bluuebunny/crossref_metadata_2025 huggingface dataset:
Pretrained Language Models for Semantics-Aware Data Harmonisation of Observational Clinical Studies in the Era of Big Data
Authors: Dylag Jakub , Zlatev Zlatko , Boniface Michael
Published: July 2024

Background

In clinical research, there is a strong drive to leverage big data from population cohort studies and routine electronic healthcare records to design new interventions, improve health outcomes and increase efficiency of healthcare delivery. Yet, realising these potential demands requires substantial efforts in harmonising source datasets and curating study data, which currently relies on costly and time-consuming manual and labour-intensive methods.

Objectives

We evaluate the applicability of AI methods for natural language processing (NLP) and unsupervised machine learning (ML) to the challenges of big data semantic harmonisation and curation. Our aim is to establish an efficient and robust technological foundation for the development of automated tools supporting data curation of large clinical datasets.

Methods

We assess NLP and unsupervised ML algorithms and propose two pipelines for automated semantic harmonisation: a pipeline for semantics-aware search for domain relevant variables and a pipeline for clustering of semantically similar variables. We evaluate pipeline performance using 94,037 textual variable descriptions from the English Longitudinal Study of Ageing (ELSA) database.

Results

We observe high accuracy of our Semantic Search pipeline with an AUC of 0.899 (SD=0.056). Our Semantic Clustering pipeline achieves a V-measure of 0.237 (SD=0.157), which is on par with leading implementations in other relevant domains. Automation can significantly accelerate the process of dataset harmonization. Manual labelling was performed at a speed of 2.1 descriptions per minute, with our automated labelling increasing speed to 245 descriptions per minute.

Conclusions

Our study findings underscore the potential of AI technologies, such as NLP and unsupervised ML, in automating the harmonisation and curation of big data for clinical research. By establishing a robust technological foundation, we pave the way for the development of automated tools that streamline the process, enabling health data scientists to leverage big data more efficiently and effectively in their studies, accelerating insights from data for clinical benefit.
RBD amplicon sequencing of wastewater reveals patterns of variant emergence and evolution
Authors: Chen Xingwen , Balliew John , Bauer Cici X. , Deegan Jennifer , Gitter Anna , Hanson Blake M. , Maresso Anthony W. , Tisza Michael J. , Troisi Catherine L. , Rios Janelle , Mena Kristina D. , Boerwinkle Eric , Wu Fuqing
Published: July 2024

Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.
Large-scale genome-wide interaction analyses on multiple cardiometabolic risk factors to identify age-specific genetic risk factors
Authors: Ao Linjun , van Heemst Diana , Luo Jiao , Teder-Laving Maris , Mägi Reedik ,   Estonian Biobank Research Team, Frikke-Schmidt Ruth , van Dijk Ko Willems , Noordam Raymond
Published: July 2024

Background

The genetic landscape of cardiometabolic risk factors has been explored extensively. However, insight in the effects of genetic variation on these risk factors over the life course is sparse. Here, we performed genome-wide interaction studies (GWIS) on different cardiometabolic risk factors to identify age-specific genetic risks.

Methods

This study included 270,276 unrelated European-ancestry participants from the UK Biobank (54.2% women, a median age of 58 [interquartile range (IQR): 50, 63] years). GWIS models with interaction terms between genetic variants and age were performed on apolipoprotein B (ApoB), low-density lipoprotein-cholesterol (LDL-C), log-transformed triglycerides (TG), body mass index (BMI), and systolic blood pressure (SBP). Replication was subsequently performed in the Copenhagen General Population Study (CGPS) and the Estonian Biobank (EstBB).

Results

Multiple lead variants were identified to have genome-wide significant interactions with age (Pinteraction<1e-08). In detail, rs429358 (taggingAPOE4) was identified for ApoB (Pinteraction= 9.0e-14) and TG (Pinteraction= 5.4e-16). Three additional lead variants were identified for ApoB: rs11591147 (R46L inPCSK9,Pinteraction= 3.9e-09), rs34601365 (nearAPOB,Pinteraction= 8.4e-09), and rs17248720 (nearLDLR,Pinteraction= 2.0e-09). Effect sizes of the identified lead variants were generally closer to the null with increasing age. No variant-age interactions were identified for LDL-C, SBP and BMI. The significant interactions of rs429358 with age on ApoB and TG were replicated in both CGPS and EstBB.

Conclusions

The majority of genetic effects on cardiometabolic risk factors remains relatively constant over age, with the noted exceptions of specific genetic effects on ApoB and TG.
A Machine Learning-Based Prediction of Hospital Mortality in Mechanically Ventilated ICU Patients
Authors: Li Hexin , Ashrafi Negin , Kang Chris , Zhao Guanlan , Chen Yubing , Pishgar Maryam
Published: July 2024

Background

Mechanical ventilation (MV) is vital for critically ill ICU patients but carries significant mortality risks. This study aims to develop a predictive model to estimate hospital mortality among MV patients, utilizing comprehensive health data to assist ICU physicians with early-stage alerts.

