bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying and Characterizing Bias at Scale in Clinical Notes Using Large Language Models
Authors: Apakama Donald U. , Nguyen Kim-Anh-Nhi , Hyppolite Daphnee , Soffer Shelly , Mudrik Aya , Ling Emilia , Moses Akini , Temnycky Ivanka , Glasser Allison , Anderson Rebecca , Parchure Prathamesh , Woullard Evajoyce , Edalati Masoud , Chan Lili , Kronk Clair , Freeman Robert , Kia Arash , Timsina Prem , Levin Matthew A. , Khera Rohan , Kovatch Patricia , Charney Alexander W. , Carr Brendan G. , Richardson Lynne D. , Horowitz Carol R. , Klang Eyal , Nadkarni Girish N.
Published: October 2024

Importance

Discriminatory language in clinical documentation impacts patient care and reinforces systemic biases. Scalable tools to detect and mitigate this are needed.

Objective

Determine utility of a frontier large language model (GPT-4) in identifying and categorizing biased language and evaluate its suggestions for debiasing.

Design

Cross-sectional study analyzing emergency department (ED) notes from the Mount Sinai Health System (MSHS) and discharge notes from MIMIC-IV.

Setting

MSHS, a large urban healthcare system, and MIMIC-IV, a public dataset.

Participants

We randomly selected 50,000 ED medical and nursing notes from 230,967 MSHS 2023 adult ED visiting patients, and 500 randomly selected discharge notes from 145,915 patients in MIMIC-IV database. One note was selected for each unique patient.

Main Outcomes and Measures

Primary measure was accuracy of detection and categorization (discrediting, stigmatizing/labeling, judgmental, and stereotyping) of bias compared to human review. Secondary measures were proportion of patients with any bias, differences in the prevalence of bias across demographic and socioeconomic subgroups, and provider ratings of effectiveness of GPT-4’s debiasing language.

Results

Bias was detected in 6.5% of MSHS and 7.4% of MIMIC-IV notes. Compared to manual review, GPT-4 had sensitivity of 95%, specificity of 86%, positive predictive value of 84% and negative predictive value of 96% for bias detection. Stigmatizing/labeling (3.4%), judgmental (3.2%), and discrediting (4.0%) biases were most prevalent. There was higher bias in Black patients (8.3%), transgender individuals (15.7% for trans-female, 16.7% for trans-male), and undomiciled individuals (27%). Patients with non-commercial insurance, particularly Medicaid, also had higher bias (8.9%). Higher bias was also seen in health-related characteristics like frequent healthcare utilization (21% for >100 visits) and substance use disorders (32.2%). Physician-authored notes showed higher bias than nursing notes (9.4% vs. 4.2%, p < 0.001). GPT-4’s suggested revisions were rated highly effective by physicians, with an average improvement score of 9.6/10 in reducing bias.

Conclusions and Relevance

A frontier LLM effectively identified biased language, without further training, showing utility as a scalable fairness tool. High bias prevalence linked to certain patient characteristics underscores the need for targeted interventions. Integrating AI to facilitate unbiased documentation could significantly impact clinical practice and health outcomes.
The structural diversity of telomeres and centromeres across mouse subspecies revealed by complete assemblies
Authors: Francis Bailey , Gozashti Landen , Costello Kevin , Kasahara Takaoki , Harringmeyer Olivia S. , Lilue Jingtao , Helmy Mohab , Kato Tadafumi , Czechanski Anne , Quail Michael , Bonner Iraad , Dawson Emma , Smith Anne Ferguson , Reinholdt Laura , Adams David J. , Keane Thomas M.
Published: October 2024

It is over twenty years since the publication of the C57BL/6J mouse reference genome, which has been a key catalyst for understanding mammalian disease biology. However, the mouse reference genome still lacks telomeres and centromeres, contains 281 chromosomal sequence gaps, and only partially represents many biomedically relevant loci. We present the first T2T mouse genomes for two key inbred strains, C57BL/6J and CAST/EiJ. These T2T genomes reveal significant variability in telomere and centromere sizes and structural organisation. We add an additional 213 Mbp of novel sequence to the reference genome containing 517 protein-coding genes. We examined two important but incomplete loci in the mouse genome - the pseudoautosomal region (PAR) on the sex chromosomes and KRAB zinc finger proteins (KZFPs) loci. We identified distant locations of the PAR boundary, different copy number and sizes of segmental duplications, and a multitude of amino acid substitution mutations in PAR genes.
Dendritome Mapping Unveils Spatial Organization of Striatal D1/D2-Neuron Morphology
Authors: Park Chang Sin , Yan Ming , Zhu Muye , Akram Masood A. , Foster Nicholas N. , Bennecke Andrew , Choi Christopher , Marrett Karl , Moradi Keivan , Zhang Jason Y. , Magat Gabrielle , Nanda Sumit , Vaca Raymond , Wijaya Kathleen , Zablan Jedrick Regala , Lee Sebastian , Song Cassidy , Lara Mary Jasmine , Louie Madeline , Cong Jason , Kim Yongsoo , Ascoli Giorgio A. , Langfelder Peter , Tward Daniel , Dong Hong-Wei , Yang X. William
Published: October 2024

