The fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), is a highly destructive polyvorous pest with a wide host range and the ability to feed continuously with seasonal changes. This destructive pest significantly damages crops and can also utilize non-agricultural plants, such as weeds, as alternative hosts. However, the adaptation mechanisms of S. frugiperda when switching between crop and non-crop hosts remain poorly understood, posing challenges for effective monitoring and integrated pest management strategies. Therefore, this study aims to elucidate the adaptability of S. frugiperda to different host plants. Results showed that corn (Zea mays L.) was more suitable for the growth and development of S. frugiperda than wheat (Triticum aestivum L.) and goosegrass (Eleusine indica). Transcriptome analysis identified 699 genes differentially expressed when fed on corn, wheat, and goosegrass. The analysis indicated that the detoxification metabolic pathway may be related to host adaptability. We identified only one SfGSTs2 gene within the GST family and investigated its functional role across different developmental stages and tissues by analysing its spatial and temporal expression patterns. The SfGSTs2 gene expression in the midgut of larvae significantly decreased following RNA interference. Further, the dsRNA-fed larvae exhibited a decreased detoxification ability, higher mortality, and reduced larval weight. The findings highlight the crucial role of SfGSTs2 in host plant adaptation. Evaluating the feeding preferences of S. frugiperda is significant for controlling important agricultural pests.

This study presents a novel approach for constructing turbulence models using the kinetic Fokker–Planck equation. By leveraging the inherent similarities between Brownian motion and turbulent dynamics, we formulate a Fokker–Planck equation tailored for turbulence at the hydrodynamic level. In this model, turbulent energy plays a role analogous to temperature in molecular thermodynamics, and the large-scale structures are characterised by a turbulent relaxation time. This model aligns with the framework of Pope’s generalised Langevin model, with the first moment recovering the Reynolds-averaged Navier–Stokes (RANS) equations, and the second moment yielding a partially modelled Reynolds stress transport equation. Utilising the Chapman–Enskog expansion, we derive asymptotic solutions for this turbulent Fokker–Planck equation. With an appropriate choice of relaxation time, we obtain a linear eddy viscosity model at first order, and a quadratic Reynolds stress constitutive relationship at second order. Comparative analysis of the coefficients of the quadratic expression with typical nonlinear viscosity models reveals qualitative consistency. To further validate this kinetic-based nonlinear viscosity model, we integrate it as a RANS model within computational fluid dynamics codes, and calculate three typical cases. The results demonstrate that this quadratic eddy viscosity model outperforms the linear model and shows comparability to a cubic model for two-dimensional flows, without the introduction of ad hoc parameters in the Reynolds stress constitutive relationship.

The interaction of a swimmer with unsteady vortices in complex flows remains a topic of interest and open discussion. The present study, employing the immersed boundary method with a flexible fin model, explores swimming behaviours behind a circular cylinder with vortex-induced vibration (VIV). Five distinct swimming modes are identified on the $U_r$–$G_0$ plane, where $U_r$ denotes the reduced velocity, and $G_0$ represents the fin’s initial position. These modes include drifting upstream I/II (DU-I/II), Karman gait I/II (KG-I/II), and large oscillation (LO), with the DU-II, KG-II and LO modes being newly reported. The fin can either move around or cross through the vortex cores in the KG-I and KG-II modes, respectively, for energy saving and maintaining a stable position. When the upstream cylinder vibrates with its maximum amplitude, a double-row vortex shedding forms in the wake, allowing the DU-II mode to occur with the fin to achieve high-speed locomotion. This is attributed to a significant reduction in the streamwise velocity caused by vortex-induced velocity. Furthermore, a symmetry breaking is observed in the fin’s wake in the DU-II mode, potentially also contributing to high-speed locomotion. Overall, compared to the case without an upstream cylinder, we demonstrate that a self-propelled fin gains hydrodynamic advantages with various swimming modes in different VIV wakes. Interestingly, increased power transferred from flows by the oscillating cylinder leads to a more favourable environment for the downstream fin’s propulsion, indicating that a fin in VIV wakes obtains more advantages compared to the vortex street generated by a stationary cylinder.

