Large Parameter Research Articles

Effect of Ca2+/Mg2+/Zr4+ concentrations on the characteristics of substituted gadolinium gallium garnet single crystals with large lattice parameter

Five substituted gadolinium gallium garnet crystals with different Ca2+/Mg2+/Zr4+ stoichiometric ratio concentrations (Zr4+: 13.0, 15.0, 15.3, 16.3, 19.5 at.%, as well as increasing Ca2+ and Mg2+ concentrations in proportion) were grown by Czochralski technique. Their structure, defect, thermal and optical properties were comparatively studied and analyzed. The lattice parameters are achieved to be 12.47–12.54 Å which are 0.7–1.2 % larger than that of Gd3Ga5O12. A linear equation with Zr4+ concentration is fitted to adjust the lattice parameter for demand. X-ray rocking curves with narrow FWHMs of 1.67′, 1.97′, 1.75′, 2.12′, 2.99′, respectively, indicating high crystalline quality when the Zr4+ concentration is below 16.3 at.%. The dislocation densities are 62, 47, 63, 315 and 3184 cm−2, suggesting the value increases rapidly when the Zr4+ concentration exceeds 16.3 at.% due to large lattice distortion. The thermal expansion coefficients are about 8.55 × 10−6 to 8.72 × 10−6 K−1, respectively. All the transmittances are above 80 % from visible to infrared wavelengths, and Sellmeier coefficients of refraction index equation were fitted, which is benefit for CaMgZr:GGG as substrate and optics application. The above results suggest that a more suitable substrate can be obtained for the series YIG magnetic-optic thin films by optimizing the Ca2+/Mg2+/Zr4+ concentrations.

Modification of the Large Parameter Approach for the Periodic Solutions of Nonlinear Dynamical Systems

This paper focuses on the modification of the large parameter approach (LPA), a novelty procedure, for estimating the periodic solutions of two degrees-of-freedom (DOF) autonomous quasi-linear systems with a first integral. This strategy is crucial because it provides an effective approach to recognizing approximate solutions to problems for which it is impossible to obtain exact solutions. These problems arise in the fields of physics, engineering, aerospace, and astronomy. They can be solved analytically using several perturbation approaches that depend on a small parameter that can be recognized according to the initial conditions and the body parameters of each problem. Therefore, we propose a large parameter instead of a small one to solve the aforementioned 2DOF systems, as well as provide a comparison between the suggested procedure and the previous approaches.

Scaling for selectivity in finite nanopores for 1:1 electrolytes: The dependence of predictability of device behavior on system parameters

The scaling properties of a cation selective nanopore mean that the device function (selectivity) depends on the input parameters (pore radius, pore length, surface charge density, electrolyte concentration, voltage) via a single scaling parameter that is a simple analytical function of the input parameters. In our previous study (Sarkadi et al., (2022) [5]), we showed that a parameter inspired by the Dukhin number (therefore, we also call it a Dukhin number) is an appropriate scaling parameter for infinitely long nanopores. Here, we extend that study to finite pores in a membrane and provide a detailed analyzes over a large parameter space for 1:1 electrolytes obtained from the Nernst-Planck transport equation coupled either to the Local Equilibrium Monte Carlo method or to the Poisson-Botzmann theory. Scaling is exact in a limiting case, where an analytical solution, such as Linearized Poisson-Boltzmann, is available (infinite pore). Here we show that scaling can work even if the solution is numerical or provided by computer simulations (finite pore). We discuss how these cases approach the limiting case as functions of the system parameters.

ESAMask: Real-Time Instance Segmentation Fused with Efficient Sparse Attention.