Morphology is a cardinal feature of a neuron that mediates its functions, but profiling neuronal morphologies at scale remains a formidable challenge. Here we describe a generalizable pipeline for large-scale brainwide study of dendritic morphology of genetically-defined single neurons in the mouse brain. We generated a dataset of 3,762 3D-reconstructed and reference-atlas mapped striatal D1- and D2- medium spiny neurons (MSNs). Integrative morphometric analyses reveal distinct impacts of anatomical locations and D1/D2 genetic types on MSN morphologies. To analyze striatal regional features of MSN dendrites without prior anatomical constraints, we assigned MSNs to a lattice of cubic boxes in the reference brain atlas, and summarized morphometric representation ("eigen-morph") for each box and clustered boxes with shared morphometry. This analysis reveals 6 modules with characteristic dendritic features and spanning contiguous striatal territories, each receiving distinct corticostriatal inputs. Finally, we found aging confers robust dendritic length and branching defects in MSNs, while Huntington's disease (HD) mice exhibit selective length-related defects. Together, our study demonstrates a systems-biology approach to profile dendritic morphology of genetically-defined single-neurons; and defines novel striatal D1/D2-MSN morphological territories and aging- or HD-associated pathologies.
Aromatase-independent estrogenesis: Wood-Ljungdahl pathway likely contributed to the emergence of estrogens in the biosphere
Authors: Wang Po-Hsiang , Wu Tien-Yu , Chen Yi-Lung , Gicana Ronnie G. , Lee Tzong-Huei , Chen Mei-Jou , Hsiao Tsun-Hsien , Jade Lu Mei-Yeh , Lai Yi-Li , Wang Tzi-Yuan , Li Jeng-Yi , Chiang Yin-Ru
Published: October 2024

Androgen and estrogen, key sex hormones, were long thought to be exclusively produced by vertebrates. The O2-dependent aromatase that converts androgen to estrogen (estrogenesis) has never been identified in any prokaryotes. Here, we report the discovery of anaerobic estrogenesis in a Peptococcaceae bacterium (strain TUW77) isolated from the gut of the great blue-spotted mudskipper (Boleophthalmus pectinirostris). This strain exhibits unprecedented testosterone fermentation pathways, transforming testosterone into estrogens and androstanediol under anaerobic conditions. Physiological experiments revealed that strain TUW77 grows exclusively on testosterone, utilizing the androgenic C-19 methyl group as both the carbon source and electron donor. The genomic analysis identified three copies of a polycistronic gene cluster,abeABC(anaerobicbacterialestrogenesis), encoding components of a classic cobalamin-dependent methyltransferase system. These genes, highly expressed under testosterone-fed conditions, show up to 57% protein identity to the characterized EmtAB from denitrifyingDenitratisomaspp., known for methylating estrogen into androgen (the reverse reaction). Tiered transcriptomic and proteomic analyses suggest that the removed C-19 methyl group is completely oxidized to CO2viathe oxidative Wood-Ljungdahl pathway, while the reducing equivalents (NADH) fully reduce remaining testosterone to androstanediol. Consistently, the addition of anthraquinone-2,6-disulfonate, an extracellular electron acceptor, to testosterone-fed TUW77 cultures enabled complete testosterone conversion into estrogen without androstanediol accumulation (anaerobic testosterone oxidation). This discovery of aromatase-independent estrogenesis in anaerobic bacteria suggests that the ancient Wood-Ljungdahl pathway may have contributed to the emergence of estrogens in the early biosphere.

Significance

Using a testosterone-grown anaerobic bacterium as a model organism, we characterized this unusual anaerobic estrogenesis at the molecular level. Our findings challenge the long-held belief that estrogen production is exclusive to aromatase-containing vertebrates, expanding our understanding of steroid hormone biosynthesis across domains of life. The involvement of ancient strictly anaerobic Peptococcaceae members and the Wood-Ljungdahl pathway suggests that bacterial estrogenesis may predate O2-dependent estrogenesis in vertebrates. Furthermore, the identification of estrogen-producing bacteria in animal guts opens new avenues for potential microbiome-based hypoestrogenism therapies to supplement estrogen in menopausal or ovariectomized females, offering an innovative alternative to current hormone replacement strategies.
Deterministic colonization arises early during the transition of soil bacteria to the phyllosphere and is shaped by plant-microbe interactions
Authors: Mayer Teresa , Teutloff Erik , Unger Kerstin , Lehenberger Pamela , Agler Matthew T.
Published: October 2024

Background

Upon seed germination, soil bacteria are activated to transition to the plant and eventually colonize mature tissues like leaves. These bacteria are poised to significantly influence plant health, but we know little about their colonization routes. We studied the mechanisms of the transition of soil bacteria to germinating plants and leaves by experimentally manipulating inoculation times and usingin-plantaisolation to understand bacteria that can make the complex soil-to-leaf transition. Using a trackable, labeledPseudomonas viridiflava(Pv3D9) amended to soil, we tested how plant-microbe-microbe interactions shape assembly mechanisms in natural soil communites.

