One of the most common harmful mites in edible fungi is Histiostoma feroniarum Dufour (Acaridida: Histiostomatidae), a fungivorous astigmatid mite that feeds on hyphae and fruiting bodies, thereby transmitting pathogens. This study examined the effects of seven constant temperatures and 10 types of mushrooms on the growth and development of H. feroniarum, as well as its host preference. Developmental time for the total immature stages was significantly affected by the type of mushroom species, ranging from 4.3 ± 0.4 days (reared on Pleurotus eryngii var. tuoliensis Mou at 28°C) to 17.1 ± 2.3 days (reared on Auricularia polytricha Sacc. at 19°C). The temperature was a major factor in the formation of facultative heteromorphic deutonymphs (hypopi). The mite entered the hypopus stage when the temperature dropped to 16°C or rose above 31°C. The growth and development of this mite were significantly influenced by the type of species and variety of mushrooms. Moreover, the fungivorous astigmatid mite preferred to feed on the ‘Wuxiang No. 1’ strain of Lentinula edodes (Berk.) Pegler and the ‘Gaowenxiu’ strain of P. pulmonarius (Fr.) Quél., with a shorter development period compared with that of feeding on other strains. These results therefore quantify the effect of host type and temperature on fungivorous astigmatid mite growth and development rates, and provide a reference for applying mushroom cultivar resistance to biological pest control.

Using the idea of local entropy theory, we characterize the sequence entropy tuple via mean forms of the sensitive tuple in both topological and measure-theoretical senses. For the measure-theoretical sense, we show that for an ergodic measure-preserving system, the $\mu $ -sequence entropy tuple, the $\mu $ -mean sensitive tuple, and the $\mu $ -sensitive in the mean tuple coincide, and give an example to show that the ergodicity condition is necessary. For the topological sense, we show that for a certain class of minimal systems, the mean sensitive tuple is the sequence entropy tuple.

Wireless capsule endoscopes (WCEs) are pill-sized camera-embedded devices that can provide visualization of the gastrointestinal (GI) tract by capturing and transmitting images to an external receiver. Determination of the exact location of the WCE is crucial for the accurate navigation of the WCE through external guidance, tracking of the GI abnormality, and the treatment of the detected disease. Despite the enormous progress in the real-time tracking of the WCE, a well-calibrated analytical model is still missing for the accurate localization of WCEs by the measurements from different onboard sensing units. In this paper, a well-calibrated analytical model for the magnetic localization of the WCE was established by optimizing the magnetic moment in the magnetic dipole model. The Jacobian-based iterative method was employed to solve the position of the WCE. An error model was established and experimentally verified for the analysis and prediction of the localization errors caused by inaccurate measurements from the magnetic field sensor. The assessment of the real-time localization of the WCE was performed via experimental trials using an external permanent magnet (EPM) mounted on a robotic manipulator and a WCE equipped with a 3-axis magnetic field sensor and an inertial measurement unit (IMU). The localization errors were measured under different translational and rotational motion modes and working spaces. The results showed that the selection of workspace (distance relative to the EPM) could lead to different positioning errors. The proposed magnetic localization method holds great potential for the real-time localization of WCEs when performing complex motions during GI diagnosis.

Everyone faces uncertainty on a daily basis. Two kinds of probability expressions, verbal and numerical, have been used to characterize the uncertainty that we face. Because our cognitive concept of living things differs from that of non-living things, and distinguishing cognitive concepts might have linguistic markers, we designed four studies to test whether people use different probability expressions when faced with animate or inanimate uncertainty. We found that verbal probability is the preferred way to express animate uncertainty, whereas numerical probability is the preferred way to express inanimate uncertainty. The “verbal-animate” and “numerical-inanimate” associations were robust enough to persist when tested with forced-choice response patterns regardless of the information (e.g., equally likely outcomes, frequencies, or personal beliefs) used to construct probabilities of events. When the response pattern was changed to free-responses, the associations were evident unless the subjects were asked to write their own probability predictions for vague uncertainty. Given that the world around us consists of both animate (i.e., living) and inanimate (i.e., non-living) things, “verbal-animate” and “numerical-inanimate” associations may play a major role in risk communication and may otherwise be useful for practitioners and consultants.

We consider $L^{2}$-constraint minimizers of the mass critical fractional Schrödinger energy functional with a ring-shaped potential $V(x)=(|x|-M)^{2}$, where $M>0$ and $x\in \mathbb {R}^{2}$. By analysing some new estimates on the least energy of the mass critical fractional Schrödinger energy functional, we obtain the concentration behaviour of each minimizer of the mass critical fractional Schrödinger energy functional when $a\nearrow a^{\ast }=\|Q\|_{2}^{2s}$, where $Q$ is the unique positive radial solution of $(-\Delta )^{s}u+su-|u|^{2s}u=0$ in $\mathbb {R}^{2}$.