Spatial intensity modulation in amplified laser beams, particularly hot spots, critically constrains attainable pulse peak power due to the damage threshold limitations of four-grating compressors. This study demonstrates that the double-smoothing grating compressor (DSGC) configuration effectively suppresses modulation through directional beam smoothing. Our systematic investigation validated the double-smoothing effect through numerical simulations and experimental measurements, with comprehensive spatiotemporal analysis revealing excellent agreement between numerical and practical pulse characteristics. Crucially, the DSGC enables a 1.74 times energy output boost compared to conventional compressors. These findings establish the DSGC as a pivotal advancement for next-generation ultrahigh-power laser systems, providing a viable pathway toward hundreds of PW output through optimized spatial energy redistribution.

The recently discovered social place cells and grid cells in hippocampal formation are believed to be the neural basis underlying relative navigation of conspecifics. In this paper, we propose a new brain-inspired relative navigation model in a large-scale 3D environment for collective UAVs that translates the neurodynamics of the social place cell–grid cell circuit to robotic relative navigation algorithm for the first time. Our approach comprises three key parts: (1) a 3D isotropic Gaussian function-based cube social place cell network (cube-SPCNet), (2) a 3D continuous attractor neural network-based cube grid cell network (cube-GCNet), and (3) a population vector-based neural decoding module. The resulting brain-inspired relative navigation model incorporates the good relative information abstraction capabilities of the cube-SPCNet with the powerful temporal filtering capabilities of the cube-GCNet, yielding robustness and accuracy performance improvement for relative navigation. Experimental results show the new method can provide more robust and precise relative navigation results than its conventional counterpart, displaying a possible brain-inspired solution for relative navigation enhancement for collective UAVs.

The whitefly, Bemisia tabaci is a cryptic species complex in which one member, Middle East-Asia Minor 1 (MEAM1) has invaded globally. After invading large countries like Australia, China, and the USA, MEAM1 spread rapidly across each country. In contrast, our analysis of MEAM1 in India showed a very different pattern. Despite the detection of MEAM1 being contemporaneous with invasions in Australia, the USA, and China, MEAM1 has not spread widely and instead remains restricted to the southern regions. An assessment of Indian MEAM1 genetic diversity showed a level of diversity equivalent to that found in its presumed home range and significantly higher than that expected across the invaded range. The high level of diversity and restricted distribution raises the prospect that its home range extends into India. Similarly, while the levels of diversity in Australia and the USA conformed to that expected for the invaded range, China did not. It suggests that China may also be part of its home range. We also observed that diversity across the invaded range was primarily accounted for by a single haplotype, Hap1, which accounted for 79.8% of all records. It was only the invasion of Hap1 that enabled outbreaks to occur and MEAM1’s discovery.

A multifunctional optical diagnostic system, which includes an interferometer, a refractometer and a multi-frame shadowgraph, has been developed at the Shenguang-II upgrade laser facility to characterize underdense plasmas in experiments of the double-cone ignition scheme of inertial confinement fusion. The system employs a 266 nm laser as the probe to minimize the refraction effect and allows for flexible switching among three modes of the interferometer, refractometer and multi-frame shadowgraph. The multifunctional module comprises a pair of beam splitters that attenuate the laser, shield stray light and configure the multi-frame and interferometric modules. By adjusting the distance and angle between the beam splitters, the system can be easily adjusted and switched between the modes. Diagnostic results demonstrate that the interferometer can reconstruct electron density below 1019 cm–3, while the refractometer can diagnose density approximately up to 1020 cm–3. The multi-frame shadowgraph is used to qualitatively characterize the temporal evolution of plasmas in the cases in which the interferometer and refractometer become ineffective.

A high-energy pulsed vacuum ultraviolet (VUV) solid-state laser at 177 nm with high peak power by the sixth harmonic of a neodymium-doped yttrium aluminum garnet (Nd:YAG) amplifier in a KBe2BO3F2 prism-coupled device was demonstrated. The ultraviolet (UV) pump laser is a 352 ps pulsed, spatial top-hat super-Gaussian beam at 355 nm. A high energy of a 7.12 mJ VUV laser at 177 nm is obtained with a pulse width of 255 ps, indicating a peak power of 28 MW, and the conversion efficiency is 9.42% from 355 to 177 nm. The measured results fitted well with the theoretical prediction. It is the highest pulse energy and highest peak power ever reported in the VUV range for any solid-state lasers. The high-energy, high-peak-power, and high-spatial-uniformity VUV laser is of great interest for ultra-fine machining and particle-size measurements using UV in-line Fraunhofer holography diagnostics.