Methods

We developed a Machine Learning (ML) framework to predict hospital mortality in ICU patients receiving MV. Using the MIMIC-III database, we identified 25,202 eligible patients through ICD-9 codes. We employed backward elimination and the Lasso method, selecting 32 features based on clinical insights and literature. Data preprocessing included eliminating columns with over 90% missing data and using mean imputation for the remaining missing values. To address class imbalance, we used the Synthetic Minority Over-sampling Technique (SMOTE). We evaluated several ML models, including CatBoost, XGBoost, Decision Tree, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Logistic Regression, using a 70/30 train-test split. The CatBoost model was chosen for its superior performance in terms of accuracy, precision, recall, F1-score, AUROC metrics, and calibration plots.

Results

The study involved a cohort of 25,202 patients on MV. The CatBoost model attained an AUROC of 0.862, an increase from an initial AUROC of 0.821, which was the best reported in the literature. It also demonstrated an accuracy of 0.789, an F1-score of 0.747, and better calibration, outperforming other models. These improvements are due to systematic feature selection and the robust gradient boosting architecture of CatBoost.

Conclusion

The preprocessing methodology significantly reduced the number of relevant features, simplifying computational processes, and identified critical features previously overlooked. Integrating these features and tuning the parameters, our model demonstrated strong generalization to unseen data. This highlights the potential of ML as a crucial tool in ICUs, enhancing resource allocation and providing more personalized interventions for MV patients.
Polycomb-associated and Trithorax-associated developmental conditions – phenotypic convergence and heterogeneity
Authors: Smail Alice , Jawahiri Eema , Baker Kate
Published: July 2024

Polycomb group (PcG) and Trithorax group (TrxG) complexes represent two major components of the epigenetic machinery. This study aimed to delineate phenotypic similarities and differences across developmental conditions arising from rare variants in PcG and TrxG genes, using data-driven approaches.

462 patients with a PcG or TrxG-associated condition were identified in the DECIPHER dataset. We analysed Human Phenotype Ontology (HPO) data to identify phenotypes enriched in this group, in comparison to other monogenic conditions within DECIPHER. We then assessed phenotypic relationships between single gene diagnoses within the PcG and TrxG group, by applying semantic similarity analysis and hierarchical clustering. Finally, we analysed patient-level phenotypic heterogeneity in this group, irrespective of specific genetic diagnosis, by applying the same clustering approach. Collectively, PcG/TrxG diagnoses were associated with increased reporting of HPO terms relating to integument, growth, head & neck, limb and digestive abnormalities. Gene group analysis identified three multi-gene clusters differentiated by microcephaly, limb/digit dysmorphologies, growth abnormalities and atypical behavioural phenotypes. Patient-level analysis identified two large clusters differentiated by neurodevelopmental abnormalities and facial dysmorphologies respectively, as well as smaller clusters associated with more specific phenotypes including behavioural characteristics, eye abnormalities, growth abnormalities and skull dysmorphologies. Importantly, patient-level phenotypic clusters did not align with genetic diagnoses. Data-driven approaches can highlight pathway-level and gene-level phenotypic convergences, and individual-level phenotypic heterogeneities. Future studies are needed to understand the multi-level mechanisms contributing to both convergence and variability within this population, and to extend data collection and analyses to later-emerging health characteristics.
Oxidative stress promotes axonal atrophy through alterations in microtubules and EB1 function
Authors: Shields Samuel , Wilkes Oliver , Gozes Illana , Sanchez-Soriano Natalia
Published: July 2024

Axons are crucial for transmitting neurochemical signals. As organisms age, the ability of neurons to maintain their axons declines; hence aged axons are more susceptible to damage or dysfunction. Understanding what causes axonal vulnerability is crucial for developing strategies to enhance overall resilience of neurons, and to prevent their deterioration during ageing or in age-related neurodegenerative diseases.

Increasing levels of reactive oxygen species (ROS) causes oxidative stress, a hallmark of ageing and age-related diseases. Despite this association, a causal relationship between oxidative stress and neuronal ageing remains unclear, particularly how subcellular physiology is affected by ROS.