The influence of second-order dispersion (SOD) on stimulated Raman scattering (SRS) in the interaction of an ultrashort intense laser with plasma was investigated. More significant backward SRS was observed with the increase of the absolute value of SOD ($\mid \kern-1pt\!{\psi}_2\!\kern-1pt\mid$). The integrated intensity of the scattered light is positively correlated to the driver laser pulse duration. Accompanied by the side SRS, filaments with different angles along the laser propagation direction were observed in the transverse shadowgraph. A model incorporating Landau damping and above-threshold ionization was developed to explain the SOD-dependent angular distribution of the filaments.

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.

A pulsed fast neutron source is critical for applications of fast neutron resonance radiography and fast neutron absorption spectroscopy. However, due to the large transversal source size (of the order of mm) and long pulse duration (of the order of ns) of traditional pulsed fast neutron sources, it is difficult to realize high-contrast neutron imaging with high spatial resolution and a fine absorption spectrum. Here, we experimentally present a micro-size ultra-short pulsed neutron source by a table-top laser–plasma wakefield electron accelerator driving a photofission reaction in a thin metal converter. A fast neutron source with source size of approximately 500 μm and duration of approximately 36 ps has been driven by a tens of MeV, collimated, micro-size electron beam via a hundred TW laser facility. This micro-size ultra-short pulsed neutron source has the potential to improve the energy resolution of a fast neutron absorption spectrum dozens of times to, for example, approximately 100 eV at 1.65 MeV, which could be of benefit for high-quality fast neutron imaging and deep understanding of the theoretical model of neutron physics.

We propose a conjectural list of Fano manifolds of Picard number $1$ with pseudoeffective normalised tangent bundles, which we prove in various situations by relating it to the complete divisibility conjecture of Francesco Russo and Fyodor L. Zak on varieties with small codegree. Furthermore, the pseudoeffective thresholds and, hence, the pseudoeffective cones of the projectivised tangent bundles of rational homogeneous spaces of Picard number $1$ are explicitly determined by studying the total dual variety of minimal rational tangents (VMRTs) and the geometry of stratified Mukai flops. As a by-product, we obtain sharp vanishing theorems on the global twisted symmetric holomorphic vector fields on rational homogeneous spaces of Picard number $1$ .

A system of mutually interacting superprocesses with migration is constructed as the limit of a sequence of branching particle systems arising from population models. The uniqueness in law of the superprocesses is established using the pathwise uniqueness of a system of stochastic partial differential equations, which is satisfied by the corresponding system of distribution function-valued processes.

Mycoplasma genitalium (MG) and Chlamydia trachomatis (CT) are the most common sexually transmitted pathogens, which can cause cervicitis, pelvic inflammation and infertility in female. In the present study, we collected the basic information, clinical results of leucorrhoea and human papillomavirus (HPV) infection of patients, who were involved in both MG and CT RNA detection in West China Second Hospital of Sichuan University from January 2019 to April 2021, ranging from 18 to 50 years old. The results showed that the infection frequencies of MG and CT were 2.6% and 6.5%, respectively. The infection rate of CT in gynaecological patients was significantly higher than that of MG (P < 0.001). Moreover, patients with CT infection often had symptoms of gynaecological diseases, while patients with MG infection remain often asymptomatic. By exploring the connection between MG or CT infection and vaginal secretions, we found that the infection of MG or CT promoted to the increase of vaginal leukocytes, and CT infection exacerbated the decrease of the number of Lactobacillus in the vagina. Further analysis suggested that independent infection and co-infection of MG or CT resulted in abnormal vaginal secretion, affecting the stability of vaginal environment, which may induce vaginal diseases. Unexpectedly, our study found no association between MG or CT infection and high-risk HPV infection. In conclusion, our study explored the infection of MG and CT among women in Southwest China for the first time, and revealed that the infection of MG or CT would affect the homeostasis of vaginal environment, which laid a foundation for the clinical diagnosis and treatment of MG and CT infection.

The rapid and accurate taxonomic identification of fossils is of great significance in paleontology, biostratigraphy, and other fields. However, taxonomic identification is often labor-intensive and tedious, and the requisition of extensive prior knowledge about a taxonomic group also requires long-term training. Moreover, identification results are often inconsistent across researchers and communities. Accordingly, in this study, we used deep learning to support taxonomic identification. We used web crawlers to collect the Fossil Image Dataset (FID) via the Internet, obtaining 415,339 images belonging to 50 fossil clades. Then we trained three powerful convolutional neural networks on a high-performance workstation. The Inception-ResNet-v2 architecture achieved an average accuracy of 0.90 in the test dataset when transfer learning was applied. The clades of microfossils and vertebrate fossils exhibited the highest identification accuracies of 0.95 and 0.90, respectively. In contrast, clades of sponges, bryozoans, and trace fossils with various morphologies or with few samples in the dataset exhibited a performance below 0.80. Visual explanation methods further highlighted the discrepancies among different fossil clades and suggested similarities between the identifications made by machine classifiers and taxonomists. Collecting large paleontological datasets from various sources, such as the literature, digitization of dark data, citizen-science data, and public data from the Internet may further enhance deep learning methods and their adoption. Such developments will also possibly lead to image-based systematic taxonomy to be replaced by machine-aided classification in the future. Pioneering studies can include microfossils and some invertebrate fossils. To contribute to this development, we deployed our model on a server for public access at www.ai-fossil.com.

