bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultrafast energy-dispersive soft-x-ray diffraction in the water window with a laser-driven source
Authors: Jarecki Jasmin , Hennecke Martin , Sidiropoulos Themistoklis , Schnuerer Matthias , Eisebitt Stefan , Schick Daniel
Published: October 2024

Time-resolved soft-x-ray-diffraction experiments give access to microscopic processes in a broad range of solid-state materials by probing ultrafast dynamics of ordering phenomena. While laboratory-based high-harmonic generation (HHG) light sources provide the required photon energies, their limited photon flux is distributed over a wide spectral range, rendering typical monochromatic diffraction schemes challenging. Here, we present a scheme for energy-dispersive soft-x-ray diffraction with femtosecond temporal resolution and photon energies across the water window from 200 to 600 eV. The experiment utilizes the broadband nature of the HHG emission to efficiently probe large slices in reciprocal space. As a proof-of-concept, we study the laser-induced structural dynamics of a Mo/Si superlattice in an ultrafast, non-resonant soft-x-ray diffraction experiment. We extract the underlying strain dynamics from the measured shift of its first order superlattice Bragg peak in reciprocal space at photon energies around 500 eV via soft-x-ray scattering simulations.
Recent developments in preventing catheter-related infections based on biofilms: A comprehensive review
Authors: So Byeongchan , Kim Jongwon , Jo Jung Ki , So Hongyun
Published: October 2024

Urinary and vascular catheters are among the most commonly used medical devices. However, infections caused by biofilm formation on the surface of catheters are a major cause of healthcare-associated infections. Traditional methods, such as using antimicrobials to prevent such infections, generally have short-term effects, and treatment is challenging owing to the emergence of antimicrobial-resistant bacteria. This review aims to evaluate the limitations of conventional catheter-related infection prevention efficacy, such as currently used antimicrobials, and analyze the efficacy and limitations of potential alternatives to prevent catheter-related infections that have not yet been commercialized, classified by the transition stages of biofilm formation. We intend to provide profound insights into the ideal technologies for preventing catheter-associated tract infections and present perspectives on future directions in this field.
On the number of limit cycles for a perturbed cubic reversible Hamiltonian system
Authors: Yang Jihua
Published: October 2024

This paper is concerned with the limit cycle problem of a cubic reversible Hamiltonian system under perturbation of polynomials of degree n with a switching line x=0. The upper and lower bounds of the number of limit cycles are obtained using the first order Melnikov function and its expansion. The method for calculating the Melnikov function relies upon some iterative formulas, which differs from other approaches.
Effective diffusion along the backbone of combs with finite-span 1D and 2D fingers
Authors: Bettarini Giovanni , Piazza Francesco
Published: October 2024

Diffusion in complex heterogeneous media, such as biological tissues or porous materials, typically involves constrained displacements in tortuous structures and sticky environments. Therefore, diffusing particles experience both entropic (excluded-volume) forces and the presence of complex energy landscapes. In this situation, one may describe transport through an effective diffusion coefficient. In this paper, we examine comb structures with finite-length 1D and finite-area 2D fingers, which act as purely diffusive traps. We find that there exists a critical width of 2D fingers, above which the effective diffusion along the backbone is faster than for an equivalent arrangement of 1D fingers. Moreover, we show that the effective diffusion coefficient is described by a general analytical form for both 1D and 2D fingers, provided the correct scaling variable is identified as a function of the structural parameters. Interestingly, this formula corresponds to the well-known general situation of diffusion in a medium with fast reversible adsorption. Finally, we show that the same formula describes diffusion in the presence of dilute potential energy traps, e.g., through a landscape of square wells. While diffusion is ultimately always the result of microscopic interactions (with particles in the fluid, other solutes, and the environment), effective representations are often of great practical use. The results reported in this paper help clarify the microscopic origins and the applicability of global, integrated descriptions of diffusion in complex media.
Thermally tunable microring resonators based on germanium-on-insulator for mid-infrared spectrometer
Authors: Lim J. , Shim J. , Kim I. , Kim S. K. , Geum D.-M. , Kim S.
Published: October 2024

We present a thermally tunable microring resonator (MRR) implemented on a Ge-on-insulator (Ge-OI) photonic platform tailored for mid-infrared spectrometer applications. Thanks to the favorable thermo-optic effect of Ge, we characterized the optical and thermal properties of the thermally tunable Ge-OI MRR through rigorous optical and thermal numerical analyses. Building upon the simulation, a ring-shaped Au heater was successfully integrated into the Ge-OI MRR that was fabricated by using a direct wafer bonding process, followed by electron-beam lithography and dry etching techniques. Observations via thermo-reflectance microscopy revealed the temperature change within the Ge induced by heat transfer from the applied bias to the Au heater. Notably, the measured temperature change of 17 K at an applied electrical power of 181.7 mW closely aligned with the simulated values. In optical measurement, the heater-integrated Ge-OI MRR exhibited the tunability of 33.7 nm/W (0.36 nm/K) and the loaded Q factor of 21k at 4.2 µm wavelength with no bias. Hence, our demonstration of the Ge-OI tunable ring filter for mid-IR spectrometers could be a promising technology employing photonic integrated circuits for diverse applications in optical communication and spectral sensing.
High-speed Ta2O5-based threshold switching memristor for LIF neurons
Authors: Yao Linyan , Ma Chuan , He Zixi , Wang Yiheng , Song Hongjia , Zhong Xiangli , Wang Jinbin
Published: October 2024

