bluuebunny/crossref_metadata_2025 huggingface dataset:
Body Mass Index and Non-invasive Cardiovascular Parameters
Authors: Wu Shenghui , Meucci Marco , Liu Zhong
Published: May 2024

Background

Epidemiological studies on body mass index (BMI) and non-invasive cardiovascular parameters are limited and inconsistent. To provide more informative data for further prevention and control, we examined associations between BMI, as well as overweight/obesity, and non-invasive cardiovascular parameters and their dose-response relationships in North Carolina Appalachian adults.

Methods

A total of 71 participants were included in this analysis. Non-invasive cardiovascular parameters included carotid-femoral pulse wave velocity for measuring central arterial stiffness, augmentation index at 75 bpm for gauging peripheral arterial stiffness, ejection time for indicating left ventricular performance, and Buckberg index for measuring coronary microvascular circulation. Logistic regression models were used for analysis.

Results

Every unit (kg/m2) increase in BMI was associated with a 25% statistically significant increased multivariable-adjusted odds of higher central arterial stiffness (odds ratio: 1.25; 95% confidence interval: 1.04-1.51), a 31% increased adjusted odds of higher peripheral arterial stiffness, a 23% statistically significant increased adjusted odds of worse left ventricular performance, and a 25% statistically significant increased adjusted odds of worse coronary microvascular circulation. Overweight/obesity was associated with a 532% statistically significant increased odds of higher arterial stiffness (6.32; 1.42-28.09), and a 704% statistically significant increased odds of worse left ventricular performance after adjusting for age, sex, physical activity, and body fat percentage.

Conclusion

Increased BMI, especially overweight/obesity, was significantly associated with the increased risk of worse cardiovascular health, measured by non-invasive cardiovascular parameters. Efforts need to be focused on improving interventions to lower BMI/reduce overweight and obesity in North Carolina, especially in Appalachian populations.
Hidden state inference requires abstract contextual representations in ventral hippocampus
Authors: Mishchanchuk Karyna , Gregoriou Gabrielle , Qü Albert , Kastler Alizée , Huys Quentin , Wilbrecht Linda , MacAskill Andrew F.
Published: May 2024

The ability to form and utilize subjective, latent contextual representations to influence decision making is a crucial determinant of everyday life. The hippocampus is widely hypothesized to bind together otherwise abstract combinations of stimuli to represent such latent contexts, and to allow their use to support the process of hidden state inference. Yet, direct evidence for this remains limited. Here we show that the CA1 area of the ventral hippocampus is necessary for mice to perform hidden state inference during a 2-armed bandit task. vCA1 neurons robustly differentiate between the two abstract contexts required for this strategy in a manner similar to the differentiation of spatial locations, despite the contexts being formed only from past probabilistic outcomes. These findings offer insight into how latent contextual information is used to optimize decision-making processes, and emphasize a key role of the hippocampus in hidden state inference.
Advancing Privacy-Aware Machine Learning on Sensitive Data via Edge-Based Continualµ-Training for Personalized Large Models
Authors: Huang Zhaojing , Yu Leping , Herbozo Contreras Luis Fernando , Eshraghian Kamran , Truong Nhan Duy , Nikpour Armin , Kavehei Omid
Published: May 2024

This paper introduces an innovative method for fine-tuning a larger multi-label model for abnormality detection, utilizing a smaller trainer and advanced knowledge distillation techniques. It delves into the effects of fine-tuning on various abnormalities, noting varied improvements based on the Original Model’s performance in specific tasks. The experimental setup, optimized for on-device inference and fine-tuning with limited computational resources, demonstrates moderate yet promising enhancements in model performance post-fine-tuning. Key insights from the study include the importance of aligning theµ-Trainer’s behavior with the Original Model and the influence of hyper-parameters like the batch size on fine-tuning outcomes. The research acknowledges limitations such as the limited exploration of loss functions in multi-label models and constraints in architectural design, suggesting potential avenues for future investigation. While the proposed Naive Continual Fine-tuning Process is in its early stages, it highlights the potential for long-term model personalization. Moreover, using weight transfer exclusively for fine-tuning amplifies user privacy protection through on-device fine-tuning, devoid of transferring data or gradients to the server. Despite modest performance improvements after fine-tuning, these layers represent a small fraction (0.7%) of the total weights in the Original Model and 1.6% in theµ-Trainer. This study establishes a foundational framework for advancing personalized model adaptation, on-device inference, and fine-tuning while emphasizing the importance of safeguarding data privacy in model development.
Predicting 30-Day In-Hospital Mortality in Surgical Patients: A Logistic Regression Model Using Comprehensive Perioperative Data
Authors: Hofmann Jonathan , Bouras Andrew , Patel Dhruv , Chetla Nitin , Balaji Nia , Boulis Michael
Published: May 2024

Background

Accurate prediction of postoperative outcomes, particularly 30-day in-hospital mortality, is crucial for improving surgical planning, patient counseling, and resource allocation. This study aimed to develop and validate a logistic regression model to predict 30-day in-hospital mortality using comprehensive perioperative data from the INSPIRE dataset.