The structure, powder diffraction patterns and bandgap measurements of a series of manganese- and tungsten-containing alkaline-earth double perovskites (CaxSr2−x)MnWO6 (x = 0.25, 0.5, 0.75, 1.5, 1.75) have been investigated. Powder X-ray diffraction patterns of this series of compounds measured at room temperature have been submitted to be included in the Powder Diffraction File (PDF). These compounds crystallize in monoclinic space group P21/n (No.14). From (Ca1.75 Sr0.25)MnWO6 to (Ca0.25Sr1.75)MnWO6, lattice parameters a range from 5.6729(2) Å to 5.6774(4) Å, b from 5.5160(2) Å to 5.6638(4) Å, c from 7.8741(3) Å to 8.0051(4) Å, V from 240.39(2) Å3 to 257.410(12) Å3, and Z = 2. These compounds are pseudo-tetragonal. They all consist of distorted MnO6 and WO6 octahedra with rotational mismatch angles and tilt angles with respect to each other. For (CaxSr2−x)MnWO6, as x increases, the mismatch angles for MnO6 octahedra increase from 7.96 (6)° to 13.12(8)° and from 9.28(7)° to 14.87(9)° for WO6 octahedra. Correspondingly, the tilt angles range from 11.60(15)° to 14.20(3)° for MnO6, and from 13.34(2)° to 16.35(3)° for WO6. Bandgap measurements suggest that these compounds to be direct-allowed semiconductors with bandgaps ranging from 1.5 to 2.5 eV, indicating that members of (CaxSr2−x)MnWO6 are potential photocatalysts and photovoltaic materials that absorb visible light of the solar spectrum.

Blood oxygen is an essential component for numerous biological processes of mammalian animals. Milk production of ruminants largely relies on the supply of nutrients, such as glucose, amino acids and fatty acids. To define the regulatory role of blood oxygen availability in regard to milk production, seventy-five healthy Guanzhong dairy goats with similar body weight, days in milk and parities were selected. For each animal, milk yield was recorded and milk sample was collected to determine compositions. Milk vein blood was collected to determine parameters including blood gas, physio-biochemistry and haematology. Another blood sample was prepared for transcriptome and RT-qPCR. Results showed that both pressure of oxygen (pO2) in the milk vein (positively) and numbers of neutrophils in mammary vein (negatively) were associated with milk yield of the animals. To learn the role of pO2 in blood cell functionality, twelve animals (six with higher yield (H-group) and six with lower yield (L-group)) from seventy-five goats were selected. Compared with animals in L-group, goats in H-group were higher in pO2 but lower in pCO2, lactate, lactate dehydrogenase activity and neutrophil abundance in milk vein, compared with L-group. The blood transcriptome analysis suggested that compared with L-group, animals in H-group were depressed in functionality including neutrophil activation and metabolic pathways including glycolysis, NF-κB and HIF-1. Our result revealed that lower milk production could be associated with neutrophil activation responding to low pO2 in the mammary vein. In the meantime, we highlighted the potential importance of blood oxygen as a milk yield regulator.

HMGR, 3-hydroxy-3-methylglutaryl-CoA reductase, is a major rate-limiting enzyme in mevalonate (MVA) pathway for isoprenoids and subsequent tanshinone biosynthesis in the Chinese traditional bulk herbal medicine Danshen, Salvia miltiorrhiza, mainly for cardiovascular disorders. In this paper, the genomic SmHMGR genes of 38 cultivated populations of S. miltiorrhiza collected in China were for the first time sequenced to reveal the genetic diversity and phylogeny. The SmHMGR gene was shown to be intron-free, 1650~1659 bp in complete CDS with the majority being 1656 bp, and two unique populations (W-FJLY-V-1 and W-SCHY-W-1) being 1659 and 1650 bp respectively. A total of 103 SNP variation sites were detected with a variation rate of 6.22%, most of which occurred in S. miltiorrhiza f. alba population W-SCHY-W-1; a total of 25 amino acid variation sites were found, of which 19 was in W-SCHY-W-1. The same four populations, W-SCHY-W-1, V-HBAG-V-1, V-JLCC-V-1 and S-NM-V-1 could be discriminated from the remaining 34 by both the SNP fingerprints and the deduced amino acid variation sites. Other or composite DNA markers are needed for better identification. The SmHMGR gene of white flower S. miltiorrhiza f. alba population W-SCHY-W-1 is especially rich in variations and worthy of further studies. Phylogenetic trees based on both the gene and the deduced amino acid sequences showed a very similar two-clade topological structure. This research enriched the content and the genetic means for the molecular identification, genetic diversity and phylogenetic studies of the cultivated S. miltiorrhiza populations, and laid a solid foundation for further related and in-depth investigations.

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.