bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental study on the unsteady behavior and frequency characteristics of high-speed submerged cavitating water jets
Authors: Zhu Runyu , Zhu Haitao , Zhang Xiaohui , Pan Shize , Zhang Chi , Xie Bin
Published: October 2024

The frequency characteristics of cavitation fluctuations in high-speed cavitating jets are intricate due to the coupling mechanisms of unsteady behaviors. This study employs high-speed photography to experimentally investigate the relationship between frequency characteristics and the unsteady behavior of cavitating jets with various cavitation numbers. Temporal evolution patterns of the cavitating jets are analyzed through spatiotemporal (s-t) diagrams. The spatial distribution and temporal evolution of cavitation fluctuation frequencies are examined using fast Fourier transform (FFT) and continuous wavelet transform (CWT), respectively. Proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) are employed to identify coherent structures and their corresponding frequencies. In results, the s-t diagrams reveal the distinct regions influenced by cavitation shedding and collapse. FFT results indicate that upstream of the jet trajectory, spectral energy is concentrated in the shedding band, shifting toward lower frequencies with increasing axial distance. The CWT spectrum exhibits a single peak in the upstream, identifying it as the shedding frequency. POD modes associated with shedding dominate the energy contribution at higher cavitation numbers, while they become less prominent at lower cavitation numbers. DMD extracts and identifies coherent structures associated with shedding through frequency-specific decomposition.
A molecular dynamics simulation study of EthylChlorophyllide A molecules confined in a SiO2 nanoslit
Authors: Roccatano Danilo , Karki Khadga Jung
Published: October 2024

This paper investigates the dynamic behavior of EthylChlorophyllide A (EChlideA) molecules in a methanol solution confined within a 4 nm silica nanoslit, using molecular dynamics simulations over a duration of 1 ms. Three systems, containing 1, 2, and 4 solutes, were studied at 298 K. The results demonstrate that EChlideA molecules predominantly adsorb onto the silica surfaces, driven by specific interactions between chlorin ring’s methyl group and the hydroxyl groups of the silica. This adsorption leads to stable binding, particularly in less crowded environments, as indicated by the potential of mean force analysis. Higher molecular concentrations, such as those with four EChlideA molecules, introduce variation in binding strength due to molecular aggregation and complex interactions. The orientation analysis reveals that the chlorin ring tends to align parallel to the surface, requiring rotational adjustments during surface diffusion. In addition, solvent coordination around the Mg ion remains consistent under bulk conditions, although with some variation in higher concentrations. This study also highlights a decrease in linear diffusion and an increase in rotational relaxation times for EChlideA molecules within the confined nanoslit, reflecting the influence of molecular concentration and arrangement on their dynamics. These findings provide valuable insights into the role of surface interactions, molecular orientation, and solvent coordination in confined environments, offering implications for the design of nanoscale systems.
Anomalous power-law behavior in the electrical impedance of endothelial cellular networks
Authors: Galpayage Dona Kalpani N. U. , Du E. , Lau A. W. C.
Published: October 2024

In this paper, we report on the electrical impedance measurement of human endothelial cellular networks and show the existence of emergent power law behavior in its admittance. In particular, we find that the admittance scales with the frequency ω as ωα, with the exponent that varies with the degree of the disruption caused by the inflammation in the endothelial cellular network. We demonstrate that the power law of the measured electrical admittance can be understood by a simple percolation model of a large R–C (resistor–capacitor) network, which allows us to relate quantitatively and the intensity of inflammation. Our results suggest that the electrical properties of heterogeneous biomaterials, like living tissues, behave as a complex microstructural network.
Analysis of dominant flow in tectonic coal during coalbed methane transport
Authors: Zhu Xinyu , Su Erlei , Cheng Zhiheng , Ni Xiaoming , Chen Liang , Zhang Jinhu , Wang Hongbing
Published: October 2024

Diffusion and seepage are the main flow forms of coal seam gas transport, and are one of the key factors in the selection of gas extraction improvement methods. Changes in the physical structure of tectonic coal make gas transport more complex during coalbed methane extraction. In this paper, we develop a multi-field coupled model of methane transport in coal seams, taking into account the effects of tectonics, and theoretically analyze the dominant flow patterns for methane extraction. Then, the evolution of gas dominated flow is analyzed for different initial pressures, initial permeabilities, and initial diffusion coefficients of tectonic and intact coal seams. The results show that the amount of daily methane seepage in tectonic coal increases with the initial pressure of the coal reservoir, but decreases with the initial diffusion coefficient of the coal reservoir. Methane seepage in tectonic coal has a longer control time than in intact coal at different initial pressures, initial permeabilities, and initial diffusion coefficients of the coal reservoir. For different coal reservoir initial pressures, coal reservoir initial permeabilities, and coal reservoir initial diffusion coefficients, the maximum seepage control time for tectonic coal is 20, 17, and 15 times longer than for intact coal, respectively. Finally, the discrepancies of methane dominant flow in tectonic coal and intact coal during methane extraction were analyzed by using the double bottleneck flow model, and methods for methane enhanced extraction in tectonic coal and intact coal were discussed. The results presented in this paper may provide a theoretical reference for the extraction of differentiated gas in coal seams.
One-grating common-path phase-shifting interferometer for quantitative phase imaging
Authors: Deng Youwei , Huang Weinan , Shen Binglin , Guo Jiaqing , Hu Rui , Qu Junle , Feng Yueshu , Liu Liwei
Published: October 2024

