In the digital information age, artificial intelligence is increasingly being applied to national governance and judicial decision-making assistance. Existing studies lack case studies and empirical analyses of the effectiveness of large models in aiding judicial decisions. To address this research gap, this study designs a comprehensive evaluation framework encompassing five core task dimensions: Task-oriented Information Extraction, Legal Article Citation, Event Extraction, Judicial Decision Generation, and Legal Opinion Generation. By using carefully crafted prompts to activate the legal reasoning capabilities of the models, we conducted extensive testing on 13 mainstream large language models (LLMs). The experimental results demonstrate that large models perform excellently in processing legal texts and providing preliminary legal opinions, but still exhibit shortcomings in complex legal reasoning and precise decision-making. On this basis, we applied a weakly supervised learning strategy to fine-tune the LLMs for targeted improvements. The results indicate that introducing a small amount of task-specific learning can significantly enhance the performance of LLMs in judicial tasks. This further underscores the critical role of data and the acquisition of domain-specific knowledge in applying AI technology to judicial tasks. Additionally, this study briefly discusses the issue of the boundaries of AI’s involvement in judicial activities, aiming to provide theoretical foundations and practical guidance for the deep integration of AI technology with legal practice.

The quarantine pest, Opisina arenosella Walker, poses a significant threat to 34 palm plant species, including economically vital coconut trees. Its adaptability and rapid spread raise concerns about global tree invasion and potential economic and environmental impacts. Utilising advanced sequencing technology, this study aims to analyse O. arenosella mitochondrial genome, comparing it with three Lepidoptera families to explore its phylogenetic status. The complete mitochondrial genome (15,389 bp) was sequenced using the Illumina HiSeq platform, with tRNA genes validated using tRNAScan-SE and MITOS WebServer. Comparative analysis involved 13 protein-coding genes and 2 ribosomal RNA genes, comparing them with outgroup species like Agapanthia amurensis. The results revealed that O. arenosella genome’s nucleotide composition is 39.24% A, 41.33% T, 12.02% C, and 7.41% G. The phylogenetic tree was constructed using maximum likelihood (ML) and Bayesian inference (BI) methods. Interestingly, in the BI analysis, (O. arenosella + Ripeacma umbellate) clustered together with ((Promalactis suzukiella + Promalactis odaiensis) + (Stathmopoda auriferella + Casmara patrona)), forming a clade with high node support, while ML lacked high node support. Additionally, both methods indicated a monophyletic clade with high node support for Comparmustilia, Oberthueria, Pseudandraca, and Andraca. This research provides valuable mitochondrial genome data, contributing to phylogenetics and taxonomy studies, establishing a foundation for future research in this field.

The nonlinear Tollmien–Schlichting waves mechanism of subcritical transitional flow in quasi-two-dimensional flow and two-dimensional (2-D) plane Poiseuille flow have been investigated (Camobreco et al. 2023 J. Fluid Mech., vol. 963, p. R2; Huang et al. 2024 J. Fluid Mech., vol. 994, p. A6). However, the subcritical transitional flow threshold has remained unsolved for 2-D shear flows since the problem was proposed in Trefethen et al. (1993 Science vol. 261, no. 5121, pp. 578–584). In this study, we proposed a theoretical analysis based on the nonlinear non-modal analysis and asymptotic analysis to quantify the scaling law for subcritical transitional flow of 2-D plane Poiseuille flow. The subcritical transitional flow induced by the critical disturbance experiences the nonlinear edge state with invariant disturbance kinetic energy (Huang et al. 2024 J. Fluid Mech. vol. 994, p. A6). Consequently, the required magnitude along with the edge state is predicted by asymptotic analysis, and the a priori threshold is achieved theoretically. All stages are validated by the numerical minimal seeds of different channels. The proposed theory predicts that the scaling laws are $O(Re^{-11/3})$ and $O(\textit{Re}^{-7/3})$ for the critical disturbances and their edge state, respectively. While the numerical thresholds of the subcritical transitional flow are $ \textit{Re}^{-11/3 \pm 0.06}$ and $ \textit{Re}^{-7/3 \pm 0.05}$, respectively.

To investigate the characteristics of a turbulent boundary layer (TBL) over the curved edge of the bow of submarine technology program office (SUBOFF) model, wall-resolved large-eddy simulation is conducted at a Reynolds number of $\mathop {\textit{Re}}\nolimits _L = 1.1 \times {10^6}$ based on the model length and free-stream velocity. Instead of using a trip wire at the bow surface, turbulent inflow is added to the simulation to induce boundary layer transition. The effects of geometric curvature and inflow turbulence intensity (ITI) are examined. With a low ITI level, natural transition takes place at the rear end of the straight section. With higher ITI levels, turbulence emerges immediately and evolves gradually, following a strong favourable-pressure-gradient (FPG) region near the forehead, which is significantly influenced by the large streamwise curvature. Within the FPG region, the root mean square of the wall pressure fluctuation (WPF) decreases rapidly, with the frequency spectra of WPF exhibiting good scalability with outer variables. Moreover, higher turbulence intensity levels lead to larger skin friction, which is related to the development of the TBL. To elucidate the generation mechanism of skin friction, the dynamic decomposition is derived in the curvilinear coordinate system. The mean convection and streamwise pressure gradient make the largest contributions to the local skin friction. Furthermore, an analysis of the energy transfer process based on the Reynolds stress transport equations in the curvilinear coordinate system is presented, highlighting the significant impact of geometric effects, particularly on the production term.

