bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clustering and temporal organization of sleep spindles underlie motor memory consolidation
Authors: Boutin Arnaud , Gabitov Ella , Pinsard Basile , Boré Arnaud , Carrier Julie , Doyon Julien 
Published: November 2022

AbstractSleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remain controversial. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organized patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only. Altogether, our findings suggest that spindles’ clustering and rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronized oscillatory activity within a subcortical-cortical network involved during learning.
NanoTrans: an integrated computational framework for comprehensive transcriptome analysis with Nanopore direct RNA sequencing
Authors: Yang Ludong , Zhang Xinxin , Wang Fan , Zhang Li , Li Jing , Yue Jia-Xing 
Published: November 2022

AbstractNanopore direct RNA sequencing (DRS) provides the direct access to native RNA strands with full-length information, shedding light on rich qualitative and quantitative properties of gene expression profiles. Here with NanoTrans, we present an integrated computational framework that comprehensively covers all major DRS-based application scopes, including isoform clustering and quantification, poly(A) tail length estimation, RNA modification profiling, and fusion gene detection. In addition to its merit in providing such a streamlined one-stop solution, NanoTrans also shines in its workflow-orientated modular design, batch processing capability, all-in-one tabular and graphic report output, as well as automatic installation and configuration supports. Finally, by applying NanoTrans to real DRS datasets of yeast,Arabidopsis, as well as human embryonic kidney and cancer cell lines, we further demonstrated its utility, effectiveness, and efficacy across a wide range of DRS-based application settings.
Single-cell Transcriptomic Analysis of Systemic Autoinflammatory Diseases with Anti-TNFα Therapy
Authors: Hua Yichao , Wu Na , Miao Junke , Shen Min 
Published: November 2022

AbstractSystemic autoinflammatory diseases (SAIDs) are a group of rare diseases characterized by recurrent or continuous inflammation, typically accompanied by genetic variants. Good responses to anti-TNFα therapy were observed in SAIDs patients. However, the mechanisms underlying the disease flare and the response to TNFα blocking therapy have not been fully elucidated. Here, we use single-cell RNA sequencing technology to describe the transcriptomic profile of PBMCs and PMNs in SAIDs patients both before and after anti-TNFα treatment. We found that interferon responses are involved in the active phase of the disease. After anti-TNFα therapy, we observed remission from clinical symptoms while unexpected elevation of TNFα and IL-1, indicating that these inflammatory cytokines are not positively correlated with disease activity. Trajectory analysis showed that inhibition of macrophage differentiation, rather than reduction of the inflammatory cytokines, as the potential mechanism of anti-TNFα treatment response in SAIDs.
The functional role of oscillatory dynamics in neocortical circuits: a computational perspective
Authors: Effenberger Felix , Carvalho Pedro , Dubinin Igor , Singer Wolf 
Published: November 2022

AbstractThe dynamics of neuronal systems are characterized by hallmark features such as oscillations and synchrony. However, it has remained unclear whether these characteristics are epiphenomena or are exploited for computation. Due to the challenge of specifically interfering with oscillatory network dynamics in neuronal systems, we simulated recurrent networks (RNNs) of damped harmonic oscillators in which oscillatory activity is enforced in each node, a choice well-supported by experimental findings. When trained on standard pattern recognition tasks, these harmonic oscillator networks (HORNs) outperformed non-oscillatory architectures with respect to learning speed, noise tolerance, and parameter efficiency. HORNs also reproduced a substantial number of characteristic features of neuronal systems such as the cerebral cortex and the hippocampus. In trained HORNs, stimulus-induced interference patterns holistically represent the result of comparing sensory evidence with priors stored in recurrent connection weights, and learning-induced weight changes are compatible with Hebbian principles. Implementing additional features characteristic of natural networks, such as heterogeneous oscillation frequencies, inhomogeneous conduction delays, and network modularity, further enhanced HORN performance without requiring additional parameters. Taken together, our model allows us to give plausible a posteriori explanations for features of natural networks whose computational role has remained elusive. We conclude that neuronal systems are likely to exploit the unique dynamics of recurrent oscillators networks whose computational superiority critically depends on the oscillatory patterning of their nodal dynamics. Implementing the proposed computational principles in analog hardware is expected to enable the design of highly energy-efficient and self-adapting devices that could ideally complement existing digital technologies.
Compression supports low-dimensional representations of behavior across neural circuits
Authors: Zhou Dale , Kim Jason Z. , Pines Adam R. , Sydnor Valerie J. , Roalf David R. , Detre John A. , Gur Ruben C. , Gur Raquel E. , Satterthwaite Theodore D. , Bassett Dani S. 
Published: November 2022

