SearcharxivSearch

arXiv subjects

Junli Li

Publications and source records attributed to Junli Li.

At least 19 recordsLinked to original sources

DetMesh-Gadep: Triangulated Surface Modeling and GPU-based Monte Carlo Efficiency Calibration of High-Purity Germanium Detectors

Sourceless efficiency calibration of high-purity germanium (HPGe) detectors can provide accurate detector-response information without experiments using radioactive calibration sources, offering advantages in both convenience and safety. In many practical implementations, this process is performed using Monte Carlo simulation; however, its performance is constrained by the accuracy of detector modeling, the operational complexity of simulation frameworks, and the computational-resource requirements associated with CPU-based parallelization. In this study, a complete detector modeling and simulation framework is proposed. The detector modeling program DetMesh can generate triangulated surface geometry from parameterized detector models, providing advantages in the representation of complex geometric boundaries. It incorporates standard geometric operations and a geometric library, and is lightweight with strong extensibility. The generated geometry is then input into Gadep, a GPU-based Monte Carlo computational kernel, to enable rapid simulation. For $1\times 10^8$ particles, a single RTX 4090 achieved a speedup factor of 13.53 compared with simultaneous computation using 60 CPU cores. The proposed framework has low implementation cost and broad applicability, providing a complete solution for refined detector modeling and calibration.

physics.ins-det

Unraveling the Redox Mechanisms Underlying FLASH Radiotherapy: Critical Dose Thresholds and NRF2-Driven Tissue Sparing

FLASH radiotherapy (FLASH-RT) achieves tumor control comparable to conventional dose-rate irradiation (CONV-RT) while significantly reducing radiation damage to normal tissues. However, the physical conditions triggering the FLASH sparing effect remain unclear, and mechanisms related to oxidative stress and redox regulation are poorly understood. This study utilizes a murine acute intestinal toxicity model to investigate how beam parameters influence the FLASH sparing effect and tumor control using innovative FLASH-RT and CONV-RT combined irradiation. Results demonstrate for the first time that a substantially reduced FLASH dose can still elicit sparing effect, provided a total dose threshold is met. Kinetic simulation and experimental validation demonstrate that FLASH-RT enhances peroxyl radical recombination, reducing reactive oxygen species (ROS) and malondialdehyde levels. Antioxidant interventions further confirm the essential role of free radicals. RNA sequencing and molecular analyses reveal that FLASH-RT activates the nuclear factor E2-related factor 2 (NRF2) antioxidant pathway while suppressing extracellular signal-regulated kinases (ERK) signaling, thereby enhancing cellular redox defenses, reducing apoptosis, and mitigating ROS-mediated tissue injury. These findings highlight the feasibility of optimizing the FLASH-RT therapeutic window through redox modulation and provide a foundation for developing free radical-targeted strategies to improve its therapeutic efficacy.

physics.med-ph

Spin order, spin excitations, and RIXS spectra of spin-1/2 tetramer chains

We investigate the spin dynamics of a 1D spin-1/2 Heisenberg tetramer chain. Employing a combination of Density Matrix Renormalization Group, quantum renormalization group, and perturbation theory techniques, we compute the energy levels and the quantum phase diagram, analyze the phase transitions, and evaluate the $L$ and $K$ -edge resonant inelastic x-ray scattering (RIXS) spectrum of fractionalized and collective (single and multi-particle) excitations. Our calculations suggest that the chain can transition between a hidden $Z_2\times Z_2$ discrete symmetry preserving tetramer phase and a Haldane phase with non-vanishing string order that breaks the hidden symmetry. These two gapped phases are intervened by an intermediate deconfined quantum critical state comprising of free spins and three-site doublets, which is a gapless critical phase with deconfined spinons. We find that the tetramer chain can support fractionalized (spinon) and collective (triplon and quinton) excitations. In the ferromagnetic intra-tetramer limit, the chain can support a quinton excitation which has a five-fold degenerate excited state. String order parameter calculations suggest CuInVO$_5$ to be in a Haldane-like phase whose $L$ -edge RIXS spectrum can support observable triplon and quinton excitations. We also identify possible two-particle excitations (two-singlon, two-triplon, triplon-quinton, and two-quinton excitations) resulting from the double spin-flip effect in the $K$ -edge RIXS spectrum.