Due to their high similarity to biological ion channels, low power consumption, small footprint, and the fact that they do not require reset circuits, threshold switching memristors have been intensively studied for simulating neurons in neuromorphic chips. Switching speed is one of the key challenges which limit the application of threshold switching memristors in chips. In this study, Ta2O5 threshold switching memristors with high switching speeds were prepared by doping with silver. The results show that 14 wt. % Ag doped Ta2O5 threshold switching memristors exhibit excellent bi-directional threshold switching performance, featuring fast switching speeds (<20 ns, <18 ns), low leakage currents (<10 pA), and high switching ratio (>107). According to the field nucleation theory, the rapid switching speed can be attributed to the low nucleation energy (0.26 eV) of silver within the Ta2O5 matrix, which is achieved by incorporating 14 wt. % Ag during the doping process. Based on Pspice, a LIF (leaky integrate-and-fire) neuron based on the silver nanoparticles doped Ta2O5 threshold switching memristors is built, and its firing function has been simulated. The results show that the LIF neuron with a short switching time is able to excite pulse spiking with high frequencies. These results demonstrated that the silver nanoparticles doped Ta2O5-based threshold switching memristors hold significant potential for constructing high-speed artificial neural networks.
Improving fluid identification in well logging using Continuous Wavelet Transform and Vision Transformers: An innovative approach
Authors: Sun Youzhuang , Pang Shanchen , Qiu Zhihan , Zhang Yongan
Published: October 2024

Well logging fluid prediction is one of the key steps in assessing oil and gas reserves. By analyzing downhole logging data, different types of fluids contained in underground rocks, such as crude oil, natural gas, and water, can be determined. This information is crucial for assessing the abundance and recoverable reserves of oil and gas resources and helps guide oil and gas exploration and development work. We have introduced a novel model called CWT (Continuous Wavelet Transform)-ViT (Vision Transformer). CWT can simultaneously provide frequency information at different scales, enabling the model to analyze downhole logging data more comprehensively and accurately at different scales. Underground rock structures often exhibit features at multiple scales, and CWT can effectively capture these features, aiding in better differentiation of different types of fluids. The ViT model utilizes the Transformer architecture, allowing for global attention over input sequences without being limited by sequence length. This enables the model to comprehensively understand the overall information of downhole logging data and extract richer features. For complex geological structures and fluid distributions in geological exploration, the global attention mechanism helps the model better grasp the overall situation, thereby improving the accuracy of fluid prediction. When we used the CWT-ViT method for well logging fluid prediction, we achieved a high accuracy rate of 97.50% in the first dataset, which further improved to 97.77% in the second dataset. These results demonstrate the significant robustness and efficiency of the CWT-ViT method in lithology prediction using well logging data. We also conducted blind well experiments, and our CWT-ViT model outperformed other models, achieving a blind well prediction accuracy of 97.36%. Therefore, the experiments indicate that the key to improving accuracy in well logging fluid prediction with CWT lies in its multiscale analysis capability, effectively capturing different fluid characteristic frequencies. Additionally, CWT enhances signal features and removes noise, increasing the precision of fluid identification. Finally, the integration with ViT further optimizes fluid prediction performance, making it outstanding in complex geological environments. The advantages of ViT in fluid prediction include its excellent sequence modeling capability, effective handling of long-distance dependencies, and enhanced ability to capture fluid characteristics in complex well logging data.
MicroLED arrays—A perspective beyond displays
Authors: Prades J. D. , Meierhofer F. , Diéguez A. , Waag A.
Published: October 2024

MicroLEDs, particularly when integrated with CMOS microelectronics, represent a significant advancement in nitride technology. While large-area, high-power LEDs for solid-state lighting have seen extensive optimization, microLEDs present unique fabrication and characterization challenges. Utilizing standard CMOS design and foundry services for silicon driver electronics, a new hybrid interconnect technology must be developed for chip–chip or wafer–wafer integration, necessitating much higher lateral resolution than current bonding technologies. Beyond display technology, microLED integration opens avenues for groundbreaking applications such as highly efficient nanosensors, miniaturized optical neuromorphic networks, and robust chip-based microscopy. This paper explores recent advancements in nitride/CMOS hybrid modules, providing an overview of current technologies and future possibilities in this dynamic field.
Direct simulation Monte Carlo-driven optimization of vacuum intakes for air-breathing electric thrusters in very low earth orbits
Authors: Fontanarosa Donato , Toscano Angelica Maria , Ficarella Antonio , Giorgi Maria Grazia De
Published: October 2024