A one-grating common-path phase-shifting interferometer for quantitative phase imaging is proposed as an improvement over the original interferometer design. In the original version, the setup is long, involving a grating pair, and requires precise mechanical translation of the grating, which poses difficulties for practical applications. The proposed interferometer utilizes grating multiplexing to reduce the length of the optical setup and uses a phase-only spatial light modulator to implement pinhole filtering and phase shifting simultaneously without any moving parts, making it more conducive for the realization of a practical version.
Steering sound propagation with Zeno barriers in acoustic waveguide arrays
Authors: Huang Ze-Xin , Wu Hong-Wei , Cheng Le-Le , Xie Peng-Xiang , Chen Xue , Xu Hua-Feng , Sheng Zong-Qiang
Published: October 2024

In quantum systems, a counterintuitive phenomenon known as quantum Zeno dynamics is usually exploited to tailor and protect the coherent evolution of quantum states by the back action of quantum measurements and strong couplings. Here, with the quantum-classical analogy, we report that the acoustic Zeno dynamics can be reproduced in acoustic waveguide arrays by setting segmented waveguides. We experimentally demonstrate that the segmented waveguide acts as an acoustic barrier to tailor the whole Hilbert space into different subspaces by separating the communication between waveguides. By arranging the acoustic Zeno barriers, we can control the sound transport in waveguide arrays into the target output ports, such as the Zeno dynamics, analog-quantum walk, and analog-quantum logic gates. In this context, we highlight that the Zeno barrier can be a versatile tool to arbitrarily control and guide the sound transport in waveguide arrays, which can provide an alternative choice for acoustic metamaterials and metasurfaces without cumbersome and complicated structure design. The acoustic Zeno barrier may provide a versatile approach to manipulate acoustic wave propagation for designing advanced on-chip integrated sound devices.
Using JADES NIRCam photometry to investigate the dependence of stellar mass inferences on the IMF in the early universe
Authors: Woodrum Charity , Rieke Marcia , Ji Zhiyuan , Baker William M. , Bhatawdekar Rachana , Bunker Andrew J. , Charlot Stéphane , Curtis-Lake Emma , Eisenstein Daniel J. , Hainline Kevin , Hausen Ryan , Helton Jakob M. , Hviding Raphael E. , Johnson Benjamin D. , Robertson Brant , Sun Fengwu , Tacchella Sandro , Whitler Lily , Williams Christina C. , Willmer Christopher N. A.
Published: October 2024

The detection of numerous and relatively bright galaxies at redshiftsz> 9 has prompted new investigations into the star-forming properties of high-redshift galaxies. Using local forms of the initial mass function (IMF) to estimate stellar masses of these galaxies from their light output leads to galaxy masses that are at the limit allowed for the state of the Lambda Cold Dark Matter (ΛCDM) Universe at their redshift. We explore how varying the IMF assumed in studies of galaxies in the early universe changes the inferred values for the stellar masses of these galaxies. We infer galaxy properties with the spectral energy distribution (SED) fitting code Prospector using varying IMF parameterizations for a sample of 102 galaxies with photometry from the James Webb Space Telescope, JWST Advanced Deep Extragalactic Survey that are spectroscopically confirmed to be atz>6.7, with additional photometry from the JWST Extragalactic Medium Band Survey for twenty-one of the galaxies. We demonstrate that models with stellar masses reduced by a factor of three or more do not affect the modeled SED.
Estimating false alarm rates of sub-dominant quasi-normal modes in GW190521
Authors: Capano Collin D , Abedi Jahed , Kastha Shilpa , Nitz Alexander H , Westerweck Julian , Wang Yi-Fan , Cabero Miriam , Nielsen Alex B , Krishnan Badri
Published: October 2024

A major aim of gravitational wave astronomy is to test observationally the Kerr nature of black holes. The strongest such test, with minimal additional assumptions, is provided by observations of multiple ringdown modes, also known as black hole spectroscopy. For the gravitational wave merger event GW190521, we have previously claimed the detection of two ringdown modes emitted by the remnant black hole. In this paper we provide further evidence for the detection of multiple ringdown modes from this event. We analyse the recovery of simulated gravitational wave signals designed to replicate the ringdown properties of GW190521. We quantify how often our detection statistic reports strong evidence for a sub-dominant

(
ℓ
,
m
,
n
)
=
(
3
,
3
,
0
)

ringdown mode, even when no such mode is present in the simulated signal. We find this only occurs with a probability ∼0.02, which is consistent with a Bayes factor of

56
±
1

(1σ uncertainty) found for GW190521. We also quantify our agnostic analysis of GW190521, in which no relationship is assumed between ringdown modes, and find that only 1 in 250 simulated signals without a

(
3
,
3
,
0
)

mode yields a result as significant as GW190521. Conversely, we verify that when simulated signals do have an observable

