Theory Research Articles

Strong-field nondipole approximation in laser-assisted thermal electron scattering

This study investigates the differential cross-section (DCS) of electrons scattered by a hydrogen molecule (H₂) under varying conditions, including temperature, momentum, laser intensity, and polarization. The objective was to understand how these parameters affect electron scattering and to compare the effects of linear and circular polarizations. Methodologically, theoretical model was developed using strong-field nondipole approximation with linear and circular polarized laser fields, examining DCS as a function of thermal electron temperature, momentum, and laser intensity. The study utilized a modified Volkov wave function model to account for thermal electron effects and analyzed DCS variations across different orbitals (n = 1, n = 2, and n = 3). Findings reveal that DCS increases with temperature due to enhanced electron oscillations, with higher orbitals (n = 3) showing greater DCS compared to lower orbitals (n = 1). Increased momentum results in decreased DCS, with higher orbitals exhibiting higher DCS values under circular polarization, contrary to linear polarization. Laser intensity decreases DCS for both polarizations, with circular polarization providing a narrower range of DCS values and generally higher DCS compared to linear polarization. This research further exploration of polarization effects on DCS in different atomic systems and extending studies to higher energy regions for a comprehensive understanding of electron scattering dynamics.

Enhancing Dispersive Readout of Superconducting Qubits through Dynamic Control of the Dispersive Shift: Experiment and Theory

The performance of a wide range of quantum computing algorithms and protocols depends critically on the fidelity and speed of the employed qubit readout. Examples include gate sequences benefiting from midcircuit real-time measurement-based feedback, such as qubit initialization, entanglement generation, teleportation, and, perhaps most importantly, quantum error correction. A prominent and widely used readout approach is based on the dispersive interaction of a superconducting qubit strongly coupled to a large-bandwidth readout resonator, frequently combined with a dedicated or shared Purcell filter protecting qubits from decay. By dynamically reducing the qubit-resonator detuning and thus increasing the dispersive shift, we demonstrate a beyond-state-of-the-art two-state-readout error of only 0.25% in 100-ns integration time. Maintaining low-readout-drive strength, we nearly quadruple the signal-to-noise ratio of the readout by doubling the readout-mode line width, which we quantify by considering the hybridization of the readout resonator and its dedicated Purcell filter. We find excellent agreement between our experimental data and our theoretical model. The presented results are expected to further boost the performance of new and existing algorithms and protocols critically depending on high-fidelity fast midcircuit measurements. Published by the American Physical Society 2024

Analysis of the Prevalence of Traumatic Dental Injuries in the Primary Dentition: Findings From a Cohort Study Involving 4-Year-Old Children From South Brazil.

To identify factors associated with the prevalence of traumatic dental injuries (TDI) in children at 4 years of age. Participants from the 2015 Pelotas (Brazil) birth cohort were included. Demographic, socioeconomic, behavioral, and environmental data were collected through interviews and physical examinations during cohort follow-up. Dental examination at 4 years of age revealed the presence of TDI. A theoretical model was constructed using a directed acyclic graph (DAG). A descriptive analysis was performed, followed by Poisson regression models relating TDI to each outcome. Data from 3650 4-year-old children were analyzed; the prevalence of dental trauma was 20.2% (95% confidence interval [CI] 18.9%-21.5%). The prevalence of TDI was lower among girls compared with boys, suggesting a protective effect of female sex (relative risk [RR] 0.80 [95% CI: 0.79-0.91]). Increased height for age (RR 1.55 [95% CI: 1.14-2.09]), increased overjet (RR 1.45 [95% CI: 1.2-1.74]), and anterior open bite (RR 1.26 [95% CI: 1.01-1.56]) demonstrated an association with TDI after testing regression models based on DAGs. Male sex, increased height, and increased overjet and open bite were factors predisposing to TDI at 4 years of age. Understanding these factors can contribute to the implementation of targeted prevention strategies for reducing TDI and their potential long-term consequences.