Results

We found that the stages of the transition of bacteria from soil to leaves before true leaf emergence were important in establishing uniquely diverse leaf bacteriomes. A wide diversity of leaf-associated taxa can individually make this transition, but most are still shaped by stochastic processes. Interestingly, deterministic processes drove some important taxa only when they transitioned from soil to leaves, but not when they were inoculated later. The opportunistic pathogenPv3D9 promoted plant growth in a natural soil, likely by activating plant immunity. These effects in turn strongly affected the soil-to-leaf transition of almost strictly taxa that colonized deterministically, demonstrating the important role of plant-microbe-microbe interactions in controlling deterministic processes.

Conclusions

Diverse, well-adapted bacterial taxa make the soil-to-leaf transition during natural colonization resulting in characteristic diversity in healthy leaf microbiomes. The domination of stochastic mechanisms during this colonization indicates that many taxa must strongly compete to establish their niche. During this complex transition, however, specific important taxa emerge that are driven by deterministic processes, suggesting they occupy unique niches. The malleability of these processes suggests that they may be controlled, for example by targeted soil manipulations. This finding is significant given the important roles of these bacteria in plant health and offers directions forward for engineering beneficial plant microbiomes.
Synaptic input architecture of visual cortical neurons revealed by large-scale synapse imaging without backpropagating action potentials
Authors: Kondo Satoru , Kikuta Kohei , Ohki Kenichi
Published: October 2024

How neurons integrate thousands of synaptic inputs to compute sharply tuned outputs is a critical question in sensory information processing. To answer this question, it is essential to record the location and activity of synaptic inputsin vivo. However, back-propagating action potential (BAP) calcium signals invade dendrites and spines, making accurate recording of spine responses difficult. In this study, we first developed a new method to record spine calcium responses without BAP signals. Using this method, we performed large-scale imaging of visually evoked spine activity from layer 2/3 pyramidal neurons and revealed three patterns of dendritic functional architectures of synaptic inputs: dendrites with clusters of spines of similar responses, dendrites with spines of diverse responses, and dendrites with spines where the majority of them show no visual response. Our model suggests that only a small fraction of spines on dendrites of clustered architectures are sufficient to generate sharply tuned output.
TFAM as a sensor of UVC-induced mitochondrial DNA damage
Authors: King Dillon E. , Beard Emily E. , Satusky Matthew J. , Ryde Ian , George Alex , Johnson Caitlin , Dolan Emma L. , Zhang Yuning , Zhu Wei , Wilkins Hunter , Corden Evan , Murphy Susan K. , Erie Dorothy , Gordân Raluca , Meyer Joel N.
Published: October 2024

Mitochondria lack nucleotide excision DNA repair; however, mitochondrial DNA (mtDNA) is resistant to mutation accumulation following DNA damage. These observations suggest additional damage sensing or protection mechanisms. Transcription Factor A, Mitochondrial (TFAM) compacts mtDNA into nucleoids. As such, TFAM has emerged as a candidate for protecting DNA or sensing damage. To examine these possibilities, we used live-cell imaging, cell-based assays, atomic force microscopy, and high-throughput protein-DNA binding assays to characterize the binding properties of TFAM to UVC-irradiated DNA and cellular consequences of UVC irradiation. Our data indicate an increase in mtDNA degradation and turnover, without a loss in mitochondrial membrane potential that might trigger mitophagy. We identified a reduction in sequence specificity of TFAM associated with UVC irradiation and a redistribution of TFAM binding throughout the mitochondrial genome. Our AFM data show increased compaction of DNA by TFAM in the presence of damage. Despite the TFAM-mediated compaction of mtDNA, we do not observe any protective effect on DNA damage accumulation in cells orin vitro. Taken together, these studies indicate that UVC-induced DNA damage promotes compaction by TFAM, suggesting that TFAM may act as a damage sensor, sequestering damaged genomes to prevent mutagenesis by direct removal or suppression of replication.

Graphical Abstract
A universal hippocampal memory code across animals and environments
Authors: Wirtshafter Hannah S , Solla Sara A , Disterhoft John F
Published: October 2024

How learning is affected by context is a fundamental question of neuroscience, as the ability to generalize learning to different contexts is necessary for navigating the world. An example of swift contextual generalization is observed in conditioning tasks, where performance is quickly generalized from one context to another. A key question in identifying the neural substrate underlying this ability is how the hippocampus (HPC) represents task-related stimuli across different environments, given that HPC cells exhibit place-specific activity that changes across contexts (remapping). In this study, we used calcium imaging to monitor hippocampal neuron activity as rats performed a conditioning task across multiple spatial contexts. We investigated whether hippocampal cells, which encode both spatial locations (place cells) and task-related information, could maintain their task representation even when their spatial encoding remapped in a new spatial context. To assess the consistency of task representations, we used advanced dimensionality reduction techniques combined with machine learning to develop manifold representations of population level HPC activity. The results showed that task-related neural representations remained stable even as place cell representations of spatial context changed, thus demonstrating similar embedding geometries of neural representations of the task across different spatial contexts. Notably, these patterns were not only consistent within the same animal across different contexts but also significantly similar across different animals, suggesting a standardized neural encoding or ‘neural syntax’ in the hippocampus. These findings bridge a critical gap between memory and navigation research, revealing how the hippocampus maintains cognitive consistency across different spatial environments. These findings also suggest that hippocampal function is governed by a neural framework shared between animals, an observation that may have broad implications for understanding memory, learning, and related cognitive processes. Looking ahead, this work opens new avenues for exploring the fundamental principles underlying hippocampal encoding strategies.
Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population: A machine learning approach
Authors: Chen Chen , Khanthiyong Bupachad , Thaweetee-Sukjai Benjamard , Charoenlappanit Sawanya , Roytrakul Sittiruk , Surit Phrutthinun , Phoungpetchara Ittipon , Thanoi Samur , Reynolds Gavin P , Nudmamud-Thanoi Sutisa
Published: October 2024

