Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention and/or hyperactivity-impulsivity, accompanied by deficits in executive function (EF). However, how the two core symptoms of ADHD are affected by EF deficits remains unclear. 649 children with ADHD were recruited. Data were collected from ADHD rating scales, the Behavior Rating Inventory of EF (BRIEF), and other demographic questionnaires. Regression and path analyses were conducted to explore how deficits in cool and hot EF influence different ADHD core symptoms. Latent class analysis and logistic regression were employed to further examine whether classification of ADHD subtypes is associated with specific EF deficits. EF deficits significantly predicted the severity of ADHD core symptoms, with cool EF being a greater predictor of inattention and hot EF having a more significant effect on hyperactivity/impulsivity. Moreover, person-centered analyses revealed higher EF deficits in subtypes of ADHD with more severe symptoms, and both cool and hot EF deficits could predict the classification of ADHD subtypes. Our findings identify distinct roles for cool and hot EF deficits in the two core symptoms of ADHD, which provide scientific support for the development of ADHD diagnostic tools and personalized intervention from the perspective of specific EF deficits.

An actively controllable cascaded proton acceleration driven by a separate 0.8 picosecond (ps) laser is demonstrated in proof-of-principle experiments. MeV protons, initially driven by a femtosecond laser, are further accelerated and focused into a dot structure by an electromagnetic pulse (EMP) on the solenoid, which can be tuned into a ring structure by increasing the ps laser energy. An electrodynamics model is carried out to explain the experimental results and show that the dot-structured proton beam is formed when the outer part of the incident proton beam is optimally focused by the EMP force on the solenoid; otherwise, it is overfocused into a ring structure by a larger EMP. Such a separately controlled mechanism allows precise tuning of the proton beam structures for various applications, such as edge-enhanced proton radiography, proton therapy and pre-injection in traditional accelerators.

This paper investigates both conditional and unconditional convergence in labor productivity within the manufacturing industries of the Eurozone over the period 1963 – 2018. We employ two innovative models: constant and varying-coefficient hierarchical panel data convergence regression models, each equipped with two sets of latent factor structures—one comprising global factors and the other industry-specific factors. These models offer distinct advantages, allowing for both global and industry-specific cross-sectional dependencies and permitting parameter heterogeneity across individual industries. Our findings reveal both conditional and unconditional convergence across the manufacturing industry as a whole, as well as among the majority of the 23 sub-manufacturing industries at the ISIC two-digit level. Moreover, we observe significant variation in convergence dynamics among these sub-manufacturing industries. Robustness checks, performed across different subperiods, confirm the reliability of our results. Furthermore, a comparison of our model’s outcomes with those of two alternative models provides additional support for our conclusions.

This paper presents a millimeter-wave end-fire dual-polarized (DP) array antenna with symmetrical radiation patterns and high isolation. The DP radiation element is formed by integrating a quasi-Yagi antenna (providing horizontal polarization) into a pyramidal horn antenna (providing vertical polarization), resulting in a DP radiation element with a symmetrical radiation aperture. To efficiently feed the DP element while maintaining high isolation, a mode-composite full-corporate-feed network is employed, comprising substrate-integrated waveguide supporting the TE10 mode and substrate-integrated coaxial line supporting the TEM mode. This design eliminates the need for additional transition structures, achieving excellent mode isolation and a reduced substrate layer number. A 1 × 4-element DP array prototype operating at 26.5–29.5 GHz using low temperature co-fired ceramic technology was designed, fabricated, and measured. The test results indicate that the prototype achieves an average gain exceeding 10 dBi for both polarizations within the operating band. Thanks to the symmetrical DP radiation element and mode-composite full-corporate-feed network, symmetrical radiation patterns for both polarizations are observed in both the horizontal and vertical planes, along with a high cross-polarization discrimination of 22 dB and polarization port isolation of 35 dB.