Stochastic Epigenetic Modification and Evolution of Sex Determination in Vertebrates.

In this report, we propose a novel mathematical model of the origin and evolution of sex determination in vertebrates that is based on the stochastic epigenetic modification (SEM) mechanism. We have previously shown that SEM, with rates consistent with experimental observation, can both increase the rate of gene fixation and decrease pseudogenization, thus dramatically improving the efficacy of evolution. Here, we present a conjectural model of the origin and evolution of sex determination wherein the SEM mechanism alone is sufficient to parsimoniously trigger and guide the evolution of heteromorphic sex chromosomes from the initial homomorphic chromosome configuration, without presupposing any allele frequency differences. Under this theoretical model, the SEM mechanism (i) predated vertebrate sex determination origins and evolution, (ii) has been conveniently and parsimoniously co-opted by the vertebrate sex determination systems during the evolutionary transitioning to the extant vertebrate sex determination, likely acting "on top" of these systems, and (iii) continues existing, alongside all known vertebrate sex determination systems, as a universal pan-vertebrate sex determination modulation mechanism.

Enhancing the Spectral Sensitivity of Prism-Based SPR Sensors: The Role of Analyte RI

A theoretical approach is presented to significantly enhance the spectral sensitivity of prism-based SPR sensors. The spectral sensitivity of prism-based SPR sensors is derived based on the coupling conditions of SPR and might exceed 105 nm/RIU for analytes with large RI values when other sensor parameters are carefully considered, including the RI of the prism, the angle of incidence, and the SPR active material. The spectral sensitivity could be markedly enhanced, reaching up to 10,000 nm/RIU by fine-tuning the effective RI of the incident light to be slightly larger, specifically 0.01~0.02 RIU, than the RI of the analyte, which is attributed to the large dielectric permittivity of the SPR active material, the key factor for achieving high sensitivity. The dynamic range is 0.040 RIU in the case of high sensitivity, which is sufficient in most applications. Moreover, the spectral sensitivity could be pushed even higher, into the range of 106~108 nm/RIU, by positioning the effective RI of the incident light closer to that of the analyte. However, it requires a careful balance between optimizing the sensitivity and maintaining an acceptable dynamic range.

Correlation Between NMR Coupling Constants and σ-Donating Properties of N-Heterocyclic Carbenes and Their Derivatives.

Is the 1JC-H coupling constant for protonated carbene a relevant measure of its σ-donation ability? This paper addresses this question by comparing calculated 1JC-H values with various experimental and theoretical approaches across a broad spectrum of carbene compounds. We examined Arduengo-type NHCs based on the 2-imidazolylidene scaffold and many other derivatives with modified frameworks, including carbenes with extended, saturated, or conjugated rings, reduced heteroatom stabilization, alternative heteroatoms, permanently charged carbenes, acyclic carbenes, amidocarbenes, and cyclic amino(alkyl/aryl) carbenes, carbodicarbenes and carbodiphosphoranes. Our findings reveal a nuanced relationship between different parameters associated with σ-interaction, such as 1JC-H, Huynh electronic parameter (HEP), σ-donation from ETS-NOCV, and lone pair energy. Notably, the best correlation was observed between 1JC-H and the ETS-NOCV method, particularly for mono- and diaminocarbenes, highlighting the utility of 1JC-H in comparing σ-donation among structurally similar carbene types. However, the use of 1JC-H as a universal measure across all carbene classes appears limited, especially when considering carbenes with significantly different structural frameworks. While HEP is less effective for carbenes with diverse structural backbones, our study suggests that 1JC-H has potential across a broader range of systems. Additionally, the analysis demonstrates that lone pair energy reflects basicity rather than σ-donor ability.