AbstractDimensionality reduction, a form of compression, can simplify representations of information to increase efficiency and reveal general patterns. Yet, this simplification also forfeits information, thereby reducing representational capacity. Hence, the brain may benefit from generating both compressed and uncompressed activity, and may do so in a heterogeneous manner across diverse neural circuits that represent low-level (sensory) or high-level (cognitive) stimuli. However, precisely how compression and representational capacity differ across the cortex remains unknown. Here we predict different levels of compression across regional circuits by using random walks on networks to model activity flow and to formulate rate-distortion functions, which are the basis of lossy compression. Using a large sample of youth (n= 1, 040), we test predictions in two ways: by measuring the dimensionality of spontaneous activity from sensorimotor to association cortex, and by assessing the representational capacity for 24 behaviors in neural circuits and 20 cognitive variables in recurrent neural networks. Our network theory of compression predicts the dimensionality of activity (t= 12.13,p <0.001) and the representational capacity of biological (r= 0.53,p= 0.016) and artificial (r= 0.61,p <0.001) networks. The model suggests how a basic form of compression is an emergent property of activity flow between distributed circuits that communicate with the rest of the network.
Next generation protein-based materials capture and preserve projectiles from supersonic impacts
Authors: Doolan Jack A. , Alesbrook Luke S. , Baker Karen B. , Brown Ian R. , Williams George T. , Hiscock Jennifer R. , Goult Benjamin T. 
Published: November 2022

AbstractExtreme energy dissipating materials are essential for a range of applications. The military and police force require ballistic armour to ensure the safety of their personnel, while the aerospace industry requires materials that enable the capture, preservation and study of hypervelocity projectiles. However, current industry standards display at least one inherent limitation. To resolve these limitations we have turned to nature, utilising proteins that have evolved over millennia to enable effective energy dissipation. Specifically, a recombinant form of the mechanosensitive protein talin was incorporated into a monomeric unit and crosslinked, resulting in the production of the first reported example of a talin shock absorbing material (TSAM). When subjected to 1.5 km/s supersonic shots, TSAMs were shown not only to absorb the impact, but to capture/preserve the projectile, making TSAMs the first reported protein material to achieve this.
Antecedents and effects of green supply chain management (GSCM) practices
Authors: Chatzoudes Dimitrios , Chatzoglou Prodromos 
Published: November 2022

PurposeDuring the previous two decades, “Green Supply Chain Management” (GSCM) has been gaining the attention of researchers and practitioners from various fields (e.g. operations, logistics and supply chain management). Its significance is constantly growing, and various studies are conducted in order to capture its overall organizational contribution. The present study attempts to bring together various organizational aspects that have never been collectively investigated before in the relevant literature. Under that rationale, a robust conceptual framework is developed and empirically tested. This framework includes 17 factors that are classified in three dimensions: (1) drivers of GSCM practices, (2) GSCM practices and (3) firm performance (GSCM outcomes).Design/methodology/approachThe examination of the proposed conceptual framework was performed using a newly developed structured questionnaire that was distributed to a sample of Greek manufacturing organizations. Supply Chain managers and Chief Executive Officers (CEOs) were used as key respondents, due to their knowledge and experience. After the completion of the three-month research period (last quarter of 2019), 292 useable questionnaires were returned. The empirical data were analyzed using the “Structural Equation Modeling” technique. The study is empirical (based on primary data), explanatory (examines cause and effect relationships), deductive (tests research hypotheses) and quantitative (includes the analysis of quantitative data collected with the use of a structured questionnaire).FindingsEmpirical results point out that internal environmental management, green innovative practices and environmental proactivity are GSCM practices with the most significant impact on firm performance. Moreover, the mediating role of GSCM practices in the relationship between GSCM drivers and firm performance is also highlighted. Finally, it was found that GSCM practices can explain 35% of the variance in firm performance and the drivers of GSCM practices can explain 78% of the variance of these practices.Originality/valueThe proposed three-dimensional conceptual framework of this empirical study and its underlining rationale has rarely been adopted in the relevant literature. Moreover, the study investigates which GSCM practices have an impact on firm performance, thus offering value to practitioners of the field. Also, it is one of the few similar studies that have been conducted on a European country.
Sustainability-oriented technology adoption in Tonga: the impact of Government's incentives and internal factors
Authors: Faasolo Malia , Sumarliah Eli 
Published: November 2022