Cognitive function is the term for the higher-order mental processes in the brain that gather and process information, and it mirrors brain activity. Cognitive function in adults exhibits variability as a result of genetic and environmental components such as gender, age[1], and lifestyle factors to name a few. Interindividual variability in cognitive trajectories has been observed in community-dwelling older adults across different cognitive domains. Inter-individual variations in cognitive response to identical physical exercise are also evident. This study aimed to explore the association between serum protein expression profiles and one measure of cognitive variability, as measured by the Wisconsin Card Sorting Test (WCST), in a healthy Thai population using a machine learning approach. This study included 199 healthy Thai subjects, ranging in age from 20 to 70 years. Cognitive performance was measured by the WCST, and the WCST % Errors was used to define the lower and higher cognitive ability groups. Serum protein expression profiles were studied by the label-free proteomics method. The Linear Model for Microarray Data (LIMMA) approach in R was utilized to assess differentially expressed proteins (DEPs) between groups; subsequently bioinformatic analysis was performed for the functional enrichment and interaction network analysis of DEPs. A random forest model was built to classify subjects from the lower and higher cognitive ability groups. Cross-validation was used for model performance evaluation. The results showed that, there were 213 DEPs identified between the poor and higher cognition groups, with 155 DEPs being upregulated in the poor cognition group. Those DEPs were significantly enriched in the IL-17 signaling pathway. Furthermore, the analysis of protein-protein interaction (PPI) network revealed that most of the selected DEPs were linked to neuroinflammation-related cognitive impairment. The random forest model achieved a test classification accuracy of 81.5%. The model’s sensitivity (true positive rate) was estimated to be 65%, and the specificity (true negative rate) was 85.9%. The AUC (0.79) indicates good binary classification performance. The results suggested that a measure of poor WCST performance in healthy Thai subjects might be attributed to higher levels of neuroinflammation.
Molecular and cellular dynamics of squamous cell carcinomas across tissues
Authors: Kudelka Matthew R. , Lavin Yonit , Sun Siman , Fuchs Elaine
Published: October 2024

Squamous cell carcinomas (SCCs), arising from the skin, head and neck, lungs, esophagus, and cervix, are collectively among the most common cancers and a frequent cause of cancer morbidity and mortality. Despite distinct stratified epithelial tissues of origin, converging evidence points toward shared biologic pathways across SCCs. With recent breakthroughs in molecular technologies have come novel SCC treatment paradigms, including immunotherapies and targeted therapy. This review compares commonalities and differences across SCCs from different anatomical sites, including risk factors and genetics, as well as cellular and molecular programs driving tumorigenesis. We review landmark discoveries of the “cancer stem cells” (CSCs) that initiate and propagate SCCs and their gene and translational regulation programs. This has led to an appreciation that interactions between CSCs and the immune system play key roles in invasion and therapeutic resistance. Here, we review the unifying principles of SCCs that have emerged from these exciting advances in our understanding of these epithelial cancers.
Universal limit on spatial quantum superpositions with massive objects due to phonons
Authors: Henkel Carsten , Folman Ron
Published: October 2024

It has been a long-standing goal to bring massive objects into a superposition of different locations in real space, not only to confirm quantum theory in new regimes, but also to explore the interface with gravity. The main challenge is usually thought to arise from forces or scattering due to environmental fields and particles that decohere the large object's wave function into a statistical mixture. We unveil a decoherence channel which cannot be eliminated by improved isolation from the environment. It originates from sound waves within the object, which are excited as part of any splitting process and carry partial information. This puts stringent constraints on future spatial superpositions of large objects.

Published by the American Physical Society
2024
Quantum dot based Kitaev chains: Majorana quality measures and scaling with increasing chain length
Authors: Svensson Viktor , Leijnse Martin
Published: October 2024

Realizing Majorana bound states (MBSs) in short, well-controllable chains of coupled quantum dots sidesteps the problem of disorder but requires finetuning and does not give the true topological protection inherent to long chains. Here, we introduce a quality measure that is also applicable in the presence of strong electron-electron interactions and that quantifies the closeness to topological protection of finetuned MBSs in short quantum dot chains. We call this measure local distinguishability (LD) because it puts a bound to the degree an arbitrary local measurement can distinguish between two states. We study the LD for quantum dot chains of different length. The three-dot chain is studied in detail, and we find that it may not always be an improvement over the two-dot case, a fact that can be understood within an effective model derived from perturbation theory. For longer chains, the LD vanishes exponentially, signaling a transition to a topological phase with two ground states that cannot be distinguished by any local measurement.