The relationship between antecedents of reverse logistics implementation and economic performance in retail: empirical study for the electronic sector

ABSTRACT This research develops a conceptual model to elucidate the relationship between antecedents of reverse logistics implementation and economic performance. A mixed-methods approach was employed, with qualitative research exploring antecedents and quantitative analysis using 405 responses from Vietnamese electronic retail enterprises to test hypotheses. The findings identified institutional pressure, resource commitment, IT capability, and corporate reputation as antecedents of reverse logistics implementation, exerting direct and/or indirect effects on economic performance. PLS-SEM analysis generated research results consistent with the previously established theoretical conceptual model, and IPMA highlighted institutional pressure and resource commitment as impactful factors despite their low average scores. Notably, resource commitment plays a moderating role in dampening the positive relationship between institutional pressure and reverse logistics implementation. This study provides deeper insights into reverse logistics theory, supporting retail decision-making to enhance economic performance. However, variations in study scope may lead to differences in outcomes, presenting a significant challenge.

The timeliness of constructionist theory in the process of journalistic content production in the digital age

This research explores the relevance of constructionist theory in the production of journalistic content in the digital age. Constructionist theory posits that reality is socially constructed and shaped by the discursive practices of the media, gaining significance within a media landscape profoundly transformed by digitization, the proliferation of social networks, and the use of algorithms. The investigation employs a qualitative methodology, utilizing a systematic literature review of publications from 2013 to 2023, aiming to map the principal theoretical and empirical approaches that discuss the impact of new technologies and communicative practices on contemporary journalism. The findings indicate that the digital era has intensified the constructionist nature of news production, given the multiplicity of voices and agents involved in the mediation process, including an actively participating public in the creation and dissemination of content. It was further observed that digital platforms, by personalizing news consumption through algorithms, create fragmented realities and filter bubbles, challenging the notion of a shared news reality. Moreover, the emergence of misinformation and “fake news” underscores the importance of a constructionist approach to understanding how news narratives are continuously negotiated and reconstructed. It is concluded that constructionist theory remains a valid analytical framework for understanding the dynamics of journalistic production in the digital age, particularly in a context where the boundaries between news producers and consumers have become increasingly fluid.

Laser ultrasonic inspection of surface and subsurface defects in materials based on deep learning

ABSTRACT Laser ultrasonic testing is an advanced non-destructive testing with high frequency and fast detection speed. However, most laser ultrasonic testing characterises defects by manually extracting the features of signals. To address this, deep learning is introduced to identify defects intelligently. Firstly, theoretical models based on finite elements are built to study the the surface and subsurface defects’ effects on surface acoustic wave (SAW) propagation. Experimental studies are also conducted on 5 samples with surface defects and 15 with subsurface defects. Then, Gaussian white noise is added to both simulation and experimental signals to expand the data set and imitate the complex conditions. The wavelet transform images of the reflected and transmitted signal are combined into a data set for training the convolutional neural network (CNN). The subsurface defects’ data set is similarly augmented. Finally, a total of 40,000 surface defect and 21,000 subsurface defect data are collected and split into training, test, and validation sets (6:2:2 ratio). The CNN accurately classifies surface defect penetration depth (minimum error 5.87%), while subsurface defect widths are determined with transfer learning (minimum error 5.6%). It proves that it is feasible to classify and identify defects by combining the laser ultrasonic method with deep learning.

Collaborative online learning in higher education—quality of digital interaction and associations with individual and group-related factors