(
3
,
3
,
0
)

mode they consistently yield a strong evidence and significant agnostic results. We also find that constraints on deviations from the

(
3
,
3
,
0
)

mode on GW190521-like signals with a

(
3
,
3
,
0
)

mode are consistent with what was obtained from our previous analysis of GW190521. Our results support our previous conclusion that the gravitational wave signal from GW190521 contains an observable sub-dominant

(
ℓ
,
m
,
n
)
=
(
3
,
3
,
0
)

mode.
Towards quantum gravity with neural networks: solving the quantum Hamilton constraint of U(1) BF theory
Authors: Sahlmann Hanno , Sherif Waleed
Published: October 2024

In the canonical approach of loop quantum gravity, arguably the most important outstanding problem is finding and interpreting solutions to the Hamiltonian constraint. In this work, we demonstrate that methods of machine learning are in principle applicable to this problem. We consider U(1) BF theory in three dimensions, quantised with loop quantum gravity methods. In particular, we formulate a master constraint corresponding to Hamilton and Gauß constraints using loop quantum gravity methods. To make the problem amenable for numerical simulation we fix a graph and introduce a cutoff on the kinematical degrees of freedom, effectively considering

U
q

(
1
)

BF theory at a root of unity. We show that the neural network quantum state ansatz can be used to numerically solve the constraints efficiently and accurately. We compute expectation values and fluctuations of certain observables and compare them with exact results or exact numerical methods where possible. We also study the dependence on the cutoff.
A new nonconvex multi-view subspace clustering via learning a clean low-rank representation tensor
Authors: Zhang Xiaoqing , Guo Xiaofeng , Pan Jianyu
Published: October 2024

Recently, low-rank tensor representation has achieved impressive results for multi-view subspace clustering (MSC). The typical MSC methods utilize the tensor nuclear norm as a convex surrogate of the tensor multi-rank to obtain a low-rank representation, which exhibits limited robustness when dealing with noisy and complex data scenarios. In this paper, we introduce an innovative clean low-rank tensor representation approach that combines the idea of tensor robust principal component analysis with a new nonconvex tensor multi-rank approximation regularization. This integration enhances the robustness of the low-rank representation, resulting in improved performance. Furthermore, to better capture the local geometric features, we employ a high-order manifold regularization term. To effectively address our new model, we develop an iterative algorithm that can be proved to converge to the desired Karush-Kuhn-Tucker critical point. The numerical experiments on widely used datasets serve to demonstrate the efficacy and effectiveness of our new method.
Efficient, multimodal, and derivative-free bayesian inference with Fisher–Rao gradient flows
Authors: Chen Yifan , Zhengyu Huang Daniel , Huang Jiaoyang , Reich Sebastian , Stuart Andrew M
Published: October 2024

In this paper, we study efficient approximate sampling for probability distributions known up to normalization constants. We specifically focus on a problem class arising in Bayesian inference for large-scale inverse problems in science and engineering applications. The computational challenges we address with the proposed methodology are: (i) the need for repeated evaluations of expensive forward models; (ii) the potential existence of multiple modes; and (iii) the fact that gradient of, or adjoint solver for, the forward model might not be feasible. While existing Bayesian inference methods meet some of these challenges individually, we propose a framework that tackles all three systematically. Our approach builds upon the Fisher–Rao gradient flow in probability space, yielding a dynamical system for probability densities that converges towards the target distribution at a uniform exponential rate. This rapid convergence is advantageous for the computational burden outlined in (i). We apply Gaussian mixture approximations with operator splitting techniques to simulate the flow numerically; the resulting approximation can capture multiple modes thus addressing (ii). Furthermore, we employ the Kalman methodology to facilitate a derivative-free update of these Gaussian components and their respective weights, addressing the issue in (iii). The proposed methodology results in an efficient derivative-free posterior approximation method, flexible enough to handle multi-modal distributions: Gaussian Mixture Kalman Inversion (GMKI). The effectiveness of GMKI is demonstrated both theoretically and numerically in several experiments with multimodal target distributions, including proof-of-concept and two-dimensional examples, as well as a large-scale application: recovering the Navier–Stokes initial condition from solution data at positive times.
Vital signs detection of moving targets using FMCW radar
Authors: Dai Xiao , Zhang Yuanhui , Luo Jingxue , Liu Kang , Fu Duo
Published: October 2024