Published by the American Physical Society
2024
Loop Feynman integration on a quantum computer
Authors: Martínez de Lejarza Jorge J. , Cieri Leandro , Grossi Michele , Vallecorsa Sofia , Rodrigo Germán
Published: October 2024

This work investigates in detail the performance and advantages of a new quantum Monte Carlo integrator, dubbed quantum Fourier iterative amplitude estimation (QFIAE), to numerically evaluate for the first time loop Feynman integrals in a near-term quantum computer and a quantum simulator. In order to achieve a quadratic speedup, QFIAE introduces a quantum neural network (QNN) that efficiently decomposes the multidimensional integrand into its Fourier series. For a one-loop tadpole Feynman diagram, we have successfully implemented the quantum algorithm on a real quantum computer and obtained a reasonable agreement with the analytical values. One-loop Feynman diagrams with more external legs have been analyzed in a quantum simulator. These results thoroughly illustrate how our quantum algorithm effectively estimates loop Feynman integrals and the method employed could also find applications in other fields such as finance, artificial intelligence, or other physical sciences.

Published by the American Physical Society
2024
Model-independent predictions for decays of double-heavy hadrons into pairs of heavy hadrons
Authors: Bruschini R.
Published: October 2024

Double-heavy hadrons can decay into pairs of heavy hadrons through transitions from confining Born-Oppenheimer potentials to heavy-hadron-pair potentials with the same Born-Oppenheimer quantum numbers. The states of the double-heavy hadron are constrained by a Born-Oppenheimer exclusion principle from the identical heavy quarks. The states of a pair of identical heavy hadrons are constrained by exclusion principles from identical particles. The transitions are also constrained by conservation of angular momentum and parity. From these constraints, we derive model-independent selection rules for decays of double-heavy hadrons into pairs of heavy hadrons. The coupling potentials are expressed as sums of products of Born-Oppenheimer transition amplitudes and angular-momentum coefficients. If there is a single dominant Born-Oppenheimer transition amplitude, it factors out of the coupling potentials between double-heavy hadrons in the same Born-Oppenheimer multiplet and pairs of heavy hadrons in specific heavy-quark-spin-symmetry multiplets and out of the corresponding partial decay rates. As examples, we discuss the Born-Oppenheimer potentials and multiplets for conventional double-heavy baryons and for double-heavy tetraquark mesons. We also discuss the relative partial decay rates for conventional double-heavy baryons into pairs of heavy hadrons.

Published by the American Physical Society
2024
Embedding space approach to Lorentzian CFT amplitudes and causal spherical functions
Authors: Agarwal Pulkit , Brower Richard C. , Raben Timothy G. , Tan Chung-I
Published: October 2024

Conformal field theory in a Minkowski setting is discussed in an embedding space approach, paying special attention to causality constraints for four-point amplitudes. The physics of dilatation and Lorentz boost is emphasized in specifying the noncompact maximal Abelian subgroup of SO(d,2). Reduction of a conformal field theory four-point amplitudes as functions of cross ratios is shown to be equivalent to enforcing H bi-invariance, i.e., F(hgh′)=F(g), with g∈SO(d,2) and H an appropriate subgroup. Causality is imposed by introducing appropriate semigroups. Causal zonal spherical functions are constructed, making contact with Minkowski conformal blocks introduced previously.

Published by the American Physical Society
2024
Nambu-Goto string as a higher-derivative Liouville theory
Authors: Makeenko Yuri
Published: October 2024

I propose a generalization of the Liouville action which corresponds to the Nambu-Goto string like the usual Liouville action corresponds to the Polyakov string. The two differ by higher-derivative terms which are negligible classically but revive quantumly. An equivalence with the four-derivative action suggests that the Nambu-Goto string in four dimensions can be described by the (4,3) minimal model analogously to the critical Ising model on a dynamical lattice. While critical indices are the same as in the usual Liouville theory, the domain of applicability becomes broader.

Published by the American Physical Society
2024
Data-driven computation of adjoint sensitivities without adjoint solvers: An application to thermoacoustics
Authors: Ozan Defne E. , Magri Luca
Published: October 2024

Adjoint methods have been the pillar of gradient-based optimization for decades. They enable the accurate computation of a gradient (sensitivity) of a quantity of interest with respect to all system parameters in one calculation. When the gradient is embedded in an optimization routine, the quantity of interest can be optimized for the system to have the desired behavior. Adjoint methods, however, require the system's governing equations and their Jacobian. In this paper, we propose a computational strategy to infer the adjoint sensitivities from data when the governing equations might be unknown (or partly unknown), and noise might be present. The key component of this strategy is an echo state network, which learns the dynamics of nonlinear regimes with varying parameters, and it evolves dynamically via a hidden state. Although the framework does not make assumptions on the dynamical system, we focus on thermoacoustics, which are governed by nonlinear and time-delayed systems. First, we show that a parameter-aware echo state network (ESN) infers the parametrized dynamics. Second, we derive the adjoint of the ESN to compute two types of sensitivity: (i) parameter sensitivity, which is the gradient of a time-averaged cost functional with respect to physical or design parameters of the system, and (ii) initial condition sensitivity, which is the gradient of a cost functional of the final state with respect to the initial condition. Third, we propose the thermoacoustic echo state network (T-ESN), which embeds the physical knowledge in the network architecture for improved generalization. Fourth, we apply the framework to a variety of nonlinear thermoacoustic regimes of a prototypical system. We show that the T-ESN accurately infers the correct adjoint sensitivities of the acoustic energy with respect to the flame parameters and initial conditions. The results are robust to noisy data, from periodic, through quasiperiodic, to chaotic regimes. The inferred adjoint sensitivities are employed to suppress an instability via steepest descent. We show that a single network predicts the nonlinear bifurcations on unseen scenarios, which allows it to converge to the minimum of the acoustic energy. This work opens new possibilities for gradient-based data-driven design optimization.