Methods

We conducted a retrospective analysis of the INSPIRE dataset, comprising approximately 130,000 surgical cases from Seoul National University Hospital between 2011 and 2020. The primary objective was to develop a logistic regression model using preoperative and intraoperative variables. Key predictors included demographic information, clinical variables, laboratory values, and the emergency status of the operation. Missing data were addressed through multiple imputation, and feature selection was performed using univariate analysis and clinical judgment. The model was validated using cross-validation and assessed for performance using ROC AUC and precision-recall AUC metrics.

Results

The logistic regression model demonstrated high predictive accuracy, with an ROC AUC of 0.978 and a precision-recall AUC of 0.958. Significant predictors of 30-day in-hospital mortality included emergency status of the operation (OR: 1.56), preoperative prothrombin time (PT/INR) (OR: 1.53), potassium levels (OR: 1.49), body mass index (BMI) (OR: 1.37), serum sodium (OR: 1.11), creatinine levels (OR: 1.04), and albumin levels (OR: 0.85).

Conclusion

This study successfully developed and validated a logistic regression model to predict 30-day in-hospital mortality using comprehensive perioperative data. The model’s high predictive accuracy and reliance on routinely collected clinical and laboratory data enhance its feasibility for integration into existing clinical workflows, providing real-time risk assessments to healthcare providers. Future research should focus on external validation in diverse clinical settings and prospective studies to assess the practical impact of this predictive model.
Clade-defining mutations in human H1N1 hemagglutinin protein from 2021-2023 have opposing effects on in vitro fitness and antigenic drift
Authors: Swanson Nicholas J , Girish Jyothsna , Yunker Madeline , Liu Hisuan , Norton Julie , Han Christa , Mostafa Heba , Fenstermacher Katherine , Rothman Richard Eric , Pekosz Andrew
Published: May 2024

Seasonal influenza viruses frequently acquire mutations that have the potential to alter both virus replication and antigenic profile. Recent seasonal H1N1 viruses have acquired mutations to their hemagglutinin (HA) protein receptor binding site (RBS) and antigenic sites, and have branched into the clades 5a.2a and 5a.2a.1. Both clades demonstrated improved in vitro fitness compared with the parental 5a.2 clade as measured through plaque formation, infectious virus production in human nasal epithelial cells, and receptor binding diversity. Both clades also showed reduced neutralization by serum from healthcare workers vaccinated in the 2022-23 Northern Hemisphere influenza season compared to the vaccine strain. To investigate the phenotypic impact of individual clade-defining mutations, recombinant viruses containing single HA mutations were generated on a 5a.2 genetic background. The 5a.2a mutation Q189E improved plaque formation and virus replication, but was more efficiently neutralized by serum from individuals vaccinated in 2022-23. In contrast, the 5a.2a mutation E224A and both 5a.2a.1 mutations P137S and K142R impaired aspects of in vitro fitness but contributed significantly to antigenic drift. Surprisingly, the E224A mutation and not Q189E caused broader receptor binding diversity seen in clinical isolates of 5a.2a and 5a.2a.1, suggesting that receptor binding diversity alone may not be responsible for the phenotypic effects of the Q189E mutation. These data document an evolutionary trade-off between mutations that improve viral fitness and those that allow for the evasion of existing host immunity.
Leveraging regulatory monitoring data for quantitative microbial risk assessment ofLegionella pneumophilain cooling towers
Authors: Sylvestre Émile , Charron Dominique , Lefebvre Xavier , Bedard Emilie , Prévost Michèle
Published: May 2024

Cooling towers are critical engineered water systems for air conditioning and refrigeration but can create favorable conditions forLegionella pneumophilagrowth and aerosolization. Human exposure toL. pneumophila-contaminated aerosols can cause Legionnaire’s disease. Routine monitoring ofL. pneumophilain cooling towers offers possibilities to develop quantitative microbial risk assessment (QMRA) to guide system design, operation, control, and maintenance. Here, we used the regulatory monitoring database from Quebec, Canada, to develop statistical models for predictingL. pneumophilaconcentration variability in cooling towers and integrate these models into a screening-level QMRA to predict human health risks. Analysis of 105,463 monthlyL. pneumophilatest results revealed that the exceedance rate of the 104colony forming unit (CFU) per liter threshold was constant at 10% from 2016 to 2020, emphasizing the need to better validate the efficacy of corrective measures following the threshold exceedances. Among 2,852 cooling towers, 51.2% reported no detections, 38.5% had up to nine positives, and 10.2% over ten. The gamma or the lognormal distributions adequately described site-specific variations inL. pneumophilaconcentrations, but parametric uncertainty was very high for the lognormal distribution. We showed that rigorous model comparison is essential to predict peak concentrations accurately. Using QMRA, we found that, to meet a health-based target of 10-6DALY/pers.-year for clinical severity infections, an averageL. pneumophilaconcentration below 1.4 × 104CFU L-1should be maintained in cooling towers. We identified 137 cooling towers at risk of exceeding this limit, primarily due to the observation or prediction of rare peak concentrations above 105CFU L-1. Effective mitigation of those peaks is critical to controlling public health risks associated withL. pneumophila.
Deep-Learning Structure Elucidation from Single-Mutant Deep Mutational Scanning
Authors: Drake Zachary C. , Day Elijah , Toth Paul , Lindert Steffen
Published: May 2024

