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Orthoptera constitutes an important ecological component of the global fauna. Its Early Jurassic record is limited in China and its evolution is poorly understood after the end-Triassic mass extinction. Several orthopterans are described herein from the Lower Jurassic Badaowan and Sangonghe formations of the southern Junggar Basin, Xinjiang, NW China. From the Badaowan Formation, a new species, Parahagla cheni sp. nov., is established and assigned to Chifengiinae (Hagloidea: Prophalangopsidae), which represents the oldest record of this subfamily. From the Sangonghe Formation, a forewing fragment is attributed to Sinagryllus xinjiangensis Wang et al., 2019 (Grylloidea: Baissogryllidae), another forewing fragment and a metathoracic leg without attribution. Discovery of these fossils increases the biodiversity of Orthoptera in the Early Jurassic, and further indicates that orthopterans likely flourished in the Junggar area during the Early Jurassic. An analysis of orthopteran biodiversity at generic and species levels reveals an extinction in Orthoptera in the Late Triassic, especially for the superfamilies Hagloidea and Oedischioidea, which suffered a substantial extinction. This extinction happened in the Late Triassic, earlier than the mass extinction of marine animals at the end of the Triassic.

The facet-dependent reactivity of CrMn catalysts was still unclear, hindering the further enhancement of their low-temperature SCR performance. Herein, the facet-dependent reactivity of CrMn

Despite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case–control comparisons detected modest expression differences that were correlated across disorders. Case–case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.

The main objective of this paper is to show the design and application on the cracking outlet temperature (COT) system using a hybrid control approach including non-minimal state-space model predictive control with an adjustable factor (AFNMSSMPC) and humanoid intelligent multimodality control (HIMMC) in two 100 k tone/year SC-1 ethylene cracking furnaces. Compared with the conventional control structure, the advanced control structure is designed based on the existing control problem. The advanced controller is developed at the platform of APC-ISYS software made by Zhejiang Supcon Company and implemented in an industrial upper computer which sets over and is connected with a CS3000 distributed control system (DCS) through OPCServer. In order to reduce the fluctuation of the COT, AFNMSSMPC is chosen as feedback controller, which guarantees system robustness together with tracking ability, and meanwhile HIMMC is as feed-forward controller based on the change in chamber temperature (measured disturbance), which can eliminate the effect on cracking outlet temperature (COT) in advance. The application results on COT of two ethylene cracking furnaces labeled M and N furnaces in practice using AFNMSSMPC-HIMMC compared to the traditional proportional–integral–differential (PID) control are presented. The standard deviation of COT reduces by 54.03% and 60.87% for M and N furnaces, respectively. The results show that the designed COT system has the capability of good tracking and strong disturbance rejection.

Temperate phages (active prophages induced from bacteria) help control pathogenicity, modulate community structure, and maintain gut homeostasis1. Complete phage genome sequences are indispensable for understanding phage biology. Traditional plaque techniques are inapplicable to temperate phages due to the lysogenicity of these phages, which curb the identification and characterization of temperate phages. Existing in silico tools for prophage prediction usually fail to detect accurate and complete temperate phage genomes2–5. In this study, by a novel computational method mining both the integrated active prophages and their spontaneously induced forms (temperate phages), we obtained 192,326 complete temperate phage genomes from bacterial next-generation sequencing (NGS) data, hence expanded the existing number of complete temperate phage genomes by more than 100-fold. The reliability of our method was validated by wet-lab experiments. The experiments demonstrated that our method can accurately determine the complete genome sequences of the temperate phages, with exact flanking sites (attP and attB sites), outperforming other state-of-the-art prophage prediction methods. Our analysis indicates that temperate phages are likely to function in the evolution of microbes by 1) cross-infecting different bacterial host species; 2) transferring antibiotic resistance and virulence genes; and 3) interacting with hosts through restriction-modification and CRISPR/anti-CRISPR systems. This work provides a comprehensive complete temperate phage genome database and relevant information, which can serve as a valuable resource for phage research.