Collaborative online learning became a necessity for universities during the COVID-19 pandemic. Even though it is known from research that online collaboration is an effective way of learning, digital interaction can be challenging for learners. Group members have to create a high-quality interaction to ensure the success of the collaborative learning process. Based on a theoretical model of collaborative learning, high-quality interaction can be determined with regard to cognitive group activities (prior knowledge activation, transactivity), meta-cognitive group activities (organization of the work process), and relational group activities (group climate, participation and task-related communication). Our study aims to examine how students manage a self-directed collaborative learning setting, how they perceive the process quality of digital interaction and how the interaction quality is related to self-reported outcomes (learning gain and satisfaction). We use a newly developed questionnaire to assess the quality of digital interaction in terms of the aforementioned dimensions. Furthermore, we focus on associations with the beliefs about web-based learning and the ability of perspective-taking at the individual level as well as the sense of community at the group level. We conducted a quantitative study within online university courses that were implemented asynchronously due to the COVID-19 pandemic. N = 298 undergraduate students in teacher education rated the quality of a digital collaborative learning settings (response rate of 72%). The students worked on collaborative tasks autonomously without any guidance from the teacher. We find differences between (meta-)cognitive and relational factors of interaction quality, and differences in the strength of the associations with outcomes and individual and group-related factors. Our study provides insights into students´ collaborative online learning and examines the relationships between different dimensions of group interaction quality and the input and outcome variables. Limitations and areas for further research are discussed.

Partial alignment between jets and megamasers: Coherent versus selective accretion

Spins play a crucial role in the appearance, evolution, and occupation fraction of massive black holes (MBHs). To date, observational estimates of MBH spins are scarce, and the assumptions commonly made in such estimates have recently been questioned. Similarly, theoretical models for MBH spin evolution, while reproducing the few observational constraints, are based on possibly oversimplified assumptions. New independent constraints on MBH spins are therefore of primary importance. We present a rigorous statistical analysis of the relative orientation of radio jets and megamaser disks in ten low-redshift galaxies. We find a strong preference for (partial) alignment between jets and megamaser that can be attributed to two different causes: coherent accretion and selective accretion. In the first case the partial alignment is due to an anisotropy in the gas reservoir fueling the growth of MBHs. In the second case the spin-dependent anisotropic feedback allows long-lived accretion only if the orbits of the gas inflows are almost aligned to the MBH equatorial plane. A discussion of the implications of the two accretion scenarios regarding the evolution of MBHs is presented, together with an outlook on future observational tests aiming at discriminating between the two scenarios and checking whether either applies to different redshifts and black hole mass regimes.

Early Bright Galaxies from Helium Enhancements in High-Redshift Star Clusters

The first few cycles of JWST have identified an overabundance of UV-bright galaxies and a general excess of UV luminosity density at z≳10 compared to expectations from most (pre-JWST) theoretical models. Moreover, some of the brightest high-redshift spectroscopically confirmed galaxies exhibit peculiar chemical abundance patterns, most notably extremely high N/O ratios. Since N/O has been empirically shown to scale strongly with He/H, as expected for hot hydrogen burning, these same bright high-redshift galaxies are likely also helium-enhanced. Under simplistic assumptions for stellar evolution, the bolometric luminosity of a star scales as L∝(4−92Y+54Y2)−1 — hence a higher He/H leads to brighter stars. In this Letter, we evolve a series of MESA models to the zero-age main-sequence and highlight that the helium enhancements at the levels measured and inferred for high-redshift galaxies can boost the 1500 A UV luminosity by up to ∼50%, while simultaneously increasing the stellar effective temperature. The combination of helium enhancements with nebular continuum emission expected for intense bursts of star formation have the potential to help reduce the tension between JWST observations and certain galaxy formation models.

Effect of Inhomogeneous Temperature in Chip‐Scale Infrared Thermal Sources: A Revisited Blackbody Radiation Formula with Experimental Validation

AbstractMiniature and low‐cost light sources are highly desirable for numerous optical microsystems. Among these, devices based on blackbody radiation of a filament heated at a few hundred degrees, perfectly fit with the requirements of producing a broad spectral range falling in the infrared range, owing to Planck's law. These light sources are of primary interest for Fourier transform infrared (FTIR) spectroscopy. Although thermal light production is simple, achieving precise light intensity is not a trivial task. Herein, the impact of the inhomogeneous temperature on the emitted radiation is studied. Blackbody radiation formulae are revisited for miniature sources, taking into account the temperature distribution and using the principle of superposition of non‐coherent sources. A theoretical model is formulated by dividing the source into multiple annular elementary sources of different temperature. This results in effective, corrected blackbody emission. Analytical formulae are derived in the case of a quadratic temperature distribution. For the experimental validation, a silicon‐based source, made of a platinum resistive micro‐heater on top of heavily doped silicon, is fabricated and experimentally characterized at temperatures ranging from 300 to 520 K. The experimental results show good agreement with the model predictions in the explored wavelength range of (λ = 2.5–4.8 µm).