Instance segmentation is a challenging task in computer vision, as it requires distinguishing objects and predicting dense areas. Currently, segmentation models based on complex designs and large parameters have achieved remarkable accuracy. However, from a practical standpoint, achieving a balance between accuracy and speed is even more desirable. To address this need, this paper presents ESAMask, a real-time segmentation model fused with efficient sparse attention, which adheres to the principles of lightweight design and efficiency. In this work, we propose several key contributions. Firstly, we introduce a dynamic and sparse Related Semantic Perceived Attention mechanism (RSPA) for adaptive perception of different semantic information of various targets during feature extraction. RSPA uses the adjacency matrix to search for regions with high semantic correlation of the same target, which reduces computational cost. Additionally, we design the GSInvSAM structure to reduce redundant calculations of spliced features while enhancing interaction between channels when merging feature layers of different scales. Lastly, we introduce the Mixed Receptive Field Context Perception Module (MRFCPM) in the prototype branch to enable targets of different scales to capture the feature representation of the corresponding area during mask generation. MRFCPM fuses information from three branches of global content awareness, large kernel region awareness, and convolutional channel attention to explicitly model features at different scales. Through extensive experimental evaluation, ESAMask achieves a mask AP of 45.4 at a frame rate of 45.2 FPS on the COCO dataset, surpassing current instance segmentation methods in terms of the accuracy-speed trade-off, as demonstrated by our comprehensive experimental results. In addition, the high-quality segmentation results of our proposed method for objects of various classes and scales can be intuitively observed from the visualized segmentation outputs.

Efficient-Lightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images.

The most significant technical challenges of current aerial image object-detection tasks are the extremely low accuracy for detecting small objects that are densely distributed within a scene and the lack of semantic information. Moreover, existing detectors with large parameter scales are unsuitable for aerial image object-detection scenarios oriented toward low-end GPUs. To address this technical challenge, we propose efficient-lightweight You Only Look Once (EL-YOLO), an innovative model that overcomes the limitations of existing detectors and low-end GPU orientation. EL-YOLO surpasses the baseline models in three key areas. Firstly, we design and scrutinize three model architectures to intensify the model's focus on small objects and identify the most effective network structure. Secondly, we design efficient spatial pyramid pooling (ESPP) to augment the representation of small-object features in aerial images. Lastly, we introduce the alpha-complete intersection over union (α-CIoU) loss function to tackle the imbalance between positive and negative samples in aerial images. Our proposed EL-YOLO method demonstrates a strong generalization and robustness for the small-object detection problem in aerial images. The experimental results show that, with the model parameters maintained below 10 M while the input image size was unified at 640 × 640 pixels, the APS of the EL-YOLOv5 reached 10.8% and 10.7% and enhanced the APs by 1.9% and 2.2% compared to YOLOv5 on two challenging aerial image datasets, DIOR and VisDrone, respectively.

FC-ResNet: A Multilingual Handwritten Signature Verification Model Using an Improved ResNet with CBAM

Offline signature verification is a widely used biometric method in finance, law, and administrative procedures. However, existing deep convolutional neural network models perform poorly on signature datasets that span different regions and ethnic people, while also suffering from problems such as large parameter counts and slow inference speeds. To address these issues, we propose an improved residual network model (FC-ResNet). This model introduces a convolutional block attention module into the classical residual network to adapt to the diversity and variability of signatures, while also compressing the model for lightweight deployment. Due to the lack of public, offline handwritten signature datasets for ethnic people, we collected a large-scale offline handwritten signature dataset, including genuine signatures and forged signatures in Chinese, Uyghur, Kazakh, and Kirgiz, totaling 38,400 images. Our FC-ResNet model achieved an accuracy of over 96% for each language in our self-built dataset, as well as accuracy rates of 96.21%, 98.42%, and 97.28% on the public datasets CEDAR, BHSig-B, and BHSig-H, respectively. Based on the above experimental results, our proposed model demonstrates great potential for both public and self-built signature datasets, while also exhibiting significant advantages in lightweight model deployment. We believe that this work can provide a feasible solution for ethnic people signature verification.