Respiratory and heartbeat rates are crucial indicators for human health assessment. Compared to contact-based measurements, millimeter-wave radar detection of these vital signs avoids the discomfort caused by physical contact and better protects personal privacy, making it highly valuable for home health monitoring. The use of millimeter-wave radar for vital sign detection of the human body is mostly focused on targets in a stationary state at present. However, the human body may sway or even move during actual detection. This article proposes a non-contact vital sign detection method for moving targets. Compared with methods for detecting vital signs of stationary targets, detecting vital signs of moving targets requires determining the range bin where the targets are located continuously and extracting target phase information. The noise components such as movement and sway contained in the phase signal need to be removed. In this paper, moving target indication is used to remove static components, an adaptive range bin selection method is proposed to determine the range bin where the targets are located, and range bin selection fluctuation is smoothed using a moving average filter. The wavelet transform is used to decompose the phase signal, remove swaying noise based on autocorrelation function, and reconstruct the life signal for different scale factors. A bandpass filter is used to separate the respiratory and heartbeat signals, and a notch filter is designed to suppress respiratory harmonic signals. The experimental results show that the proposed method can separate vital signs signals from the phase signals of moving targets, achieving detection of respiration and heartbeat rate. The average accuracy of respiration and heartbeat rate detection is 94.7% and 95.5%, respectively.
Label-free quantitative phase imaging and analysis of airborne pollen
Authors: Kumar Anand , Dhawan Sachin , Bhatt Sunil , Saxena Anuj , Khare Mukesh , Dubey Satish Kumar , Mehta Dalip Singh
Published: October 2024

Pollen morphology, involving the physical characteristics of pollen grains from seed plants during reproduction, plays an important role in plant biology, ecology, and evolution. High pollen concentrations in the air can degrade air quality and exacerbate respiratory conditions such as asthma. Understanding pollen morphology and its implications for air quality is significant for mitigating respiratory health risks. Conventionally, fluorescence microscopy is used for pollen imaging, but photobleaching, quenching, and phototoxicity affect the surface morphology and do not provide quantitative data on the pollen grains. For this study, we used bright field (BF) imaging and quantitative phase imaging (QPI), a label-free interferometric microscopy method, to look at differences in the shape of pollen. BF imaging provides information about the shape and size of the different pollens but has a limitation of low contrast. To obtain high-contrast images and quantitative data on the pollen grains without any exogenous agents, we employed QPI and BF imaging in the present study. QPI enables the extraction of detailed information regarding the cell wall, aperture, and thickness of pollen while also maintaining their natural state without the need for chemical treatments. In the present work, we sampled the ambient air from May 2023 to January 2024 on the IIT Delhi campus. Subsequently, QPI and BF imaging have been done for pollen identification and phase analysis of arboreal and non-arboreal pollen. Further, by utilizing the information obtained from BF microscopy and QPI, different species of pollen have been identified, and a pollen calendar has been prepared for exhibiting pollen season throughout the year. To the best of the authors’ knowledge, they have conducted the QPI of airborne pollen grains for the first time; this technique holds great potential for characterizing airborne pollens without the need for staining or sample preparation.
Study on the effects of strain and electrostatic doping on the magnetic anisotropy of GaN/VTe2 van der waals heterostructure
Authors: Xue Junjun , Chen Wei , Hu Shanwen , Chen Zhouyu , Fang Haoyu , Zhi Ting , Shao Pengfei , Cai Qing , Yang Guofeng , Gu Yan , Wang Jin , Chen Dunjun
Published: October 2024

Using a first-principles approach, this study delves into the effects of strain and electrostatic doping on the electronic and magnetic properties of the GaN/VTe2 van der Waals (vdW) heterostructure. The results reveal that when the GaN/VTe2 vdW heterostructure is doped with 0.1 h/0.2 h of electrostatic charge, its magnetization direction undergoes a remarkable reversal, shifting from out-of-plane orientation to in-plane direction. Therefore, we conduct a thorough investigation into the influence of electron orbitals on magnetic anisotropy energy. In addition, as the strain changes from −1% to 1%, the 100% spin polarization region of the GaN/VTe2 vdW heterostructure becomes smaller. It is worth noting that at a doping concentration of 0.1 h, the GaN/VTe2 vdW heterostructure has a Curie temperature of 30 K above room temperature. This comprehensive study provides valuable insights and provides a reference for analyzing the electronic and magnetic properties of low-dimensional systems.
Educational research in physics teacher education: the role of mathematics in physics teaching
Authors: Jacobsson Ebba , Wallenlind Simon , Pendrill Ann-Marie
Published: October 2024

Do student teachers benefit from contact with research, as required in our national teacher education curriculum? This paper describes the experiences of two pre-service teachers, who learned about common challenges encountered in the intersection between mathematics and physics. After a literature survey, they decided to try out a few questions with second-year high-school students (age 17). One of the student teachers constructed a pre- and post-test, confirming earlier results that students perform better on computational tasks. The second pre-service teacher included a few additional questions on a test given by another teacher. Based on the results on the test, four students were selected for interviews. The students interviewed all stated that they spend the majority of their time on calculations, whereas none of them had the habit of reading the textbook to understand the concepts. The interviews also revealed that solving a problem does not guarantee that the student understands the calculation. All students described a strategy of looking for a suitable formula on the sheet provided and just inserting numbers given. Through the test and the interviews, the student teachers gained training in assessment and an increased awareness of conceptual challenges and also of what Physics Education Research can offer.
A low-cost method for quantifying bouncing ball dynamics with smartphone video
Authors: Poonyawatpornkul Jiraporn , Snguanrat Banthita , Chaiworn Panupat
Published: October 2024