Deep learning has revolutionized the field of protein structure prediction. AlphaFold2, a deep neural network, vastly outperformed previous algorithms to provide near atomic-level accuracy when predicting protein structures. Despite its success, there still are limitations which prevent accurate predictions for numerous protein systems. Here we show that sparse residue burial restraints from deep mutational scanning (DMS) can refine AlphaFold2 to significantly enhance results. Burial information extracted from DMS is used to explicitly guide residue placement during structure generation. DMS-Fold was validated on both simulated and experimental single-mutant DMS, with DMS-Fold outperforming AlphaFold2 for 89% of protein targets and with 253 proteins having an improvement greater than 0.1 in TM-score. DMS-Fold is free and publicly available:https://github.com/LindertLab/DMS-Fold.
Cryo-EM structure of the bicarbonate receptor GPR30
Authors: Kaneda Shota , Jo-Watanabe Airi , Akasaka Hiroaki , Oshima Hidetaka S. , Yokomizo Takehiko , Shihoya Wataru , Nureki Osamu
Published: May 2024

G-protein-coupled receptor 30 (GPR30) is a bicarbonate receptor that plays a vital role in cellular responses to extracellular pH and ion homeostasis. Despite its significance, the mechanisms by which GPR30 interacts with bicarbonate ions remain elusive. There is no consensus on a drug that targets GPR30, and the difficulty in the pharmacological analysis has limited biological and drug discovery researches on GPR30. Here, we present the cryo-electron microscopy structure of human GPR30 in the presence of bicarbonate ions at 3.2 Å resolution. Our structure reveals unique extracellular pockets and critical residues for bicarbonate binding and activation. Functional assays demonstrate that mutations in these residues impair bicarbonate-induced GPR30 activation, underscoring their importance in receptor function. This study also provides insights into the G-protein coupling, highlighting the structural divergence between GPR30 and other GPCRs. Our findings not only advance the understanding of the role of GPR30 in pH homeostasis but also pave the way for the development of high-affinity drugs targeting GPR30 for therapeutic interventions in diseases associated with acid-base imbalance.
Hospital Characteristics Associated with Observed Transcatheter Aortic Valve Replacement Prices
Authors: Ochakovski Roni , Zhang Yuqi , Cerullo Marcelo
Published: May 2024

Transcatheter aortic valve replacement (TAVR) has emerged as a revolutionary treatment for aortic stenosis. However, TAVR prices vary considerably, and factors associated with this variation remain unclear. We aim to describe the variation in TAVR prices in relation to hospital financial performance among institutions ranked by the U.S. News and World Report (USNWR). Using a modified two-part model, we examined financial and operational characteristics (TAVR performance scores, median all-payer within-hospital TAVR price, net hospital profit margin, hospital markups [i.e., charge-to-cost ratio], bed days available, and CMS wage index) of 640 TAVR-performing hospitals ranked by the USNWR. After determining observed to expected (O:E) ratios for TAVR prices for each hospital, we then examined hospital characteristics across O:E quintiles. Overall, price disclosure was 48.6% (n=311). Between the lowest and highest O:E quintiles, median hospital markup (4.75 vs 5.33; p=0.41) and median net hospital margin (1.76 vs 3.15; p=0.12) were comparable. The highest O:E ratio quintile had lower median TAVR prices compared to the lowest O:E ratio quintile ($72,129.12 vs $49,022.03; p<0.001). Most significantly, TAVR price IQR’s within hospitals had a linear decline from the lowest to the highest O:E ratio quintiles ($119,043 vs $27,240; p<0.001). USNWR ranking scores had no significant variation across the quintiles (p=0.95). We concluded that hospitals that charge more than expected for TAVRs do not have higher profit margins nor markups and are not higher ranked by USNWR as those that charge less than expected. Additionally, with higher observed over expected TAVR prices, the variation in TAVR rates within hospitals decreased linearly. Finally, O:E TAVR price ratios appear to have no association with publicly reported hospital quality.
Impact of COVID-19 pandemic on rates of congenital heart disease procedures among children: Prospective cohort analyses of 26,270 procedures in 17,860 children using CVD-COVID-UK consortium record linkage data
Authors: Karthikeyan Suseeladevi Arun , Denholm Rachel , Babu-Narayan Sonya , Sinha Shubhra , Stoica Serban , Dong Tim , Angelini Gianni , Sudlow Cathie , Walker Venexia , Brown Katherine , Caputo Massimo , Lawlor Deborah A
Published: May 2024

Background

The COVID-19 pandemic necessitated major re-allocation of health care services. Our aim was to assess the impact on paediatric congenital heart disease procedures during different pandemic periods compared to the pre-pandemic period, to inform appropriate responses to future major health services disruptions.