Phase-variable antibiotic resistance genes (ARGs) can mitigate the fitness cost of maintaining ARGs in the absence of antibiotics and could potentially prolong the persistence of ARGs in bacterial populations. However, the origin, prevalence, and distribution of phase-variable ARGs remains poorly understood. Here, we sought to assess the threat posed by phase-variable ARGs by systematically searching for phase-variable ARGs in the human gut microbiome and examining their origin, prevalence, and distribution. Through metagenomic assembly of 2227 human gut metagenomes and genomic analysis of the Unified Human Gastrointestinal Genome (UHGG) collection, we identified phase-variable ARGs and categorized them into three classes based on the invertase regulating phase variation. In the human gut microbiome, phase-variable ARGs are commonly and exclusively distributed in Bacteroidales species. Through genomic analysis, we observed that phase-variable ARGs have convergently originated from ARG insertions into phase-variable capsule polysaccharide biosynthesis (CPS) loci at least three times. Moreover, all identified phase-variable ARGs are located within integrative conjugative elements (ICEs). Therefore, horizontal transfer via ICEs could explain the wide taxonomic distribution of phase-variable ARGs. Overall, these findings reveal that phase-variable CPS loci in Bacteroidales species are an important hotspot for the emergence of clinically-relevant phase-variable ARGs.

The spherical and hierarchical ZSM-5 zeolite was hydrothermally synthesized with the function of organofunctionalized silica and organic additive. The obtained materials were prepared with nanocrystalline stacking and also its hierarchical meso-microporous architectures were explained by the modern analysis methods including X-Ray Powder Diffraction, Scanning Electron Microscope, Transmission Electron Microscope, Fourier Transform Infrared Spectroscopy, Differential Thermogravimetric Analysis and N2 adsorption/desorption. It found that the size of nanocrystals and surface topography for ZSM-5 was influenced by both the organofunctionalized silica and the organic additive. Moreover, the abundant mesoporous volumes including intercrystalline and intracrystalline mesopores for zeolitic nanocrystals and the mesoporous pore diameter could be controlled by the degrees of silanization for silica. Moreover, the evaluation on the performance of ad/desorption and cyclic application in toluene for the ZSM-5 zeolites further revealed its high adsorption ability (the highest adsorption amounts was 57.9621 mg/g) and excellent cyclic performance because of its lower steric limitations and higher diffusion rate for the organic molecules, especially the large molecule. More importantly, the exploration of Fourier Transform Infrared Spectroscopy and Differential Thermogravimetric Analysis for the hierarchical ZSM-5 directly explained the existence of organosilane phenylaminopropyl-trimethoxysilane and organic additives in the zeolitic nanocrystals. Based on the above exploration, the crystallization mechanism of ZSM-5 was put forward, which was significant to design and synthesize the hierarchical zeolites.

In view that the previous control methods usually rely too much on the models of batch process and have difficulty in a practical batch process with unknown dynamics, a novel data-driven two-dimensional (2D) off-policy Q-learning approach for optimal tracking control (OTC) is proposed to make the batch process obtain a model-free control law. Firstly, an extended state space equation composing of the state and output error is established for ensuring tracking performance of the designed controller. Secondly, the behavior policy of generating data and the target policy of optimization as well as learning is introduced based on this extended system. Then, the Bellman equation independent of model parameters is given via analyzing the relation between 2D value function and 2D Q-function. The measured data along the batch and time directions of batch process are just taken to carry out the policy iteration, which can figure out the optimal control problem despite lacking systematic dynamic information. The unbiasedness and convergence of the designed 2D off-policy Q-learning algorithm are proved. Finally, a simulation case for injection molding process manifests that control effect and tracking effect gradually become better with the increasing number of batches.

A robust model predictive control method based on time-varying trajectory is proposed for discrete chemical process systems with uncertainties, bounded disturbances and time-varying target trajectories. Firstly, based on the traditional system state space model, the output tracking error is extended to the state space model, and the system controller is designed based on this extended model. Secondly, by means of Lyapunov stability theory and H-infinite performance index, the problems are solved for the process with model uncertainty, bounded disturbance and time-varying target trajectory, which can ensure the stability of the system. Then the linear matrix inequality (LMI) method is used to calculate the control law of the system. Finally, an example is given to verify the effectiveness and feasibility of the proposed method.