By usingDrosophila-derived primary neuronal cultures and a recently developedin vivoneuronal model of ageing, which involves the visualisation ofDrosophilamedulla neurons, we investigated the interplay between oxidative stress, neuronal ageing and the microtubule cytoskeleton. We find that oxidative stress as a key driver of axonal and synaptic decay, including the appearance of axonal swellings, microtubule alterations in both axons and synapses and the morphological transformation of axonal terminals during ageing. We demonstrate that increased ROS sensitises the microtubule plus end binding factor, end-binding protein 1 (EB1), leading to microtubule defects, affecting neuronal integrity. Furthermore, manipulating EB1 proved to be a valuable therapeutic strategy to prevent ageing hallmarks observed in conditions of elevated ROS. In summary, we demonstrate a mechanistic pathway linking cellular oxidative stress, the microtubule cytoskeleton and axonal deterioration during ageing and provide evidence of the therapeutic potential of enhancing microtubule plus end physiology to improve the resilience of axons.
Tert-expressing cells contribute to salivary gland homeostasis and tissue regeneration after radiation therapy
Authors: Guan Li , Viswanathan Vignesh , Jiang Yuyan , Vijayakumar Sivakamasundari , Cao Hongbin , Zhao Junfei , Colburg Deana Rae Crystal , Neuhöfer Patrick , Zhang Yiru , Wang Jinglong , Xu Yu , Laseinde Eyiwunmi E. , Hildebrand Rachel , Rahman Mobeen , Frock Richard , Kong Christina , Beachy Philip A. , Artandi Steven , Le Quynh-Thu
Published: July 2024

Salivary gland homeostasis and regeneration after radiotherapy depend significantly on progenitor cells. However, the lineage of submandibular gland (SMG) progenitor cells remains less defined compared with other normal organs. Here, using a mouse strain expressing regulated CreERT2 recombinase from the endogenous Tert locus, we identify a distinct telomerase-expressing (TertHigh) cell population located in the ductal region of the adult SMG. These TertHighcells contribute to ductal cell generation during SMG homeostasis and to both ductal and acinar cell renewal 1 year after radiotherapy. TertHighcells maintain self-renewal capacity during in vitro culture, exhibit resistance to radiation damage, and demonstrate enhanced proliferative activity after radiation exposure. Similarly, primary human SMG cells with high Tert expression display enhanced cell survival after radiotherapy, and CRISPR-activated Tert in human SMG spheres increases proliferation after radiation. RNA sequencing reveals upregulation of “cell cycling” and “oxidative stress response” pathways in TertHighcells following radiation. Mechanistically, Tert appears to modulate cell survival through ROS levels in SMG spheres following radiation damage. Our findings highlight the significance of TertHighcells in salivary gland biology, providing insights into their response to radiotherapy and into their use as a potential target for enhancing salivary gland regeneration after radiotherapy.
Bayesian inference for near-field interferometric tests of collapse models
Authors: Laing Shaun , Bateman James
Published: July 2024

We explore the information which proposed matterwave interferometry experiments with large test masses can provide about parameterizable extensions to quantum mechanics, such as have been proposed to explain the apparent quantum to classical transition. Specifically, we consider a matterwave near-field Talbot interferometer and Continuous Spontaneous Localization (CSL). Using Bayesian inference we compute the effect of decoherence mechanisms including pressure and blackbody radiation, find estimates for the number of measurements required, and provide a procedure for optimal choice of experimental control variables. We show that in a simulated space-based experiment it is possible to reach masses of ∼109u, and we quantify the bounds which can be placed on CSL. These specific results can be used to inform experimental design, and the general approach can be applied to other parameterizable models.

Published by the American Physical Society
2024
Role of Higgs and Leggett modes for the third harmonic response in noncentrosymmetric superconductors
Authors: Klein S. , Manske D.
Published: July 2024

The amplitude and phase of the third harmonic response in superconductors provide important insights into collective Higgs and Leggett modes, respectively, in the superconducting state. In particular, for twice the incident frequency equal to the binding energy (2ω=2Δ), one finds a resonance of the amplitude and a corresponding phase jump in the third harmonic response, respectively. We generalize these concepts to superconductors without an inversion symmetry, which can be effectively described by a two-band model with an order parameter consisting of spin-singlet (even parity) and spin-triplet (odd parity) components. In our work we use an effective action approach for the derivation of the nonlinear response and assign the underlying physical processes to their respective Feynman diagrams. We calculate the third harmonic signal exemplary for the noncentrosymmetric compound CePt3Si, showing that it contains contributions from three distinguishable sources, namely the Higgs mode, the Leggett mode, and quasiparticles (broken Cooper-pairs). Only in the clean limit diamagnetic Raman-like processes contribute to the third harmonic signal, whereas the quasiparticle contributions dominate the collective modes for all triplet-singlet ratios of the gap structure. In the dirty limit, we find a significant enhancement of the Higgs mode contributions to the third harmonic response, due to the inclusion of nonvanishing paramagnetic diagrams. Finally, we argue that the phase difference between the third harmonic and the fundamental signal might reveal a jump, where its size is dependent on the light-matter coupling.

Published by the American Physical Society
2024
Double Floquet-Bloch transforms and the far-field asymptotics of Green's functions tailored to periodic structures
Authors: Shanin Andrey V. , Assier Raphaël C. , Korolkov Andrey I. , Makarov Oleg I.
Published: July 2024

We propose a general procedure to study double integrals arising when considering wave propagation in periodic structures. This method, based on a complex deformation of the integration surface to bypass the integrands' singularities, is particularly efficient to estimate the Green's functions of such structures in the far field. We provide several illustrative examples and explicit asymptotic formulas. Special attention is devoted to the pathological cases of degeneracies, such as Dirac conical points.

