bluuebunny/crossref_metadata_2025 huggingface dataset:
Humoral and cellular immune correlates of protection against COVID-19 in kidney transplant recipients
Authors: Kemlin D. , Gemander N. , Depickère S. , Olislagers V. , Georges D. , Waegemans A. , Pannus P. , Lemy A. , Goossens M. E. , Desombere I. , Michiels J. , Vandevenne M. , Heyndrickx L. , Ariën K.K. , Matagne A. , Ackerman M.E. , Moine A. Le , Marchant A.
Published: August 2022

As solid organ recipients are at high risk of severe COVID-19 and respond poorly to primary SARS-CoV-2 mRNA vaccination, they have been prioritized for booster vaccination. However, an immunological correlate of protection has not been identified in this vulnerable population. We conducted a prospective monocentric cohort study of 65 kidney transplant recipients who received three doses of SARS-CoV-2 BNT162b2 mRNA vaccination. Associations between symptomatic breakthrough infection (BTI) and vaccine responses, patient demographic and clinical characteristics were explored. Symptomatic COVID-19 was diagnosed in 32% of kidney transplant recipients during a period of six months after the administration of the third vaccine dose. During this period, SARS-CoV-2 delta and omicron were the dominant variants in the general population. Univariate analyzes identified avidity of SARS-CoV-2 receptor binding domain (RBD) binding IgG, neutralizing antibodies and SARS-CoV-2 S2 domain-specific IFN-γ responses as correlates of protection against BTI. Some demographic and clinical parameters correlated with vaccine responses, but none correlated with the risk of BTI. In multivariate analysis, the risk of BTI was best predicted by neutralizing antibody and S2-specific IFN-γ responses, adjusting for age, graft function and mycophenolate mofetil use. In conclusion, both antibody and T cell responses predict the risk of BTI in kidney transplant recipients who received three doses of SARS-CoV-2 mRNA vaccine. T cell responses may help compensate for the suboptimal antibody response to vaccination in this vulnerable population.

One Sentence Summary

Antibody and T cell responses to booster SARS-CoV-2 vaccination predict the risk of symptomatic breakthrough infection in kidney transplant recipients
A pilot analysis of circulating cfRNA transcripts for the detection of lung cancer
Authors: Seneviratne Chamindi , Shetty Amol C. , Geng Xinyan , McCracken Carrie , Cornell Jessica , Mullins Kristin , Jiang Feng , Stass Sanford
Published: August 2022

Lung cancers are the leading cause of cancer-related deaths worldwide. Studies have shown that non-small cell lung cancer (NSCLC) which constitutes majority of lung cancers, are significantly more responsive to early-stage interventions. However, the early stages are often asymptomatic, and current diagnostic methods are limited in their precision and safety. The cell-free RNAs (cfRNA) circulating in plasma (Liquid biopsies) offer non-invasive detection of spatial and temporal changes occurring in primary tumors since early stages. To address gaps in current cfRNA knowledgebase, we conducted a pilot study for comprehensive analysis of transcriptome-wide changes in plasma cfRNA in NSCLC patients. Total cfRNA was extracted from archived plasma collected from NSCLC patients (N=12), cancer-free former smokers (N=12) and non-smoking healthy volunteers (N=12). Plasma cfRNA expression levels were quantified by using a tagmentation-based library preparation and sequencing. The comparisons of cfRNA expression levels between patients and the two control groups revealed a total of 2357 differentially expressed cfRNA enriched in 123 pathways. Of these, 251 transcripts were previously reported in primary NSCLCs. A small subset of genes (N=5) was validated in an independent sample (N=50) using qRT-PCR. Our study provides a framework for developing blood-based assays for early detection of NSCLC and warrants further validation.
SARS-CoV-2 IgM and IgG serology and clinical outcomes in COVID-19 patients
Authors: Mohan S , Kumar Pratap , Panda Prasan Kumar , Jain Vikram , Raina Rohit , Saha Sarama , Vivekandan S , Omar Balram J
Published: August 2022

Background

The SARS-CoV-2 virus has become pandemic for the last 2 years. Inflammatory response to the virus leads to organ dysfunction and death. Predicting the severity of inflammatory response helps in managing critical patients using serology tests IgG and IgM. We conducted a longitudinal study to correlate serum SARS-CoV-2 IgM and IgG serology with clinical outcomes in COVID-19 patients.

Methods

We analyzed patient data from March to December of 2020 for those who were admitted at AIIMS Rishikesh. Clinical and laboratory data of these patients were collected from the e-hospital portal and analysed. Correlation was seen with clinical outcomes and was assessed using MS Excel 2010 and SPSS software.