This study employed a low-cost method for quantifying bouncing ball dynamics with smartphone video. High-speed video analysis was used to investigate the bouncing behaviour of different balls, including table tennis, rubber, and tennis balls, on a table tennis surface. To examine the effect of surface material on bouncing dynamics, the table tennis ball was also tested on wood and tile surfaces. Key parameters analysed included bounce height decay, the coefficient of restitution (COR), and the bounce half-life. Additionally, we measured the total bouncing time and analysed the relationship between changes in gravitational potential energy, kinetic energy, and total mechanical energy (ME). Our results revealed a significant correlation between the COR and the decay rate of bounce height. Balls with higher COR values, indicative of lower energy loss per bounce, exhibited slower decay rates, resulting in longer bounce half-lives and extended total bounce times. For instance, the table tennis ball on a tile surface demonstrated a high COR of 0.93, a bounce half-life of 4.65 bounces, and a total bounce time of 8.22 ± 0.34 s. This suggests that material properties such as stiffness and elasticity of both the ball and the surface significantly influence the COR and decay rate, beyond just surface smoothness. Furthermore, our analysis of ME changes in the bouncing balls aligns with theoretical predictions, providing insights into the energy transformations occurring during bouncing. This improved understanding can also be a valuable tool for educators, helping teachers and students bridge the gap between theory and real-world observations, leading to a deeper grasp of the concepts.
Intensity vs amplitude of polarised light produced by a polariser
Authors: Goh Ker Liang
Published: October 2024

The intensity of unpolarised light after passing through a polariser is halved. This is a well-documented fact in contemporary textbooks. But how do their amplitudes compare before and after passing through the polariser? This is not mentioned in textbooks, and hence it is our intention to discuss this in this frontline.
Hybrid modality dual-energy imaging aggregating complementary advantages of kV-CT and MV-CBCT: concept proposal and clinical validation
Authors: Qi Junfeng , Yu Shutong , Dong Zhengkun , Liu Jiang , Deng Juan , Mei Guojian , Yin Chuou , Li Qiao , Li Tian , Wang Shi , Zhang Yibao
Published: October 2024

Objective. Megavoltage cone-beam CT (MV-CBCT) is advantageous in metal artifact reduction during image-guided radiotherapy (IGRT), although it is limited by poor soft tissue contrast. This study proposed and evaluated a novel hybrid modality dual-energy (DE) imaging method combining the complementary advantages of kilovoltage CT kV-CT and MV-CBCT. Approach. The kV-CT and MV-CBCT images were acquired on a planning CT scanner and a Halcyon linear accelerator respectively. After rigid registration, images of basis materials were generated using the iterative decomposition method in the volumetric images. The decomposition accuracy was quantitatively evaluated on a Gammex 1472 phantom. The performance of contrast enhancement and metal artifact reduction in virtual monochromatic images were evaluated on both phantom and patient studies. Main results. Using the proposed method, the mean percentage errors for relative electron density (RED) and stopping power ratio were 0.90% and 0.81%, outperforming the clinical single-energy mapping method with mean errors of 1.28% and 1.07%, respectively. The contrasts of soft-tissue insets were enhanced by a factor of 2–3 at 40 keV compared to kV-CT. The standard deviation in the metal artifact area was reduced by ∼67%, from 42 HU (kV-CT) to 14 HU (150 keV monochromatic). The head and neck patient test showed that the percent error of soft-tissue RED in the metal artifact area was reduced from 18.1% (HU-RED conversion) to less than 1.0% (the proposed method), which was equivalent to the maximum dosimetric difference of 28.7% based on the patient-specific plan. Significance. Without hardware modification or extra imaging dose, the proposed hybrid modality method enabled kV–MV DE imaging, providing improved accuracy of quantitative analysis, soft-tissue contrast and metal artifact suppression for more accurate IGRT.
Dual convolution-transformer UNet (DCT-UNet) for organs at risk and clinical target volume segmentation in MRI for cervical cancer brachytherapy
Authors: Kim Gayoung , Viswanathan Akila N , Bhatia Rohini , Landman Yosef , Roumeliotis Michael , Erickson Beth , Schmidt Ehud J , Lee Junghoon
Published: October 2024

Objective. MRI is the standard imaging modality for high-dose-rate brachytherapy of cervical cancer. Precise contouring of organs at risk (OARs) and high-risk clinical target volume (HR-CTV) from MRI is a crucial step for radiotherapy planning and treatment. However, conventional manual contouring has limitations in terms of accuracy as well as procedural time. To overcome these, we propose a deep learning approach to automatically segment OARs (bladder, rectum, and sigmoid colon) and HR-CTV from female pelvic MRI. Approach. In the proposed pipeline, a coarse multi-organ segmentation model first segments all structures, from which a region of interest is computed for each structure. Then, each organ is segmented using an organ-specific fine segmentation model separately trained for each organ. To account for variable sizes of HR-CTV, a size-adaptive multi-model approach was employed. For coarse and fine segmentations, we designed a dual convolution-transformer UNet (DCT-UNet) which uses dual-path encoder consisting of convolution and transformer blocks. To evaluate our model, OAR segmentations were compared to the clinical contours drawn by the attending radiation oncologist. For HR-CTV, four sets of contours (clinical + three additional sets) were obtained to produce a consensus ground truth as well as for inter/intra-observer variability analysis. Main results. DCT-UNet achieved dice similarity coefficient (mean ± SD) of 0.932 ± 0.032 (bladder), 0.786 ± 0.090 (rectum), 0.663 ± 0.180 (sigmoid colon), and 0.741 ± 0.076 (HR-CTV), outperforming other state-of-the-art models. Notably, the size-adaptive multi-model significantly improved HR-CTV segmentation compared to a single-model. Furthermore, significant inter/intra-observer variability was observed, and our model showed comparable performance to all observers. Computation time for the entire pipeline per subject was 12.59 ± 0.79 s, which is significantly shorter than the typical manual contouring time of >15 min. Significance. These experimental results demonstrate that our model has great utility in cervical cancer brachytherapy by enabling fast and accurate automatic segmentation, and has potential in improving consistency in contouring. DCT-UNet source code is available at https://github.com/JHU-MICA/DCT-UNet.
Magnetic resonance cavitation imaging for the monitoring of ultrasound therapies
Authors: Ishak Ounay , Breton Elodie , Cabras Paolo , Dumont Erik , Mondou Paul , Novell Anthony , Larrat Benoît , Vappou Jonathan
Published: October 2024