Published by the American Physical Society
2024
Determination of
KS0
fragmentation functions including BESIII measurements and using neural networks
Authors: Soleymaninia Maryam , Hashamipour Hadi , Salajegheh Maral , Khanpour Hamzeh , Spiesberger Hubert , Meißner Ulf-G.
Published: July 2024

In this study, we revisit the extraction of parton-to-KS0 hadron fragmentation functions, named FF24-KS0, focusing on both next-to-leading-order and next-to-next-to-leading-order accuracy in perturbative QCD. Our approach involves the analysis of single inclusive electron-positron annihilation (SIA) data. The two key improvements are, on the one hand, the incorporation of the latest experimental data from the BESIII experiment and, on the other hand, the adoption of neural networks in the fitting procedure. To address experimental uncertainties, the Monte Carlo method is employed. Our investigation also explores the impact of hadron mass corrections on the description of SIA data, spanning a broad kinematic regime with a particular emphasis on the range of small z values. The theory prediction for KS0 production at both NLO and NNLO accuracy exhibits good agreement with experimental data within their respective uncertainties.

Published by the American Physical Society
2024
Solution generation of a capped black hole
Authors: Suzuki Ryotaku , Tomizawa Shinya
Published: July 2024

Utilizing the electric Harrison transformation developed in five-dimensional minimal supergravity, we construct an exact solution characterizing non-BPS (Bogomol’nyi-Prasad-Sommerfield) charged rotating black holes with a horizon cross section of a lens space L(n;1). Among these solutions, only the ones corresponding to n=0 and n=1 do not have any curvature singularities, conical singularities, Dirac-Misner string singularities, and orbifold singularities both on and outside the horizon; additionally, they are free from closed timelike curves. The solution for n=0 corresponds to the charged dipole black ring that we constructed in the previous paper. The specific solution for n=1, referred to as the “capped black hole,” was introduced in our previous article. This provides the first example of a non-BPS exact solution, representing an asymptotically flat, stationary spherical black hole with a domain of outer communication (DOC) having a nontrivial topology in five-dimensional minimal supergravity. We demonstrate that the DOC on a time slice has the topology of [R4#CP2]\B4. Differing from the well-known Myers-Perry and Cvetič-Youm black holes describing a spherical horizon topology and a DOC with a trivial topology of R4\B4 on a timeslice, the capped black hole’s horizon is capped by a disk-shaped bubble. We explicitly demonstrate that the capped black hole carries mass, two angular momenta, an electric charge, and a magnetic flux, with only three of these quantities being independent. Furthermore, we reveal that this black hole can possess identical conserved charges as the Cvetič-Youm black hole. The existence of this solution challenges black hole uniqueness beyond both the black ring and the BPS spherical black hole. Moreover, within specific parameter regions, the capped black hole can exhibit larger entropy than the Cvetič-Youm black hole.

Published by the American Physical Society
2024
Scalar probes on wormholes in Lovelock theories with unique vacuum
Authors: Fierro Octavio , Narbona Daniela , Oliva Julio , Quijada Constanza , Rubilar Guillermo
Published: July 2024

In this paper we construct new wormhole solutions of Lovelock theories in vacuum, when the coupling constants are such that all the maximally symmetric solutions coincide, extending to arbitrary dimensions wormhole solutions previously known in the Chern-Simons case. Like the latter, the wormholes are characterized by an integration constant ρ0 that controls the contribution to the energy content from one of the boundaries. Then, we study the effects of the constant ρ0 on the spectrum of a massive, (non)minimally coupled scalar probes, with Dirichlet boundary conditions at both asymptotic regions. As a result, a deformed Breitenlohner-Freedman bound emerges, which is sensitive to the value of ρ0. The scalar spectra are numerically obtained in detail in dimension five, and in such dimension we also present a new family of wormhole geometries for the Einstein-Gauss-Bonnet theory with a unique vacuum. The new geometries are constructed via a double analytic continuation of a wormhole previously reported in the literature, but now the constant ρ0 appears in the centrifugal terms of the equations for the geodesic and scalar probes. The mass of these configurations vanishes nontrivially, since the contributions to the mass integral from each boundary are nonvanishing, but only differ in sign, providing a new example of a spacetime having “mass without mass.”

Published by the American Physical Society
2024
Gravitational Faraday and spin-Hall effects of light: Local description
Authors: Shoom Andrey A.
Published: July 2024

A gravitational field can cause a rotation of the polarization plane of light. This phenomenon is known as the gravitational Faraday effect. It arises due to different spin-orbit interactions of left- and right-handed circularly polarized components of light. Such an interaction also causes transverse displacement in the light trajectory, in opposite directions for each component. This phenomenon is known as the gravitational spin-Hall effect of light. We study these effects in a local inertial frame in arbitrary vacuum spacetime and show that they are observer dependent and arise due to interaction of light polarization with a local gravitomagnetic field measured by the observer. Thus, to address the effects to a gravitational field alone, one has to consider zero angular momentum observers.