Results

Out of 494 patients, the mean age of patients was 48.95 ± 16.40 years and there were more male patients in the study (66.0%). The patients were classified into 4 groups; mild-moderate 328 (67.1%), severe 131 (26.8%) and critical 30 (6.1%). The mean duration from symptom onset to serology testing was 19.87 ± 30.53 days. In-hospital mortality was observed in 25.1% patients. The seropositivity rate (i.e., either IgG or IgM >10 AU) was 50%. There was a significant difference between the 2 groups in terms of IgM Levels (AU/mL) (W = 33428.000, p = <0.001) and IgG Levels (AU/mL) (W = 39256.500, p = <0.001), with the median IgM/ IgG Levels (AU/mL) being highest in the RT-PCR-Positive group. There was no significant difference between the groups in terms of IgM Levels and IgG levels with all other clinical outcomes (disease severity, septic shock, Intensive care admission, mechanical ventilation and mortality).

Conclusion

Serology (IgM and IgG) levels are high in RTPCR positive group compared to clinical COVID-19. However, serology cannot be useful for the prediction of disease outcomes except few situations. The study also highlights the importance of doing serology at a particular time as antibody titres vary with the duration of the disease.
Associations of proton pump inhibitors with susceptibility to influenza, pneumonia, and COVID-19: Evidence from a large population based cohort study
Authors: Zeng Ruijie , Ma Yuying , Zhang Lijun , Luo Dongling , Jiang Rui , Wu Huihuan , Zhuo Zewei , Yang Qi , Li Jingwei , Leung Felix W , Duan Chongyang , Sha Weihong , Chen Hao
Published: August 2022

Adverse effects of proton pump inhibitors (PPIs) have raised wide concerns. The association of PPIs with influenza is unexplored, while that with pneumonia or COVID-19 remains controversial. Our study aims to evaluate whether PPI use increases the risks of these respiratory infections. The current study included 160,923 eligible participants at baseline who completed questionnaires on medication use, which included PPI or histamine-2 receptor antagonist (H2RA), from the UK Biobank. Cox proportional hazards regression and propensity score-matching analyses were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Comparisons with H2RA users were tested. PPI use was associated with increased risks of developing influenza (HR 1.32, 95%CI 1.12-1.56) and pneumonia (hazard ratio [HR] 1.42, 95% confidence interval [CI] 1.26-1.59). In contrast, the risk of COVID-19 infection was not significant with regular PPI use (HR 1.08, 95%CI 0.99-1.17), while the risks of severe COVID-19 (HR 1.19. 95%CI 1.11-1.27) and mortality (HR 1.37. 95%CI 1.29-1.46) were increased. However, when compared with H2RA users, PPI users were associated with a higher risk of influenza (HR 1.74, 95%CI 1.19-2.54), but the risks with pneumonia or COVID-19-related outcomes were not evident. In conclusion, PPI users are associated with increased risks of influenza, pneumonia, as well as COVID-19 severity and mortality compared to non-users, while the effects on pneumonia or COVID-19-related outcomes under PPI use were attenuated when compared to the use of H2RAs. Appropriate use of PPIs based on comprehensive evaluation is required.
Macroevolutionary dynamics of gene family gain and loss along multicellular eukaryotic lineages
Authors: Domazet-Lošo Mirjana , Široki Tin , Domazet-Lošo Tomislav
Published: August 2022

The recent analyses in animals show that gene gain and loss fluctuate during evolutionary time. However, these studies lack the full profile of macroevolutionary trajectories as they do not consider other eukaryotic lineages and deeper evolutionary periods that go back to the origin of cellular organisms. To give a more inclusive view on the macroevolutionary patterns of genome complexity across the tree of life, we here recovered the evolutionary dynamics of gene family gain and loss ranging from the ancestor of cellular organisms to four focal species that represent animal, plant, and fungal diversity. We show that in all considered lineages the gene family content follows a common evolutionary pattern, where the number of gene families reaches the highest value at a major evolutionary and ecological transition, and then gradually decreases towards extant organisms. This pattern suggests that the genome complexity, approximated by the number of residing gene families, does not continuously increase through evolutionary time. We conclude that simplification by gene family loss is a dominant force in Phanerozoic genomes of various lineages, probably underpinned by intense ecological specializations and functional outsourcing. These findings support current theoretical predictions on the macroevolutionary change in genome complexity.
Model based control can give rise to devaluation insensitive choice
Authors: Garrett Neil , Allan Sean , Daw Nathaniel D.
Published: August 2022

Influential recent work aims to ground psychiatric dysfunction in the brain’s basic computational mechanisms. For instance, compulsive symptoms as in drug abuse have been argued to arise from imbalance between multiple systems for instrumental learning. Computational models suggest that such multiplicity arises because the brain adaptively simplifies laborious “model-based” deliberation by sometimes relying on a cheaper, more habitual “model-free” shortcut. Support for this account comes in part from failures to appropriately change behavior in light of new events. Notably, instrumental responding can, in some circumstances, persist despite reinforcer devaluation, perhaps reflecting control by model-free mechanisms that are driven by past reinforcement rather than knowledge of the (now devalued) outcome. However, another important line of theory – heretofore mostly studied in Pavlovian conditioning – posits a different mechanism that can also modulate behavioral change. It concerns how animals identify different rules or contingencies that may apply in different circumstances, by covertly clustering experiences into distinct groups identified with different “latent causes” or contexts. Such clustering has been used to explain the return of Pavlovian responding following extinction.