This study is dedicated to achieving efficient active noise control in a supersonic underexpanded planar jet, utilizing control parameters informed by resolvent analysis. The baseline supersonic underexpanded jet exhibits complex wave structures and substantial high-amplitude noise radiations. To perform the active control, unsteady blowing and suction are applied along the nozzle inner wall close to the exit. Employing both standard and acoustic resolvent analyses, a suitable frequency and spanwise wavenumber range for the blowing and suction is identified. Within this range, the control forcing can be significantly amplified in the near field, effectively altering the original sound-producing energetic structure while minimizing far-field amplification to prevent excessive noise. A series of large-eddy simulations are further conducted to validate the control efficiency, demonstrating an over 10 dB reduction in upstream-propagated screech noise. It is identified that the present unsteady control proves more effective than steady control at the same momentum coefficient. The controlled jet flow indicates that the shock structures become more stable, and the stronger the streamwise amplification of the forcing, the more likely it is to modify the mean flow characteristics, which is beneficial for reducing far-field noise radiation. Spectral proper orthogonal decomposition analysis of the controlled flow confirms that the control redistributes energy to higher forcing frequencies and suppresses large-scale antisymmetric and symmetric modes related to screech and its harmonics. The findings of this study highlight the potential of resolvent-guided control techniques in reducing noise in supersonic underexpanded jets and provide a detailed understanding of the inherent mechanisms for effective noise reduction through active control strategies.

To characterize fluid flow in the slip regime, the use of Navier–Stokes–Fourier (NSF) equations with slip boundary conditions is prevalent. This trend underscores the necessity of developing reliable and accurate slip boundary conditions. According to kinetic theory, slip behaviours are intrinsically linked to the gas scattering processes at the surface. The widely used Maxwell scattering model, which employs a single accommodation coefficient to describe gas scattering processes, reveals its limitations when the difference between accommodation coefficients in the tangential and normal directions becomes significant. In this work, we provide a derivation of velocity slip and temperature jump boundary conditions based on the Cercignani–Lampis–Lord scattering model, which applies two independent accommodation coefficients to describe the gas scattering process. A Knudsen layer correction term is introduced to account for the impact of the surface on the velocity distribution function, which is associated with the scattering model. The governing equation of the correction term is established based on the linearized Boltzmann equation. Additionally, two moments are derived to capture the collision effect in the Knudsen layer: a conserving moment of collision invariants, and an approximate higher-order conserving moment. These moments are then employed to determine the coefficients in the correction term. We demonstrate that the derived slip coefficients align closely with numerical results obtained by solving the Boltzmann equation in the Knudsen layer. Besides, we apply the derived slip boundary conditions within the framework of the NSF equations, yielding numerical results that exhibit excellent consistency with those obtained through molecular-level simulations.

We consider a robust optimal investment–reinsurance problem to minimize the goal-reaching probability that the value of the wealth process reaches a low barrier before a high goal for an ambiguity-averse insurer. The insurer invests its surplus in a constrained financial market, where the proportion of borrowed amount to the current wealth level is no more than a given constant, and short-selling is prohibited. We assume that the insurer purchases per-claim reinsurance to transfer its risk exposure to a reinsurer whose premium is computed according to the mean–variance premium principle. Using the stochastic control approach based on the Hamilton–Jacobi–Bellman equation, we derive robust optimal investment–reinsurance strategies and the corresponding value functions. We conclude that the behavior of borrowing typically occurs with a lower wealth level. Finally, numerical examples are given to illustrate our results.

We define a knot to be half ribbon if it is the cross-section of a ribbon 2-knot, and observe that ribbon implies half ribbon implies slice. We introduce the half ribbon genus of a knot K, the minimum genus of a ribbon knotted surface of which K is a cross-section. We compute this genus for all prime knots up to 12 crossings, and many 13-crossing knots. The same approach yields new computations of the double slice genus. We also introduce the half fusion number of a knot K, that measures the complexity of ribbon 2-knots of which K is a cross-section. We show that it is bounded below by the Levine–Tristram signatures, and differs from the standard fusion number by an arbitrarily large amount.