A type of signal-interference fourth-order dual-band bandpass filter (BPF) with multiple out-of-band transmission zeros (TZs) is reported. A second-order dual-band BPF block is firstly discussed, which is composed of two microstrip-to-slotline vertical transitions that are back-to-back connected by means of an in-parallel asymmetrical microstrip-line-based closed loop. It exhibits spectrally symmetrical passbands regarding the design frequency fD and three TZs at the inter-band region. Subsequently, by using stepped-impedance-line segments at the longest path of the transversal signal-interference closed loop, its dual-band BPF counterpart with second-order spectrally asymmetrical dual passbands is presented. Next, in order to increase the filter order as well as the number of out-of-band TZs for augmented stopband attenuation, a fourth-order dual-band BPF circuit is conceived. To this aim, two Y-shaped stepped-impedance microstrip stubs are loaded at the input and output ports of the previously devised second-order frequency-symmetrical dual-band BPF block. The RF operational principles of all these dual-band BPFs are detailed through their associated transmission-line-based equivalent circuits. Moreover, for experimental-demonstration purposes, a 1.154-/2.818-GHz two-layer microstrip proof-of-concept prototype of a fourth-order sharp-rejection dual-band BPF is designed, simulated, and characterized. It features inter-band power-rejection levels higher than 28.68 dB and lower-/upper-stopband attenuation levels above 40.92 dB from DC to 4.64 GHz.

Posttraumatic stress disorder (PTSD) is a heterogenous disorder with frequent diagnostic comorbidity. Research has deciphered this heterogeneity by identifying PTSD subtypes and their neural biomarkers. This review summarizes current approaches, symptom-based group-level and data-driven approaches, for generating PTSD subtypes, providing an overview of current PTSD subtypes and their neural correlates. Additionally, we systematically assessed studies to evaluate the influence of comorbidity on PTSD subtypes and the predictive utility of biotypes for treatment outcomes. Following the PRISMA guidelines, a systematic search was conducted to identify studies employing brain imaging techniques, including functional magnetic resonance imaging (fMRI), structural MRI, diffusion-weighted imaging (DWI), and electroencephalogram (EEG), to identify biomarkers of PTSD subtypes. Study quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. We included 53 studies, with 44 studies using a symptom-based group-level approach, and nine studies using a data-driven approach. Findings suggest biomarkers across the default-mode network (DMN) and the salience network (SN) throughout multiple subtypes. However, only six studies considered comorbidity, and four studies tested the utility of biotypes in predicting treatment outcomes. These findings highlight the complexity of PTSD’s heterogeneity. Although symptom-based and data-driven methods have advanced our understanding of PTSD subtypes, challenges remain in addressing the impact of comorbidities and the limited validation of biotypes. Future studies with larger sample sizes, brain-based data-driven approaches, careful account for comorbidity, and rigorous validation strategies are needed to advance biologically grounded biotypes across mental disorders.

The attachment-line boundary layer is critical in hypersonic flows because of its significant impact on heat transfer and aerodynamic performance. In this study, high-fidelity numerical simulations are conducted to analyse the subcritical roughness-induced laminar–turbulent transition at the leading-edge attachment-line boundary layer of a blunt swept body under hypersonic conditions. This simulation represents a significant advancement by successfully reproducing the complete leading-edge contamination process induced by a surface roughness element in a realistic configuration, thereby providing previously unattainable insights. Two roughness elements of different heights are examined. For the lower-height roughness element, additional unsteady perturbations are required to trigger a transition in the wake, suggesting that the flow field around the roughness element acts as a perturbation amplifier for upstream perturbations. Conversely, a higher roughness element can independently induce the transition. A low-frequency absolute instability is detected behind the roughness, leading to the formation of streaks. The secondary instabilities of these streaks are identified as the direct cause of the final transition.

This paper presents a method to design the response threshold (RT) of energy selective surface (ESS) based on series LC circuits (SLC_based_ESS). A simple SLC_based_ESS structure composed of metal strips and PIN diodes is used for demonstration. According to our research, the RT is rarely related to the geometry parameters of unit cells. By contrast, the RT could be designed by introducing auxiliary structures (ASs) to SLC_based_ESS arrays. With the AS, the induced currents on diodes are enhanced and thus RT is greatly reduced. Prototypes are fabricated and measured under different power levels. The results agree well with simulations, proving an effective design of RT by the proposed method.

The seminal Bolgiano–Obukhov (BO) theory established the fundamental framework for turbulent mixing and energy transfer in stably stratified fluids. However, the presence of BO scalings remains debatable despite their being observed in stably stratified atmospheric layers and convective turbulence. In this study, we performed precise temperature measurements with 51 high-resolution loggers above the seafloor for 46 h on the continental shelf of the northern South China Sea. The temperature observation exhibits three layers with increasing distance from the seafloor: the bottom mixed layer (BML), the mixing zone and the internal wave zone. A BO-like scaling $\alpha =-1.34\pm 0.10$ is observed in the temperature spectrum when the BML is in a weakly stable stratified ($N\sim 0.0018$ rad s$^{-1}$) and strongly sheared ($Ri\sim 0.0027$) condition, whereas in the unstably stratified convective turbulence of the BML, the scaling $\alpha =-1.76\pm 0.10$ clearly deviated from the BO theory but approached the classical $-$5/3 scaling in isotropic turbulence. This suggests that the convective turbulence is not the promise of BO scaling. In the mixing zone, where internal waves alternately interact with the BML, the scaling follows the Kolmogorov scaling. In the internal wave zone, the scaling $\alpha =-2.12 \pm 0.15$ is observed in the turbulence range and possible mechanisms are provided.