Here we combine both lines of theory to investigate the consequences of latent cause inference on instrumental sensitivity to reinforcer devaluation. We show that because segregating events into different latent clusters prevents generalization between them, instrumental insensitivity to reinforcer devaluation can arise in this theory even using only model-based planning, and does not require or imply any habitual, model-free component. In simulations, these ersatz habits (like laboratory ones) emerge after overtraining, interact with contextual cues, and show preserved sensitivity to reinforcer devaluation on a separate consumption test, a standard control. While these results do not rule out a contribution of model-free learning per se, they point to a subtle and important role of state inference in instrumental learning and highlight the need for caution in using reinforcer devaluation procedures to rule in (or out) the contribution of different learning mechanisms. They also offer a new perspective on the neurocomputational substrates of drug abuse and the relevance of laboratory reinforcer devaluation procedures to this phenomenon.
Edge-focused network-based approach: an improved kernel density estimator for home range
Authors: Vyasanakere Jayanth , Mukherjee Jayanti Ray , Fernandez Rahul Joseph
Published: August 2022

1. One of the central challenges in ecology and animal behaviour is to generate animal home range estimations. Kernel density estimate for home range has been one of the most widely used estimates these last few decades, despite its limitations. More recently a network-based kernel density (NKDE) approach has been proposed, which uses Delaunay triangulation.
2. Here we show that NKDE has a discontinuous kernel density. We then develop a new network-based method that emphasises entirely on the edges, instead of the nodes in the network. We call this Edge-Focused Network-based Kernel Density Estimation (EFNKDE). In this method, a unit weight is distributed uniformly along each edge of the network and Euclidean distance is used to compute the contribution of each segment of the edge to the kernel density at a given point.
3. This is a network based method that leads to a continuous and differentiable kernel density. An analytical expression for the same is obtained for the Gaussian kernel. By taking concrete examples and studying different methods and through different perspectives across a range of bandwidths, we show that EFNKDE has many advantages over other methods. We present a model that provides a theoretical basis to the effectiveness of EFNKDE in linear regimes.
4. EFNKDE is easy to apply, can work with minimal data, provides a smooth kernel density that highlights the network and does not overemphasise the data. This method is most suitable for estimating home ranges with narrow corridors and forbidden regions.
Human neurogenesis is altered via glucocorticoid-mediated regulation ofZBTB16expression
Authors: Krontira Anthi C. , Cruceanu Cristiana , Dony Leander , Kyrousi Christina , Link Marie-Helen , Kappelmann Nils , Pöhlchen Dorothee , Raimundo Catarina , Goeke Signe-Penner , Schowe Alicia , Czamara Darina , Lahti-Pulkkinen Marius , Sammallahti Sara , Wolford Elina , Heinonen Kati , Roeh Simone , Sportelli Vincenza , Wölfel Barbara , Ködel Maik , Sauer Susann , Rex-Haffner Monika , Räikkönen Katri , Labeur Marta , Cappello Silvia , Binder Elisabeth B.
Published: August 2022

Glucocorticoids are important for proper organ maturation and their levels are tightly regulated during development. Here we use human cerebral organoids and mice to study cell-type specific effects of glucocorticoids on neurogenesis. We show that glucocorticoids increase a specific type of basal progenitors (co-expressingPAX6andEOMES) that has been shown to drive cortical expansion in gyrified species. This effect is mediated via the transcription factorZBTB16and leads to increased production of neurons. A phenome-wide mendelian randomization analysis of an enhancer variant that moderates glucocorticoid-inducedZBTB16levels, reveals causal relationships with higher educational attainment and altered brain structure. The relationship with postnatal cognition is supported by data from a prospective pregnancy cohort. This study provides a novel cellular and molecular pathway for the effects of glucocorticoids on human neurogenesis that relates to lasting postnatal phenotypes.
Dicamba drift alters patterns of chewing herbivory in three common agricultural weeds
Authors: Johnson Nia , Zhang Grace , Soble Anah , Baucom Regina S
Published: August 2022

How agricultural regimes, such as novel herbicide exposure, may influence plant-herbivore interactions and specifically patterns of plant herbivory has come under increased interest in recent years due to rapidly changing herbicide use in agroecosystems. This paper examines patterns of plant herbivory using three common agricultural weeds exposed to low doses of dicamba, a synthetic auxin herbicide that is exponentially increasing in use given the adoption of dicamba tolerant crops. We used a replicated field study to examine how the amount and type of chewing herbivory may be altered in Ipomoea purpurea (common morning glory, Convolvulaceae), Datura stramonium (jimsonweed, Solanaceae), and Abutilon theophrasti (velvetleaf, Malvaceae) exposed to dicamba drift (i.e., 1% of the field dose). We found an increase in chewing herbivory damage when plants were exposed to dicamba and changes in the type of herbivory following exposure. Chewing herbivory differed among species in the presence of dicamba drift: A. theophrasti and D. stramonium showed more total leaf-chewing herbivory than controls, but I. purpurea showed no difference in the overall amount of herbivory. We also found that the type of herbivory was significantly altered in drift. A. theophrasti and I. purpurea both exhibited declines in hole feeding but increases in margin feeding, whereas D. stramonium showed no such changes. Overall, our results show that herbicide drift can induce shifts in plant-herbivore interactions, highlighting the need for mechanistic studies to uncover the cause underlying the shifts and comparative studies on weed communities to understand long-term consequences.
The Ecosystem Integrity Index: a novel measure of terrestrial ecosystem integrity
Authors: Hill S.L.L. , Harrison M.L.K , Maney C. , Fajardo J. , Harris M. , Ash N. , Bedford J. , Danks F.S. , Guaras D. , Hughes J. , Jones M. , Mason T. , Burgess N.
Published: August 2022

