Pulse shaping is a powerful tool for mitigating implosion instabilities in direct-drive inertial confinement fusion (ICF). However, the high-dimensional and nonlinear nature of implosions makes the pulse optimization quite challenging. In this research, we develop a machine-learning pulse shape designer to achieve high compression density and stable implosion. The facility-specific laser imprint pattern is considered in the optimization, which makes the pulse design more relevant. The designer is applied to the novel double-cone ignition scheme, and simulation shows that the optimized pulse increases the areal density expectation by 16% in one dimension, and the clean-fuel thickness by a factor of four in two dimensions. This pulse shape designer could be a useful tool for direct-drive ICF instability control.

In this paper, we prove that the ratio of the modulus of the iterates of two points in an escaping Fatou component could be bounded even if the orbit of the component contains a sequence of annuli whose moduli tend to infinity, and this cannot happen when the maximal modulus of the meromorphic function is uniformly large enough. In this way we extend certain related results for entire functions to meromorphic functions with infinitely many poles.

The mitochondrial genome provides important information for phylogenetic analysis and an understanding of evolutionary origin. In this study, the mitochondrial genomes of Ilisha elongata and Setipinna tenuifilis were sequenced, which are typical circular vertebrate mitochondrial genomes composed of 16,770 and 16,805 bp, respectively. The mitogenomes of I. elongata and S. tenuifilis include 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA), two ribosomal RNA (rRNA) genes and one control region (CR). Both two species' genome compositions were highly A + T biased and exhibited positive AT-skews and negative GC-skews. The genetic distance and Ka/Ks ratio analyses indicated that 13 PCGs were affected by purifying selection and the selection pressures were different from certain deep-sea fishes, which were most likely due to the difference in their living environment. Results of phylogenetic analysis support close relationships among Chirocentridae, Denticipitidae, Clupeidae, Engraulidae and Pristigasteridae based on the nucleotide and amino acid sequences of 13 PCGs. Within Clupeoidei, I. elongata and S. tenuifilis were most closely related to the family Pristigasteridae and Engraulidae, respectively. These results will help to better understand the evolutionary position of Clupeiformes and provide a reference for further phylogenetic research on Clupeiformes species.

Recently, the collisionless pitch-angle scattering for relativistic runaway electrons (REs) in toroidal geometries such as tokamaks was discovered through a full orbit simulation approach (Liu et al., Nucl. Fusion, vol. 56, 2016, p. 064002), and it was then theoretically investigated that a new expression for the magnetic moment, including the second-order corrections, could essentially reproduce the so-called collisionless pitch-angle scattering process (Liu et al., Nucl. Fusion, vol. 58, 2018, p. 106018). In this paper, with synchrotron radiation, extensive numerical verification of the validity of the high-order guiding-centre theory is given for simulations involving REs by incorporating such an expression for the magnetic moment into our particle tracing code. A high-order guiding-centre simulation approach with synchrotron radiation (HGSA) is applied. Synchrotron radiation plays an essential role in the life cycle of REs. The energy of REs first increases and then becomes saturated until the electric field acceleration is balanced by the radiation dissipation. Unfortunately, the process cannot be simulated accurately with the standard guiding-centre model, i.e. the first-order guiding-centre model. Remarkably, it is found that the HGSA can effectively produce the fundamental process of REs. Since the time scale of the energy saturation of REs is close to seconds, the computational cost becomes significant. In order to save costs, it is necessary to estimate the time of energy saturation. An analytical estimate is derived for the time it takes for synchrotron drag to balance an accelerating electric field and the provided formula has been numerically verified. Test calculations reveal that HGSA is favourable for exploiting the dynamics of REs in tokamak plasmas.

This paper examines the economic implications of the tariff increases by the United States and by China during the Trump era trade dispute and the gains from their potential removal. The increases were dramatic, with the US raising tariffs on industrial products by a factor of six – with particularly large tariff increases on intermediate and capital goods – and China increasing its tariffs on US agricultural products more than five-fold. These changes distort trade and production decisions in both countries and undercut the global trading system. They resulted in substantial economic losses to each country, with import volumes reduced by 4.9% in China and 4.5% in the USA, and bilateral trade patterns were massively distorted. Their cost to the United States rose at the end of 2021, when the import expansion provisions of the Trump era Phase One Agreement expired. Negotiating the abolition of these costly and disruptive tariffs would generate substantial real income gains for both countries and help lower US consumer prices.

The optimization of laser pulse shapes is of great importance and a major challenge for laser direct-drive implosions. In this paper, we propose an efficient intelligent method to perform laser pulse optimization via hydrodynamic simulations guided by the genetic algorithm and random forest algorithm. Compared to manual optimizations, the machine-learning guided method is able to efficiently improve the areal density by a factor of 63% and reduce the in-flight-aspect ratio by a factor of 30% at the same time. A relationship between the maximum areal density and ion temperature is also achieved by the analysis of the big simulation dataset. This design method has been successfully demonstrated by the 2021 summer double-cone ignition experiments conducted at the SG-II upgrade laser facility and has great prospects for the design of other inertial fusion experiments.

We evaluated the distributions of dental splatters and the corresponding control measure effects with high-speed videography and laser diffraction. Most of the dental splatters were small droplets (<50 μm). High-volume evacuation combined with a suction air purifier could clear away most of the droplets and aerosols.