The oriental armyworm, Mythimna separata (Walker), is a highly migratory pest known for its sudden larval outbreaks, which result in severe crop losses. These unpredictable surges pose significant challenges for timely and accurate monitoring, as conventional methods are labour-intensive and prone to errors. To address these limitations, this study investigates the use of machine learning for automated and precise identification of M. separata larval instars. A total of 1577 larval images representing different instar were analysed for geometric, colour, and texture features. Additionally, larval weight was predicted using 13 regression models. Instar identification was conducted using Support Vector Classifier (SVC), Random Forest, and Multi-Layer Perceptron. Key feature contributing to classification accuracy were subsequently identified through permutation feature importance analysis. The results demonstrated the potential of machine learning for automating instar identification with high efficiency and accuracy. Predicted larval weight emerged as a key feature, significantly enhancing the performance of all identification models. Among the tested approaches, BaggingRegressor exhibited the best performance for larval weight prediction (R2 = 98.20%, RMSE = 0.2313), while SVC achieved the highest instar identification accuracy (94%). Overall, the integration of larval weight with other image-derived features proved to be a highly effective strategy. This study demonstrates the efficacy of machine learning in enhancing pest monitoring systems by providing a scalable and reliable framework for precise pest management. The proposed methodology significantly improves larval instar identification accuracy and efficiency, offering actionable insights for implementing targeted biological and chemical control strategies.

Land use change has significantly altered most ecosystem functioning, such as nutrition provisioning, water flows and pollination services. So far, the impact of land use change on the dietary diversity of predatory insects has remained largely unexplored. In this study, we explored the prey composition of reared yellow-legged hornets Vespa velutina Lepeletier (Hymenoptera: Vespidae) in landscapes with a gradient of surrounding green lands, using metabarcoding of feces eliminated by larvae. The hornets primarily fed upon insects, with dipterans, coleopterans, lepidopterans, hemipterans, hymenopterans, and orthopterans being the dominant prey groups. The percentage of green lands had a significantly positive effect on prey richness at a spatial scale of 1500 m, but no effect on Shannnon index of the prey community. Meanwhile, the green lands had significantly positive effects on richness of coleopteran prey and lepidopteran prey, but no significant effect on richness of dipteran prey, hemipteran prey, hymenopteran prey, or orthopteran prey. In terms of beta diversity, the percentage of green lands explained the dissimilarity of prey communities among landscapes, whereas local factors, such as the distance to green lands and the distance to buildings, did not explain the dissimilarity. Our study indicated that the green lands in the landscape positively affected the dietary diversity of reared yellow-legged hornets, but this effect varied among different taxonomic groups of prey.

The greatest challenge in pressure reconstruction from the measured velocity fields is that the error of material acceleration is significantly contaminated due to error propagation. Particularly for flows with moving boundaries, accurate boundary velocities are difficult to obtain due to error propagation, and a complex boundary processing technique is needed to treat the moving boundaries. The present work proposes a machine-learning-based method to determine the pressure for incompressible flows with moving boundaries. The proposed network consists of two neural networks: one network, named the boundary network, is used to track the Lagrangian boundary points; the other physics-informed neural network, named the flow network, is adopted to approximate the flow fields. These two networks are coupled by imposing boundary conditions. We further propose a new dynamic weight strategy for the loss terms to guarantee convergence and stability. The performance of the proposed method is validated by two examples: the flow over an oscillating cylinder and the flow around a swimming fish. The proposed method can accurately determine the pressure fields and boundary motion from synthetic particle image velocimetry (PIV) flow fields. Moreover, this method can also predict the boundary and pressure at a given instant without supervised data. Finally, this method was applied to reconstruct the pressure from the two-dimensional and three-dimensional PIV velocities of the left ventricle. All of the results indicate that the proposed method can accurately reconstruct the pressure fields for flows with moving boundaries and is a novel method for surface pressure estimation.