Friction drag reduction of Taylor–Couette flow over air-filled microgrooves

Reducing drag under high turbulence is a critical but challenging issue that has engendered great concern. This study utilizes hydrophilic tips in superhydrophobic (SHP) grooves to enhance the stability of plastron, which results in a considerable drag reduction ( $DR$ ) up to 62 %, at Reynolds number ( $Re$ ) reaching $2.79 \times 10^{4}$ . The effect of the spacing width $w$ of the microgrooves on both $DR$ and flow structures is investigated. Experimental results demonstrate that $DR$ increases as either microgroove spacing $w$ or $Re$ increases. The velocity fields obtained using particle image velocimetry indicate that the air-filled SHP grooves induce a considerable wall slip. This slip significantly weakens the intensity of Taylor rolls, reduces local momentum transport, and consequently lowers drag. This phenomenon becomes more pronounced with increasing $w$ . Furthermore, to quantify the multiscale relationship between global response and geometrical as well as driving parameters, $DR\sim (w, \phi _s, Re)$ , a theoretical model is established based on angular momentum defect theory and magnitude estimate. It is demonstrated that a decrease in the surface solid fraction can reduce wall shear, and an increase in the groove width can weaken turbulence kinetic energy production, rendering enhanced slip and drag reduction. This research has implications for designing and optimizing turbulent-drag-reducing surfaces in various engineering applications, such as transportation and marine engineering.

On marketization and public spending growth

Abstract I contribute to the literature on the growth of public spending in Western economies with a novel mechanism that ties it to the marketization process, i.e. the substitution of home with market production. I argue that a key contributor to the expansion of social spending is the replacement of family-based transfers with public pensions and other public transfer programs. I provide empirical support for this hypothesis by establishing the long-run relationship between government size and marketization, alongside other established determinants of government spending, in a panel of Western economies. I then illustrate a potential mechanism behind the results with a theoretical model in which, as a result of the productivity advantage of the market over the home sector, family-based intergenerational transfers decline unexpectedly, providing a rationale for government intervention in the form of public pensions with a poverty relief component.

Electric-field-induced polarization anisotropy of interband photoluminescence in GaAs

Near-infrared photoluminescence spectra of the n-doped gallium arsenide epilayer under heating lateral electric field conditions are studied. The field dependences of hot electron and hole temperatures are determined from photoluminescence spectra and from solving the power balance equation using current–voltage characteristic. Polarization anisotropy of the photoluminescence radiation arising due to the anisotropy of hot electron distribution function and angular dependence of the interband optical matrix element in the momentum space is observed and investigated. The obtained experimental data are in satisfactory agreement with the theoretical model.

An innovation potential and organizational performance: an integrative role of company’s dynamic capabilities

AbstractThe restaurant business plays a crucial role in the food economy and, like many industries, faces numerous challenges due to the rapid pace of change, driven by consumer trends and shifting demographics. In response to the pressure on businesses to adapt to these changing circumstances, new restaurant concepts, organizational structures and technologies have emerged in the hope of finding methods that are more agile during unpredictable times. The development of dynamic capabilities is a critical issue for both academics and practitioners, as it can enhance competitive advantages and improve organizational performance. The purpose of this paper is to examine the impact of dynamic capabilities on innovative potential and organizational performance. Through a literature review and the dynamic capability view, a theoretical model is proposed. This model was validated using the PLS-SEM technique, based on responses from 143 restaurants across eight of the largest Russian cities. The results indicate that dynamic capabilities related to the value proposition serve as a complete mediator in the relationship between a company's innovative potential and its performance in a highly volatile context. The proposed theoretical model is both unique and effective, demonstrating high explanatory power. This study enriches the existing literature on dynamic capabilities by addressing empirical research gaps and elucidating the mechanisms through which dynamic capabilities influence organizational performance.