While the importance of ecosystem integrity has long been recognised (Leopold, 1949), conservation science has tended to focus on measuring and monitoring species and habitats, avoiding the complexities of working at the ecosystem level. Ecosystems are highly dynamic, defined by both living and non-living components as well as their interactions (CBD, 1992), making it difficult to assess baseline levels of integrity. We present a novel index that represents the integrity of all terrestrial ecosystems globally at 1km2resolution: the Ecosystem Integrity Index (EII). The index provides a simple, yet scientifically robust, way of measuring, monitoring and reporting on ecosystem integrity. It is formed of three components; structural, compositional and functional integrity, and measured against a natural (current potential) baseline on a scale of 0 to 1. We find that ecosystem integrity is severely impacted in terrestrial areas across the globe with approximately one fifth of all ecosystems and one quarter of all ecoregions having lost, on average, over half of their ecosystem integrity. At a national scale, we estimate similar challenges with 115 nations or territories having lost, on average, over half of their ecosystem integrity. This presents a significant threat for humanity as such levels of degradation are likely to be linked to substantial declines in the ecosystem services on which humanity is reliant. The EII has been developed principally to help national governments measure and report on Goal A of the Kunming-Montreal Global Biodiversity Framework (GBF) (CBD, 2022a), for which it has been listed as a Component Indicator. The EII will also be useful in helping non-state actors measure and report their contributions to the GBF and is listed as an indicator by both the Taskforce for Nature-Related Financial Disclosures (TNFD) (TNFD, 2023) and the Science Based Targets Network (SBTN) (SBTN, 2023). The EII aims to enable these actors to make informed decisions on the conservation, restoration and sustainable use of ecosystems for which they are wholly or partly responsible. We propose that with sufficient effort, ecosystem integrity can be restored and contribute towards the GBF’s vision of living in harmony with nature, resulting in the safeguarding of the ecosystem services on which humanity depends.
“Correcting” gene trees to be more like species trees increases topological error when incomplete lineage sorting is high
Authors: Yan Zhi , Ogilvie Huw A. , Nakhleh Luay
Published: August 2022

The evolutionary histories of individual loci in a genome can be estimated independently, but this approach is error-prone due to the limited amount of sequence data available for each gene, which has led to the development of a diverse array of gene tree error correction methods which reduce distance to the species tree. We investigate the performance of two representatives of these methods: TRACTION and TreeFix, in the case where incomplete lineage sorting is high. We found that gene tree error correction only increases the level of error in gene tree topologies by “correcting” them to be closer to the species tree, even when the true gene and species trees are discordant. We confirm that full Bayesian inference of the gene trees under the multispecies coalescent model is more accurate than independent inference. Gene tree correction must be considered a multi-locus task where the gene tree distribution is taken into account, rather than treating gene trees independently.

Significance statement

Gene tree information is essential for studying elucidating gene, genome, species, and phenotypic evolution, and a wide array of phylogenetic methods have been developed for gene tree estimation. Given that gene tree estimates are often inaccurate, several methods for “correcting” gene tree estimates have been devised. Here we show that correction methods that neglect the distribution of gene trees that is induced by the species phylogeny could produce poor results, calling for the development of species phylogeny-aware gene tree correction.
Recent Trends in Aspirin Use for Cardiovascular Disease Prevention in the United States - 2015-2023
Authors: Murugiah Karthik , See Claudia , Huang Chenxi
Published: August 2022

BACKGROUND

Recent trials show a lack of benefit of routine aspirin use for primary prevention. We assessed recent trends in aspirin use for both primary and secondary prevention in the United States population.

METHODS

We used National Health Interview Survey (NHIS) data from 2015-2023 and reported the annual weighted proportion of aspirin use among participants ≥40 years without a self-reported history of angina, coronary heart disease, myocardial infarction, or stroke (primary prevention cohort) and those with (secondary prevention cohort), overall and by subgroups. Statistical comparisons were made only between 2019 and 2023 due to an NHIS study redesign in 2019.