Zinc (Zn) is widely known as an essential trace element for fish and new ways to supply it to them are needed. Palygorskite (Pal) is a natural silicate clay mineral and the palygorskite structure contains nano-channels, which are filled with water and exchangeable ions. Zn-bearing palygorskites (Zn-Pal) prepared using ion exchange have attracted attention due to the durable antibacterial properties that limit pathogens and as a potential new Zn source for livestock. The present study was conducted to evaluate the effects of Zn-Pal supplementation on the growth performance, nutrient retention, meat quality, Zn accumulation, and intestinal Zn transporter protein gene expression in blunt snout bream Megalobrama amblycephala. The fish were fed a basal diet without an exogenous Zn source and the basal diet was supplemented with 125 mg/kg Zn as Zn sulfate (ZnSO4) or 35, 80, or 125 mg/kg Zn as Zn-Pal. Each diet was tested using three replicates for 7 weeks. The results showed that dietary Zn-Pal supplementation quadratically (P 0.05), increased mRNA expression of the metal-response element-binding transcription factor-1 in the intestine (P

This study investigated the responses of fast- (FG) and slow- (SG) growing broilers to dietary methionine (Met) status. The broilers were subjected to low (LM, 0.38 and 0.28 g/100 g), adequate (AM, 0.51 and 0.42 g/100 g) and high (HM, 0.65 and 0.52 g/100 g) Met during 1–21 and 22–42 d, respectively. Compared with the LM diets, the AM and HM diets increased body weight gain only in the FG broilers. The HM diets increased breast muscle yield only in the FG broilers, although insulin-like growth factor-I (IGF-I) concentration was increased in both strains of broilers. The HM diets increased mRNA levels of myogenic regulatory factors (MRF4, Myf5) and myocyte enhancer factor 2 (MEF2A and MEF2B) in the FG broilers, and increased MEF2A and decreased myostatin mRNA level in the SG broilers. Extracellular signal-regulated kinase (ERK) phosphorylation of breast muscle was increased by the HM diets in both strains of broilers, but mechanistic target of rapamycin (mTOR) phosphorylation was increased by the AM and HM diets only in the FG broilers. These results reflect a strain difference in broiler growth and underlying mechanism in response to dietary Met.

In order to enable the calibration model to be effectively transferred among multiple instruments and correct the differences between the spectra measured by different instruments, a new feature transfer model based on partial least squares regression (PLS) subspace (PLSCT) is proposed in this paper. Firstly, the PLS model of the master instrument is built, meanwhile a PLS subspace is constructed by the feature vectors. Then the master spectra and the slave spectra are projected into the PLS subspace, and the features of the spectra are also extracted at the same time. In the subspace, the pseudo predicted feature of the slave spectra is transferred by the ordinary least squares method so that it matches the predicted feature of the master spectra. Finally, a feature transfer relationship model is constructed through the feature transfer of the PLS subspace. This PLS-based subspace transfer provides an efficient method for performing calibration transfer with only a small number of standard samples. The performance of the PLSCT was compared and assessed with slope and bias correction (SBC), piecewise direct standardization (PDS), calibration transfer method based on canonical correlation analysis (CCACT), generalized least squares (GLSW), multiplicative signal correction (MSC) methods in three real datasets, statistically tested by the Wilcoxon signed rank test. The obtained experimental results indicate that PLSCT method based on the PLS subspace is more stable and can acquire more accurate prediction results.

The meta distribution of the signal-to-interference ratio (SIR) provides more fine-grained information about the link performance than the standard success probability. This paper studies the reliability in cellular networks with physical layer security constraints using the meta distribution. We consider a cellular network where the BSs are distributed as Possion point process. We provide the distribution of the opportunistic secure spectrum access probability when connection success and secrecy success occurs simultaneously, taking into account the interference correlation. We gain insights on the links reliability in the network under different security levels and the effect on the link reliability of the distance between legitimate user and eavesdropper.