Methods and Results

We analysed 26,270 procedures from 17,860 children between 01-Jan-2018 and 31-Mar-2022 in England, linking them to primary/secondary care data. The study period included pre-pandemic and pandemic phases, with latter including three restriction periods and corresponding relaxation periods. We compared procedure characteristics and outcomes between each pandemic periods and the pre-pandemic period. There was a reduction in all procedures across all pandemic period with the largest reductions during the first, most severe restriction period (23-Mar-2020 to 23-Jun-2020), and the relaxation period following second restrictions (03-Dec-2020 to 04-Jan-2021) coinciding with winter pressures. During the first restrictions, median procedures per week dropped by 51 compared with the pre-pandemic period(80 vs 131 per week, p = 4.98×10-08). Elective procedures drove these reductions, falling from 96 to 44 per week, (p = 1.89×10-06), while urgent (28 vs 27 per week, p = 0.649) and life-saving/emergency procedures (7 vs 6 per week, p = 0.198) remained unchanged. Cardiac surgery rates increased, and catheter-based procedure rates reduced during the pandemic. Procedures for children under 1-year were prioritized, especially during the first four pandemic periods. No evidence was found for differences in post procedure complications (age adjusted odds ratio 1.1 (95%CI: 0.9, 1.4) or post procedure mortality (age and case mix adjusted odds ratio 0.9 (0.6, 1.3)).

Conclusions

Prioritization of urgent, emergency and life-saving procedures during the pandemic, particularly in infants, did not impact paediatric CHD post procedure complications or mortality. This information is valuable for future major health services disruptions, though longer-term follow-up of the effects of delaying elective surgery is needed.
Exploring nonstandard
Hbb¯
interactions at future electron-proton colliders
Authors: Haghighat Gholamhossein , Jafari Reza , Khanpour Hamzeh , Mohammadi Najafabadi Mojtaba
Published: May 2024

In this paper, we use the charged-current Higgs boson production process at future electron-proton colliders, e−p→Hjνe, with the subsequent decay of the Higgs boson into a bb¯ pair, to probe the Standard Model effective field theory with dimension-six operators involving the Higgs boson and the bottom quark. The study is performed for two proposed future high-energy electron-proton colliders, the Large Hadron Electron Collider (LHeC) and the Future Circular Collider (FCC-he) at the center-of-mass energies of 1.3 TeV and 3.46 TeV, respectively. Constraints on the CP-even and CP-odd Hbb¯ couplings are derived by analyzing the simulated signal and background samples. A realistic detector simulation is performed and a multivariate technique using the gradient boosted decision trees algorithm is employed to discriminate the signal from background. Expected limits are obtained at 95% confidence level for the LHeC and FCC-he assuming the integrated luminosities of 1, 2 and

10

 

 

ab

−

1

. We find that using 1  ab−1 of data, the CP-even and CP-odd Hbb¯ couplings can be constrained with accuracies of the order of 10−3 and 10−2, respectively, and a significant region of the unprobed parameter space becomes accessible.

Published by the American Physical Society
2024
Probing the four-fermion operators via the transverse double spin asymmetry at the Electron-Ion Collider
Authors: Wang Hao-Lin , Wen Xin-Kai , Xing Hongxi , Yan Bin
Published: May 2024

The chirality-flipping operators of light fermions are currently poorly constrained by experimental analyses due to the lack of interference with standard model (SM) amplitudes in traditional observables. In this work, we propose to investigate the semileptonic scalar and tensor four-fermion operators of electron and quarks through the transverse double spin asymmetry (DSA) at Electron-Ion Collider, where both the electron and proton beams could be highly transversely polarized. Due to the chirality-flipping nature of these operators, we demonstrate that their interference with the SM results in an unsuppressed contribution to the DSA, and could lead to nontrivial azimuthal cos2ϕ and sin2ϕ distributions that are linearly dependent on their Wilson coefficients. This new method has the potential to significantly improve the current constraints on these scalar and tensor four-fermion operators without relying on theoretical assumptions about other types of new physics effects, particularly for the tensor-type operator of the u quark. Additionally, our findings indicate that both the real and imaginary parts of these operators can be simultaneously constrained and offer a new opportunity for probing potential CP-violation effects. However, it is important to note that these results would be sensitive to the quark transversity distributions, which are currently poorly constrained by the experimental data, but could be significantly improved at the upcoming Electron-Ion Collider. Therefore, our work opens up a new avenue to utilize this new spin asymmetry for exploring the new physics effects from the scalar/tensor four-fermion operators.