Electromagnetic inverse-scattering problems (ISPs) are concerned with determining the properties of an unknown object using measured scattered fields. ISPs are often highly nonlinear, causing the problem to be very difficult to address. In addition, the reconstruction images of different optimization methods are distorted which leads to inaccurate reconstruction results. To alleviate these issues, we propose a new linear model solution of generative adversarial network-based (LM-GAN) inspired by generative adversarial networks (GAN). Two sub-networks are trained alternately in the adversarial framework. A linear deep iterative network as a generative network captures the spatial distribution of the data, and a discriminative network estimates the probability of a sample from the training data. Numerical results validate that LM-GAN has admirable fidelity and accuracy when reconstructing complex scatterers.

What are the major factors contributing to ship accidents, and how do these factors evolve in the long term? This study addresses these two questions by leveraging an unsupervised machine learning method named structural topic modelling to identify the causes of ship accidents. The study analysed 2,341 task errors manually collected from 441 reports issued by four government agencies covering a 45-year time span. The results show that the structure of causes of ship accidents remained essentially the same during this period. This highlights the social-material aspect of navigation technology, indicating that the use of advanced technology may not necessarily lead to safer navigation practices, and the interaction between the technology and human agency must be focused on in the bridge management context. Additionally, the computer-assisted textual data analysis highlights pilot-related factors, which might be rooted in the unsupervised and difficult-to-verify handover procedures between pilots and captains, thereby underlining the importance of appropriate piloting regulations.

In the laser plasma interaction of quantum electrodynamics (QED)-dominated regime, γ-rays are generated due to synchrotron radiation from high-energy electrons traveling in a strong background electromagnetic field. With the aid of 2D particle-in-cell code including QED physics, we investigate the preplasma effect on the γ-ray generation during the interaction between an ultraintense laser pulse and solid targets. We found that with the increasing preplasma scale length, the γ-ray emission is enhanced significantly and finally reaches a steady state. Meanwhile, the γ-ray beam becomes collimated. This shows that, in some cases, the preplasmas will be piled up acting as a plasma mirror in the underdense preplasma region, where the γ-rays are produced by the collision between the forward electrons and the reflected laser fields from the piled plasma. The piled plasma plays the same role as the usual reflection mirror made from a solid target. Thus, a single solid target with proper scale length preplasma can serve as a manufactural and robust γ-ray source.

Obstacle avoidance navigation for an unmanned surface vessel is a research focus for ship autonomy in which the real-time requirement in practical application is very serious, and always necessitates a complicated structure model to guarantee real-time performance. This paper proposes the grid cell activation model to reduce the complexity of modelling and to simplify an obstacle avoidance algorithm. Combined with the goal-oriented probability model to design a dynamic positive-loss-rate expectation evaluation function, it produces the proper strategy for obstacle avoidance. Case studies on multi-obstacle layouts and special circumstances are conducted and presented. The results indicate that the grid cell obstacle avoidance algorithm can effectively implement obstacle avoidance planning and ensure real-time requirements. A comparison with the potential field algorithm is performed, which shows good results and verifies the feasibility of the algorithm.

The Wulian complex is located on the northern margin of the Sulu orogenic belt, and was formed by collision between the North China Craton (NCC) to the north and South China Craton (SCC) to the south. It consists of the metasedimentary Wulian Group, gneissic granite and meta-diorite. The U–Pb analyses for the detrital zircons from the Wulian Group exhibit one predominant age population of 2600–2400 Ma with a peak at c. 2.5 Ga and several secondary age populations of > 3000, 3000–2800, 2800–2600, 2200–2000, 1900–1800, 1500–1300 and 1250–950 Ma; some metamorphic zircons have metamorphic ages of c. 2.7, 2.55–2.45, 2.1–2.0 and 1.95–1.80 Ga, which are consistent with magmatic-metamorphic events in the SCC. Additionally, the Wulian Group was intruded by the gneissic granite and meta-diorite at c. 0.76 Ga, attributed to Neoproterozoic syn-rifting bimodal magmatic activity in the SCC and derived from partial melting of Archaean continental crust and depleted mantle, respectively. The Wulian Group therefore has tectonic affinity to the SCC and was mainly sourced from the SCC. The detrital zircons have positive and negative ϵHf(t) values, indicating that their source rocks were derived from reworking of both ancient and juvenile crustal rocks. The major early Precambrian crustal growth took place during c. 3.4–2.5 Ga with a dominant peak at 2.96 Ga and several secondary peaks at 3.27, 2.74 and 2.52 Ga. The two oldest zircons with ages of 3307 and 3347 Ma record the recycling of ancient continental crust (> 3.35 Ga) and crustal growth prior to c. 3.95 Ga in the SCC.

This paper studies the parameter estimation for Ornstein–Uhlenbeck stochastic volatility models driven by Lévy processes. We propose computationally efficient estimators based on the method of moments that are robust to model misspecification. We develop an analytical framework that enables closed-form representation of model parameters in terms of the moments and autocorrelations of observed underlying processes. Under moderate assumptions, which are typically much weaker than those for likelihood methods, we prove large-sample behaviors for our proposed estimators, including strong consistency and asymptotic normality. Our estimators obtain the canonical square-root convergence rate and are shown through numerical experiments to outperform likelihood-based methods.