Objective. Focused ultrasound (FUS) is a promising non-invasive therapeutic approach that can be used to generate thermal and non-thermal bioeffects. Several non-thermal FUS therapies rely on FUS-induced oscillations of microbubbles (MBs), a phenomenon referred to as cavitation. Cavitation monitoring in real time is essential to ensure both the efficacy and the safety of FUS therapies. This study aims to introduce a new magnetic resonance (MR) method for cavitation monitoring during FUS therapies. Approach. By finely synchronizing the FUS pulse with an accelerated turbo spin-echo MR sequence, the cavitation effect could be quantitatively estimated on the acquired images at 1-Hz refresh rate. The proposed method was assessed in vitro in a water bath. A series of FUS pulses were generated on a silicone tube filled with MBs at different acoustic pressures (0.07–2.07 MPa) and pulse durations (20–2000 μs). MR images and passive cavitation detection (PCD) signals were simultaneously acquired for each FUS pulse. Main results. Inertial cavitation was found to induce a quantitatively interpretable signal loss on the MR image. The transition from stable to inertial cavitation was identified on MR cavitation maps with high repeatability. These results were found to be in good agreement with PCD measurements in terms of pressure thresholds between stable and inertial cavitation. MR cavitation imaging was shown to be sensitive to short and even ultrashort FUS pulses, from 2 ms down to 20 μs. The presented theoretical model suggests that the signal loss in MR cavitation imaging relies on susceptibility changes related to the diameter of the oscillating MBs. Significance. The proposed MR cavitation imaging method can both locate and characterize cavitation activity. It has therefore the potential to improve the efficacy and safety of FUS therapies, particularly for localized drug delivery applications.
The dosimetric accuracy of a commercial model-based dose calculation algorithm in modeling a six-groove direction modulated brachytherapy tandem applicator
Authors: Meftahi Moeen , Song William Y
Published: October 2024

Objective. With advancements in high-dose rate brachytherapy, the clinical translation of intensity modulated brachytherapy (IMBT) innovations necessitates utilization of model-based dose calculation algorithms (MBDCA) for accurate and rapid dose calculations. This study uniquely benchmarks a commercial MBDCA, BrachyVision ACUROSTM (BVA), against Monte Carlo (MC) simulations, evaluating dose distributions for a novel IMBT applicator, termed as the six-groove Direction Modulated Brachytherapy (DMBT) tandem, expanding beyond previous focus on partially shielded vaginal cylinder applicators, through a novel methodology. Approach. The DMBT tandem applicator, made of a tungsten alloy with six evenly spaced grooves, was simulated using the GEANT4 MC code. Subsequently, two main scenarios were created using the BVA and reproduced by the MC simulations: ‘Source at the Center of the Water Phantom (SACWP)’ and ‘Source at the Middle of the Applicator (SAMA)’ for three cubical virtual water phantoms (20 cm)3, (30 cm)3, and (40 cm)3. A track length estimator was utilized for dose calculation and 2D/3D scoring were performed. The difference in isodose surfaces/lines (i.e. coverage) at each voxel, ΔD
Isodose Levels/Lines, was thus calculated for relevant normalization points (r
ref). Results. The coverage was comparable, based on 2D scoring, between the BVA and MC isodose surfaces/lines for the region of clinical relevance, (i.e. within 5 cm radius from the source) with ΔD
Isodose Lines (r
ref: 1 cm from the source) falling within 2% for the two scenarios for all phantom sizes. For the phantom (20 cm)3, ΔD
Isodose Levels (3D scoring) recorded the range [−3.0% +6.5%] ([−7.4% +7.3%]) for 95% of the voxels of the same scoring volume for the SACWP (SAMA) scenario. Significance. The results indicated that the BVA could render comparable coverage as compared to the MC simulations in the region of clinical relevance for different phantom sizes. ΔD
Isodose Lines may offer an advantageous metric for evaluation of MBDCAs in clinical setting.
The influence of equilibrium points and initial values on multistability of a multi-scroll chaotic system and predefined-time synchronization
Authors: Yan Shaohui , Zhang Yunhe , Zhang Hanbing
Published: October 2024