PurposeThe paper seeks to investigate the impacts of government's incentives and internal aspects (i.e. firms' ethics and firms' attitudes) on the implementation of sustainability-oriented technology (SOT) among small and medium-sized enterprises (SMEs) in Tonga. Those aspects are imperative to examine as numerous enterprises in developing nations possess insufficient assets that suspend applying innovations, specifically SOT incorporated with enterprise management. Thus, it is unavoidable for an intermediary to intervene in technology implementation, and developing the more effective implementation process is reckoned. Meanwhile, governments possess the assets and authority to motivate the SOT implementation extensively. Therefore, this paper assesses governmental factors as influencing drivers for realizing cost-effective and well-organized implementation.Design/methodology/approachThe paper employs the partial least squares structural equation modeling (PLS-SEM) technique to assess the information collected from 266 Tongan SMEs.FindingsThe outcomes indicate that government's policy and subsidies positively and significantly shape firms' ethics and attitudes regarding SOT implementation in Tonga.Research limitations/implicationsThe research analyzes the SOT implementation in a single country of Tonga; thus, the findings cannot be generalized to other emerging countries. Besides, this study selects SMEs as the sample; hence, it cannot be used to explain the behaviors of large companies.Originality/valueThe research is the first attempt to assess such impacts in the SMEs of a South Pacific nation.
From the “age of instability” to the “age of responsibility”: economic uncertainty and sustainable investments
Authors: Caferra Rocco , Falcone Pasquale Marcello 
Published: November 2022

PurposeThis paper sets out to investigate investors' sustainable preferences under different market conditions. Specifically, the authors examine the existence of a positive sustainable asset pricing gap, and whether it is influenced by the socioeconomic and financial sentiments. The increase of uncertainty rises investors' skepticism whether sustainable companies are under-performing the traditional counterparts, causing larger increasing gap. Conversely, if sustainable assets are overperforming, the increase of market uncertainty raises investors' sustainable preferences.Design/methodology/approachThe authors examine the existence of a positive sustainable asset pricing gap, and whether it is influenced by the socioeconomic and financial sentiments. Through a quantile regression, the authors remark the variability of sustainable preferences where market participants, although recognizing the present and future value added of sustainable investing, also show skepticism (i.e. asymmetric tail behavior). However, the analysis of the total change of sustainable investments returns over time demonstrates the emergence of positive viewpoints incentivized by economic and market uncertainty.FindingsThe market-driven social responsibility exalts the positive insights regarding the future of sustainable developments. As the authors discuss along the paper, investors are gaining awareness about the environmental and social goals pursued by socially responsible companies. Hence, the authors consider how economic instability might stimulate the assessment of the social and environmental impact of the unsustainable production systems, switching investments toward virtuous sustainable companies. This could generate a series of positive externalities that might improve the welfare conditions of the whole society.Originality/valueThe authors conduct an original empirical exercise, combining different techniques (i.e. quantile regressions and wavelet analysis). To the best of the authors’ knowledge, this is the first paper trying to evidence a systematic connection between market uncertainty and sustainable preferences accounting for different market states (thanks to quantile regressions).
The effects of military expenditures on labor productivity, innovation and economic growth for the most militarized countries: panel data analysis
Authors: Inal Veysel , Gurdal Temel , Degirmenci Tunahan , Aydin Mucahit 
Published: November 2022

PurposeThere is extensive literature on the effect of military expenditure on economic growth. However, there is also a wide gap in the literature on the relationship between productivity and innovation, which is considered the driving force of economic growth and military expenditures. To this end, this study examines the effect of military expenditures on economic growth, innovation and labor productivity for the period 1995–2019 in most militarized countries.Design/methodology/approachThe tests used in the study's empirical analysis are techniques that take into account cross-sectional dependence and heterogeneity. The stationarity of the variables was tested with the Pesaran’s (2007) unit root test. Then, empirical findings were revealed based on the analysis through Westerlund’s (2008) cointegration test and Emirmahmutoglu and Kose’s (2011) panel causality test.FindingsAccording to the empirical results, there is a long-run relationship, in other words, a cointegration between military expenditures and productivity, innovation and economic growth. Additionally, there are causality relationships between military expenditures and productivity, innovation and economic growth.Practical implicationsThese results support the arguments of military Keynesianism and the Benoit hypothesis.Originality/valueDespite the widespread theoretical debate, no empirical study tests the effect of military expenditure on productivity and innovation to the author's best knowledge. Hence, this study aims to fill this gap in the literature. Moreover, the fact that the econometric method used is based on second generation tests and the timeliness of the period range makes the study's findings more significant.
A review: effect of copper percentage solder alloy after laser soldering
Authors: Abdullah Asyraf , Aisha Idris Siti Rabiatull 
Published: November 2022

