physical as well as mental health impairments are associated with support for higher earnings retention rates.Originality/valueThe findings suggest that citizens support the core features of in-work benefit regulations but do not consider in-work benefit recipients as a homogenous group when assessing the adequate level of benefit receipt.
Discovering a tourism destination with social media data: BERT-based sentiment analysis
Authors: Viñán-Ludeña Marlon Santiago , de Campos Luis M. 
Published: August 2022

Purpose
The main purpose of this paper is to analyze a tourist destination using sentiment analysis techniques with data from Twitter and Instagram to find the most representative entities (or places) and perceptions (or aspects) of the users.

Design/methodology/approach
The authors used 90,725 Instagram posts and 235,755 Twitter tweets to analyze tourism in Granada (Spain) to identify the important places and perceptions mentioned by travelers on both social media sites. The authors used several approaches for sentiment classification for English and Spanish texts, including deep learning models.

Findings
The best results in a test set were obtained using a bidirectional encoder representations from transformers (BERT) model for Spanish texts and Tweeteval for English texts, and these were subsequently used to analyze the data sets. It was then possible to identify the most important entities and aspects, and this, in turn, provided interesting insights for researchers, practitioners, travelers and tourism managers so that services could be improved and better marketing strategies formulated.

Research limitations/implications
The authors propose a Spanish-Tourism-BERT model for performing sentiment classification together with a process to find places through hashtags and to reveal the important negative aspects of each place.

Practical implications
The study enables managers and practitioners to implement the Spanish-BERT model with our Spanish Tourism data set that the authors released for adoption in applications to find both positive and negative perceptions.

Originality/value
This study presents a novel approach on how to apply sentiment analysis in the tourism domain. First, the way to evaluate the different existing models and tools is presented; second, a model is trained using BERT (deep learning model); third, an approach of how to identify the acceptance of the places of a destination through hashtags is presented and, finally, the evaluation of why the users express positivity (negativity) through the identification of entities and aspects.
Mental health professionals’ views of the borderline personality disorder diagnosis for children and young people: a Q-methodological study
Authors: Vickers Gemma , Combes Helen , Lonsdale Jennie 
Published: August 2022

Purpose
Borderline personality disorder (BPD) is a controversial psychiatric diagnosis. Despite an increasing amount of research looking at the BPD diagnosis when applied to young people, there is limited understanding of the key viewpoints of mental health professionals working with young people in the UK. This research aims to use Q-methodology to contribute to understanding the multiple views of the diagnosis.

Design/methodology/approach
Q-statements about views of the BPD diagnosis were selected from relevant journals, internet sites and social media platforms and were validated by a Q-methodology research group, the research supervisors and an online group of individuals with BPD. Q-sorts were then used to explore the viewpoints of 27 mental health professionals in the UK working with children and adolescents. Analysis of the data was completed using Q-methodology analysis software.

Findings
Three main factors emerged from the data, explaining 66% of the variance. Of the 27 participants, 24 loaded onto these three factors, defined as: harmful not helpful; language and optimism; and caution and specialist services. Three Q-sorts did not load significantly onto any one factor.

Originality/value
There appears to be at least three ways of understanding the BPD diagnosis for young people. It may be useful for clinicians to consider and share their own viewpoint, be open to difference and formulate difficulties from an individual perspective.
Condition-based monitoring of the rail wheel using logical analysis of data and ant colony optimization
Authors: Osman Hany , Yacout Soumaya 
Published: August 2022

PurposeIn this paper, a data mining approach is proposed for monitoring the conditions leading to a rail wheel high impact load. The proposed approach incorporates logical analysis of data (LAD) and ant colony optimization (ACO) algorithms in extracting patterns of high impact loads and normal loads from historical railway records. In addition, the patterns are employed in establishing a classification model used for classifying unseen observations. A case study representing real-world impact load data is presented to illustrate the impact of the proposed approach in improving railway services.Design/methodology/approachApplication of artificial intelligence and machine learning approaches becomes an essential tool in improving the performance of railway transportation systems. By using these approaches, the knowledge extracted from historical data can be employed in railway assets monitoring to maintain the assets in a reliable state and to improve the service provided by the railway network.FindingsResults achieved by the proposed approach provide a prognostic system used for monitoring the conditions surrounding rail wheels. Incorporating this prognostic system in surveilling the rail wheels indeed results in better railway services as trips with no-delay or no-failure can be realized. A comparative study is conducted to evaluate the performance of the proposed approach versus other classification algorithms. In addition to the highly interpretable results obtained by the generated patterns, the comparative study demonstrates that the proposed approach provides classification accuracy higher than other common machine learning classification algorithms.Originality/valueThe methodology followed in this research employs ACO algorithm as an artificial intelligent technique and LDA as a machine learning algorithm in analyzing wheel impact load alarm-collected datasets. This new methodology provided a promising classification model to predict future alarm and a prognostic system to guide the system while avoiding this alarm.
When sensemaking remains local: implications for distributed sensemaking in reform implementation
Authors: Filstad Cathrine , Olsen Trude Høgvold , Thomassen Anja Overgaard 
Published: August 2022

Purpose
This paper aims to contribute to the literature on distributed sensemaking by studying how the police establish and develop their new position as police contacts during the police reform.