First spectropolarimetric observation of the neutron star low-mass X-ray binary GX 3+1

We report the first simultaneous X-ray spectropolarimetric observation of the bright atoll neutron star low-mass X-ray binary performed by the Imaging X-ray Polarimetry Explorer ( joint with and The source does not exhibit significant polarization in the 2--8 keV energy band, with an upper limit of 1.3<!PCT!> at a 99<!PCT!> confidence level on the polarization degree. The observed spectra can be well described by a combination of thermal disk emission, the hard Comptonization component, and reflected photons off the accretion disk. In particular, from the broad Fe Kalpha line profile, we were able to determine the inclination of the system ($i which is crucial for comparing the observed polarization with theoretical models. Both the spectral and polarization properties of are consistent with those of other atoll sources observed by Therefore, we may expect a similar geometrical configuration for the accreting system and the hot Comptonizing region. The low polarization is also consistent with the low inclination of the system.

Optimal data-driven strategy for in-house and outsourced technological innovations by open banking APIs

AbstractOpen banking is a customer consent-driven data-sharing framework to maintain interoperability among financial and non-financial institutions through secure application programming interfaces. Traditional retail banks are losing their competitive edge against digital banks, FinTech, and BigTech firms due to a higher outflow of customer account data than inflow. These firms capitalize on open banking data to launch innovative products and introduce “ready-to-deploy” Banking-as-a-Service platforms for end-to-end banking operations without the need to build full-scale infrastructures. Therefore, banks must reshape data-driven strategies to stay competitive. This research proposes a decision-support tool to select optimal digital strategies using the Strategic Value Index (SVI), a metric derived from analyzing multiple strategic objectives of bank stakeholders. The SVI minimizes implementation time and costs while maximizing operational action importance to a balanced digital strategy that combines both in-house and outsourced technological developments. The importance of operational action is quantified using evidential reasoning with fuzzy logic to address the challenge of aggregating incomplete and ambiguous banking data and assessments from multiple stakeholders. The theoretical approach is validated through a real application in a Latin American bank, and its findings are globally transferable. Cost and time data were sourced from public repositories, as made available accessible through government-mandated disclosures. The sensitivity analysis revealed that hybrid in-house and outsourced development is more flexible in meeting tight timelines and budget constraints. The combined approach is more cost-effective, time-efficient, and aligned with the internal needs of banks compared to either entirely in-house or fully outsourced models.

Developing a stochastic linear elastic material model and composite laminate theory including failures, using the fiber bundle–based approach

This paper presents a novel theoretical statistical material model, which is a kind of extension of the usual 3D Hooke’s law and can take into account the damage process up to the final failure as well. This material model can provide the stress response also together with the damages to multiaxial short time alternating strain loads. It was developed by utilizing our earlier validated results of applying E-bundles for modelling stress-strain curve of different types of fibrous materials and fibre-reinforced composite sheets subjected to simple (uniaxial) mechanical loads. Based on the fiber bundle cells (FBC) theory, we introduced the so-called memory reliability functions to take into account the different changing strain loads including both the monotone, the pulsating and the alternating modes. We proved that the duplex compressive–tensile memory reliability function is the product of the compressive and the tensile memory reliability functions. Utilizing the generalized Hooke’s law and the memory reliability functions, we developed a stochastic linear elastic material law that also represents the damage and failure processes with normal and shear strain loads. This made it possible to calculate the expected value as the variance of the stress response process and determine its confidence interval at any strain load.