Published by the American Physical Society
2024
Field Theory of the Fermi Function
Authors: Hill Richard J. , Plestid Ryan
Published: July 2024

The Fermi function F(Z,E) accounts for QED corrections to beta decays that are enhanced at either small electron velocity β or large nuclear charge Z. For precision applications, the Fermi function must be combined with other radiative corrections and with scale- and scheme-dependent hadronic matrix elements. We formulate the Fermi function as a field theory object and present a new factorization formula for QED radiative corrections to beta decays. We provide new results for the anomalous dimension of the corresponding effective operator complete through three loops, and resum perturbative logarithms and π enhancements with renormalization-group methods. Our results are important for tests of fundamental physics with precision beta decay and related processes.

Published by the American Physical Society
2024
Image-Current Mediated Sympathetic Laser Cooling of a Single Proton in a Penning Trap Down to 170 mK Axial Temperature
Authors: Will C. , Wiesinger M. , Micke P. , Yildiz H. , Driscoll T. , Kommu S. , Abbass F. , Arndt B. P. , Bauer B. B. , Erlewein S. , Fleck M. , Jäger J. I. , Latacz B. M. , Mooser A. , Schweitzer D. , Umbrazunas G. , Wursten E. , Blaum K. , Devlin J. A. , Ospelkaus C. , Quint W. , Soter A. , Walz J. , Smorra C. , Ulmer S. ,   BASE Collaboration
Published: July 2024

We demonstrate a new temperature record for image-current mediated sympathetic cooling of a single proton in a cryogenic Penning trap by laser-cooled Be+9. An axial mode temperature of 170 mK is reached, which is a 15-fold improvement compared to the previous best value. Our cooling technique is applicable to any charged particle, so that the measurements presented here constitute a milestone toward the next generation of high-precision Penning-trap measurements with exotic particles.

Published by the American Physical Society
2024
Escaping Kinetic Traps Using Nonreciprocal Interactions
Authors: Osat Saeed , Metson Jakob , Kardar Mehran , Golestanian Ramin
Published: July 2024

Kinetic traps are a notorious problem in equilibrium statistical mechanics, where temperature quenches ultimately fail to bring the system to low energy configurations. Using multifarious self-assembly as a model system, we introduce a mechanism to escape kinetic traps by utilizing nonreciprocal interactions between components. Introducing nonequilibrium effects offered by broken action-reaction symmetry in the system pushes the trajectory of the system out of arrested dynamics. The dynamics of the model is studied using tools from the physics of interfaces and defects. Our proposal can find applications in self-assembly, glassy systems, and systems with arrested dynamics to facilitate escape from local minima in rough energy landscapes.

Published by the American Physical Society
2024
Crystal structure of catena-poly[[methanoldioxidouranium(VI)]-μ-2-[5-(2-oxidophenyl)-1H-1,2,4-triazol-3-yl]acetato-κ2
O:O′]
Authors: Vashchenko Oleksandr V. , Khomenko Dmytro M. , Doroshchuk Roman O. , Stoica Alexandru-Constantin , Vassilyeva Olga Yu. , Lampeka Rostyslav D.
Published: July 2024

In the title complex, [U(C10H7N3O3)O2(CH3OH)]
n
, the UVI cation has a typical pentagonal–bipyramidal environment with the equatorial plane defined by one N and two O atoms of one doubly deprotonated 2-[5-(2-hydroxyphenyl)-1H-1,2,4-triazol-3-yl]acetic acid ligand, a carboxylate O atom of the symmetry-related ligand and the O atom of the methanol molecule [U—N/Oeq 2.256 (4)–2.504 (5) Å]. The axial positions are occupied by two oxide O atoms. The equatorial atoms are almost coplanar, with the largest deviation from the mean plane being 0.121 Å for one of the O atoms. The benzene and triazole rings of the tetradentate chelating–bridging ligand are twisted by approximately 21.6 (2)° with respect to each other. The carboxylate group of the ligand bridges two uranyl cations, forming a neutral zigzag chain reinforced by a strong O—H...O hydrogen bond. In the crystal, adjacent chains are linked into two-dimensional sheets parallel to the ac plane by C/N—H...N/O hydrogen bonding and π–π interactions. Further weak C—H...O contacts consolidate the three-dimensional supramolecular architecture. In the solid state, the compound shows a broad medium intensity LMCT transition centred around 463 nm, which is responsible for its red colour.
What else? Immigrant–native cohorts entering the labour market under a context of adverse shocks: the great recession and COVID-19
Authors: Escalonilla Marta , Cueto Begoña , Perez-Villadoniga Maria Jose
Published: July 2024

Purpose

This paper aims to analyse the short- and long-term effects of entering the Spanish labour market under tough economic conditions on young immigrant–native earnings and employment outcomes.