The scaling relations mapping the turbulence statistics in compressible turbulent boundary layers (TBLs) onto their incompressible counterparts are of fundamental significance for turbulence modelling, such as the Morkovin scaling for velocity fields, while for pressure fluctuation fields, a corresponding scaling relation is currently absent. In this work, the underlying scaling relations of pressure fluctuations about Mach number ($M$) contained in their generation mechanisms are explored by analysing a series of direct numerical simulation data of compressible TBLs over a wide Mach number range $(0.5\leq M \leq 8.0)$. Based on the governing equation of pressure fluctuations, they are decomposed into components according to the properties of source terms. It is notable that the intensity of the compressible component, predominantly originating from the acoustic mode, obeys a monotonic distribution about the Mach number and wall distance; further, the intensity of the rest of the pressure components, which are mainly generated by the vorticity mode, demonstrates a uniform distribution consistent with its incompressible counterpart. Moreover, the coupling between the two components is negligibly weak. Based on the scaling relations, semiempirical models for the fluctuation intensity of both pressure and its components are constructed. Hence, a mapping relation is obtained that the profiles of pressure fluctuation intensities in compressible TBLs can be mapped onto their incompressible counterparts by removing the contribution from the acoustic mode, which can be provided by the model. The intrinsic scaling relation can provide some basic insight for pressure fluctuation modelling.

Trauma is a significant health issue that not only leads to immediate death in many cases but also causes severe complications, such as sepsis, thrombosis, haemorrhage, acute respiratory distress syndrome and traumatic brain injury, among trauma patients. Target protein identification technology is a vital technique in the field of biomedical research, enabling the study of biomolecular interactions, drug discovery and disease treatment. It plays a crucial role in identifying key protein targets associated with specific diseases or biological processes, facilitating further research, drug design and the development of treatment strategies. The application of target protein technology in biomarker detection enables the timely identification of newly emerging infections and complications in trauma patients, facilitating expeditious medical interventions and leading to reduced post-trauma mortality rates and improved patient prognoses. This review provides an overview of the current applications of target protein identification technology in trauma-related complications and provides a brief overview of the current target protein identification technology, with the aim of reducing post-trauma mortality, improving diagnostic efficiency and prognostic outcomes for patients.

Aphis spiraecola Patch is one of the most economically important tree fruit pests worldwide. The pyrethroid insecticide lambda-cyhalothrin is commonly used to control A. spiraecola. In this 2-year study, we quantified the resistance level of A. spiraecola to lambda-cyhalothrin in different regions of the Shaanxi province, China. The results showed that A. spiraecola had reached extremely high resistance levels with a 174-fold resistance ratio (RR) found in the Xunyi region. In addition, we compared the enzymatic activity and expression level of P450 genes among eight A. spiraecola populations. The P450 activity of A. spiraecola was significantly increased in five regions (Xunyi, Liquan, Fengxiang, Luochuan, and Xinping) compared to susceptible strain (SS). The expression levels of CYP6CY7, CYP6CY14, CYP6CY22, P4504C1-like, P4506a13, CYP4CZ1, CYP380C47, and CYP4CJ2 genes were significantly increased under lambda-cyhalothrin treatment and in the resistant field populations. A L1014F mutation in the sodium channel gene was found and the mutation rate was positively correlated with the LC50 of lambda-cyhalothrin. In conclusion, the levels of lambda-cyhalothrin resistance of A. spiraecola field populations were associated with P450s and L1014F mutations. Our combined findings provide evidence on the resistance mechanism of A. spiraecola to lambda-cyhalothrin and give a theoretical basis for rational and effective control of this pest species.