RESULTS

From 2019 to 2023 overall aspirin use for primary prevention decreased from 20.6% to 15.7%. It declined in all subgroups, including among individuals ≥70 years from 38.7% to 30.7%, and those age <60 years but with ≥3 CVD risk factors (29.1% to 19.7%). Overall aspirin use for secondary prevention also declined, but to a lesser extent from 65.7% to 61.9%. (all P <0.001)

CONCLUSION

In response to recent data there has been a significant reduction in aspirin use for primary prevention, appropriately among older participants, but also among younger participants with multiple cardiovascular risk factors. There was also a minor decrease in its use for secondary prevention which warrants further study.
Coding nucleic acid sequences with graph convolutional network
Authors: Wang Ruo Han , Ng Yen Kaow , Zhang Xianglilan , Wang Jianping , Li Shuai Cheng
Published: August 2022

Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network-based methods can be prime candidates for retrieving insights from these sequences because of their applicability to large and diverse datasets.However, the highly variable lengths of nucleic acid sequences severely impair the presentation of sequences as input to the neural network. Genetic variations further complicate tasks that involve sequence comparison or alignment. Here, we propose a graph representation of nucleic acid sequences calledgapped pattern graphs. These graphs can be transformed through a Graph Convolutional Network to form lower-dimensional embeddings for downstream tasks. On the basis of the gapped pattern graphs, we implemented a neural network model and demonstrated its performance in studying phage sequences. We compared our model with equivalent models based on other forms of input in performing four tasks related to nucleic acid sequences—phage and ICE discrimination, phage integration site prediction, lifestyle prediction, and host prediction. Other state-of-the-art tools were also compared, where available. Our method consistently outperformed all the other methods in various metrics on all four tasks. In addition, our model was able to identify distinct gapped pattern signatures from the sequences.
Cortical Betz cells analogue in songbirds utilizes Kv3.1 to generate ultranarrow spikes
Authors: Zemel Benjamin M. , Nevue Alexander A. , Tavares Leonardo E. , Dagostin Andre , Lovell Peter V. , Jin Dezhe Z. , Mello Claudio V. , von Gersdorff Henrique
Published: August 2022

Complex motor skills in vertebrates require specialized upper motor neurons with precise action potential (AP) firing. To examine how diverse populations of upper motor neurons subserve distinct functions and the specific repertoire of ion channels involved, we conducted a thorough study of the excitability of upper motor neurons controlling somatic motor function in the zebra finch. We found that robustus arcopallialis projection neurons (RAPNs), key command neurons for song production, exhibit ultranarrow spikes and higher firing rates compared to neurons controlling non-vocal somatic motor functions (AId neurons). This striking difference was primarily due to the expression of a high threshold, fast-activating voltage-gated K+ channel, Kv3.1 (KCNC1). RAPN properties thus mirror those of the sparse, specialized Betz cells in the motor cortex of humans and other primates, which also fire ultranarrow spikes enabled by Kv3.1 expression. These large layer 5 pyramidal neurons are involved in fine digit control and are notably absent in rodents. Our study thus provides evidence that songbird RAPNs and primate Betz cells have convergently evolved the use of Kv3.1 to ensure precise, rapid AP firing required for fast and complex motor skills.
Strategies used by students with autism when solving multiplicative problems: an exploratory study
Authors: Goñi-Cervera Juncal , Martínez Romillo María Cristina , Polo-Blanco Irene
Published: August 2022

Purpose

This paper aims to study the strategies used by ten students diagnosed with autism when solving multiplication and division problems because these operations are rarely studied in students with this condition.

Design/methodology/approach

This study conducted an exploratory study with ten students diagnosed with autism to explore and describe the strategies used in solving equal group problems. The authors also describe in detail the case of a student whom the authors deem to be representative because of the reasoning the student employed.

Findings

The informal strategies that they used are described, as well as the difficulties observed in the various problems, depending on the operation required to solve them. The strategies used include direct modeling with counting and others that relied on incorrect additive relationships, with strategies based on multiplication and division operations being scarce. Difficulties were observed in several problems, with measurement division being particularly challenging for the study participants.

Practical implications

The detailed description of the strategies used by the students revealed the meanings that they associate with the operations they are executing and brought to light potential difficulties, which can help teachers plan their instruction.

Originality/value

This research supplements other studies focusing on mathematical problem-solving with autistic students.
Effect of cluster initiatives and natural clusters on business performance
Authors: Zizka Miroslav , Stichhauerova Eva
Published: August 2022

Purpose

This study aims to determine how much company participation in a type of cluster affects its economic performance.

Design/methodology/approach

This study includes companies operating in seven industries (automotive, engineering, textiles, information technology (IT) services, furniture, packaging and nanotechnology) in the Czech Republic. The companies are divided into three groups: members of institutionalized cluster, operating in the same region (natural clusters) and operating in other regions. Data envelopment window analysis is used to measure their performance for 2009–2019.

Findings

Results show that the effect of clustering differs among industries. Companies in three industries (automotive, engineering, nanotechnology) reveal a positive impact of the cluster initiative on performance growth. Two industries (textile, packaging) with companies operating in a natural cluster show better performance than those in an institutionalized cluster. Moreover, the IT services and the furniture industries show no positive effect of clustering on corporate performance.