cond-mat.str-el

Impact of Oxygen on DNA Damage Distribution in 3D Genome and its Correlation to Oxygen Enhancement Ratio after High-LET Irradiation

The variation of the oxygen enhancement ratio (OER) across linear energy transfer (LET) currently lacks a comprehensive mechanistic interpretation and a mechanistic model. Our earlier research revealed a significant correlation between the distribution of double-strand breaks (DSBs) within 3D genome and radiation-induced cell death, which offers valuable insights into the oxygen effect. We propose a model where the reaction of oxygen is represented as the probability of inducing DNA strand breaks. Then it is integrated into a track-structure Monte Carlo simulation to investigate the impact of oxygen on the distribution of DSBs within 3D genome. Using the parameters from our previous study, we calculate the OER values related to cell survival. Results show that the incidence ratios of clustered DSBs within a single topologically associating domain (TAD) (case 2) and within frequently interacting TADs (case 3) under aerobic and hypoxic conditions align with the trend in the OER of cell survival across LET. Our OER curves exhibit good correspondence with experimental data. This study provides a potentially mechanistic explanation for changes in OER across LET. High-LET irradiation leads to dense ionization events, resulting in an overabundance of lesions that readily induce case 2 and case 3, which have substantially higher probabilities of cell killing than other damage patterns. This may contribute to the main mechanism governing the variation of OER for high LET. Our study further underscores the importance of the DSB distribution within 3D genome in the context of radiation-induced cell death.

physics.bio-ph

Correlation Between DNA Double-Strand Break Distribution in 3D Genome and Radiation-Induced Cell Death

The target theory is the most classical hypothesis explaining radiation-induced cell death, the physical or biological nature of the "target" remains ambiguous. This study hypothesizes that the distribution of DNA double-strand breaks (DSBs) within the 3D genome is a pivotal factor affecting the probability of radiation-induced cell death. We propose that clustered DSBs in DNA segments with high interaction frequencies are more susceptible to leading to cell death than isolated DSBs. Topologically associating domains (TAD) can be regarded as the reference unit for evaluating the impact of DSB clustering in the 3D genome. To quantify this correlation between the DSB distribution in 3D genome and radiation-induced effect, we developed a simplified model considering the DSB distribution across TADs. Utilizing track-structure Monte Carlo codes to simulate the electron and carbon ion irradiation, we calculated the incidence of each case across a variety of radiation doses and LETs. Our simulation results indicate that DSBs in TADs with frequent interactions (case 3) are significantly more likely to induce cell death than clustered DSBs within a single TAD (case 2). Moreover, case 2 is significantly more likely to induce cell death than isolated DSBs (case 1). The curves of the incidence of case 2 and case 3 versus LETs have a similar shape to the radiation quality factor used in radiation protection. This indicates that these two cases are also associated with the stochastic effects induced by high LET irradiation. Our study underscores the significance of the 3D genome structure in the fundamental mechanisms of radiobiological effects. The hypothesis in our research offers novel perspectives on the mechanisms that regulate radiobiological effects. Moreover, it serves as a valuable reference for establishing mechanistic models that can predict cell survival under different doses and LETs.

physics.med-ph

Influencing Factors of the FLASH Effect: Unveiling the Importance of Free Radicals