The performance of an atmosphere-breathing electric propulsion (ABEP) intake has been investigated with a focus on the direct simulation Monte Carlo (DSMC) method. A numerical dataset was derived from extensive DSMC analysis of rarefied flow across various intake configurations. The intake geometry, based on a concept from the literature, comprises a cylindrical body with four annular coaxial channels and a conical convergent diffuser. By maintaining the aspect ratio of the coaxial channels, the DSMC simulations were performed by changing three key parameters: inlet area, convergent diffuser angle, and operating discharge voltage, at altitudes ranging from 140 to 200 km. The analysis of the ABEP system revealed that altitude has the most significant influence on the discharge power, while the effects of the diffuser angle and inlet area are comparatively smaller. Analysis at fixed altitudes reveals a strong influence of altitude on discharge power, while the diffuser angle and the inlet area play a minor role. The results also show that the sensitivity of the discharge power to the diffuser angle increases as the altitude approaches the highest level of 200 km. Furthermore, an evolutionary-based optimization methodology was applied, taking into account the requirements of a drag-to-thrust ratio of less than 1 and a discharge power of less than 12 kW. Optimization analysis in the full altitude range revealed that the optimal diffuser angle falls within the narrow range of 15°–20°, corresponding to an optimal operating altitude range of 170–178 km.
Dynamic control of elastic wave transmission by a digital metalayer
Authors: Hong Guangfu , Jia Han , Yang Yu , Yang Yunhan , Yang Yuzhen , Yang Jun , Yuan Xujin
Published: October 2024

Piezoelectric materials with shunt circuits have aroused much research interest due to flexible parameter adjustment. However, shunted piezoelectric elements are difficult to respond to the dynamic changes in the whole system due to the absence of autonomous control ability, which constrains their practical applications. Here, we propose a digital metalayer to control the wave energy transmission across different materials in real time. This digital metalayer comprises a stack of multiple piezoelectric lead zirconate titanate (PZT) disks connected with shunt capacitance circuits (SCCs). The external digital control system adjusts the effective acoustic impedance of the PZT disks through digital potentiometers and microprogrammed control unit, thereby enabling digital manipulation of wave transmission. Utilization of optimized SCCs further enhances adjustment accuracy, supporting both negative and positive capacitance values. The experiments demonstrate that this digital metalayer exhibits remarkable performance in controlling wave transmission. Moreover, the distinct variations in transmitted amplitudes, precisely controlled by the digital metalayer, are harnessed as binary signals for information transmission. An image of letters is encoded into a series of amplitude-modulated waves by the digital metalayer and clearly transmitted. The proposed digital metalayer shows great promise for applications in intelligent impedance matching and the real-time modulation systems.
On the isotropy of temperature fluctuations in passive scalar turbulence
Authors: Paul Immanuvel
Published: October 2024

We use direct numerical simulation to investigate the scalar gradient skewness downstream of a square grid element. The passive scalar is generated by applying a constant heat flux on the grid element. We primarily focus on the far-downstream grid-element centerline, where the scalar turbulence is homogeneous, and there are no mean velocity or scalar gradients. In this region, some discrepancy exists in the literature concerning the isotropy of the scalar. To the best of our knowledge, this is the first study that measures scalar gradients in all three directions. We detect nonzero skewness for the lateral scalar gradients, while in the streamwise direction, the skewness is zero. We show, through statistical analysis, that the nonzero values are solely due to steep gradients called cliffs. The cliffs originate from the bars of the grid-element that generate sharp mean scalar gradients along the lateral directions in the near wake. These mean gradients decay as the flow develops downstream, but the convected cliffs remember the generating upstream conditions and, in particular, the direction of the mean scalar gradient. Due to this memory effect, the cliffs align preferentially along a specific direction despite the absence of a local mean scalar gradient, thus making the homogeneous scalar field anisotropic. We also report some hitherto undocumented properties of cliffs and ramps through conditional statistical analysis. Finally, we corroborate our conclusions with two additional simulations, one involving grid-element turbulence in the presence of a transverse mean scalar gradient and the other scalar turbulence due to a heated cylinder.
Non-monotonic dependence of the bow shock stand-off distance on the velocity of a CO2 flow about a sphere
Authors: Bondar Yevgeniy A. , Shoev Georgy V.
Published: October 2024

A non-monotonic dependence of the bow shock stand-off distance around a spherical body recently observed in ballistic range experiments in CO2 is explained by a qualitative theoretical analysis and confirmed numerically. The analysis is based on the estimation of the average density in the shock layer with the Rankine–Hugoniot relations on the normal shock for chemically frozen and chemically equilibrium limits using a simplified chemistry model. The analysis reveals that a maximum of the density ratio across the shock and, therefore, a minimum of the stand-off distance as functions of the flight velocity are normally observed in CO2 and other gases, such as additionally considered N2, both in frozen and equilibrium flows. The low dissociation energy of CO2 results in relatively low flight velocities (around 5 km/s) at which the extrema are observed. It makes the effect more readily detectable in experiments in CO2 than in the Earth's atmosphere gases. The results of numerical simulations of the CO2 flow by solving the Navier–Stokes equations agree well with the ballistic range experiments and fully support the results of the theoretical analysis.
Effects of a spoiler attachment on the wake flow of a bed-mounted horizontal pipe
Authors: Devi Kalpana , Hanmaiahgari Prashanth Reddy , Pu Jaan H.
Published: October 2024