Microlensing of gravitational waves by dark matter structures

Gravitational lensing of gravitational waves provides a potential new probe of dark matter structures. In this work, we consider the microlensing effect on gravitational wave signals from black hole binaries induced by low-mass dark matter halos that do not retain enough baryonic matter to hold stars. We clarify systematically when this microlensing effect is relevant and study in detail its detectability by future gravitational wave observatories. We consider lensing by cold dark matter halos and by solitonic cores that reside in fuzzy dark matter halos. Our results show that although the effect can be detectable at relatively large impact parameters, the probability of detecting such lensed events is low. In particular, we find that the expected number of events lensed by cold dark matter halos is 𝒪(0.01) per year for BBO and the expected number of events lensed by solitonic cores inside fuzzy dark matter halos is 𝒪(0.01) per year for ET. In the case that a significant fraction of dark matter consists of 𝒪(100 M ⊙) objects that are relatively compact, R < 𝒪(0.1 pc), we show that the expected number of lensed events per year for ET can be very large, 𝒪(1000).

Same-sided successive-shock HED instability experiments

Inertial confinement fusion (ICF) and high-energy density (HED) physics experiments experience complicated forcing for instability growth and mix due to the ubiquitous presence of multiple shocks interacting with perturbations on multiple material interfaces. One common driver of instability growth is successive shocks from the same direction. However, there is a severe lack of analytic work and modeling validation for same-sided successive shocks since they are extremely difficult to achieve with conventional (non-HED) drivers. Successive shocks access a large instability parameter space; idealized fluid theory [K. O. Mikaelian, Phys. Rev. A 31, 410 (1985)] predicts 15 different interface evolution scenarios for a sinusoidal perturbation. Growth becomes more complex for multi-mode, compressible HED systems. The Mshock campaign is the first experiment in any fluid regime to probe a wide portion of successive shock parameter space. This is enabled by our development of a hybrid direct/indirect drive platform capable of creating independently controllable successive shocks on the National Ignition Facility. These experiments have delivered the first data capable of rigorously challenging our models and their ability to accurately capture Richtmyer–Meshkov growth under successive shocks. Single-mode and two-mode experiments have successfully demonstrated the ability to access and control the various growth scenarios of the shocked interface, including re-inversion, freeze out, and continued growth. Simulations and theoretical modeling are shown to accurately capture the experimental observations in the linear growth phase, giving us confidence in our ICF/HED design codes.

Theoretical Considerations for Optimizing the Use of Optogenetics with Complex Behavior.

Optogenetic approaches have allowed researchers to address complex questions about behavior that were previously unanswerable. However, as optogenetic procedures involve a large parameter space across multiple dimensions, it is crucial to consider such parameters in conjunction with the behaviors under study. Here, we discuss strategies to optimize optogenetic approaches with complex behavior by identifying critical experimental design considerations, including frequency specificity, temporal precision, activity-controlled optogenetics, stimulation pattern, and cell-type specificity. We highlight potential limitations or theoretical considerations to be made when manipulating each of these factors of optogenetic experiments. This overview emphasizes the importance of optimizing optogenetic study design to enhance the conclusions that can be drawn about the neuroscience of behavior. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Testing SALT Approximations with Numerical Radiation Transfer Code. I. Validity and Applicability

Absorption line spectroscopy offers one of the best opportunities to constrain the properties of galactic outflows and the environment of the circumgalactic medium. Extracting physical information from line profiles is difficult; however, for the physics governing the underlying radiation transfer is complicated and depends on many different parameters. Idealized analytical models are necessary to constrain the large parameter spaces efficiently, but are typically plagued by model degeneracy and systematic errors. Comparison tests with idealized numerical radiation transfer codes offer an excellent opportunity to confront both of these issues. In this paper, we present a detailed comparison between SALT, an analytical radiation transfer model for predicting UV spectra of galactic outflows, with the numerical radiation transfer software, RASCAS. Our analysis has led to upgrades to both models including an improved derivation of SALT and a customizable adaptive mesh refinement routine for RASCAS. We explore how well SALT, when paired with a Monte Carlo fitting procedure, can recover flow parameters from nonturbulent and turbulent flows. Overall we find that turbulence leads to biases in the recovery of kinematic parameters and the optical depth, but find that derived quantities (e.g., mass outflow rates, column density, etc.) are still well recovered. From the analysis, we estimate average uncertainties in our ability to measure metal flow rates spanning 0.65 (0.95) dex in M ⊙ yr−1 and uncertainties spanning 0.54 (0.94) dex in cm−2 for column densities at a resolution of 20 (100) km s−1 and signal-to-noise ratio = 10.