Purpose: Our aim was to elucidate the critical factors responsible for inducing the FLASH effect, focusing on the role of free radicals through simulation and experimental approaches. Methods and Materials: The whole abdomen of C57BL/6 mice was irradiated with 6 MeV electron beam. The endpoint was acute intestinal toxicity quantified by histological score. Total doses ranging from 6 to 15 Gy were evaluated. The impact of the mean dose rate (MDR) was assessed in the range of 40 to 900 Gy/s. Dose per pulse (DPP) of 0.5 Gy and 3 Gy were compared. The recombination of peroxyl radicals were simulated. Further comparisons were conducted by incorporating the antioxidant amifostine. Results: When varying total doses with a constant MDR of 900 Gy/s, the FLASH effect was not observed until the dose reached 15 Gy. For a total dose of 15 Gy and varying MDR, the FLASH effect was observed only when MDR reached 100 Gy/s. For a dose of 15 Gy and an MDR of 150 Gy/s, no significant difference in biological effect was observed between low DPP and high DPP. The simulation results indicated that the fraction of peroxyl radicals recombination remained nearly zero at conventional dose rates. For FLASH irradiation, the recombination fraction increased linearly with the dose. Notably, the dose delivery time corresponding to 50% change in the recombination fraction was approximately 300 ms. The addition of amifostine effectively eliminated the difference between FLASH group and CONV group. Conclusions: The critical requirement for observing the sparing effect at the biological endpoint is the administration of an adequate dose within the time window of the radical reaction. Additionally, the important role of free radical was verified after introducing antioxidants, suggesting that the generation and recombination of free radicals are pivotal factors influencing the FLASH sparing effect.

physics.med-ph

Resonant inelastic x-ray scattering spectra of spinon, doublon, and quarton excitations of a spin-$\frac{1}{2}$ antiferromagnetic Heisenberg trimer chain

We investigate the excitation spectra of a spin-1/2 antiferromagnetic Heisenberg trimer spin chain by employing a combination of numerical and theoretical techniques. Utilizing the Krylov-space correction-vector method in density matrix renormalization group (DMRG), we calculate both the direct and indirect resonant inelastic x-ray scattering (RIXS) spectra for the trimer spin chain. To interpret the observed features in the RIXS spectra, we perform a theoretical perturbative analysis to compute the energy dispersions which are then utilized to determine the density of states (DOS) for both the single-particle and the two-particle excitation spectra. Our results show that the single-particle continua of the direct RIXS spectrum align with the energy levels observed in the DOS spectra of spinon, doublon, and quarton excitations. Furthermore, the two-particle continua are revealed in the indirect RIXS process, where all possible single particle excitations combine to form the various two-particle excitations of the trimer spin chain. Based on our calculations, we propose the RIXS mechanism of generating the fractionalized (spinon) and collective (doublon and quarton) excitations in the trimer spin chain at both the $L$-edge and the $K$-edge, including discussing the interplay of these excitations in the RIXS spectrum for various trimer coupling strength. The computed energy range of the excitations suggest the possibility of experimental detection at both the $L$-edge and the $K$-edge within the current capabilities of RIXS instrumentation resolution.

cond-mat.str-el

Mathematical Analysis of FLASH Effect Models Based on Theoretical Hypotheses

Clinical applications of FLASH radiotherapy require formulas to describe how the FLASH radiation features and other related factors determine the FLASH effect. Mathematical analysis of the models can connect the theoretical hypotheses with the radiobiological effect, which provides the foundation for establishing clinical application models. We abstract the complex models of the oxygen depletion hypothesis and radical recombination-antioxidants hypothesis into concise mathematical equations. The equations are solved to analyze how the radiation features and other factors influence the FLASH effect. Then we propose methodologies for determining the parameters in the models and utilizing the models to predict the FLASH effect.The formulas linking the physical, chemical and biological factors to the FLASH effect are obtained through mathematical derivation of the equation. The analysis indicates that the initial oxygen concentration, radiolytic oxygen consumption and oxygen recovery are key factors for the oxygen depletion hypothesis and that the level of antioxidants is the key factor for the radical recombination-antioxidants hypothesis. According to the model derivations and analysis, the methodologies for determining parameters and predicting the FLASH effect are proposed: the criteria for data filtration, the strategy of hybrid FLASH and conventional dose rate irradiation to ensure the acquisition of effective experimental data across a wide dose range, the pipelines of fitting parameters and predicting the FLASH effect. The derived formulas can be used to calculate the FLASH effect in future clinical FLASH radiotherapy. The proposed methodologies guide to obtain sufficient high-quality datasets and utilize them to predict the FLASH effect. Furthermore, this study indicates the key factors of the FLASH effect and offers clues to further explore the FLASH mechanism.