Published by the American Physical Society
2024
Importance of undergraduate institution prestige in physics faculty hiring networks
Authors: Grunspan Daniel Z. , Komperda Regis , Offerdahl Erika G. , Abraham Anna E. , Etebari Sara , Maas Samantha A. , Roberts Julie A. , Ghafoor Suhail , Brownell Sara E.
Published: May 2024

Reforming the professionalization experiences of future faculty members, including their undergraduate experience, provides a possible means to create scalable change in higher education. However, this requires an understanding of where faculty undergraduate training occurs. We analyze data from 7748 tenure-line faculty members across 611 U.S. physics departments, including their undergraduate alma mater and their employer university. The resulting undergraduate professionalization network reveals a prestige hierarchy similar in strength to those previously found in hiring networks at the Ph.D. level, indicating that the road to faculty jobs begins during undergraduate admissions. Furthermore, 42% of physics faculty members earned their undergraduate degrees from institutions outside of the United States. These results reinforce the importance of institutional prestige in academia and offer a potential strategy for driving systemic change.

Published by the American Physical Society
2024
Transverse-electric surface plasmon polaritons in periodically modulated graphene
Authors: Ahmad Zeeshan , Oh Sang Soon , Muljarov Egor A.
Published: May 2024

Transverse-electric (TE) surface plasmon polaritons are unique eigenmodes of a homogeneous graphene layer that are tunable with the chemical potential and temperature. However, as their dispersion curve spectrally lies below the light line, they cannot be resonantly excited by an externally incident wave. Here, we propose a way of exciting the TE modes and tuning their peaks in the transmission by introducing a one-dimensional graphene grating. Using the scattering-matrix formalism, we show that periodic modulation of graphene makes transmission more pronounced, potentially allowing for experimental observation of the TE modes. Furthermore, we propose the use of turbostratic graphene to enhance the role of the surface plasmon polaritons in optical spectra.

Published by the American Physical Society
2024
Colloid phase separation dynamics driven by chiral turbulent flows
Authors: Yuan Jiaxing , Tanaka Hajime
Published: May 2024

Hydrodynamic interactions significantly influence phase-ordering kinetics in complex fluids. While passive fluid phase separation is well studied, the impact of active components remains relatively unexplored. We examine pure- and quasi-two-dimensional mixtures of attractive colloids and self-rotating particles in a solvent. Varying rotor rotational speed and area fraction yield diverse dynamic patterns such as percolated networks and round droplets composed of passive colloids alone. At intermediate rotation speeds, inertial chiral flows, accompanied by the inverse energy cascade, lead to self-similar power-law coarsening with a growth exponent of 1/2. The flows spontaneously organize within fluid domains, exhibiting turbulent and chiral characteristics. Surprisingly, these turbulent flows can sustain hexatic order hydrodynamically stabilized by the Magnus force under certain conditions. Conversely, at higher speeds, nonlinear hydrodynamic interactions impede phase separation. Our findings illuminate the intriguing dynamic interplay between phase separation and chiral turbulence, effectively bridging the realms of phase ordering and turbulent physics.

Published by the American Physical Society
2024
Runaway transition in irreversible polymer condensation with cyclization
Authors: Panoukidou Maria , Weir Simon , Sorichetti Valerio , Fosado Yair Gutierrez , Lenz Martin , Michieletto Davide
Published: May 2024

The process of polymer condensation, i.e., the formation of bonds between reactive end groups, is ubiquitous in both industry and biology. Here we study generic systems undergoing polymer condensation in competition with cyclization. Using a generalized Smoluchowski theory, molecular dynamics simulations and experiments with DNA and ATP-consuming T4 ligase, we find that this system displays a transition, from a ring-dominated regime with finite-length chains at infinite time to a linear-polymers-dominated one with chains that keep growing in time. Finally, we show that fluids prepared close to the transition may have widely different compositions and rheology at large condensation times.

Published by the American Physical Society
2024
Superconductivity in atomically thin films: Two-dimensional critical state model
Authors: Gaggioli Filippo , Blatter Gianni , Novoselov Kostya S. , Geshkenbein Vadim B.
Published: May 2024

The comprehensive understanding of superconductivity is a multiscale task that involves several levels, starting from the electronic scale determining the microscopic mechanism, going to the phenomenological scale describing vortices and the continuum-elastic scale describing vortex matter, to the macroscopic scale relevant in technological applications. The prime example for such a macro-phenomenological description is the Bean model that is hugely successful in describing the magnetic and transport properties of bulk superconducting devices. Motivated by the development of novel devices based on superconductivity in atomically thin films, such as twisted-layer graphene, here, we present a simple macro-phenomenological description of the critical state in such two-dimensional (2D) thin films. While transverse screening and demagnetization can be neglected in these systems, thereby simplifying the task in comparison with usual film- and platelet-shaped samples, surface and bulk pinning are important elements to be included. We use our 2D critical state model to describe the transport and magnetic properties of 2D thin-film devices, including the phenomenon of nonreciprocal transport in devices with asymmetric boundaries and the superconducting diode effect.