Cosmic birefringence from neutrino and dark matter asymmetries

In light of the recent measurement of the nonzero Cosmic Microwave Background (CMB) polarization rotation angle from the Planck 2018 data, we explore the possibility that such a cosmic birefringence effect is induced by coupling a fermionic current with photons via a Chern-Simons-like term. We begin our discussion by rederiving the general formulae of the cosmic birefringence angle with correcting a mistake in the previous study.We then identify the fermions in the current as the left-handed electron neutrinos and asymmetric dark matter (ADM) particles, since the rotation angle is sourced by the number density difference between particles and antiparticles. For the electron neutrino case, with the value of the degeneracy parameter ξν e recently measured by the EMPRESS survey, we find a large parameter space which can explain the CMB photon polarization rotations. On the other hand, for the ADM solution, we consider two benchmark cases with Mχ = 5 GeV and 5 keV. The former is the natural value of the ADM mass if the observed ADM and baryon asymmetry in the Universe are produced by the same mechanism, while the latter provides a warm DM candidate. In addition, we explore the experimental constraints from the CMB power spectra and the DM direct detections.

Novel lead-free 2–1–2 composite: predicted high piezoelectric sensitivity and significant hydrostatic response

A parallel-connected composite with 2–1–2 connectivity and two lead-free single-crystal (SC) components is proposed. Its high piezoelectric sensitivity is highlighted and its large hydrostatic parameters are described. The first type of composite layer represents a ferroelectric domain-engineered [001]-poled [Li, (K, Na)](Nb, Ta)O3 SC. In the second type of composite layer, piezoelectric Li2B4O7 SC rods in the form of an elliptic cylinder are regularly aligned in a large polymer matrix. The effective electromechanical properties of the composite were found in three stages, using the effective field and matrix methods that are applicable to piezoelectric media. A new orientation effect was studied, linked with rotations of SC rod bases in the polymer medium that forms the second type of layer. Since these rotations are in a Li2B4O7 SC with a unique elastic and piezoelectric anisotropy, the second type of layer exhibits a noticeable influence on the piezoelectric performance and hydrostatic response of the composite. A variation of the aspect ratio of the Li2B4O7 rod base becomes another important factor that can improve the hydrostatic parameters of the composite. Some effective parameters of related 2–1–2 composites were compared for different polymer components. Three diagrams were first constructed for the high-performance 2–1–2 [Li, (K, Na)](Nb, Ta)O3/Li2B4O7/polyethylene composite to show the ranges of rotation angles and volume fractions that correspond to the longitudinal piezoelectric voltage coefficient > 500 mV m N−1, hydrostatic piezoelectric coefficient > 200 mVm N−1 and hydrostatic figure of merit >10−11 Pa−1. These effective parameters are important in piezoelectric sensors and hydroacoustic and other applications of novel lead-free composites.

Multiple effects of forced cooling on joint quality in coolant-assisted friction stir welding

To understand the multiple effects of forced cooling on the joint quality in coolant-assisted friction stir welding and the underlying mechanism, commercial pure aluminum AA1050 was welded by liquid–CO2–assisted friction stir welding (FSW) within a large process parameter range. The cooling effects on the weld formation, microstructure, and mechanical properties were investigated by comparison with conventional FSW. The microstructure evolution during the liquid–CO2–assisted FSW process was revealed by EBSD characterization together with thermal cycle measurement and short-time annealing. The results show that the process parameter window was narrowed by the liquid CO2 cooling. Forced cooling led to weld surface grooves and interior cavities under “too cold” welding conditions. The grains in the weld zone were refined and the areas of the weld cross-section were reduced by the forced cooling, resulting in the tensile strength of the joint being improved but the elongation being reduced. The thermal cycle shows that the liquid CO2 cooling compressed the welding temperature field by decreasing the heating rate and increasing the cooling rate, giving rise to the decrease in deformation temperature at the stirring stage. The low deformation temperature promotes dynamic recrystallization by changing the way of recrystallization and thus refines the grains. Further, the liquid CO2 cooling suppresses the grain growth which should have happened in natural cooling. Combining the above two aspects, the grain in the weld zone was refined and the tensile properties of the joints were changed. Nevertheless, the contribution of decreasing the deformation temperature to the grain refinement is more significant than that of increasing the cooling rate.