This research investigated the spatial flow field of a pipe with a spoiler attachment and the modifications in the wake flow field of a bed-mounted horizontal pipe due to the attachment of a spoiler to the pipe for two different approach flow conditions. To attain the above-mentioned objective, the spatial evolution of the mean and turbulence flow properties in the flow field of the cylinder with an attached spoiler was determined. In addition, the mean flow and turbulence properties of a pipe without a spoiler attachment were compared with the properties of a pipe with an attached spoiler of height 0.2 D. For this purpose, two approach flow Reynolds numbers based on the pipe's diameter (D) and the free-stream velocity (U∞), Re∞ = 8850 and 11650, were considered. Three-dimensional (3D) velocity measurements were recorded with an acoustic Doppler velocimetry (ADV) between locations 4 D upstream (u/s) and 12 D downstream (d/s) of the pipe. It is observed that the length of the recirculation region is increased extensively due to the spoiler on the pipe from 6 D and 6.4 D to 10.7 D. The peak streamwise velocities for both Reynolds numbers are located near the free-water surface, as separated flows are deflected upward and result in enhanced free-stream velocities, which are higher than their approach flow free-stream velocities. In addition to that, the strength of the backflow is enhanced by 23% due to the attachment of the spoiler as compared to that of the pipe without the spoiler. The streamwise and vertical turbulence intensities are increased by 24% and 36%, respectively, and the wake flow field is found to be highly anisotropic. The streamwise turbulence intensities, Reynolds shear stress (RSS), turbulent kinetic energy (TKE), and turbulence indicator are attaining their peaks near the top level of the spoiler in the wake region. The triple velocity correlations indicate that the switching of sweeps and ejection events takes place near the top level of the spoiler. Therefore, it can be concluded that the spoiler attachment has increased the turbulence level in the wake region, and their highest magnitudes are located near the top level of the spoiler.
Estimation of gas diffusion coefficient for gas/oil-saturated porous media systems by use of early-time pressure-decay data: An experimental/numerical approach
Authors: Yang Mingyang , Huang Shijun , Zhao Fenglan , Sun Haoyue , Chen Xinyang , Yang Changhe
Published: October 2024

This paper presented a novel numerical method for estimating the gas diffusion coefficient based on the early-time pressure-decay data. Experimentally, “flooding–soaking” procedures were developed to perform the gas diffusion in an oil-saturated tight core under different gas phase volume conditions. After flooding, the capillary bundle model was used to calculate the oil–gas contact area. The early-time pressure-decay data of the gas phase were monitored and recorded during the soaking process. Theoretically, a non-equilibrium inner boundary condition coupled with the characteristics of experimental early-time pressure had been incorporated to develop a diffusion model for a gas/oil-saturated tight core system. Based on gas-phase mass balance equations and gas equation of state, the diffusion coefficients were optimized once the discrepancy between experimental data and numerical solutions was minimized. According to the estimated results in this study, the CH4 diffusion coefficients were 3.74 × 10−11 and 3.86 × 10−11 m2/s in tight core saturated with crude oil, respectively. Moreover, the oil–gas contact area significantly impacts the diffusion flux in oil-saturated porous media. Specifically, an additional 10% contact area results in a 75% increase in CH4 diffusion mass. In addition, with the application of our proposed model to CH4/bitumen and CO2/bitumen systems, the diffusion coefficients were in close agreement with the results reported in previous literature, indicating that the proposed model was applicable to both gas/liquid and gas/liquid-saturated porous media systems.
A fluid temperature interpolation method for wide temperature range distributed flow calorimeter
Authors: Zhang Tao , Lv Yiming , Xie Tiancheng , Hu Dongfang , Xu Jinxin , Hou Dexin , Ding Jiong
Published: October 2024

The distributed flow calorimeter is employed to measure reaction enthalpy, mixing enthalpy, and other thermodynamic parameters of hydrocarbon fuels. This information serves as a foundation for selecting and developing hydrocarbon fuels for hypersonic flight. The fluid temperature in the tube is a key factor in characterizing its thermodynamic behavior. Given the challenges of monitoring fluid temperature within a tube using current flow calorimetry, a distributed method for calculating fluid temperature in tubes under high-temperature conditions is proposed. This method realizes the interpolation of the enthalpy function of the experimental fluid through several sets of experiments with varying power levels. The fluid temperature in the tube is calculated by considering the microelement as the research object. First, the methodology for calculating fluid temperature in narrow pipes across a wide temperature range is presented. Second, the simulation model of the flow calorimeter is established, and the methodology is verified through numerical simulation. Finally, a flow calorimetric experimental device is setup. N-decane was used as the fluid in the experiment, and the temperature was calculated, and the calculated results were compared with the NIST data. In the temperature range of 295.50–609.38 K, the relative error range of the calculation of n-decane temperature is −0.61% to 1.24%. The experimental results show that the method can effectively estimate the fluid temperature of the distributed flow calorimeter.
Self-supervised learning for effective denoising of flow fields
Authors: Yu Linqi , Yousif Mustafa Z. , Zhou Dan , Zhang Meng , Lee Jung Sub , Lim Hee-Chang
Published: October 2024