Published by the American Physical Society
2024
Continuous optimization by quantum adaptive distribution search
Authors: Morimoto Kohei , Takase Yusuke , Mitarai Kosuke , Fujii Keisuke
Published: May 2024

We introduce the quantum adaptive distribution search (QuADS), a quantum continuous optimization algorithm that integrates Grover adaptive search (GAS) with the covariance matrix adaptation evolution strategy (CMA-ES), a classical technique for continuous optimization. QuADS utilizes the quantum-based search capabilities of GAS and enhances them with the principles of CMA-ES for more efficient optimization. It employs a multivariate normal distribution for the initial state of the quantum search and repeatedly updates it throughout the optimization process. Our numerical simulations show that QuADS outperforms both GAS and CMA-ES. This is achieved through adaptive refinement of the initial state distribution rather than consistently using a uniform state, resulting in fewer oracle calls. This study presents an important step toward exploiting the potential of quantum computing for continuous optimization.

Published by the American Physical Society
2024
Magneto-induced topological phase transition in inverted InAs/GaSb bilayers
Authors: Han Zhongdong , Li Tingxin , Zhang Long , Du Rui-Rui
Published: May 2024

We report a magneto-induced topological phase transition in inverted InAs/GaSb bilayers from a quantum spin Hall insulator to a normal insulator. We utilize a dual-gated Corbino device in which the degree of band inversion, or equivalently the electron and hole densities, can be continuously tuned. We observe a topological phase transition around the magnetic field where a band crossing occurs, accompanied by a bulk-gap closure characterized by a bulk conductance peak (BCP). In another set of experiments, we study the transition under a tilted magnetic field (tilt angle ). We observe the characteristic magnetoconductance around BCP as a function of , which dramatically depends on the density of the bilayers. In a relatively deep inversion (hence a higher density) regime, where the electron-hole hybridization dominates the excitonic interaction, the BCP grows with . On the contrary, in a shallowly inverted (a lower density) regime, where the excitonic interaction dominates the hybridization, the BCP is suppressed indicating a smooth crossover without a gap closure. This suggests the existence of a low-density, correlated insulator with spontaneous symmetry breaking near the critical point. Our highly controllable electron-hole system offers an ideal platform to study interacting topological states as proposed by recent theories.

Published by the American Physical Society
2024
Efficiency of neural-network state representations of one-dimensional quantum spin systems
Authors: Pan Ruizhi , Clark Charles W.
Published: May 2024

Neural-network state representations of quantum many-body systems are attracting great attention and more rigorous quantitative analysis of their expressibility and complexity is warranted. Our analysis of the restricted Boltzmann machine (RBM) state representation of one-dimensional (1D) quantum spin systems provides new insight into their computational complexity. We define a class of long-range-fast-decay (LRFD) RBM states with quantifiable upper bounds on truncation errors and provide numerical evidence for a large class of 1D quantum systems that may be approximated by LRFD RBMs of at most polynomial complexities. These results lead us to conjecture that the ground states of a wide range of quantum systems may be exactly represented by LRFD RBMs or a variant of them, even in cases where other state representations become less efficient. At last, we provide the relations between multiple typical state manifolds. Our work proposes a paradigm for doing complexity analysis for generic long-range RBMs which naturally yields a further classification of this manifold. This paradigm and our characterization of their nonlocal structures may pave the way for understanding the natural measure of complexity for quantum many-body states described by RBMs and are generalizable for higher-dimensional systems and deep neural-network quantum states.

Published by the American Physical Society
2024
Framework of managerial wisdom: an analysis using the TOPSIS and MICMAC process
Authors: Valiyan Hasan , Abdoli Mohammadreza , Ashrafi Mehdi , Barati Hadi
Published: May 2024

Purpose

Behavioral characteristics and the existence of personal knowledge and skills that are essential in forming a capable manager with specialized insight, is one of the most important evaluation processes in appointing a manager. Wisdom as a trait of a set of personal characteristics and cognitive knowledge of a capable manager will gain competitive advantages for the company and external stakeholders. The purpose of this study is to present the framework of managerial financial wisdom through qualitative and quantitative research methodologies.

Design/methodology/approach

The study uses grounded theory methodology to identify factors for managerial financial wisdom and uses a MICMAC process to evaluate the power of driving and dependence among factors. MaxQDA software was used for data coding and analysis. The MICMAC process by determining the location of each of the sub-themes in the four-dimensional matrix, seeks to determine the most effective criterion in the context of the study. The method of data collection is mixed and in terms of philosophical nature, this study is inductive/comparative.

Findings

The results of the research in the qualitative part indicate the presentation of a framework based on two categories, four components, and thirty themes. The results of the quantitative part of the study also showed that the most important factor of managerial financial wisdom is market-oriented values. Finally, it was found that the social trust caused by managerial financial wisdom is considered a factor in gaining more shares in the capital market due to the positive stimulus in this dimension.