Mobile self-organizing networks, such as vehicular ad-hoc network (VANET), in most cases rely on infrastructure deployment to provide access to internet services and other resource. Therefore, it is crucial to optimize the deployment of roadside units (RSUs) in vehicle network. In this paper, we propose a RSU optimized deployment scheme based on large vehicle data, which considers the deployment cost and latency performance synthetically. We deploy the RSU problem as a multiobjective optimization problem for mathematical modeling. On this basis, two-step solution is proposed: firstly, the RSU candidate positions can be obtained by considering the road topology and large vehicle data; secondly, the branch and bound algorithm is used to obtain the better RSU deployment based on the mathematical model. The simulation results show that the proposed RSU deployment scheme uses a small amount of RSU can achieve high coverage and greatly reduce the deployment cost. Moreover, the low latency performance of the vehicle access network and the quality of the latency sensitive application service can also be ensured.

Curcumin–chitosan (Cur–CH) blend films were prepared by solution casting. The Cur–CH and pure chitosan (PCH) films were characterized by molecular simulation, physicochemical properties and antibacterial properties. The molecular model showed that probable interaction between curcumin and chitosan was hydrogen bonding, which was further determined by FTIR. The SEM revealed a good compatibility between curcumin and chitosan. Thermal behavior and X-ray diffraction showed that the structure of Cur–CH film was changed and the crystallinity was decreased compared with PCH film. The blend films showed a larger tensile strength and a higher hydrophilic property than PCH film. Antibacterial activity of Cur–CH film against Staphylococcus aureus and Rhizoctonia solani was studied by the zone inhibition method. Results suggest that it is promising to study natural curcumin chitosan blend films with excellent tensile strength and antibacterial activity for food packaging and agricultural products storage.

A kind of dimer nanostructure similar to panda's eyes (P-Es), consisting two center biased elliptical rings, is proposed in this paper. The finite element method is used to study the nanostructure with the vertical incident light. The structure exhibits high order magnetic modes and the magnetic modes intensity can be manipulated independently by changing the structure parameters. The intensities of the magnetic dipole and magnetic quadrupole modes can be controlled by changing the angle between two rings and the distance of two cavity centers, respectively. Moreover, when two circular cavities increase simultaneously, the intensity of the magnetic octupole mode increases accordingly. Fano resonance can be induced when the electric mode couples with the magnetic mode. When the radius of the left circular cavity decreases, triple Fano resonance is formed. And when the whole structure is rotated, quintuple Fano resonance can be formed. More interesting, when the radii of the circular cavities of the two elliptical rings increase to 50 and 55 nm, the nanostructure becomes crescent dimer, and the enhancements of magnetic field and electric field reach 36 and 390, respectively. The P-Es structure has potential application value in multiwavelength surface enhanced spectroscopy and biochemical sensing.

As the basic geometric structure unit for generating surface plasmon, the split ring and the disk have been researched widely in both theory and experiment. A split asymmetric ring-disk (SAR-D) nanostructure is proposed to achieve both magnetic double Fano resonances and near field enhancement, which is investigated numerically based on the finite element method. In this nanostructure, Fano resonance is produced by the destructive interference between the bright electric mode and the dark magnetic mode. The extinction spectra can be modulated by changing the distance between the split asymmetric ring (SAR) and the disk, the thickness of the nanostructure and the radii of the SAR or the disk. Magnetic double Fano resonances can be excited effectively by rotation the SAR-D structure or splitting the disk along y-axis. Calculation results show that near field intensity is enhanced greatly at resonance peaks. Splitting the disk along y-axis, the strongest electric and magnetic field enhancements are achieved at the split gap, which are 386 and 118, respectively. This SAR-D nanostructure have potential applications in the surface enhance plasmon spectroscopy, the propagation of low-loss magnetic plasmons and the multiwavelength spectrometer.