In this study, we proposed an efficient approach based on a deep learning (DL) denoising autoencoder (DAE) model for denoising noisy flow fields. The DAE operates on a self-learning principle and does not require clean data as training labels. Furthermore, investigations into the denoising mechanism of the DAE revealed that its bottleneck structure with a compact latent space enhances denoising efficacy. Meanwhile, we also developed a deep multiscale DAE for denoising turbulent flow fields. Furthermore, we used conventional noise filters to denoise the flow fields and performed a comparative analysis with the results from the DL method. The effectiveness of the proposed DL models was evaluated using direct numerical simulation data of laminar flow around a square cylinder and turbulent channel flow data at various Reynolds numbers. For every case, synthetic noise was augmented in the data. A separate experiment used particle-image velocimetry data of laminar flow around a square cylinder containing real noise to test DAE denoising performance. Instantaneous contours and flow statistical results were used to verify the alignment between the denoised data and ground truth. The findings confirmed that the proposed method could effectively denoise noisy flow data, including turbulent flow scenarios. Furthermore, the proposed method exhibited excellent generalization, efficiently denoising noise with various types and intensities.
A depth graph attention-based multi-channel transfer learning network for fluid classification from logging data
Authors: Li Hengxiao , Qiao Sibo , Sun Youzhuang
Published: October 2024

Fluid classification is a fundamental task in the field of geological sciences to achieve effective reservoir characterization and hydrocarbon exploration. Traditional fluid classification methods are often limited by long processing times and an inability to capture complex relationships within the data. To address this issue, this paper proposes a novel deep learning approach—the Deep Graph Attention Multi-channel Transfer Learning Network (DGMT), aimed at improving the efficiency and accuracy of fluid classification from logging data. This model comprises three key components: a graph attention layer, a multi-channel feature extractor, and a transfer learning module. The graph attention layer is designed to handle spatial dependencies between different logging channels, enhancing classification accuracy by focusing on critical features. The multi-channel feature extractor integrates information from various data sources, ensuring comprehensive utilization of the rich information in logging data. The transfer learning module allows the model to transfer knowledge from pre-trained models of similar tasks, accelerating the training process and significantly improving the model's generalization ability and robustness. This feature enables the DGMT model to adapt to different geological environments and logging conditions, showing superior performance over traditional methods. To validate the effectiveness of the DGMT model, we conducted experiments on actual logging datasets containing multiple oil wells. The experimental results indicate that, compared to common machine learning algorithms and other deep learning methods, the DGMT model significantly improves in accuracy and other classification performance metrics.
Interface defect state induced spin injection in organic magnetic tunnel junctions
Authors: Soujanya Pamulapati , Deb Debajit
Published: October 2024

This article analytically explores defect assisted spin injection in organic magnetic tunnel junctions (MTJs) [x/rubrene/Co, x = La2O3, LaMnO3, La0.7Ca0.3MnO3 (LCMO), La0.7Sr0.3MnO3 (LSMO)] employing nonequilibrium Green’s function (NEGF). Spin precession at ferromagnet (FM)/organic semiconductor (OSC) interface defect states have been considered while modeling the MTJ devices. Variations in voltage dependent parallel (RP) and antiparallel (RAP) resistances have been attributed to modified spin dependent scattering at modified spin resolved density of states of magnetic electrodes. Moreover, change in distribution of defect state depths at a spin injection interface has also been observed to modify RP/RAP, and hence, tunnel magnetoresistance (TMR) across the devices. Localization of defect state distribution due to a high spin split band may have resulted in large TMR for La2O3 devices. Nonlinear spin transfer torque (STT) in devices other than LSMO indicates compensation of spin damping, resulting in a high TMR response across the devices. Hence, the localization of defect state distribution and the choice of magnetic electrodes with high spin split bands may be exercised to realize spintronic devices for low power spin memory applications.
Integrative taxonomy of Teucriogethes pollen beetles (Coleoptera: Nitidulidae: Meligethinae), with implications on the systematics of the genus Teucrium (Lamiaceae)
Authors: Liu Meike , Li Qiuhong , Gardini Pietro , Audisio Paolo , Sabatelli Simone
Published: October 2024

In highly specialised phytophagous insects, important insights on phylogeny of the involved insect group can be often inferred from the evolutionary history of their host plants, and vice-versa, as in the case for a new, peculiar species of pollen beetles, recently discovered in Central China (Hubei Province). This new species is described herein as Teucriogethes huangae Liu & Audisio, sp. nov., and information on its ecology and systematic position is provided. The new species, associated as larvae with a strongly isolated member of the genus Teucrium L. (Lamiaceae), T. ornatum Hemsl., exhibiting a problematic taxonomic position, represents in turn an isolated and morphologically rather aberrant taxon in its lineage, probably the largest in size (2.2–2.8 mm), and the first endemic representative of its genus in the whole Eastern Palaearctic. An updating of the taxonomic assessment of members of Teucriogethes and on possible evolutionary relationships with their larval host plants, based on an integrative taxonomy approach, is finally presented. A key to identification of all known species is also introduced. ZooBank: urn:lsid:zoobank.org:pub:E349044B-29A5-416C-85CA-56143C7A29BE
A multilocus perspective on the evolutionary dynamics of multistrain pathogens
Authors: McLeod David V. , Bank Claudia , Gandon Sylvain
Published: October 2024