Originality/value

The study is relevant for both practitioners and academia and has significant implications. For practitioners, the structural linkages identified will help enhance managerial wisdom effectiveness and drive the critical metrics for financial decisions and shareholders' rights protection. The study may help financial market practitioners better understand future policies. Academia and researchers can take reference from methodologies used in this study for exploring factors of interest and developing matrix linkages among them.
Competency development opportunities and organizational citizenship behaviors: the mediating role of subjective career success
Authors: Teow Hui Hui , Au Wee Chan , Ahmed Pervaiz
Published: May 2024

Purpose

Building upon Social Exchange Theory, this study explores the relationship between perceived opportunities for competency development (POCD), subjective career success (SCS), and organizational citizenship behaviors (OCBs). Given the importance of SCS in providing mutual benefits for both the employee and the organization, this study examines how SCS plays a mediating role in the relationship between POCD and OCBs.

Design/methodology/approach

Data was collected from 353 full-time working professionals in Malaysian organizations through a two-wave hardcopy questionnaire survey. The data was then analyzed using structural equation modeling and the bootstrapping method.

Findings

The study found no significant direct relationship between POCD and OCBs. However, the bootstrapping analysis uncovered that SCS mediated this relationship, indicating a significant full mediation effect.

Research limitations/implications

To increase the external validity of findings, future studies should include samples from various industries in both the public and private sectors.

Originality/value

In contrast to the findings from previous studies, this study adds value to the career literature by demonstrating that without a sense of SCS, even with competency development opportunities, employees are less likely to engage in OCBs. It highlights the importance of SCS in fostering mutual benefits for both the employee and the organization.
Big data, machine learning and uncertainty in foresight studies
Authors: Muraro Vinicius , Salles-Filho Sergio
Published: May 2024

Purpose

Currently, foresight studies have been adapted to incorporate new techniques based on big data and machine learning (BDML), which has led to new approaches and conceptual changes regarding uncertainty and how to prospect future. The purpose of this study is to explore the effects of BDML on foresight practice and on conceptual changes in uncertainty.

Design/methodology/approach

The methodology is twofold: a bibliometric analysis of BDML-supported foresight studies collected from Scopus up to 2021 and a survey analysis with 479 foresight experts to gather opinions and expectations from academics and practitioners related to BDML in foresight studies. These approaches provide a comprehensive understanding of the current landscape and future paths of BDML-supported foresight research, using quantitative analysis of literature and qualitative input from experts in the field, and discuss potential theoretical changes related to uncertainty.

Findings

It is still incipient but increasing the number of prospective studies that use BDML techniques, which are often integrated into traditional foresight methodologies. Although it is expected that BDML will boost data analysis, there are concerns regarding possible biased results. Data literacy will be required from the foresight team to leverage the potential and mitigate risks. The article also discusses the extent to which BDML is expected to affect uncertainty, both theoretically and in foresight practice.

Originality/value

This study contributes to the conceptual debate on decision-making under uncertainty and raises public understanding on the opportunities and challenges of using BDML for foresight and decision-making.
Analysing impact of corporate attributes on sustainability disclosures through India’s new BRSR framework
Authors: Kajal Abhishek , Bansal Siddharth
Published: May 2024

Purpose

The purpose of this study is to analyse the impact of corporate attributes like a company’s profitability, size, age, leverage and board size on companies’ sustainability reporting as measured through India’s new business responsibility and sustainability reporting (BRSR) framework.

Design/methodology/approach

A random sample of 130 companies was taken from the top 1,000 listed companies on the National Stock Exchange. Sequential mixed methods research approach was used to prepare a sustainability quality index. Then, a hierarchical multiple regression analysis was performed to examine the impact on the quality of reporting by Indian companies.

Findings

Interestingly, the analysis revealed that traditional metrics like age, profitability, board size and leverage did not have significant associations with reporting quality. Rather, the size of a company in terms of market capitalisation was found to have a strong positive impact on sustainability reporting.

Research limitations/implications

This was a cross-sectional study, as time series data for BRSR reporting is not yet available. Also, only five parameters were taken for analysis. Lastly, subjective judgment in content analysis may be involved.

Practical implications

This suggests that only larger companies in India are prioritising sustainability reporting over smaller ones. It affirms the legitimacy and stakeholder theory in the Indian context.

Originality/value

To the best of the authors’ knowledge, this study is one of the first endeavours to assess the efficacy of the new Indian BRSR framework and test its primary objectives. Furthermore, significant implications have been given for managers to catalyse and reinforce the sustainability momentum down the lane across companies of all sizes in India.
Determinants and indicators for destination competitiveness: the case of Shiraz city, Iran
Authors: Amini Alireza , Khodadadi Masood , Nikbakht Amin , Nemati Fatemeh
Published: May 2024

Purpose

Nowadays, the tourism industry is considered the largest and most diverse industry in the world, which can play a significant role in the economic growth and development of a country as the main source of income and employment. In this regard, the purpose of this study is to focus on evaluating the competitiveness indicators of Shiraz city tourism destination based on a combined model.

Design/methodology/approach

For this purpose, a questionnaire with 78 questions was used to evaluate the indicators, in which a total of 1,432 tourists participated, including 927 domestic tourists and 505 international tourists. The collected data were analyzed to determine the hierarchical relationship between the indicators using equation structural modeling.