A lightweight crack segmentation network based on knowledge distillation

This paper presents a novel approach for addressing the challenges of large parameter volumes and high computational complexity in existing deep learning models for crack detection. This method involves training a student model using a pretrained teacher model to guide the learning process. The novelty of the method is the use of channel-wise knowledge distillation to normalize activation maps between the teacher and student models, followed by the minimization of the asymmetric Kullback–Leibler divergence to achieve optimal model performance. By focusing on imitating regions with prominent activation values, the student model achieves accurate crack localization. Test results show that the method improves crack segmentation, based on improvements in the F1_score and intersection over union by 2.17% and 3.55%, respectively, and outperforms other compared knowledge distillation methods. A lightweight crack segmentation model that ensures accuracy and efficiency is established in this study, which can provide an efficient solution for crack segmentation in real-world scenarios.

New asymptotic representations of the noncentral t‐distribution

AbstractNew asymptotic approximations of the noncentral t distribution are given a generalization of the Student's t distribution. Using new integral representations, we give new asymptotic expansions not only for large values of the noncentrality parameter but also for large values of the degrees of freedom parameter. In some cases, we accept more than one large parameter. These results are not only in terms of elementary functions, but also in terms of the complementary error function and the incomplete gamma function. A number of numerical tests demonstrate the performance of the asymptotic approximations.

Travelling Waves in the Ring of Coupled Oscillators with Delayed Feedback

We studied travelling waves in N nonlinear differential equations with a delay and large parameter. This system is important because it can be regarded as a phenomenological model of N-coupled neuron-like oscillators with delay. The problem of the existence of travelling-wave-type solutions was reduced to the study of the dynamics of an auxiliary equation with two delays. Using a special asymptotic method for the large parameter we proved that this equation has a relaxation cycle, studied its properties (amplitude, period and asymptotics) and found the sufficient stability conditions. Based on this periodic solution the travelling waves of the initial model were constructed.

UNDERGROUND UTILITY LOCATOR EQUIPPED WITH A TWO-STROKE PULSE TRANSDUCER

With detailed large-scale topographic surveys of cities, especially when photographing executive master plans of industrial facilities, geodetic services perform work on measuring not only ground sites, but also - on detecting and localizing of underground utilities: water, oil and gas metal pipelines, power and telephone cables, etc. The search for underground communications by various services is carried out at use of special electronic devices for searching of underground communications: tracers, cable detectors. A number of shortcomings have been identified when operating these devices, including difficulties in detecting and fixing of pipes or cables in conditions of increased industrial interference, insufficient efficacy and accuracy of the search process, high energy consumption, low level of ease of operation, due to relatively large weight and size parameters. A comparative analysis of currently used search devices has proven technical defects of circuit solutions, and has formed the basis for developing of an electronic circuit. A working model of an underground utility finder with a pulse converter has been produced. Main technical characteristics were obtained after testing. The technical solution has been patented in the GU of the Intellectual Property Center of the Republic of Uzbekistan.