Research limitations/implications

This research includes 686 companies from seven industries and monitored for 11 years. On the one hand, the sample includes a relatively high number of companies overall; but on the other hand, the sample is relatively small, especially for nonclustered companies. The reason is the lack of available financial statements for small companies.

Practical implications

From the perspective of practical cluster policy, the authors can recommend that monitoring the performance of member companies in clusters must be one of the criteria for evaluating the success of a cluster, such as cluster initiatives.

Originality/value

This study distinguishes between long-standing natural clusters in a given industry and institutionalized ones that have emerged because of a top-down initiative. An original database is created for clustered and nonclustered companies in seven industries, covering the entire Czech Republic.
Measuring the impact of remote working adaptation on employees' well-being during COVID-19: insights for innovation management environments
Authors: Alvarez-Torres Francisco Javier , Schiuma Giovanni
Published: August 2022

Purpose

A new type of digital-based worker emerged during the COVID-19. As a result, during the adjustment to this scenario, family, resources and emotions were impacted. Technological and emotional skills were crucial to give continuity and certainty to business. However, despite benefits, remote working has negative consequences, especially in well-being perception. This study proposes a model to measure the impact on the well-being perception of workers that adapted their job to remote positions during a pandemic and offers a valuable framework to understand future emerging changes in remote working and the relationship with well-being perception, especially during crisis scenarios.

Design/methodology/approach

The study used an online questionnaire and a structural equation methodology by partial least squares (PLS) using SmartPLS 3.3.3. Data were obtained from 567 respondents workers who adapted to their jobs during the pandemic in Mexico.

Findings

The results showed that six model dimensions: human relations (RH), emotions (E), well-being behaviors related to Covid-19 (CB), family economics (EF), routines and habits (RS) and family life (VF) were positive and significant to reflect the Index of Perception of Well-being (iWB) using a structural equation model. This indicates how the lockdown process changed people's perception of well-being and concerns. According with this, for remote working employees, two dimensions were relevant: RH and EF. This finding is relevant because during emergency lockdown, these workers needed to adapt their activities and were separated from all human interactions.

Practical implications

The researchers’ model of Index of Perception of Well-being (iWB) has conceptual and practical implications. From a conceptual point of view, it offers a methodology to measure the relationships between remote working and employees' well-being perception. While for practice, it offers managerial implications to better manage remote working adaptation without compromising people's well-being to create future innovation management environments (IME) for organizations.

Originality/value

This study contributes to develop research about changes in workers' well-being perception during digital adaptation.
Decision support system (DSS) for facilities rehabilitation and management (part 1): development of integrated AHP-MAUT performance assessment model (PAM)
Authors: Aldeeb Owais , Qasem Altayeb
Published: August 2022

Purpose

The purpose of this paper (Part 1 of 2) is to develop a systematic performance assessment model (PAM) for measuring facilities condition in terms of physical, environmental and operational impacts on performance.

Design/methodology/approach

The methodology entailed a review of literature to identify performance impacting factors (PIFs) of a facility. PIFs were categorized as physical, environmental and operational. Subsequently, 71 experts were interviewed to prioritize the identified PIFs in terms of their impact on facility performance via analytical hierarchy process (AHP) technique. A second round of interviews with 11 experts was conducted to set a utility scoring mechanism for the PIFs via multiattribute utility theory (MAUT) technique, the utility score in correlation to a set scale would describe the level of service(LoS). Finally, AHP and MAUT outputs were mathematically integrated to determine the final condition rating index of all PIFs and the whole facility as a result.

Findings

First, PIFs of a case study mosque facility under three scenarios with different groupings of functional spaces were defined. Functional spaces’ prioritization was as follows: prayer hall (57%–65%), wet areas (25%–26%), minaret (9%–10%), and yard/site (7%–8%). Subsequently, each space’s PIFs and its subcategories were assigned weights as well, the first level of PIFs’ relative weights was as follows: physical (68%–73%), operational (19%–20%) and environmental (7%–13%). Physical PIFs weights differed per functional space but structural factor dominated with (38%–71%) relative weight except for the yard/site. Finally, a detailed condition evaluation mechanism for each PIF was defined.

Originality/value

This study contributes to facilities management industry and offers a systematic approach encompassing multiple PIFs that will regulate inspection then maintenance through desired corrective actions by facility managers to achieve desired LoS.
Becoming accustomed to online teaching: nursing lecturers' experiences in the era of COVID-19
Authors: Ligita Titan , Mita  , Murtilita  , Winarianti
Published: August 2022

Purpose

This study aimed to explore nursing lecturers' experiences of online teaching and learning during the coronavirus disease 2019 (COVID-19) pandemic. The COVID-19 policy on social and physical distancing urges nursing lecturers to provide online teaching delivery for their students using both synchronous and asynchronous methods. However, the experiences of nursing lecturers providing online teaching delivery in the era of COVID-19 are yet unknown.

Design/methodology/approach

The authors used an interpretive phenomenological analysis study design. Participants were seven nursing lecturers, with whom we conducted in-depth interviews using semi structured questions through telephone calls or video conferences. Interpretive phenomenology analysis was adopted to analyse the generated data.