The sulphur microbial diet (SMD), a dietary pattern associated with forty-three sulphur-metabolising bacteria, may influence gut microbiota composition and contribute to ageing process through gut-produced hydrogen sulfide (H2S). We aimed to explore the association between SMD and biological age (BA) acceleration, using the cross-sectional study that included 71 579 individuals from the UK Biobank. The SMD score was calculated by multiplying β-coefficients by corresponding serving sizes and summing them, based on dietary data collected using the Oxford WebQ, a 24-hour dietary assessment tool. BA was assessed using Klemerae–Doubal (KDM) and PhenoAge methods. The difference between BA and chronological age refers to the age acceleration (AgeAccel), termed ‘KDMAccel’ and ‘PhenoAgeAccel’. Generalised linear regression was performed. Mediation analyses were used to investigate underlying mediators including BMI and serum aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio. Following adjustment for multiple variables, a positive association was observed between consuming a dietary pattern with a higher SMD score and both KDMAccel (βQ4 v. Q1 = 0·35, 95 % CI = 0·27, 0·44, P < 0·001) and PhenoAgeAccel (βQ4 v. Q1 = 0·32, 95 % CI = 0·23, 0·41, P < 0·001). Each 1-SD increase in SMD score was positively associated with the acceleration of BA by 7·90 % for KDMAccel (P < 0·001) and 7·80 % for PhenoAgeAccel (P < 0·001). BMI and AST/ALT mediated the association. The stratified analysis revealed stronger accelerated ageing impacts in males and smokers. Our study indicated a higher SMD score is associated with elevated markers of biological ageing, supporting the potential utility of gut microbiota-targeted dietary interventions in attenuating the ageing process.

Rogue waves (RWs) can form on the ocean surface due to the well-known quasi-four-wave resonant interaction or superposition principle. The first is known as the nonlinear focusing mechanism and leads to an increased probability of RWs when unidirectionality and narrowband energy of the wave field are satisfied. This work delves into the dynamics of extreme wave focusing in crossing seas, revealing a distinct type of nonlinear RWs, characterised by a decisive longevity compared with those generated by the dispersive focusing (superposition) mechanism. In fact, through fully nonlinear hydrodynamic numerical simulations, we show that the interactions between two crossing unidirectional wave beams can trigger fully localised and robust development of RWs. These coherent structures, characterised by a typical spectral broadening then spreading in the form of dual bimodality and recurrent wave group focusing, not only defy the weakening expectation of quasi-four-wave resonant interaction in directionally spreading wave fields, but also differ from classical focusing mechanisms already mentioned. This has been determined following a rigorous lifespan-based statistical analysis of extreme wave events in our fully nonlinear simulations. Utilising the coupled nonlinear Schrödinger framework, we also show that such intrinsic focusing dynamics can be captured by weakly nonlinear wave evolution equations. This opens new research avenues for further explorations of these complex and intriguing wave phenomena in hydrodynamics as well as other nonlinear and dispersive multi-wave systems.

This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

Eotetranychus kankitus is an important pest on several agricultural crops, and its resistance to pesticides has promoted the exploration of biological control strategies. Beauveria bassiana and Neoseiulus barkeri have been identified as potential agents for suppressing spider mites. This study aimed to investigate the pathogenicity of B. bassiana on E. kankitus and its compatibility with N. barkeri. Results showed that among the five tested strains of B. bassiana, Bb025 exhibited the highest level of pathogenicity on E. kankitus. Higher application rates (1 × 108 conidia/mL) of Bb025 led to a higher mortality rate of E. kankitus (90.402%), but also resulted in a 15.036% mortality of N. barkeri. Furthermore, preference response tests indicated that both E. kankitus and N. barkeri actively avoided plants sprayed with Bb025 compared to the control group that was sprayed with Tween-80. In a no-choice test, we observed that N. barkeri actively attacked Bb025-treated E. kankitus with no adverse effect on its predatory capacities. Furthermore, N. barkeri laid more eggs when fed on Bb025-treated E. kankitus compared to Tween-80-treated E. kankitus, but the subsequent generation of surviving individuals fed on Bb025-treated E. kankitus was reduced. These findings demonstrate that the Bb025 strain of B. bassiana is highly virulent against E. kankitus while causing less harm to N. barkeri. Consequently, a promising strategy for controlling E. kankitus could involve the sequential utilisation of Bb025 and N. barkeri at appropriate intervals.

The betatron radiation source features a micrometer-scale source size, a femtosecond-scale pulse duration, milliradian-level divergence angles and a broad spectrum exceeding tens of keV. It is conducive to the high-contrast imaging of minute structures and for investigating interdisciplinary ultrafast processes. In this study, we present a betatron X-ray source derived from a high-charge, high-energy electron beam through a laser wakefield accelerator driven by the 1 PW/0.1 Hz laser system at the Shanghai Superintense Ultrafast Laser Facility (SULF). The critical energy of the betatron X-ray source is 22 ± 5 keV. The maximum X-ray flux reaches up to 4 × 109 photons for each shot in the spectral range of 5–30 keV. Correspondingly, the experiment demonstrates a peak brightness of 1.0 × 1023 photons·s−1·mm−2·mrad−2·0.1%BW−1, comparable to those demonstrated by third-generation synchrotron light sources. In addition, the imaging capability of the betatron X-ray source is validated. This study lays the foundation for future imaging applications.