physics.med-ph

Efficient Monaural Speech Enhancement using Spectrum Attention Fusion

Speech enhancement is a demanding task in automated speech processing pipelines, focusing on separating clean speech from noisy channels. Transformer based models have recently bested RNN and CNN models in speech enhancement, however at the same time they are much more computationally expensive and require much more high quality training data, which is always hard to come by. In this paper, we present an improvement for speech enhancement models that maintains the expressiveness of self-attention while significantly reducing model complexity, which we have termed Spectrum Attention Fusion. We carefully construct a convolutional module to replace several self-attention layers in a speech Transformer, allowing the model to more efficiently fuse spectral features. Our proposed model is able to achieve comparable or better results against SOTA models but with significantly smaller parameters (0.58M) on the Voice Bank + DEMAND dataset.

cs.SD

Periodicity staircase in a Fe/Gd magnetic thin film

Presence of multiple competing periodicities may result in a system to go through states with modulated periodicities, an example of which is the self-similar staircase-like structure called the Devil's staircase. Herein we report on a novel staircase structure of domain periodicity in an amorphous and achiral Fe/Gd magnetic thin film wherein the reciprocal space wavevector \textbf{Q} due to the ordered stripe domains does not evolve continuously, rather exhibits a staircase structure. Resonant X-ray scattering experiments show jumps in the periodicity of the stripe domains as a function of an external magnetic field. When resolved in components, the step change along Q$_x$ was found to be an integral multiple of a minimum step height of 7 nm, which resembles closely to the exchange length of the system. Modeling the magnetic texture in the Fe/Gd thin film as an achiral spin arrangement, we have been able to reproduce the steps in the magnetization using a Landau-Lifshitz spin dynamics calculation. Our results indicate that anisotropy and not the dipolar interaction is the dominant cause for the staircase pattern, thereby revealing the effect of achiral magnetism.

cond-mat.mtrl-sci

SPP-CNN: An Efficient Framework for Network Robustness Prediction

This paper addresses the robustness of a network to sustain its connectivity and controllability against malicious attacks. This kind of network robustness is typically measured by the time-consuming attack simulation, which returns a sequence of values that record the remaining connectivity and controllability after a sequence of node- or edge-removal attacks. For improvement, this paper develops an efficient framework for network robustness prediction, the spatial pyramid pooling convolutional neural network (SPP-CNN). The new framework installs a spatial pyramid pooling layer between the convolutional and fully-connected layers, overcoming the common mismatch issue in the CNN-based prediction approaches and extending its generalizability. Extensive experiments are carried out by comparing SPP-CNN with three state-of-the-art robustness predictors, namely a CNN-based and two graph neural networks-based frameworks. Synthetic and real-world networks, both directed and undirected, are investigated. Experimental results demonstrate that the proposed SPP-CNN achieves better prediction performances and better generalizability to unknown datasets, with significantly lower time-consumption, than its counterparts.

cs.LG

Raman scattering study of multimagnon (bi- and tri-magnon) excitations and rotonlike points in the distorted triangular lattice antiferromagnet