In order to provide a theoretical foundation for the utilization of tailings as supplementary cementitious materials, the pozzolanic activity of muscovite—a typical mineral phase in tailings—before and after mechanical activation was investigated. In this study, significant pozzolanic activity of muscovite was obtained as a result of the structural and morphological changes that were induced by mechanical activation. The activated muscovite that was obtained after mechanical activation for 160 min satisfies the requirements for use as an active supplementary cementitious material, and the main characteristics of the pozzolana were as follows: median particle size (D50) of 11.7 μm, BET specific surface area of 28.82 m2 g−1, relative crystallinity of 14.99%, and pozzolanic activity index of 94.36%. Continuous grinding led to a gradual reduction in the relative crystallinity and an increase in the pozzolanic activity index due to the dehydroxylation reaction induced by mechanical activation, which occurred despite the fact that the specific surface area showed a decreasing trend when the grinding time was prolonged. Mechanically activated muscovite exhibited the capacity to react with calcium hydroxide to form calcium silicate hydrate, which is a typical characteristic of pozzolana. This experimental study provided a theoretical basis for evaluating the pozzolanic activity of muscovite using mechanical activation.

Fast neutron absorption spectroscopy is widely used in the study of nuclear structure and element analysis. However, due to the traditional neutron source pulse duration being of the order of nanoseconds, it is difficult to obtain a high-resolution absorption spectrum. Thus, we present a method of ultrahigh energy-resolution absorption spectroscopy via a high repetition rate, picosecond duration pulsed neutron source driven by a terawatt laser. The technology of single neutron count is used, which results in easily distinguishing the width of approximately 20 keV at 2 MeV and an asymmetric shape of the neutron absorption peak. The absorption spectroscopy based on a laser neutron source has one order of magnitude higher energy-resolution power than the state-of-the-art traditional neutron sources, which could be of benefit for precisely measuring nuclear structure data.

This study presents a comprehensive analysis on the extreme positive and negative events of wall shear stress and heat flux fluctuations in compressible turbulent boundary layers (TBLs) solved by direct numerical simulations. To examine the compressibility effects, we focus on the extreme events in two representative cases, i.e. a supersonic TBL of Mach number $M=2$ and a hypersonic TBL of $M=8$, by scrutinizing the coherent structures and their correlated dynamics based on conditional analysis. As characterized by the spatial distribution of wall shear stress and heat flux, the extreme events are indicated to be closely related to the structural organization of wall streaks, in addition to the occurrence of the alternating positive and negative structures (APNSs) in the hypersonic TBL. These two types of coherent structures are strikingly different, namely the nature of wall streaks and APNSs are shown to be related to the solenoidal and dilatational fluid motions, respectively. Quantitative analysis using a volumetric conditional average is performed to identify and extract the coherent structures that directly account for the extreme events. It is found that in the supersonic TBL, the essential ingredients of the conditional field are hairpin-like vortices, whose combinations can induce wall streaks, whereas in the hypersonic TBL, the essential ingredients become hairpin-like vortices as well as near-wall APNSs. To quantify the momentum and energy transport mechanisms underlying the extreme events, we proposed a novel decomposition method for extreme skin friction and heat flux, based on the integral identities of conditionally averaged governing equations. Taking advantage of this decomposition method, the dominant transport mechanisms of the hairpin-like vortices and APNSs are revealed. Specifically, the momentum and energy transports undertaken by the hairpin-like vortices are attributed to multiple comparable mechanisms, whereas those by the APNSs are convection dominated. In that, the dominant transport mechanisms in extreme events between the supersonic and hypersonic TBLs are indicated to be totally different.

According to the public data collected from the Health Commission of Gansu Province, China, regarding the COVID-19 pandemic during the summer epidemic cycle in 2022, the epidemiological analysis showed that the pandemic spread stability and the symptom rate (the number of confirmed cases divided by the sum of the number of asymptomatic cases and the number of confirmed cases) of COVID-19 were different among 3 main epidemic regions, Lanzhou, Linxia, and Gannan; both the symptom rate and the daily instantaneous symptom rate (daily number of confirmed cases divided by the sum of daily number of asymptomatic cases and daily number of confirmed cases) in Lanzhou were substantially higher than those in Linxia and Gannan. The difference in the food sources due to the high difference of the population ethnic composition in the 3 regions was probably the main driver for the difference of the symptom rates among the 3 regions. This work provides potential values for prevention and control of COVID-19 in different regions.