Many human pathogens, including malaria, dengue, influenza,
Streptococcus
pneumoniae
, and cytomegalovirus, coexist as multiple genetically distinct strains. Understanding how these multistrain pathogens evolve is of critical importance for forecasting epidemics and predicting the consequences of vaccination. One factor believed to play an important role is naturally acquired immunity. Consequently, a large body of research has sought to predict how acquired immunity molds the genomics of pathogen populations (i.e., what shapes pathogen strain structure). The diversity of existing models has resulted in conflicting evolutionary predictions and has sparked an ongoing debate about which predictions are most broadly applicable. Here, we adopt a multilocus population genetics perspective that unifies the predictions of existing models. We identify three key factors that determine the role of naturally acquired immunity in the evolution of pathogen strain structure: i) the strength and specificity of immune protections, ii) the dynamic immunological landscape, and iii) the number of loci coding for the antigens of the pathogen. Isolating and discussing these three factors clarifies the relationship among previous models of multistrain dynamics, and establishes a solid theoretical foundation for the study of the evolutionary epidemiology of multistrain pathogens.
Nuclear compensatory evolution driven by mito-nuclear incompatibilities
Authors: Princepe Debora , de Aguiar Marcus A. M.
Published: October 2024

Mitochondrial function relies on the coordinated expression of mitochondrial and nuclear genes, exhibiting remarkable resilience despite high mitochondrial mutation rates. The nuclear compensation mechanism suggests deleterious mitochondrial alleles drive compensatory nuclear mutations to preserve mito-nuclear compatibility. However, prevalence and factors conditioning this phenomenon remain debated due to its conflicting evidence. Here, we investigate how mito-nuclear incompatibilities impact substitutions in a model for species radiation. Mating success depends on genetic compatibility (nuclear DNA) and spatial proximity. Populations evolve from partially compatible mito-nuclear states, simulating mitochondrial DNA (mtDNA) introgression. Mutations do not confer advantages nor disadvantages, but individual fecundity declines with increasing incompatibilities, selecting for mito-nuclear coordination. We find that selection for mito-nuclear compatibility affects each genome differently based on their initial state. In compatible gene pairs, selection reduces substitutions in both genomes, while in incompatible nuclear genes, it consistently promotes compensation, facilitated by more mismatches. Interestingly, high mitochondrial mutation rates can reduce nuclear compensation by increasing mtDNA rectification, while substitutions in initially compatible nuclear gene are boosted. Finally, the presence of incompatibilities accelerates species radiation, but equilibrium richness is not directly correlated to substitution rates, revealing the complex dynamics triggered by mitochondrial introgression and mito-nuclear coevolution. Our study provides a perspective on nuclear compensation and the role of mito-nuclear incompatibilities in speciation by exploring extreme scenarios and identifying trends that empirical data alone cannot reveal. We emphasize the challenges in detecting these dynamics and propose analyzing specific genomic signatures could shed light on this evolutionary process.
Gut bacteria of lepidopteran herbivores facilitate digestion of plant toxins
Authors: Zhang Nan , Qian Zhaoyi , He Jintao , Shen Xiaoqiang , Lei Xiaoyu , Sun Chao , Fan Jie , Felton Gary W. , Shao Yongqi
Published: October 2024

Lepidopterans commonly feed on plant material, being the most significant insect herbivores in nature. Despite plant resistance to herbivory, such as producing toxic secondary metabolites, herbivores have developed mechanisms encoded in their genomes to tolerate or detoxify plant defensive compounds. Recent studies also highlight the role of gut microbiota in mediating detoxification in herbivores; however, convincing evidence supporting the significant contribution of gut symbionts is rare in Lepidoptera. Here, we show that the growth of various lepidopteran species was inhibited by a mulberry-derived secondary metabolite, 1-deoxynojirimycin (DNJ); as expected, the specialist silkworm
Bombyx mori
grew well, but interestingly, gut microbiota of early-instar silkworms was affected by the DNJ level, and several bacterial species responded positively to enriched DNJ. Among these, a bacterial strain isolated from the silkworm gut (
Pseudomonas fulva
ZJU1) can degrade and utilize DNJ as the sole energy source, and after inoculation into nonspecialists (e.g., beet armyworm
Spodoptera exigua
),
P. fulva
ZJU1 increased host resistance to DNJ and significantly promoted growth. We used genomic and transcriptomic analyses to identify genes potentially involved in DNJ degradation, and CRISPR-Cas9-mediated mutagenesis verified the function of
ilvB
, a key binding protein, in metabolizing DNJ. Furthermore, the
ilvB
deletion mutant, exhibiting normal bacterial growth, could no longer enhance nonspecialist performance, supporting a role in DNJ degradation in vivo. Therefore, our study demonstrated causality between the gut microbiome and detoxification of plant chemical defense in Lepidoptera, facilitating a mechanistic understanding of host–microbe relationships across this complex, abundant insect group.
Atomic electron transitions of hydrogen-like atoms induced by gravitational waves
Authors: Chen Bo-Hung , Chiou Dah-Wei
Published: October 2024