Findings

The core theme of this current study is that of becoming accustomed to online teaching delivery. The main theme is supported by three sub-themes, which are being comfortable with the technology, difficulties and how to overcome them and caring for students to explain the online teaching experiences of nursing lecturers.

Originality/value

The results of this study demonstrate that familiarity with technology is critical for lecturers to facilitate their online teaching. There is a need for further enhancement of technology and application usage to improve the quality of nursing lecturers' teaching methods and ensure the provision of theory and nursing skill competency to students.
Determinants of article processing charges for hybrid and gold open access journals
Authors: Asai Sumiko
Published: August 2022

Purpose

While the number of hybrid journals has increased with the conversion from subscription journals, article processing charges (APCs) have not been examined as frequently as gold open access journals. This study compared the factors affecting APCs for hybrid and gold open access journals by formulating a charge equation.

Design/methodology/approach

This study examined the APCs for 1,354 hybrid and gold open access journals in the Springer imprint. Using the ordinary least squares method, it investigated the determinants of charges, including the relationship between subscription prices and APCs for hybrid journals.

Findings

The results revealed that the charges set by hybrid journals were higher than those set by gold open access journals by US$1,620, after controlling for other variables. A reason could be the oligopolistic market structure of the leading publishers. Although the publisher imprint set the APCs based on the journal characteristics, the difference in the determinants of the charges between the two journal types may be due to the business models specific to the journal types.

Research limitations/implications

The findings suggested that policymakers must consider the market power of leading publishers to establish a healthy scholarly communication market.

Originality/value

This study examined the relationship between subscription prices and charges for hybrid journals as well as the determinants of charges for both journal types, considering various characteristics of individual journals.
Dynamic relationship between energy efficiency, health expenditure and economic growth: in pursuit for SDGs in Malaysia
Authors: Matahir Hylmee , Yassin Jain , Marcus Herniza Roxanne , Shafie Nur Aima , Mohammed Nor Farizal
Published: August 2022

Purpose

This paper aims to examine the dynamic relationship among energy efficiency, health expenditure and economic growth in Malaysia over the sample period of 1980–2016.

Design/methodology/approach

This study uses autoregressive distributed lag cointegration analysis and the causality approach by the vector error correction model to analyse the relationship among energy efficiency, which is proxied by energy intensity and the determinant factors.

Findings

The findings of this paper suggest long-run cointegration causal links between economic growth and health expenditure. However, a mixed conclusion for both determinants exists: an increase in real income contributes to more efficient use of energy sources, whereas an increase in government spending on health intensifies energy usage.

Originality/value

Most previous relevant research has focussed on energy efficiency as measured by economic intensity and economic growth and do not relate to the issue of health expenditure. The recent health catastrophe brought on by the COVID-19 epidemic emphasises the significance of allocating more resources to health care. The findings will be helpful in the development of energy efficiency and economic policies in pursuit of sustainable development goals.
A method for detecting and monitoring changes to the Okotoks Erratic – “Big Rock” provincial historic site
Authors: Dawson Peter , Brink Jack , Farrokhi Alireza , Jia Fengman , Lichti Derek
Published: August 2022

Purpose

Designing and implementing effective strategies for managing heritage resources throughout the world has become critically important as the impacts of climate change and human-caused destruction are increasingly felt. Of particular importance is the ability to identify and track fast- and slow-moving processes associated with weathering, erosion and the movement or removal of heritage objects by natural and human agents. In this paper, the authors demonstrate how 3D laser scanning can be used to detect and monitor changes to the Okotoks Erratic “Big Rock” Provincial Historic Resource in Alberta, Canada, over a period of 7 years.

Design/methodology/approach

Terrestrial laser scanning surveys of the Okotoks Erratic “Big Rock” Provincial Historic Resource were undertaken in 2013, 2016 and 2020. Registration was used to place the three epochs of point clouds into a unique datum for comparison using the cloud-to-cloud distance function in Cloud Compare.

Findings

The movement/repositioning of rocks around the base of the erratic, the emergence of “unofficial” paths and changes to interpretive trails and fencing were all identified at the site over the time period of the study.

Practical implications

Current conservation at the Okotoks Big Rock focus primarily on the rock art panels that are scattered over the erratic. The results of this study indicate they should be broadened so that the geological integrity of the site, which is intrinsically linked to its cultural value, can also be maintained.