Published by the American Physical Society
2024
Application of quantum graph theory to metamaterial design: Negative refraction of acoustic waveguide modes
Authors: Lawrie T. M. , Starkey T. A. , Tanner G. , Moore D. B. , Savage P. , Chaplain G. J.
Published: October 2024

We leverage quantum graph theory to quickly and accurately characterize acoustic metamaterials comprising networks of interconnected pipes. Anisotropic bond lengths are incorporated in the model that correspond to space-coiled acoustic structures to exhibit dispersion spectra reminiscent of hyperbolic metamaterials. We construct two metasurfaces with embedded graph structure and, motivated by the graph theory, infer and fine-tune their dispersive properties to engineer nonresonant negative refraction of acoustic surface waves at their interface. Agreement between the graph model, full-wave simulations, and experiments bolsters quantum graph theory as a new paradigm for metamaterial design.

Published by the American Physical Society
2024
P-type Schottky-barrier-free contact to
MoS2
via layer-number-assisted interface engineering
Authors: Zhao Xiao-Lin , Wang Nie-Wei , Zhang Yue-Jiao , Gao Yu-Meng , Gong Peng-Lai , Jin Chen-Dong , Zheng Xiaohong , Wang Jiang-Long , Shi Xing-Qiang
Published: October 2024

Bilayer and few-layer MoS2 show intrinsically higher electronic quality and substantially improved device performance than monolayer, and high-quality MoS2 wafers with controlled layer number have been grown. In addition, MoS2 has different polymorphs such as the semiconducting H phase and semimetallic distorted T (dT) phase, and vertically stacked dT-/H-MoS2 metal-semiconductor junctions (MSJs) have been synthesized. However, the contact mechanism of dT-/H (few layer)-MoS2 MSJs remains to be elucidated, and p-type ohmic contact to MoS2 is difficult to realize due to the high ionization energy of MoS2. In the current work, we reveal a mechanism of two-dimensional (2D) semiconductors (2DSCs) layer-number-assisted metal-semiconductor (SC) interface engineering for Schottky barrier height (SBH) reduction and

p

-type ohmic contact is achieved based on this mechanism; 2DSCs here mean H (few layer)-MoS2 and metal-SC interfaces are the dT-/H-MoS2 interfaces with increasing 2DSC layers. Specifically speaking, the mechanism is as follows: (1) two competing effects coexist, namely, the interface dipole (ΔV) at the metal-SC interface and the quasibonding (QB) between all adjacent layers, with ΔV (QB) increasing (decreasing) SBH; (2) the effect of QB beats ΔV and hence the overall effect is decreasing SBH at the metal-SC interface; and (3) the SBH reduction effect increases with increasing 2DSC layers. The mechanism of 2DSC layer-number-assisted metal-SC interface engineering should apply also for other 2DSCs with a suitable metal and hence our current work paves an avenue for ohmic contact to few-layer 2DSCs by the accumulated interlayer QBs that widely present in 2DSCs.

Published by the American Physical Society
2024
Imaging Quantum Interference in a Monolayer Kitaev Quantum Spin Liquid Candidate
Authors: Kohsaka Y. , Akutagawa S. , Omachi S. , Iwamichi Y. , Ono T. , Tanaka I. , Tateishi S. , Murayama H. , Suetsugu S. , Hashimoto K. , Shibauchi T. , Takahashi M. O. , Nikolaev S. , Mizushima T. , Fujimoto S. , Terashima T. , Asaba T. , Kasahara Y. , Matsuda Y.
Published: October 2024

Single atomic defects are prominent windows to look into host quantum states because collective responses from the host states emerge as localized states around the defects. Friedel oscillations and Kondo clouds in Fermi liquids are quintessential examples. However, the situation is quite different for quantum spin liquid (QSL), an exotic state of matter with fractionalized quasiparticles and topological order arising from a profound impact of quantum entanglement. Elucidating the underlying local electronic property has been challenging due to the charge neutrality of fractionalized quasiparticles and the insulating nature of QSLs. Here, using spectroscopic-imaging scanning tunneling microscopy, we report atomically resolved images of monolayer α−RuCl3, the most promising Kitaev QSL candidate, on metallic substrates. We find quantum interference in the insulator manifesting as incommensurate and decaying spatial oscillations of the local density of states around defects with a characteristic bias dependence. The oscillation differs from any known spatial structures in its nature and does not exist in other Mott insulators, implying it is an exotic oscillation involved with excitations unique to α−RuCl3. Numerical simulations suggest that the observed oscillation can be reproduced by assuming that itinerant Majorana fermions of Kitaev QSL are scattered across the Majorana Fermi surface. The oscillation provides a new approach to exploring Kitaev QSLs through the local response against defects like Friedel oscillations in metals.