The effect of the polarizations of two counter-propagating relativistic laser pulses interacting with subwavelength thin solid-density foil is investigated. Three-dimensional particle-in-cell simulations and analytical modelling show that the interaction and resulting transverse instability depend strongly on the polarization directions as well as the intensity distribution of the resultant light field in the foil. The left- and right-handed circularly polarized laser pair with the same phase at the common focal spot in the ultrathin foil leads to the strongest distortion of the foil. The fastest growing mode and maximum growth rate depend mainly on the laser intensity. For all polarization and phase-difference combinations, the instability is weakest when the two laser pulses are exactly out of phase at the common focusing point in the foil.

This study employs direct numerical simulations to examine the effects of varying backpressure conditions on the turbulent atomisation of impinging liquid jets. Using the incompressible Navier–Stokes equations, and a volume-of-fluid approach enhanced by adaptive mesh refinement and an isoface-based interface reconstruction algorithm, we analyse spray characteristics in the environments with ambient gas densities ranging from 1 to 40 times the atmospheric pressure under five different backpressure scenarios. We investigate the behaviour of turbulent jets, incorporate realistic orifice geometries and identify significant variations in the atomisation patterns depending on backpressure. Two distinct atomisation types emerge, namely jet-sheet-ligament-droplet at lower backpressures and jet-sheet-fragment-droplet at higher ones, alongside a transition from dilute to dense spray patterns. This variation affects the droplet size distribution and spray dynamics, with increased backpressure reducing the spray's spreading angle and breakup length, while increasing the droplet size variation. Furthermore, these conditions promote distributions that induce rapid, nonlinear wavy motion in liquid sheets. Topological analysis of the atomisation field using velocity-gradient tensor invariants reveals significant variations in topology volume fractions across different regions. Downstream, the droplet Sauter mean diameter increases and then stabilises, reflecting the continuous breakup and coalescence processes, notably under higher backpressures. This research underscores the substantial impact of backpressure on impinging-jet atomisation and provides essential insights for nozzle design to optimise droplet distributions.

The flexible delivery of single-frequency lasers is far more challenging than that of conventional lasers due to the onset of stimulated Brillouin scattering (SBS). Here we present the successful delivery of 100 W single-frequency laser power through 100 m of anti-resonant hollow-core fiber (AR-HCF) in an all-fiber configuration, with the absence of SBS. By employing a custom-designed AR-HCF with a mode-field diameter matching that of a large-mode-area panda fiber, the system achieves high coupling efficiency without the need for free-space components or fiber post-processing. The AR-HCF attains a transmission efficiency of 92%, delivering an output power of 100.3 W with a beam quality factor (M2) of 1.22. The absence of SBS is confirmed through monitoring backward light, which shows no increase in intensity. This all-fiber architecture ensures high stability, compactness and efficiency, potentially expanding the application scope of single-frequency lasers in high-precision metrology, optical communication, light detection and ranging systems, gravitational wave detection and other advanced applications.

Palygorskite (Pal) shows great potential for physical, chemical and biological uses due to its colloidal, catalytic and adsorption properties. Pal mines, however, are facing the challenge of low-grade materials (5–15%), making it difficult to use Pal in emerging fields such as new materials, environmental protection and health. Therefore, there is an urgent need to develop an efficient method for separating and purifying Pal to obtain high purity levels. Hence, we have developed a dispersant-assisted rotating liquid film reactor separation strategy based on sodium hexametaphosphate as the dispersant. This strategy utilizes the double electron layer of Pal and the density difference between impurities to achieve effective disaggregation and purification of Pal bundles through the promotion of repulsive driving effects. Under optimal conditions, the purity of Pal can be increased from less than 10% to over 80%. This research presents a novel approach to the efficient refining of low-grade Pal. The crudely purified Pal’s adsorption capacity for methylene blue increased from 84.2 to 256.4 mg g–1.