As a realistic model of a quantum system of matter, this paper investigates the gravitational-wave effects on a hydrogen-like atom using a first-principles approach. By formulating the tetrad formalism of linearized gravity, we naturally incorporate gravitational-wave effects through minimal coupling in the covariant Dirac equation. The atomic electron transition rates induced by the gravitational wave are calculated using first-order perturbation theory, revealing a distinctive selection rule along with Fermi’s golden rule. This rule can be elegantly understood in terms of gravitons as massless spin-2 particles. Our results suggest the existence of gravitons and may lead to a novel approach to probing ultra-high-frequency gravitational waves.
Ground-LIO: enhanced LiDAR-inertial odometry for ground robots based on ground optimization
Authors: Zhu Housheng , Zou Chunlong , Yun Juntong , Jiang Du , Huang Li , Liu Ying , Tao Bo , Xie Yuanmin
Published: October 2024

In the field of LiDAR-based Simultaneous Localization and Mapping, the potential of ground point clouds to enhance pose estimation in mobile robots has yet to be fully realized. This paper focuses on leveraging ground point clouds to improve the performance of LiDAR-Inertial Odometry (LIO) systems for ground-based mobile robots. We begin by analyzing the characteristics of ground point clouds and the typical types of noise that affect their extraction and utilization. Ground point clouds are then extracted from denoised data. Given the generally local planar nature of ground point clouds, we propose a segmentation-and-refitting approach to process them. This method reduces the computational burden of residual calculation in pose estimation by avoiding redundant plane fitting. Additionally, we introduce a data structure designed for the efficient management and utilization of ground point clouds obtained through segmentation and refitting. This structure is particularly suited to the ground point cloud data produced by our method, enabling efficient access and registration through the continuous maintenance and consolidation of local plane parameters. Our method has been integrated into advanced LIO systems (Bai et al 2022 IEEE Robot. Autom. Lett.
7 4861–8), and experimental results on challenging datasets demonstrate its promising performance.
Fluid-filled lattices for responsive orthotic insoles
Authors: Cracknell Dayna , Battley Mark , Fernandez Justin , Amirpour Maedeh
Published: October 2024

Orthotic insoles are essential for alleviating discomfort and preventing injuries in the foot caused by high peak pressures in the plantar tissue. Traditional orthotic insoles, often prescribed to address these issues, are designed based on the static foot shape and pressure measurements, lacking responsiveness to dynamic movements. This study explores the behaviour of fluid-filled lattices for improving the functionality of orthotic insoles, focusing on energy dissipation and pressure redistribution capabilities. Using numerical homogenisation, the research integrates hyperelastic and permeability models to simulate the behaviour of Solid–Liquid Composites. Experimental tests validated these models, examining the influence of fluid viscosity and structural variations on energy dissipation and pressure distribution. Results show that fluid-filled lattices provide enhanced energy dissipation and reduce peak pressures by evening out the pressure distribution compared to non-fluid-filled samples. These findings highlight the potential of fluid-filled lattices to improve the performance and comfort of orthotic insoles.
Structural design and test of superconducting magnet coil for the cooling storage ring external-target experiment
Authors: Lu Jiaqi , Chen Yuquan , Mei Enming , Wu Beimin , You Wei , Tong Yujin , Feng Wentian , Ou Xianjin , Ni Dongsheng , Wu Wei , Yao Qinggao , Yu Yuhong , Ma Lizhen , Sun Zhiyu
Published: October 2024

Heavy ion collision is a unique method for studying cold and dense nuclear matter in labs. The cooling storage ring external-target experiment at the Heavy Ion Research Facility in Lanzhou, China, is the first multi-purpose nuclear physics experimental device to operate in the GeV energy range. One of the key parts is a large acceptance dipole magnet, which is used to bend particles so that they can be detected by various detectors. A superconducting coil with a size of 3.1 m × 3.6 m × 2 m was designed to verify the rationality of the scheme. Although the coil-dominated superconducting magnet with NbTi has been used to reduce the weight and size of the magnet, large deformation and stress will occur in the cooldown and excitation stages owing to the large volume and weight. Therefore, it is crucial to design a reasonable structure to ensure the strength of the magnet and prevent the magnet from interfering with other components due to large deformation, and even the possibility of quenching. A truss supporter is proposed for the support of the superconducting coil. In this study, the structural design of the cold mass of a superconducting magnet is introduced, and its mechanical behaviors during cooldown and excitation are analyzed in detail. To verify the feasibility of the coil design and process route, a sub-size prototype was manufactured and tested at 4.2 K and reached the design current successfully.
Efficient and broadband sound absorption properties of slotted aluminum foam
Authors: Chen Jin , Qiao Jiangyu , Liang Lisi , Zhang Lixing , Cui Zhongyi , Wang Zeming , Zhang Zhuyue
Published: October 2024