Design/methodology/approach

The authors use cohorts, where the entry cohort into the labour market is the unit of observation. As a database, the authors use the continuous sample of working histories covering the period 2007–2021. Then, the authors estimate the model using weighted least squares.

Findings

The results show that the great recession and COVID-19 led to a blockage at the entrance of the labour market, reducing the number of workers. Additionally, the authors observe an adverse impact in terms of employment and earnings on those entering the labour market. Besides, this effect varies in intensity and persistence for natives and immigrants, as well as by country of birth, age of entry, gender and educational level.

Originality/value

A contribution to the literature is the analysis of the earnings and employment trajectories of young people entering the Spanish labour market for the first time during an adverse shock, such as the 2008 economic crisis or the COVID-19 crisis, and the possible differences that exist between native and immigrant workers. So, the authors analyse the labour market trajectories of workers covering the most recent years. Likewise, the authors carry out an extensive heterogeneity analysis in which they distinguish workers by educational level, gender, age of entry into the labour market and immigrants by their country of birth. This represents an additional contribution. The use of a cohort approach also contributes to the existing literature.
Digital consumerism in times of crisis: exploring the shift in online shopping behaviour
Authors: Akar Ezgi
Published: July 2024

Purpose

This research delves into consumer online shopping behaviour during the different phases of the COVID-19 pandemic, utilising the Theory of Planned Behaviour and the Behavioural Inhibition System.

Design/methodology/approach

A unique and comprehensive repeated cross-sectional methodology was meticulously employed, capturing the nuances of consumer online shopping behaviour across three distinct phases of the pandemic: the initial phase following the outbreak of COVID-19, the transition phase marked by the relaxation of restrictions, and the adaptation phase as society moved towards a new normal. The study involved a sample of 1,155 participants. Structural equation modelling was used to analyse the effects of behavioural attitudes, subjective norms, perceived behavioural control, and the moderating role of pandemic-induced consumer anxiety on online purchase intention.

Findings

The impact of behavioural attitudes on online purchase intentions increased continuously from the initial phase to the adaptation phase. In contrast, the influence of subjective norms on online shopping intentions gradually declined over the same period. During the early stages of the pandemic, consumer anxiety amplified the influence of personal attitudes towards online shopping while diminishing the impact of social pressures on the same behaviour.

Originality/value

This study’s originality lies in its nuanced analysis of how online purchase intentions evolved across different stages of the COVID-19 pandemic, integrating insights from both the Theory of Planned Behaviour and the Behavioural Inhibition System. The study offers a comprehensive understanding of the shifts in consumer behaviour over time. It enables more strategic and proactive marketing tactics in a changing environment.
Does the quality grading system matter? Chinese consumer response to pork quality grading labels and the impact of information
Authors: Shen Qinyuan , Gao Zhifeng , Zhu Zhanguo
Published: July 2024

Purpose

A meat quality grading system is essential to meet consumers' increasingly diversified demand for food quality in the global market. This study aims to determine the effectiveness of the upcoming Chinese quality grading labels and examine the information effect of labeling standards on pork consumption choices.

Design/methodology/approach

Using an online survey with choice experiments, this study estimates consumer valuation for the fat thickness of different pork primal cuts by simulating three scenarios. Generalized mixed logit models in WTP space are used to analyze the choice experiment data.

Findings

Chinese consumers prefer lean pork to fatty pork and this preference does not vary significantly between primal cuts. Consumer valuation for ungraded high-quality (lean) pork increases after the implementation of the quality grading. Meanwhile, they are willing to pay high premiums for labeled pork (including level 1, 2, 3), and there are higher premiums for pork with higher levels. Besides, incomplete information on labeling standards could achieve more premiums for pork than relatively complete information.

Originality/value

This study pays attention to essential but few-noticed pork quality grading. The findings provide references for pork industry practices and policy-making of the meat quality grading system in China and globally by examining incomplete and relatively complete information effects on consumer choices.
Who do you choose? Employees' perceptions of artificial intelligence versus humans in performance feedback
Authors: Biswas Mohammad Islam , Talukder Md. Shamim , Khan Atikur Rahman
Published: July 2024

Purpose

Firms have already begun integrating artificial intelligence (AI) as a replacement for conventional performance management systems owing to its technological superiority. This transition has sparked a growing interest in determining how employees perceive and respond to performance feedback provided by AI as opposed to human supervisors.

Design/methodology/approach

A 2 x 2 between-subject experimental design was employed that was manipulated into four experimental conditions: AI algorithms, AI data, highly experienced human supervisors and low-experience human supervisor conditions. A one-way ANOVA and Welch t-test were used to analyze data.

