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.

The vertebrate retina contains a large number of different types of neurons that can be distinguished by their morphological properties. Assuming that no location should be without a contribution from the circuitry and function linked to a specific type of neuron, it is expected that the dendritic trees of neurons belonging to a type will cover the retina in a regular manner. Thus, for most types of neurons, the contribution to visual processing is thought to be independent of the exact location of individual neurons across the retina. Here, we have investigated the distribution of AII amacrine cells in rat retina. The AII is a multifunctional amacrine cell found in mammals and involved in synaptic microcircuits that contribute to visual processing under both scotopic and photopic conditions. Previous investigations have suggested that AIIs are regularly distributed, with a nearest-neighbor distance regularity index of ~4. It has been argued, however, that this presumed regularity results from treating somas as points, without taking into account their actual spatial extent which constrains the location of other cells of the same type. When we simulated random distributions of cell bodies with size and density similar to real AIIs, we confirmed that the simulated distributions could not be distinguished from the distributions observed experimentally for AIIs in different regions and eccentricities of the retina. The developmental mechanisms that generate the observed distributions of AIIs remain to be investigated.

Hypertension represents one of the most common pre-existing conditions and comorbidities in Coronavirus disease 2019 (COVID-19) patients. To explore whether hypertension serves as a risk factor for disease severity, a multi-centre, retrospective study was conducted in COVID-19 patients. A total of 498 consecutively hospitalised patients with lab-confirmed COVID-19 in China were enrolled in this cohort. Using logistic regression, we assessed the association between hypertension and the likelihood of severe illness with adjustment for confounders. We observed that more than 16% of the enrolled patients exhibited pre-existing hypertension on admission. More severe COVID-19 cases occurred in individuals with hypertension than those without hypertension (21% vs. 10%, P = 0.007). Hypertension associated with the increased risk of severe illness, which was not modified by other demographic factors, such as age, sex, hospital geological location and blood pressure levels on admission. More attention and treatment should be offered to patients with underlying hypertension, who usually are older, have more comorbidities and more susceptible to cardiac complications.

Aggressive behaviour is common in animals and typically has lifetime consequences. As younger males have higher residual reproductive value than older males and lose more from injuries than older males do, the propensity for fighting tends to increase with age in many empirical reports and species. However, fighting patterns in those empirical reports cannot confirm the hypothesis that individuals cannot readily inflict injuries on their opponents. To address this shortcoming, a parasitoid wasp species, Anastatus disparis (Hymenoptera: Eupelmidae), was used as an experimental model to explore the characteristics of aggression from a life-history perspective; this wasp exhibits extreme fighting, resulting in contestants experiencing injury and death. Results showed that the energetic costs of fighting to injury significantly shortened life and caused the loss of most mating ability. Inconsistent with general predictions, the frequency and intensity of fighting in A. disparis significantly decreased with male age. Further study results showed significantly more young males were received by and successfully mated with virgin females, and most genes related to energy metabolism were downregulated in aged males. Our study provided supporting evidence that young A. disparis males show more aggression likely because of their resource holding potential and sexual attractiveness decline with age.

To determine whether a potassium dihydrogen phosphate (KDP) surface mitigated by micro-milling would potentially threaten downstream optics, we calculated the light-field modulation based on angular spectrum diffraction theory, and performed a laser damage test on downstream fused silica. The results showed that the downstream light intensification caused by a Gaussian mitigation pit of 800 μm width and 10 μm depth reached a peak value near the KDP rear surface, decreased sharply afterward, and eventually kept stable with the increase in downstream distance. The solved peak value of light intensification exceeded 6 in a range 8–19 mm downstream from the KDP rear surface, which is the most dangerous for downstream optics. Laser damage sites were then induced on the fused silica surface in subsequent laser damage tests. When the distance downstream was greater than 44 mm with a downstream light intensification of less than 3, there were no potential damage threats to downstream optics. The study proves that a mitigated KDP surface can cause laser damage to downstream optical components, to which attention should be paid in an actual application. Through this work, we find that the current manufacturing process and the mitigation index still need to be improved. The research methods and calculation models are also of great reference significance for related studies like optics mitigation and laser damage.

In this work, sulfurizing metal precursors prepared by magnetron sputtering was applied in Cu2ZnSnS4 (CZTS) thin film fabrication. Three precursor structures, namely substrate/ Zn/(Cu&Sn), substrate/Zn/Cu/Sn/Cu and substrate/Zn/Sn/Cu, were compared for their synthesized CZTS film quality. It is notable that CZTS film made of the precursor structure of substrate/Zn/(Cu&Sn) has the best film quality with no obvious voids and biggest average grain size. When applying this precursor structure into device fabrication, a working CZTS device with an efficiency of 2.26% was made. The impact of metal precursors on the structural property of CZTS film were characterised by SEM, XRD, Raman and TEM. Thick MoS2 interfacial layer (∼200nm) between absorber and back Mo contact and ZnS formed in the front and back absorber regions are the possible reasons limiting short-circuit current and fill factor of the cell.

Secondary phases are likely to occur in the Cu2ZnSnS4 (CZTS) films since the CZTS is thermodynamically stable in only a narrow region of the phase diagram. The CZTS solar cell performance can be influenced by the existence and precipitated position of secondary phases. Therefore, locally investigate the distribution of secondary phases is important to further improve CZTS solar cell efficiency. In this study, two different kinds of transmission electron microscopy imaging techniques, bright field scanning TEM image (BF-STEM) and High-angle annular dark-field (HAADF) image, are applied to analyze the distribution of secondary phases. Due to the atomic number differences between CZTS and secondary phases, secondary phases are evident in the HAADF images. Therefore, HAADF image is a more powerful and convenient method to analyze the secondary phases than the BF-STEM image.

A simple empirical method that extracts the elastic moduli of both thin films and the underlying substrates is proposed and validated by both new nanoindentation experiments and published data. Deconvolution of thin film’s elastic properties from the substrate is achieved by statistical estimation, where a simple function relating the elastic moduli of the thin film and substrate to the film-substrate composite modulus is used to fit the experimental data plotted against the logarithmic indentation depth normalized by film thickness. Experimental data from a wide range of soft and hard films on substrate were used to demonstrate the deconvolution and validate the method. The estimated elastic moduli of thin films and substrates agree well with their corresponding standard values or values obtained by other methods. The advantages of this method are discussed, and recommendations are made on how to design experiments to obtain reliable data for this method.