Originality/value

This is the first study the authors are aware of that utilizes terrestrial laser scanning + change detection analysis to identify and track changes to a heritage site over a period as long as 7 years.
The turn-of-the-month effect and investor trading activities in the KOSDAQ stock market
Authors: Kim Ryumi
Published: August 2022

The turn-of-the-month (TOM) effect is observed as one of the seasonalities in many markets. The author examines the TOM effect in the KOSDAQ market and finds that the effect is significant. The TOM effect in the KOSDAQ market is not due to size, turn-of-the-year, turn-of-the-quarter or index rebalancing effect. The author also finds that individual and institutional traders do not trade and buy more stocks at the TOM than on the rest days, not consistent with existing explanations of the increased liquidity by individual investors or institutional window-dressing activity. When the author investigated the net buying volume and net turnover of each investor, the net volume and turnover of individual investors at the TOM were significantly lower than those on the other days, rejecting the hypothesis of their increased demand. Interestingly, net foreign volumes at the TOM are significantly higher than on the other days. Finally, using panel regressions, the author finds that stocks with a higher net buying volume of foreigners for the TOM period tend to have higher returns, while stocks with a higher net buying volume of individual traders for the TOM period are likely to have lower returns. The results confirm that the TOM effect is not due to the increased demand of individual investors. Instead, higher net buying volume by foreigners may partially cause the TOM effect. Therefore, this study contributes to the literature by revealing the presence of the TOM effect in the KOSDAQ market and the foreign role in the anomaly in the market even mainly traded by retail investors.
A mathematical model for integrated aircraft and crew recovery after a disruption: a Benders’ decomposition approach
Authors: Khiabani Amir , Rashidi Komijan Alireza , Ghezavati Vahidreza , Mohammadi Bidhandi Hadi
Published: August 2022

Purpose

Airline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling strategy is vital for a commercial airline. The purpose of this paper is to present an integrated aircraft and crew recovery plans to reduce delay and prevent delay propagation on airline schedule with the minimum cost.

Design/methodology/approach

A mixed-integer linear programming model is proposed to formulate an integrated aircraft and crew recovery problem. The main contribution of the model is that recovery model is formulated based on individual flight legs instead of strings. This leads to a more accurate schedule and better solution. Also, some important issues such as crew swapping, reassignment of aircraft to other flights as well as ground and sit time requirements are considered in the model. Benders’ decomposition approach is used to solve the proposed model.

Findings

The model performance is also tested by a case including 227 flights, 64 crew, 56 aircraft and 40 different airports from American Airlines data for a 24-h horizon. The solution achieved the minimum cost value in 35 min. The results show that the model has a great performance to recover the entire schedule when disruption happens for random flights and propagation delay is successfully limited.

Originality/value

The authors confirm that this is an original paper and has not been published or under consideration in any other journal.
Industry 4.0 and intelligent predictive maintenance: a survey about the advantages and constraints in the Italian context
Authors: Stefanini Roberta , Tancredi Giovanni Paolo Carlo , Vignali Giuseppe , Monica Luigi
Published: August 2022

Purpose

In the context of the Industry 4.0, this paper aims to investigate the state of the art of Italian manufacturing, focusing the attention on the implementation of intelligent predictive maintenance (IPdM) and 4.0 key enabling technologies (KETs), analyzing advantages and limitations encountered by companies.

Design/methodology/approach

A survey has been developed by the University of Parma in cooperation with the Italian Workers' Compensation Authority (INAIL) and was submitted to a sample of Italian companies. Overall, 70 answers were collected and analyzed.

Findings

Results show that the 54% of companies implemented smart technologies, increasing quality and safety, reducing the operating costs and sometimes improving the process' sustainability. However, IPdM was implemented only by the 37% of respondents: thanks to big data collection and analytics, Internet of Things, machine learning and collaborative robots, they reduced downtime and maintenance costs. These changes were implemented mainly by large companies, located in northern Italy. To spread the use of IPdM in Italian manufacturing, the high initial investment, lack of skilled labor and difficulties in the integration of new digital technologies with the existing infrastructure are the main obstacles to overcome.

Originality/value

The article gives an overview on the current state of the art of 4.0 technologies implementation in Italy: it is useful not only for companies that want to discover the implementations' advantages but also for institutions or research centres that could help them to solve the encountered obstacles.
How social presence influences consumer purchase intention in live video commerce: the mediating role of immersive experience and the moderating role of positive emotions
Authors: Huang Zhen , Zhu Yidan , Hao Andy , Deng Jia
Published: August 2022

Purpose

This paper aims to examine the relationship between social presence and consumer purchase intention in the context of livestreaming commerce and test the mediating role of immersive experience and the moderating role of positive emotions.

Design/methodology/approach

The authors used a convenience sampling method to select 408 college students from a university in Ganzhou as the participants. They employed structural equation modeling to test the hypotheses, as well as Hayes' PROCESS to test the mediation and moderation effects.

Findings

The authors found that immersion experiences partially mediate the relationship between social presence and consumers' purchase intentions and positive emotions moderate the “social presence–immersion experience–consumer purchase intentions” path. Therefore, social presence constitutes a moderating mediating effect on consumer purchase intentions.

Practical implications

This study offers meaningful insights into how livestreamers and e-retailers can stimulate consumers' buying behavior in livestreaming environments. E-commerce platforms should strengthen consumer interactions and increase consumers' perceptions of social presence. In addition, companies should meet the social and psychological needs of consumers and generate positive emotional resonance.

Originality/value

This research sheds light on the effect of social presence on consumer purchase intentions in livestreaming commerce and extends the social presence literature by investigating the mediation mechanism of immersive experience.