Findings

Our findings revealed that with a predefined fixed formula employed for performance feedback, employees exhibited higher levels of trust in AI algorithms, had greater performance expectations and showed stronger intentions to seek performance feedback from AI algorithms than highly experienced human supervisors. Conversely, when performance feedback was provided by human supervisors, even those with less experience, in a discretionary manner, employees' perceptions were higher compared to similar feedback provided by AI data. Moreover, additional analysis findings indicated that combined AI-human performance feedback led to higher levels of employees' perceptions compared to performance feedback solely by AI or humans.

Practical implications

The findings of our study advocate the incorporation of AI in performance management systems and the implementation of AI-human combined feedback approaches as a potential strategy to alleviate the negative perception of employees, thereby increasing firms' return on AI investment.

Originality/value

Our study represents one of the initial endeavors exploring the integration of AI in performance management systems and AI-human collaboration in providing performance feedback to employees.
Co-creating inclusion in research practices in the South Pacific: some highlights and challenges
Authors: Ofe-Grant Maulupeivao Betty , Elikana Miura , SauLilo Losi , Vimahi Lillian , O'Brien Seipua , Joseph Evangeleen
Published: July 2024

Purpose

Colonial epistemes distort ideologies through power structures and control, perpetuating differences and the development of an inferior status. This study aims to serve dual purposes: Firstly, the authors advocate for Pacific and international business (IB) researchers to consider adopting inclusive research practices, particularly regarding Pacific and indigenous populations. Secondly, the authors argue that decolonization presents conflicting challenges, demonstrating that the authors still have a long way to go regarding the decolonization agenda within academia, the university, IB and broader society.

Design/methodology/approach

An essay style is adopted to introduce inclusive Pacific research practices specific to the Pacific context, what that looks like and the advantages of using culturally appropriate methods.

Findings

This paper highlights some examples that justify why Pacific methods should be used, such as spirituality and prayers underpinned by the va (i.e. relational spaces) – a concept well-known in Pacific cultures but missing in Western academic frameworks, models and approaches. Additionally, the authors found that the endeavours to be inclusive can paradoxically lead to exclusion and marginalization within academia, the university and popular mainstream media.

Social implications

This paper enriches IB theory and pedagogy by advocating for the co-creation of inclusive research practices in collaboration with Pacific and indigenous communities. It contributes to the broader movement to restore indigenous knowledge and scholarship research spaces.

Originality/value

The originality and value of the viewpoint lie in its potential to stimulate conversations and reflections among IB researchers regarding inclusive research practices of decoloniality. Thereby strengthening the “trumpet-shell” call to decolonize the field and academia, which IB as a discipline should not be immune to.
Sustainable development goals and organizations: exploring the role of employee emotional capital
Authors: Gupta Parul , Bakhru Kanupriya Misra , Shankar Amit
Published: July 2024

Purpose

This study aims to understand the association between employee emotional capital, organizational commitment and implementation of the targeted sustainable development goals (SDGs) by businesses. It explores how the various emotional competencies possessed by employees of an organization and accumulated in the form of a capital, can be utilized to ensure effective pursuit of SDG implementation by businesses.

Design/methodology/approach

This study is based on extensive literature exploration to identify competencies crucial for SDG attainment by a business. The conceptual model built on the same is then tested by conducting a survey on working professionals. Subsequent statistical analysis is conducted to establish the relationship as defined in the theoretical model.

Findings

The results of our analysis indicate a relationship between organizational commitment and emotional capital of the employees. In line with our conceptual framework, the statistical analysis also corroborates to the idea that emotional capital can improve the SDG attainment by an organization by influencing the organizational commitment. This study also identifies the specific emotional competencies which can play an important role in this direction.

Originality/value

This study connects the dots to establish a micro-meso-macro framework which can facilitate active participation of individuals and the businesses in achieving the SDGs. This study presents strong managerial and academic implications by identifying specific intervention areas which can and be focused upon by managers and academicians to focus on SDG implementation.
Stuck in a moment you can't get out of: the psychological effects of expatriates' coping with a crisis situation
Authors: Koveshnikov Alexei , Lehtonen Miikka J.
Published: July 2024

Purpose

We draw upon stress theory and utilize the context of the COVID-19 pandemic to investigate how various coping strategies employed by expatriates affect their psychological stress, subsequently influencing their expatriation satisfaction and intention to withdraw from the host country.

Design/methodology/approach

We utilize structural equation modeling to analyze a sample of 453 expatriates residing and working in the United Arab Emirates during the COVID-19 pandemic.

Findings

Our analysis shows that the effects of different coping strategies on expatriates vary. Depending on the nature of the strategy, they can have either positive or negative effects. While coping via problem-focused and denial strategies decreases expatriates' stress, coping by distancing increases it. Social support-seeking is not found to be an effective stress-coping strategy. In terms of implications, the problem-focused strategy leads to the most positive outcomes, whereas distancing leads to the most negative outcomes.