We investigate the experimental signatures of Raman spectroscopy of bi- and tri-magnon excitations in the distorted triangular lattice antiferromagnets alpha-LCr2O4 (L=Sr, Ca). We utilize spin wave theory to analyze the nearly 120 degree spin-3/2 spiral ordered antiferromagnetic ground state to compute the single-magnon density of states, single-magnon dispersion, and bimagnon and trimagnon Raman spectra (polarized and unpolarized). It is found that Raman scattering is capable of capturing the effect of the rotonlike M and M' points on the bimagnon Raman spectrum. Our calculation confirms the connection between single-magnon rotonlike excitation energy and bimagnon Raman excitation spectrum observed experimentally. The roton energy minimum in momentum space is half of the energy of a bimagnon excitation signal. The experimental magnetic Raman scattering result displays two peaks which have a Raman shift of 15 meV and 40 meV, respectively. Theoretical modeling and analysis of the experimental spectrum of alpha-SrCr2O4 within our distorted Heisenberg Hamiltonian lattice suggests that the low-energy peak at 15 meV is associated with the bimagnon excitation, whereas the high-energy peak around 40 meV is primarily a trimagnon excitation. Based on our fitting procedure we propose a new set of magnetic interaction parameters for alpha-SrCr2O4. These parameters reproduce not only the experimental Raman spectrum, but also the inelastic neutron scattering response (including capturing high energy magnon branches). We also compute the unpolarized bimagnon and trimagnon Raman spectra for alpha-CaCr2O4. Furhtermore, we found that the polarization sensitivity of Raman spectrum can be utilized to distinguish the bi- and tri-magnon excitation channels.

cond-mat.str-el

CNN-based Prediction of Network Robustness With Missing Edges

Connectivity and controllability of a complex network are two important issues that guarantee a networked system to function. Robustness of connectivity and controllability guarantees the system to function properly and stably under various malicious attacks. Evaluating network robustness using attack simulations is time consuming, while the convolutional neural network (CNN)-based prediction approach provides a cost-efficient method to approximate the network robustness. In this paper, we investigate the performance of CNN-based approaches for connectivity and controllability robustness prediction, when partial network information is missing, namely the adjacency matrix is incomplete. Extensive experimental studies are carried out. A threshold is explored that if a total amount of more than 7.29\% information is lost, the performance of CNN-based prediction will be significantly degenerated for all cases in the experiments. Two scenarios of missing edge representations are compared, 1) a missing edge is marked `no edge' in the input for prediction, and 2) a missing edge is denoted using a special marker of `unknown'. Experimental results reveal that the first representation is misleading to the CNN-based predictors.

eess.SY

A Learning Convolutional Neural Network Approach for Network Robustness Prediction

Network robustness is critical for various societal and industrial networks again malicious attacks. In particular, connectivity robustness and controllability robustness reflect how well a networked system can maintain its connectedness and controllability against destructive attacks, which can be quantified by a sequence of values that record the remaining connectivity and controllability of the network after a sequence of node- or edge-removal attacks. Traditionally, robustness is determined by attack simulations, which are computationally very time-consuming or even practically infeasible. In this paper, an improved method for network robustness prediction is developed based on learning feature representation using convolutional neural network (LFR-CNN). In this scheme, higher-dimensional network data are compressed to lower-dimensional representations, and then passed to a CNN to perform robustness prediction. Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors; 2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability; 3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations; 4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures.

eess.SY

SAGE : A Monte Carlo Simulation Framework for Experiments with Germanium Detectors

A Geant4-based simulation framework for rare event searching experiments with germanium detectors named SAGE is presented with details. It is designed for simulating, assessing background distribution, and investigating the response of the germanium detectors. The SAGE framework incorporates its experiment-specific geometries and custom attributes, including the event generators, physics lists and output format, to satisfy various simulation objectives. Its docker image has been prepared for virtualizing and distributing the SAGE framework. Deployment of a Geant4-based simulation will be convenient under this docker image. The implemented geometries include p-type point contact and broad energy germanium detectors with environmental surroundings, and these hierarchical geometries can be easily extended. Users select these custom attributes via the JSON configuration files. The aforementioned attributes satisfy the simulation demands and make SAGE a generic and powerful simulation framework for the CDEX experiment.

physics.ins-det

A marine radioisotope gamma-ray spectrum analysis method based on Monte Carlo simulation and MLP neural network