Design/methodology/approach
The authors studied how the position of police contact, a cornerstone of the recent Norwegian police reform, was interpreted and practised. The authors interviewed police contacts at two different times during reform implementation to explore how they made sense of and practised their job.

Findings
The authors identified three interpretations of the position of police contact and describe them as ideal types: an administrative position, a professional position and a strategic position. The ideal types were reinforced rather than developing towards a shared understanding. Our data demonstrate that the sensemaking processes and experimentation to settle into the new position involved local actors internally in the police and externally in relation to local authorities, and reinforced local interpretations.

Originality/value
This study supports the notion of sensemaking as distributed but extends previous research by suggesting that “ideal types” help us understand the content of interpretations. This study also extends the understanding by showing that distributed sensemaking takes place as individuals make sense of more open-ended problems. This challenges the understanding of the term distributed, because unless challenged, distributed sensemaking in isolated pockets of the organization remain local, and the authors suggest that the term local distributed sensemaking captures this phenomenon.
Distinguishing the most valuable consumers in social commerce using graphical evaluation and review technique – in the view of incentives
Authors: Chen Xu , Wu Yingliang , Liao Junfeng , Zuo Wenming , Zhong Rujie 
Published: August 2022

PurposeThe incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers’ responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.Design/methodology/approachBased on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of “network stage”, “consumer type”, and “resource type” to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.FindingsThe results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.Practical implicationsUnder the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers > agent consumers > commenting consumers > potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.Originality/valueThis paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises’ customer relationship management and marketing decisions.
Benchmarking eleven biodiversity indicators based on environmental DNA surveys: More diverse functional traits and evolutionary lineages inside marine reserves
Authors: Dalongeville Alicia , Boulanger Emilie , Marques Virginie , Charbonnel Eric , Hartmann Virginie , Santoni Marie Catherine , Deter Julie , Valentini Alice , Lenfant Philippe , Boissery Pierre , Dejean Tony , Velez Laure , Pichot Franck , Sanchez Loic , Arnal Veronique , Bockel Thomas , Delaruelle Gwenaelle , Holon Florian , Milhau Tristan , Romant Lola , Manel Stéphanie , Mouillot David 
Published: August 2022

Abstract

To mitigate the ongoing threats to coastal ecosystems, and the biodiversity erosion they are causing, marine‐protected areas (MPAs) have emerged as powerful and widespread conservation tools. Strictly no‐take MPAs, also called marine reserves, undeniably promote fish biomass and density, but it remains unclear how biodiversity responds to protection. Identifying which facets of biodiversity respond to protection is critical for the management of MPAs and the development of relevant conservation strategies towards the achievement of biodiversity targets.

We collected 99 environmental DNA (eDNA) samples inside and outside nine marine reserves in the Mediterranean Sea to assess the effect of protection on 11 biodiversity indicators based on fish traits, phylogeny and vulnerability to fishing. We controlled for the effect of environmental heterogeneity (habitat, bathymetry, productivity, temperature and accessibility) using a principal component analysis, and for spatial autocorrelation due to potential unmeasured factors.

We found a positive and significant effect of protection on only 3 out of 11 indicators: functional and phylogenic diversity but also the ratio between demerso‐pelagic and benthic species richness. Rather, total fish richness responded significantly and negatively to protection. We did not detect any significant effect of protection on threatened and elasmobranch species richness, probably due to their large home range compared to the size of Mediterranean marine reserves.

Synthesis and applications: Our findings highlight the importance of looking beyond the mere number of species to fully depict and understand the effect of marine reserves on biodiversity and evaluate the effectiveness of conservation measures. Rather, we propose a dashboard of three eDNA‐based indicators that can provide an early signal of ecosystem deterioration or recovery. eDNA metabarcoding offers a powerful tool to supply site‐specific and standardized taxonomic‐, phylogenetic‐ and trait‐based biodiversity assessments, in complement to other classical techniques, such as visual censuses or video surveys, able to estimate species abundance but also individual life‐stage and size.