The role of small airway function parameters in preschool asthmatic children

BackgroundSmall airways are the major sites of inflammation and airway remodeling in all severities of asthma patients. However, whether small airway function parameters could reflect the airway dysfunction feature in preschool asthmatic children remain unclear. We aim to investigate the role of small airway function parameters in evaluating airway dysfunction, airflow limitation and airway hyperresponsiveness (AHR).MethodsEight hundred and fifty-one preschool children diagnosed with asthma were enrolled retrospectively to investigate the characteristics of small airway function parameters. Curve estimation analysis was applied to clarify the correlation between small and large airway dysfunction. Spearman’s correlation and receiver-operating characteristic (ROC) curves were employed to evaluate the relationship between small airway dysfunction (SAD) and AHR.ResultsThe prevalence of SAD was 19.5% (166 of 851) in this cross-sectional cohort study. Small airway function parameters (FEF25-75%, FEF50%, FEF75%) showed strong correlations with FEV1% (r = 0.670, 0.658, 0.609, p<0.001, respectively), FEV1/FVC% (r = 0.812, 0.751, 0.871, p<0.001, respectively) and PEF% (r = 0.626, 0.635, 0.530, p<0.01, respectively). Moreover, small airway function parameters and large airway function parameters (FEV1%, FEV1/FVC%, PEF%) were curve-associated rather than linear-related (p<0.001). FEF25-75%, FEF50%, FEF75% and FEV1% demonstrated a positive correlation with PC20 (r = 0.282, 0.291, 0.251, 0.224, p<0.001, respectively). Interestingly, FEF25-75% and FEF50% exhibited a higher correlation coefficient with PC20 than FEV1% (0.282 vs. 0.224, p = 0.031 and 0.291 vs. 0.224, p = 0.014, respectively). ROC curve analysis for predicting moderate to severe AHR showed that the area under the curve (AUC) was 0.796, 0.783, 0.738, and 0.802 for FEF25-75%, FEF50%, FEF75%, and the combination of FEF25-75% and FEF75%, respectively. When Compared to children with normal lung function, patients with SAD were slightly older, more likely to have a family history of asthma and airflow obstruction with lower FEV1% and FEV1/FVC%, lower PEF% and more severe AHR with lower PC20 ( all p<0.05).ConclusionSmall airway dysfunction is highly correlated with large airway function impairment, severe airflow obstruction and AHR in preschool asthmatic children. Small airway function parameters should be utilized in the management of preschool asthma.

The stochastic relaxion

We revisit the original proposal of cosmological relaxation of the electroweak scale by Graham, Kaplan and Rajendran in which the Higgs mass is scanned during inflation by an axion field, the relaxion. We investigate the regime where the relaxion is subject to large fluctuations during inflation. The stochastic dynamics of the relaxion is described by means of the Fokker-Planck formalism. We derive a new stopping condition for the relaxion taking into account transitions between the neighboring local minima of its potential. Relaxion fluctuations have important consequences even in the “classical-beats-quantum” regime. We determine that for a large Hubble parameter during inflation, the random walk prevents the relaxion from getting trapped at the first minimum. The relaxion stops much further away, where the potential is less shallow. Interestingly, this essentially jeopardises the “runaway relaxion” threat from finite-density effects, restoring most of the relaxion parameter space. We also explore the “quantum-beats-classical” regime, opening large new regions of parameter space. We investigate the consequences for both the QCD and the non-QCD relaxion. The misalignment of the relaxion due to fluctuations around its local minimum opens new phenomenological opportunities.

A secure and efficient authenticated key exchange scheme for smart grid

Smart grid provides convenience for power generation, consumption and distribution. Authenticated key exchange (AKE) is a fundamental technique to protect data transmission from interception and tampering in smart grid. However, since the smart meters only have limited resources in computation and communication, most of the existing AKE schemes are inefficient for smart grid. First, many schemes have to use large security parameters to compensate the loose reduction in their security proofs. Second, most of these schemes require at least three-round of communication to negotiate a secret session key with explicit key confirmation. To alleviate these issues, we propose a novel two-round AKE scheme with tight security for smart grid. Our proposed scheme integrates Diffie-Hellman key exchange and a tightly secure digital signature, in which not only mutual authentication can be realized but also the communicating parties can confirm that session keys are negotiated between them explicitly. Compared with the existing AKE schemes, the overheads in both communication and computation are lighter in our proposed scheme, because fewer rounds of communication are required and smaller security parameters can be used to achieve the same security level. Therefore, our scheme contributes to a more practical solution for secure key establishment in smart grid.