The monitoring of Cs-137 in seawater using scintillation detector relies on the spectrum analysis method to extract the Cs-137 concentration. And when in poor statistic situation, the calculation result of the traditional net peak area (NPA) method has a large uncertainty. We present a machine learning based method to better analyze the gamma-ray spectrum with low Cs-137 concentration. We apply multilayer perceptron (MLP) to analyze the 662 keV full energy peak of Cs-137 in the seawater spectrum. And the MLP can be trained with a few measured background spectrums by combining the simulated Cs-137 signal with measured background spectrums. Thus, it can save the time of preparing and measuring the standard samples for generating the training dataset. To validate the MLP-based method, we use Geant4 and background gamma-ray spectrums measured by a seaborne monitoring device to generate an independent test dataset to test the result by our method and the traditional NPA method. We find that the MLP-based method achieves a root mean squared error of 0.159, 2.3 times lower than that of the traditional net peak area method, indicating the MLP-based method improves the precision of Cs-137 concentration calculation

physics.ins-det

Study on cosmogenic activation in copper for rare event search experiments

The rare event search experiments using germanium detectors are performed in the underground laboratories to prevent cosmic rays. However, the cosmogenic activation of the cupreous detector components on the ground will generate long half-life radioisotopes and contribute continually to the expected background level. We present a study on the cosmogenic activation of copper after 504 days of exposure at an altitude of 2469.4 m outside the China Jinping Underground Laboratory (CJPL). The specific activities of the cosmogenic nuclides produced in the copper bricks were measured using a low background germanium gamma-ray spectrometer at CJPL. The production rates at sea level, in units of nuclei/kg/day, are 18.6 \pm 2.0 for Mn-54, 9.9 \pm 1.3 for Co-56, 48.3 \pm 5.5 for Co-57, 51.8 \pm 2.5 for Co-58 and 39.7 \pm 5.7 for Co-60, respectively. Given the expected exposure history of the germanium detectors, a Monte Carlo simulation is conducted to assess the cosmogenic background contributions of the detectors' cupreous components.

physics.ins-det

Modeling of cellular response after FLASH irradiation: a quantitative analysis based on the radiolytic oxygen depletion hypothesis

Purpose: Recent studies suggest ultra-high dose rate (FLASH) irradiation can spare normal tissues from radiotoxicity, while efficiently controlling the tumor, and this is known as the FLASH effect. This study performed theoretical analyses about the impact of radiolytic oxygen depletion (ROD) on the cellular responses after FLASH irradiation. Methods: Monte Carlo simulation was used to model the ROD process, determine the DNA damage, and calculate the amount of oxygen depleted (LROD) during FLASH exposure. A mathematical model was applied to analyze oxygen tension (pO2) distribution in human tissues and the recovery of pO2 after FLASH irradiation. DNA damage and cell survival fractions (SFs) after FLASH irradiation were calculated. The impact of initial cellular pO2, FLASH pulse number, pulse interval, and radiation quality of the source particles on ROD and subsequent cellular responses were systematically evaluated. Results: The simulated electron LROD range was 0.38-0.43 μM/Gy when pO2 ranged from 7.5-160 mmHg. The calculated DNA damage and SFs show that radioprotective effect is only evident in cells with a lower pO2. Different irradiation setups alter the cellular responses by modifying the pO2. Single pulse delivery or multi-pulse delivery with pulse intervals shorter than 10-50 ms resulted in fewer DNA damages and higher SFs. Source particles with a low radiation quality have a higher capacity to deplete oxygen, and thus, lead to a more conspicuous radioprotective effect. Conclusions: The FLASH radioprotective effect due to ROD may only be observed in cells with a low pO2. Single pulse delivery or multi-pulse delivery with short pulse intervals are suggested for FLASH irradiation to avoid oxygen tension recovery during pulse intervals. Source particles with low radiation quality are preferred for their conspicuous radioprotective effects.

physics.med-ph