To enhance the sound absorption performance of aluminum foam, a slotted structure was developed. Firstly, the theoretical model of sound absorption for the slotted aluminum foam was established by the transfer matrix method. Secondly, the finite element model was established using COMSOL software to predict the sound absorption coefficient. The reliability of the theoretical and finite element models was validated through impedance tube experiments. The sound absorption mechanism is investigated by analyzing the internal sound field. Finally, the sound absorption properties of aluminum foam with other slot patterns are investigated. Additionally, the factors that influence sound absorption properties are investigated. The results indicate that the slots alter the sound pressure distribution within the material, inducing a pressure diffusion effect. When sound waves enter the interior of the material through the narrow slots, they are absorbed and dissipated by the matrix material on the sides of the slots. The sound absorption coefficient can be improved by increasing the thickness, slot scale, and slot depth of the slotted aluminum foam. Specifically, when the slot depth is 15 mm, and the slot width is 5 mm, the average sound absorption coefficient of incompletely slotted aluminum foam in the frequency range of 1000 ∼ 6300 Hz is 0.86, which can realize broadband sound absorption. With the increase of slot depth, the sound absorption peak becomes more pronounced.
Two-core photonic quasicrystal fiber - surface plasmon resonance (PQF-SPR) methane sensor comprising the ZnO/Au composite film: design and FEM simulation
Authors: Liu Qiang , Wang Kaiyu , Sun Yudan , Li Xinrui , Liu Wei , Zhao Xueyan , Lv Tingting , Lv Jingwei , Chu Paul K , Liu Chao
Published: October 2024

A photonic quasicrystal fiber - surface plasmon resonance (PQF-SPR) methane sensor made up of the eight-fold photonic quasicrystal fiber has been designed and analyzed. The PQF is used to construct the double-core D-type structure with air holes forming a hole groove on the D-type surface. The grooves are plated with ZnO and Au films successively, following the deposition of a methane-sensitive film containing Cryptophane-E. The effects of the air hole diameter, materials, and relative thickness of the composite film on the sensing properties are studied by finite element simulation. The results show that the wavelength sensitivity of the sensor with the ZnO-Au and TiO2-Au composite film with the same thickness is significantly higher than that with a single gold film coating in the methane concentration range of 0%–3.5%, confirming that the composite film enhances the SPR effect and improves the sensing properties. The ZnO-Au composite film has the best properties such as maximum and average wavelength sensitivities of 64 nm/% and 40.24 nm/%, respectively. The performance of this sensor is notably superior to that of comparable methane sensors previously documented.
Design and optimization of dielectric resonator based MIMO antenna with beam tilting at mm-wave for enhanced 5G communication using machine learning
Authors: Pandey Ashish , Sehgal Aakash , Kumar Vinay , Singh Akhilendra Pratap
Published: October 2024

In this paper, a dual-port ceramic-based multiple-input multiple-output (MIMO) antenna is designed for operation at mm-wave frequencies. The design incorporates a partially reflecting surface (PRS) positioned above the dual-port antenna to facilitate beam tilting. Additionally, various machine learning (ML) algorithms are utilized to optimize the unit cell length and the distance between the Dielectric Resonator Antenna (DRA) and the PRS, thereby achieving the desired beam tilting characteristics. The ceramic element is excited through an aperture, which generates the HEM11δ
mode in the cylindrical dielectric resonator antenna (CDRA). The proposed antenna demonstrates excellent port isolation, exceeding 35 dB, and operates effectively within the 25.9–27.4 GHz frequency range. The PRS enables a broadside beam tilt of ±30 degrees, incorporating pattern diversity into the design. These characteristics make the proposed antenna an ideal candidate for mm-wave vehicle-to-vehicle and 5G communication systems.
Nonlinear evolution of weakly coupled double tearing modes with equilibrium sheared toroidal flow
Authors: Ying Y. Y. , Wang Z. M. , Zhang Y. Y. , Zhang W. , Meng X. D. , Ma Z. W.
Published: October 2024

The nonlinear evolution of weakly coupled double tearing modes (DTMs) with and without sheared toroidal flow is systematically investigated with the three-dimensional, toroidal-geometry, and nonlinear magneto-hydro-dynamics code CLT. Due to the explosive growth of the weakly coupled DTMs, the pressure crashes are much more severe than those caused by the strongly coupled DTMs. The weakly coupled DTMs can easily be decoupled by sheared toroidal flow, and then the mutually driven term between the two tearing modes becomes periodically positive and negative, leading to periodic growth. The interaction slows the rotation between the two tearing modes when the phase difference is close to 180°. When the islands are sufficiently large, the interaction can overcome the decoupling effect of the shear flow, and the two tearing modes then lock with each other. Due to the different coupling effects of the two tearing modes, the threshold island width or perturbed magnetic field for mode-locking increases with increasing separation. The coupling effect between the two tearing modes is also related to the resistivity. If the resistivity is high, the coupling effect between the two tearing modes can be huge. A stronger shear flow is needed to decouple them, and even a small island can lead to mode-locking in high-resistivity plasma.