Published by the American Physical Society
2024
Robust Teleportation of a Surface Code and Cascade of Topological Quantum Phase Transitions
Authors: Eckstein Finn , Han Bo , Trebst Simon , Zhu Guo-Yi
Published: October 2024

Teleportation is a facet where quantum measurements can act as a powerful resource in quantum physics, as local measurements allow us to steer quantum information in a nonlocal way. While this has long been established for a single Bell pair, the teleportation of a many-qubit entangled state using nonmaximally entangled resources presents a fundamentally different challenge. Here, we investigate a tangible protocol for teleporting a long-range entangled surface-code state using elementary Bell measurements and its stability in the presence of coherent errors that weaken the Bell entanglement. We relate the underlying threshold problem to the physics of anyon condensation under weak measurements and map it to a variant of the Ashkin-Teller model of statistical mechanics with Nishimori-type disorder, which gives rise to a cascade of phase transitions. Tuning the angle of the local Bell measurements, we find a continuously varying threshold. Notably, the threshold moves to infinity for the X+Z angle along the self-dual line—indicating that infinitesimally weak entanglement is sufficient in teleporting a self-dual topological surface code. Our teleportation protocol, which can be readily implemented in dynamically configurable Rydberg-atom arrays, thereby gives guidance for a practical demonstration of the power of quantum measurements.

Published by the American Physical Society
2024
How influencers can enhance consumer responses by value co-creation
Authors: Zhang Jin , Cai Lingkui , Zheng Xiaoying
Published: October 2024

Purpose

This paper aims to explore whether, how and when influencers’ value co-creation behavior in a post – influencers investing operant resources to enhance the value gained from using the product – shapes consumers’ responses toward an influencer’s recommendation. Based on value co-creation theory and consumer inference, this paper proposes that consumers infer influencers have more expertise with and more favorable attitude toward the product from value co-creation. Consequently, such behavior can foster consumer engagement and favorable attitude toward the recommended product.

Design/methodology/approach

The authors collected real-world data and conducted four sets of experimental studies. In the experimental studies, the presence of an influencer’s value co-creation behavior (i.e. co-creation vs. control) was manipulated to test the causal effect and mechanisms of co-creation on engagement and product attitude.

Findings

Results show that influencers’ value co-creation behavior positively affects consumers’ engagement and attitudes toward the product. These effects are driven by perceived influencer’s expertise with and favorability toward the product (Studies 1 and 2). Co-creating utilitarian value is more effective than co-creating hedonic value (Studies 3A and 3B). In addition, influencers with a larger number of followers benefit more from co-creation behavior than those with fewer followers (Study 4).

Research limitations/implications

This research adds to the literature on value co-creation by investigating how, why and when influencers’ value co-creation enhances consumer responses to the post. Our investigation concretizes value co-creation behavior in the context of influencer marketing and demonstrates its signaling effect with nuanced role of value type in shaping the effect. The findings provide a novel cue that influencers can use to enhance consumer responses to their posts.

Practical implications

Brands should encourage influencers to focus on value-in-use co-creation when promoting their products. While emphasizing value co-creation in influencer partnership, brands should also carefully consider the type and size of influencers they collaborate with based on the nature of their products and target audience. The research findings also provide practical implications for influencers, offering guidance on how they can optimize their content creation strategies and enhance their effectiveness in influencer marketing collaborations.

Originality/value

This research enriches understanding of value co-creation in the context of influencer marketing and the role of content specifics in influencers’ posts. The findings provide a novel cue that influencers can use to enhance consumer responses to their posts.
Exploring value relevance of EVA over different stages of business lifecycle
Authors: Tripathi Manju , Ghalke Avinash , Kashiramka Smita
Published: October 2024

Purpose

This study aims to determine whether the financial ecosystem is reliable for evaluating a company’s financial performance at various lifecycle stages or whether value-based performance metrics like Economic Value Added (EVA) are the most comprehensive indicators regardless of the company’s lifecycle stage. The evaluation will analyse the importance of value-based and accounting performance benchmarks (EVA, Return on Capital Employed, Return on Equity and Earnings per Share) in creating shareholder value, as measured by market value added, throughout the company’s lifecycle.

Design/methodology/approach

This study is based on a robust empirical analysis of 228 Indian firms listed on the National Stock Exchange Nifty 500 Index from 2006 to 2023. By considering firms of different sizes and ages, the authors aim to capture and analyse any distinct impact across various stages of their lifecycles. Using quantile regression for analysis equips the authors to effectively address extreme events such as the 2008 global financial crisis and the COVID-19 pandemic, making the method particularly suitable for conditionally distributed samples based on size and age.

Findings

The research reveals that various performance indicators are crucial at different stages of a company’s lifecycle for generating wealth for shareholders. However, considering the significance of the EVA measure, it is recommended that policymakers standardize the calculation of EVA and mandate its disclosure.