Originality/value

Our study provides significant theoretical and practical insights into expatriates' coping mechanisms within the context of natural crises.
Efficiency evaluation of intellectual capital for value creation: a case study of the semiconductor industry in Taiwan
Authors: He Dong-Sing , Liu Te-Wei , Lin Yi-Ying
Published: July 2024

Purpose

This study constructs an efficiency evaluation framework for assessing the human, structural and relational capital in the semiconductor industry of Taiwan. Furthermore, we analyze whether there are significant differences in efficiency across different levels concerning the industry supply chain (upstream, midstream and downstream), employee service tenure, capital scale and company establishment years.

Design/methodology/approach

This study focuses on Taiwanese semiconductor companies, utilizing data sourced from the Taiwan Economic Journal (TEJ) Database for the period spanning 2017 to 2021, encompassing a total of five years. Due to the nondisclosure of intangible asset values by all companies, an effort was made to ensure a comparable baseline by excluding companies with incomplete or missing data. Finally, empirical analysis was conducted on a sample of 64 companies using the dynamic network data envelopment analysis method.

Findings

(1) Overall efficiency demonstrates structural capital as the most prominent, followed by relational capital, while human capital shows relatively poorer efficiency. (2) To enhance the efficiency of intellectual capital, priority should be given to improving the efficiency of outputs related to intellectual property rights such as patents. (3) The midstream segment exhibits the best efficiency in both structural and relational capital. (4) Companies with longer employee service tenures exhibit superior efficiency in human capital in the long run. (5) Companies with extended establishment years and larger capital scales demonstrate superior efficiency in both human and structural capital.

Originality/value

Reflecting on past literature, scholars have primarily focused on the relationship between intellectual capital and firm efficiency, often emphasizing the overall efficiency of intellectual capital. However, within organizations, human capital, structural capital, and relational capital are interrelated. This study, for the first time, assesses the efficiency of these three components within an organization. The research addresses the challenges in analyzing the efficiency of intellectual capital and introduces a highly contemporary approach – dynamic network data envelopment analysis (DNDEA). Using the semiconductor industry in Taiwan as a case study, this paper conducts empirical analysis in a captivating and worthy industry. Therefore, the ideas presented in this paper are original.
Technostress and disengagement from knowledge sharing: insights from pre-pandemic and mid-pandemic data sets
Authors: Mahapatra Monalisa , Ford Dianne P.
Published: July 2024

Purpose

This study aims to examine a common failure in knowledge sharing, called disengagement from knowledge sharing (DKS), and investigates how technostress may contribute to this unintentional withholding of knowledge for knowledge workers. The authors apply the Job Demands-Resources (JD-R) model to explain the dual path of technostress creators and inhibitors on DKS via burnout and job engagement. The authors also examine how the pandemic and the changes in remote work and information and communication technology (ICT)-related stress may have impacted DKS.

Design/methodology/approach

Using a time-lag survey, two independent samples of knowledge workers who use information and communication technologies for their jobs were surveyed during early 2020 and mid-2021. Analyses were completed with partial least squares-structural equation modelling.

Findings

Technostress (via the JD-R model) explained DKS. Technostress creators were positively associated with burnout, which was in turn positively related to DKS. Technostress inhibitors were positively associated with job engagement, which in turn was also positively related to disengagement to knowledge sharing. Technostress inhibitors were negatively associated with burnout. Results from the multigroup analysis indicated that technostress inhibitors had a stronger relationship with engagement pre-pandemic than mid-pandemic.

Originality/value

This research addresses a more common source of knowledge sharing failures and illustrates how ICTs may impact this DKS via burnout and job engagement. In addition, this research captures a change in relationships associated with the pandemic.
Applying the anthropological theory of didactics to enhance a multicultural approach to statistics education for engineering students
Authors: Díaz Palencia José Luis
Published: July 2024

Purpose

This work aims to introduce basic principles of the Anthropological Theory of Didactics applied to enhance the multicultural sensitivity in engineering statistics classroom. The approach emphasizes understanding learners’ socio-cultural backgrounds to tailor educational practices that resonate more effectively with engineering students.

Design/methodology/approach

This paper examines the application of the Anthropological Theory of Didactics within the context of statistics education for engineering students. This study aims to explore how integrating socio-cultural dimensions of learning can make teaching statistics more effective and engaging.

Findings

The application of the Anthropological Theory of Didactics reveals significant potential for enhancing the educational experience in statistics. By acknowledging and incorporating the diverse cultural perspectives of students, educators can develop teaching methods that are not only more inclusive but also more engaging. This methodology encourages a deeper connection between statistical concepts and engineering practices, aiding in the conceptualization of statistics among future engineers.

Originality/value

The paper contributes to the field by providing concrete activities and pedagogical strategies that use the Anthropological Theory of Didactics in a novel context. These activities are designed to foster a better integration of statistical education with engineering, highlighting the theory’s versatility and its relevance to modern educational challenges. This innovative approach promises to enhance how statistics is taught to engineering students, potentially leading to more profound educational outcomes and a stronger grasp of statistical applications in engineering.