In order to explore the effect of the initial value on the symmetry of the coexisting attractor, a novel multi-scroll chaotic system is designed in this paper. The system is proved to be chaotic by analysing the phase diagram, Lyapunov exponential spectrum and dissipativity of the system. Then the equilibrium point of the system is investigated and it is found that the system has four symmetric saddle focus of index 2. By analysing the dynamical behaviour of the system, it is found that the system has a special kind of multistability. Combining the properties of the orbits near the saddle focus of indicator 2, the reason for this special multistability is explained, and the effect of the positional relationship between the initial value and the saddle focus on the symmetry of the coexisting attractors is illustrated, which provides a new way of thinking to analyse the symmetric coexistence of chaotic systems. In order to verify the feasibility and application value of the system, simulation circuits are designed and predefined-time synchronization between systems of different dimensions is achieved.
Design of a robust intelligent controller based neural network for trajectory tracking of high-speed wheeled robots
Authors: Xue Wenkui , Zhou Baozhi , Chen Fenghua , Ghaderpour Ebrahim , Mohammadzadeh Ardashir
Published: October 2024

The control design of wheeled mobile robots is often accomplished based on the robot’s kinematics which imposes critical challenges in the motion tracking control of such systems. In the related literature, most works designed dynamic controllers based on the terms of voltage or torque; however, the velocity is often utilized in industrial and commercial applications. To address this issue, this paper focuses on the design of a velocity-based control for the trajectory-tracking problem of mobile robots in practical applications including measurement acquisition. The control design of the mobile robot is realized in two separate parts using kinematic control and dynamic control. The design of kinematic control is carried out based on the robot’s kinematics where the motion is described without considering the forces and torques. A radial basis function (RBF) neural network (NN) based on the model-free controller is designed for the dynamic controller of mobile robots without relying on the system dynamics. In the proposed dynamic control, a time-delay estimation is adopted to estimate the disturbances and noises in the mobile robot and remove them from the feedback loop control. Several typical scenarios of mobile robots with high-speed movements are conducted to assess the feasibility of the proposed NN controller-based time-delay estimation under noises and disturbances. To show the supremacy of the suggested controller, the dynamic responses of the mobile robot test system are compared with the prevalent controllers. The extensive simulation and real-time examinations reveal the capability of the proposed NN controller-based time-delay estimation to control high-speed mobile robots under high-level noises and disturbances.
Topological 4D gravity and gravitational defects
Authors: Boujakhrout Y , Sammani R , Saidi E H
Published: October 2024

Using the Chern-Simons formulation of AdS3 gravity as well as the Costello-Witten-Yamazaki (CWY) theory for quantum integrability, we construct a novel topological 4D gravity given by equation (5.1) with observables based on gravitational gauge field holonomies. The field action

S

4
D

grav

of this gravity has a gauge symmetry

SL
(
2
,
C
)

and reads also as the difference

S

4
D

CWY

L

−

S

4
D

CWY

R

with 4D Chern-Simons field actions

S

4
D

CWY

L

/

R

given by left/right CWY theory equation (3.9). We also use this 4D gravity derivation to build observables describing gravitational topological defects and their interactions. We conclude our study with few comments regarding quantum integrability and the extension of AdS3/CFT2 correspondence with regard to the obtained topological 4D gravity.
DFT study of electronic and nonlinear optical properties of alkaline earth metals and superalkalis doped all-cis-1, 2, 3, 4, 5, 6-hexafluorocyclohexane as an efficient excess electron system
Authors: Sohaib Muhammad , Maqbool Maria , Ayub Khurshid
Published: October 2024

Continual advancements are being pursued to discover innovative strategies for developing materials with remarkable nonlinear optical (NLO) response. Herein, electronic, geometric, thermodynamic and NLO properties of excess electron systems based on stacked Janus dimer, all-cis-1,2,3,4,5,6-hexafluorocyclohexane (C6H6F6)2 are thoroughly investigated. The excess electron systems are designed by doping alkaline earth metals (AEMs) on fluorine face and superalkalis on hydrogen face of Janus dimer. The higher values of vertical ionization energies (VIE) and interaction energies (Eint), confirm the electronic and thermodynamic stabilities of the designed complexes, respectively. Natural bond orbital (NBO) analysis is performed, and the excess electron character of the complexes is confirmed through frontier molecular orbital (FMO) analysis by highest occupied molecular orbital (HOMO) iso-densities. FMO shows a significant decrease in energy gaps (Egap) of the complexes (i.e., Eg = 1.80–3.12 eV), compared to the stacked Janus dimer (i.e., Eg = 9.41 eV). The transparency of the complexes to UV region is confirmed through UV–vis analyses, revealing their maximum absorption in visible and near-IR regions. The higher NLO response of the designed excess electron systems is further proved by the greater values of first hyperpolarizability (β

o
) i.e., up to 1.70 × 106 au. Moreover, the time dependent-density functional theory (TD-DFT) computations and two-level model are employed to investigate the controlling factors of hyperpolarizability, illustrating the contribution of transition energy (∆E3), change in dipole moment (∆μ) and oscillator strength (f

o
) in controlling the β

o
. Ab-initio molecular dynamics (AIMD) simulation further confirm that the designed superalkalide complexes are kinetically and thermally stable. The thorough investigation of these excess electron systems proves them an appropriate candidate for NLO applications.
Reconstructing redshift distributions with photometric galaxy clustering
Authors: Peng Hui , Yu Yu
Published: October 2024