PurposeThis study aims to review the effect of copper percentage in Sn-based solder alloys (Sn-xCu,x= 0–5 Wt.%) on intermetallic compound (IMC) formation and growth after laser soldering.Design/methodology/approachThis study reviews the interfacial reactions at the solder joint interface, solder joint morphology and the theory on characterizing the formation and growth of IMCs. In addition, the effects of alloying and strengthening mechanism, including wettability, melting and mechanical properties are discussed.FindingsThis paper presents a comprehensive overview of the composition of tin-copper (Sn-Cu) solders with a potential to enhance their microstructure, mechanical characteristics and wettability by varying the Cu percentage. The study found that the best Cu content in the Sn-xCu solder alloy was 0.6–0.7 Wt.%; this composition provided high shear strength, vibration fracture life value and ideal IMC thickness. A method of solder alloy preparation was also found through powder metallurgy and laser soldering to improve the solder joint reliability.Research limitations/implicationsThis study focuses on interfacial reactions at the solder joint interface, solder joint morphology, modelling simulation of joint strength and the theory on characterising the formation and growth of IMC.Originality/valueThe paper comprehensively summarises the useful findings of the Sn-Cu series. This information will be important for future trends in laser soldering on solder joint formation.
Prioritising the determinants of Industry-4.0 for implementation in MSME in the post-pandemic period – a quality function deployment analysis
Authors: Agarwal Alpana , Ojha Ravindra 
Published: November 2022

PurposeMicro, Small, Medium Enterprises (MSMEs) are witnessing an accelerated transformation by the advent of Industry-4.0 (I4.0) in the post-pandemic period. It is offering promising customer responsiveness, competitiveness, business growth and sustainability and thereby, compelling its integration to MSMEs. Therefore, it is imperative for researchers to explore Industry 4.0 challenges and their specific implementation requirements and also provide useful insights to the stakeholders.Design/methodology/approachThis research paper has identified, explained and analysed various determinants of the I4.0 implementation, in MSME context. Focus group approach has been applied for taking inputs from experts for developing the House of Quality (HOQ) tool of the Quality Function Deployment (QFD) methodology from the Total Quality Management (TQM) tool-box.FindingsBased on the responses and after applying QFD, a conceptual model suggesting relevant strategies to execute I4.0 by Indian MSMEs has been developed. The model highlights three key challenges being faced by the Indian MSMEs –Top management support, Incompatible resources and Transition cost. The model also reveals vital few designer's descriptors – Cultural reorientation, IT enabled digitization, Process automation and knowledge and skill in I4.0 implementation (Knowhow) for a structured implementation of I4.0.Practical implicationsThe evolved HOQ framework has provided some useful insights - priority areas in the MSME challenges and the designer's descriptors for I4.0 implementation in MSME. The research has also provided the understanding of the dynamics between the I4.0 components through the 10 × 10 interrelationship matrix of the HOQ. Farsighted MSME leaders, practising consultants, sourcing managers and policy makers can use the developed framework as a reference in formulating tactics to mitigate the I4.0 implementation barriers.Originality/valueThe non-conventional application of HOQ in the QFD approach from the TQM tool-box is a useful value addition to the TQM practitioners. The useful insights to the MSME leaders, policy makers, sourcing managers of OEM, consultants engaged in I4.0 transformation and academic researchers are the other contribution.
Understanding barriers to inbound medical tourism in the United Arab Emirates from a provider's perspective
Authors: Mishra Vinaytosh , Rana Sudhir 
Published: November 2022

PurposeThe purpose of the study is to identify the important barriers to the development of medical tourism in the United Arab Emirates (UAE). Further, it aims to establish a relationship among these barriers and propose a framework to overcome them.Design/methodology/approachThe study uses a narrative review of the literature to identify barriers to medical tourism development (MDT) in the UAE. Using a graph theory-based Total Interpretive Structural Modelling (TISM) approach to explaining the hierarchy of the identified barriers and interpret the relationship links. The study further uses Cross-impact matrix multiplication applied to classification (MICMAC) analysis to validate the finding of the study and derive conclusions.FindingsThe study identifies barriers related to MDT as (1) Policies and Regulations (2) Government support (3) Healthcare costs (4) Healthcare Capacity (5) Healthcare Quality (6) Medical Insurance (7) Facilitator and Marketing (8) International Relations (9) Ease of Travel, and (10) Religion, Culture, and Language. The study concludes that Healthcare Cost, Healthcare Quality, and the inapplicability of international medical insurance are the most important barriers. More than fifty percent of barriers fall under the linkage quadrant in MICMAC analysis which reflects that overcoming one barrier helps in overcoming other barriers as well.Originality/valueThis study is one of the most comprehensive accounts of the barriers to MDT in the UAE and strategies to overcome these barriers. To the best of our knowledge, we were not able to find a similar study.