Findings

The research findings indicate that the most effective and influential indicators in the field of tourism competitiveness are natural and handmade resources, and the most influential factors are demand conditions and cultural and natural resources. In this hierarchy, each factor affects its previous level and influences the next level.

Originality/value

This study offers significant potential for uncovering credible and robust approaches to further investigate the contextualization of tourism competitiveness on both national and international scales, thereby generating valuable new insights. By conceptualizing the diverse dimensions of tourism competitiveness and delving into the variations in its impacts across multiple levels, this research not only challenges existing notions but also aids destinations in maintaining and enhancing their market position and share over time. This study offers valuable insights and practical implications for both researchers and practitioners in the field of urban tourism. It enhances the understanding of destination competitiveness, informs policy decisions, facilitates benchmarking and best practices, guides strategic decision-making and promotes sustainable tourism development.
Enforced work-from-home and its impact on psychological conditions: a qualitative investigation in India
Authors: Bhattcharjee Amitabh , Chakraborty Shreyashi , Elembilassery Varun
Published: May 2024

Purpose

Enforced work-from-home (EWFH) was the norm during the COVID-19 pandemic and continues to be implemented by many organizations owing to its long-term financial benefits. This study aims to understand the consequences of EWFH on the three psychological conditions of employee engagement: psychological safety, psychological availability and psychological meaningfulness.

Design/methodology/approach

Semi-structured interviews were conducted with 21 employees from different Indian companies. Thematic analysis was adopted to understand the consequences of EWFH on employee psychological safety, availability and meaningfulness.

Findings

The findings demonstrated that psychological meaningfulness, availability and safety were adversely impacted owing to limited choice and autonomy in EWFH.

Research limitations/implications

This study contributes to the literature by examining the concept of EWFH in relation to psychological conditions, which is novel and relevant. Also, the job demands and resources framework and the COR theory are used together to explain the findings, which strengthens the concept of EWFH.

Practical implications

Organizations should consider various aspects of EWFH and make decisions to improve employees’ engagement at work.

Originality/value

This study focuses on an unexplored area and facilitates a better understanding of the concept of EWFH and its impact on employees’ psychological conditions. This study is valuable for both management professionals and organizations considering the continuation of EWFH after the pandemic. It also offers new avenues for future research.
Mapping the barrier and strategic solutions of halal supply chain implementation in small and medium enterprises
Authors: Ardiantono Dewie Saktia , Ardyansyah Gde Dharma , Sugihartanto Mushonnifun Faiz , Al Mustofa Muhammad Ubaidillah , Lisdiantini Netty
Published: May 2024

Purpose

This study aims to identify the challenges, promote respective solutions and construct strategies for the implementation of the halal supply chain in Indonesia’s small and medium-sized enterprises (SMEs).

Design/methodology/approach

This research used the analytic network process in nine respondents categorised into three groups of relevant stakeholders: government, academia and industry.

Findings

Seven essential criteria for the implementation of a halal supply chain in SMEs were identified, namely, the process, packaging, storage, transportation, fundamental aspects, supporting policy and technology. Notably, the high cost of adopting blockchain technology was the most crucial issue, particularly in SMEs.

Practical implications

Through the findings, several critical factors to consider in the implementation of halal supply chains for SMEs were identified. The investment in halal supply chain technology, which incurs a high cost carried by entrepreneurs, is a burden for SMEs. For this reason, further studies are required to formulate and develop cost-effective halal supply chain technology for SMEs.

Originality/value

To the best of the authors’ knowledge, this research is the first attempt of comprehensively mapping the barriers and developing strategic solutions to implement the halal supply chain by Indonesia’s SMEs.
Busting the blackbox between managerial coaching behaviors and employee outcomes from a perspective of discrete emotional process mechanism
Authors: Liu Wei , Zhang Bobo , Sun Rui , Li Shuwen
Published: May 2024

Purpose

As coaching assumes an increasingly critical role in satisfying employees' demands for growth, the function of coaching has progressively shifted towards direct supervisors. This study seeks to investigate the distinct effects of managerial coaching behaviors on employee outcomes from an emotional perspective. Specifically, we aim to explore whether leaders' encourage-to-explore and guide-to-learn behaviors impact employees' creativity and performance through discrete emotional mechanisms upon appraisal theory of emotion.

Design/methodology/approach

We conducted two studies to test our proposition. In study 1, an experiment using coaching scenarios was performed with 128 students majoring in management. In study 2, data were collected from 311 supervisor-subordinate dyads.

Findings

The results indicate that encourage-to-explore behaviors are positively related to employee creativity by fostering feelings of inspiration, and guide-to-learn behaviors are positively related to employee performance by alleviating anxiety. These findings suggest that different leaders’ coaching behaviors influence employee outcomes through different emotional processes. The theoretical and practical implications of the findings are also discussed.

Originality/value

These findings suggest that different leaders’ coaching behaviors influence employee outcomes through different emotional processes. The theoretical and practical implications of the findings are also discussed.