Originality/value

The authors comprehensively analysed the economic value addition relative to a company’s size and age, going beyond previous studies that focused solely on specific size categories. This offers managers valuable insights into aligning business performance measures with the various stages of the business lifecycle.
Fractal momentum investment strategies based on liquidity non-linear fluctuations in Chinese stock market
Authors: Yan Ruzhen , Zhu Xin , Wang Kun , Ma Fanming , Wu Xu
Published: October 2024

Purpose

This paper aims to the relationship between liquidity fluctuation trends and stocks’ expected returns.

Design/methodology/approach

The authors use the multi-fractal detrended fluctuation analysis to study the liquidity non-linear multi-fractal characteristics of stock market and predict the future volatility trend of market liquidity with the help of potential entropy dimensional model and also consider the non-linear volatility trend of liquidity, construct a fractal momentum strategy under different sorting periods and holding periods, to test the liquidity momentum effects of Chinese stock market and, finally, compare with the traditional price momentum strategy.

Findings

The result suggests that: Chinese stock market liquidity has obvious non-linear multi-fractal characteristics; the trend entropy dimensional model can accurately predict the future volatility trend of market liquidity; significant liquidity trend momentum effects persist in the Chinese stock market, while price momentum effects exist only in the short term; a significant liquidity premium exists in the Chinese equity market; the fractal momentum strategy constructed in this paper achieves higher returns and less risk than the price momentum strategy.

Originality/value

Based on the above analysis, this paper will further construct a momentum strategy incorporating liquidity trends, i.e. fractal momentum strategy (LMP strategy), with the realistic background that Chinese stock market liquidity has non-linear multi-fractal characteristics – the main contribution of this paper is to overcome the shortcomings of existing momentum strategies, which seldom combine the trend of future liquidity fluctuations with momentum strategies, and to incorporate the real characteristics of the market.
Community-based economic romance and integration: assessing the feasibility of a currency union in South Asia
Authors: Verdie Jean-François , Salloum Charbel , Jarrar Hajer , Dana Léo-Paul
Published: October 2024

Purpose

This purpose of this study aims to critically evaluate the feasibility of establishing a single currency area within the South Asian Association for Regional Cooperation (SAARC) by examining the economic integration of its member states. The analysis focuses on the extent to which the region meets the criteria of the optimum currency area (OCA) theory, particularly in terms of business cycle synchronization, labor mobility and capital flows.

Design/methodology/approach

Using a vector autoregression (VAR) model within the aggregate demand-aggregate supply framework, this research investigates the symmetry of supply and demand shocks across SAARC economies. The study analyzes the synchronization of business cycles and the mobility of labor and capital to determine the readiness of SAARC for a unified currency.

Findings

The results indicate significant asymmetries in business cycles among SAARC countries, with substantial disparities in economic responses to shocks. These findings suggest that the region lacks the necessary economic synchronization required for a successful single currency area. Limited labor and capital mobility further complicate the potential for economic integration within SAARC.

Research limitations/implications

The study is constrained by data inconsistencies and the limited range of economic indicators available for SAARC countries. Future research should expand the analysis to include a broader set of socioeconomic factors and more comprehensive data sets to better assess the region’s potential for monetary integration.

Practical implications

The study highlights the challenges of forming a currency union in South Asia due to economic disparities and limited mobility. However, gradual steps toward deeper regional integration, improved financial infrastructure and enhanced cross-border collaboration could foster long-term economic stability, growth and social cohesion in the SAARC region.

Social implications

The research highlights the potential social benefits of enhanced economic integration, such as increased community resilience and social cohesion, while also warning of the risks associated with premature monetary union in a region with significant economic disparities.

Originality/value

This study provides a detailed analysis linking the theoretical framework of the OCA to the practical realities of economic integration in South Asia. By focusing on the specific economic conditions of SAARC member states, the research offers valuable insights for policymakers considering regional monetary integration.
A scoping review of robotic technology in hospitality and tourism
Authors: Sun Sunny , Ye Huiyue , Law Rob
Published: October 2024

Purpose

With the disruptive evolution of artificial intelligence (AI), the roles of robotics in hospitality and tourism are shifting rapidly from automatic to emotional works. Although academics have focused on examining robotic applications in hospitality and tourism, concrete images of the different roles of robots are unclear. Thus, this study aims to systematically aggregate and evaluate existing robotic technology-related studies published in Social Science Citation Index-listed hospitality and tourism journals to link the fragmented knowledge and provide an up-to-date overview of robotic technology in hospitality and tourism.

Design/methodology/approach

This study retrieved 134 robotic technology-related articles and used descriptive and content analyses to analyze the retrieved papers thoroughly.

Findings

The top keyword identified was service robot. Robotic technologies are categorized into AI-supplemented, AI-generated, robotic technology anthropomorphism (RTA)-facilitated and RTA-mediated.

Research limitations/implications

Future studies can consider exploring service robots further from the perspectives of suppliers in tourism. A more comprehensive categorization of robotic technologies is also recommended.

Originality/value

This study contributes to the robotic research realm by providing a holistic view of robotic applications in hospitality and tourism research. This study also attempts to pin down the potential research directions to guide researchers in expanding future studies.