The accurate determination of the true redshift distributions in tomographic bins is
critical for cosmological constraints from photometric surveys. The proposed redshift
self-calibration method, which utilizes the photometric galaxy clustering alone, is highly
convenient and avoids the challenges from incomplete or unrepresentative spectroscopic samples in
external calibration. However, the imperfection of the theoretical approximation on broad bins as
well as the flaw of the algorithm in previous work [1] risk the accuracy and
application of the method. In this paper, we propose the improved self-calibration algorithm that
incorporates novel update rules, which effectively accounts for heteroskedastic weights and noisy
data with negative values. The improved algorithm greatly expands the application range of
self-calibration method and accurately reconstructs the redshift distributions for various mock
data. Using the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument
(DESI) survey, we find that the reconstructed results are comparable to the state-of-the-art
external calibration. This suggests the exciting prospect of using photometric galaxy clustering
to reconstruct redshift distributions in the cosmological analysis of survey data.
Numerical methods for scalar field dark energy in tabletop experiments and Lunar Laser Ranging
Authors: Fischer Hauke , Sedmik René I.P.
Published: October 2024

Numerous tabletop experiments have been dedicated to exploring the manifestations of screened scalar field dark energy, such as symmetron or chameleon fields. Precise theoretical predictions require simulating field configurations within the respective experiments. This paper focuses onto the less-explored environment-dependent dilaton field, which emerges in the strong coupling limit of string theory. Due to its exponential self-coupling, this field can exhibit significantly steeper slopes compared to symmetron and chameleon fields, and the equations of motion can be challenging to solve with standard machine precision. We present the first exact solution for the geometry of a vacuum region between two infinitely extended parallel plates. This solution serves as a benchmark for testing the accuracy of numerical solvers. By reparametrizing the model and transforming the equations of motion, we show how to make the model computable across the entire experimentally accessible parameter space. To simulate the dilaton field in one- and two-mirror geometries, as well as spherical configurations, we introduce a non-uniform finite difference method. Additionally, we provide an algorithm for solving the stationary Schrödinger equation for a fermion in one dimension in the presence of a dilaton field. The algorithms developed here are not limited to the dilaton field, but can be applied to similar scalar-tensor theories as well. We demonstrate such applications at hand of the chameleon and symmetron field. Our computational tools have practical applications in a variety of experimental contexts, including gravity resonance spectroscopy (q
Bounce), Lunar Laser Ranging (LLR), and the upcoming Casimir and Non-Newtonian Force Experiment (cannex). A Mathematica implementation of all algorithms is provided.
Parametric resonance of gravitational waves in general scalar-tensor theories
Authors: Cai Yi-Fu , Domènech Guillem , Ganz Alexander , Jiang Jie , Lin Chunshan , Wang Bo
Published: October 2024

Gravitational waves offer a potent mean to test the underlying theory of gravity. In general theories of gravity, such as scalar-tensor theories, one expects modifications in the friction term and the sound speed in the gravitational wave equation. In that case, rapid oscillations in such coefficients, e.g. due to an oscillating scalar field, may lead to narrow parametric resonances in the gravitational wave strain. We perform a general analysis of such possibility within DHOST theories. We use disformal transformations to find the theory space with larger resonances, within an effective field theory approach. We then apply our formalism to a non-minimally coupled ultra-light dark matter scalar field, assuming the presence of a primordial gravitational wave background, e.g., from inflation. We find that the resonant peaks in the spectral density may be detectable by forthcoming detectors such as LISA, Taiji, Einstein Telescope and Cosmic Explorer.
Deep Neural Network Closed-loop with Raw Data for Optical Resident Space Object Detection
Authors: Zhao He , Sun Rong-Yu , Yu Sheng-Xian
Published: October 2024

Optical survey is an important means for observing resident space objects and space situational awareness. With the application of astronomical techniques and reduction method, wide field of view telescopes have made significant contributions in discovering and identifying resident space objects. However, with the development of modern optical and electronic technology, the detection limit of instruments and infrastructure has been greatly extended, leading to an extensive number of raw images and many more sources in these images. Challenges arise when reducing these data in terms of traditional measurement and calibration. Based on the amount of data, it is particularly feasible and reliable to apply machine learning algorithms. Here an end-to-end deep learning framework is developed, it is trained with a priori information on raw detections and the automatic detection task is performed on the new data acquired. The closed-loop is evaluated based on consecutive CCD images obtained with a dedicated space debris survey telescope. It is demonstrated that our framework can achieve high performance compared with the traditional method, and with data fusion, the efficiency of the system can be improved without changing hardware or deploying new devices. The technique deserves a wider application in many fields of observational astronomy.